A.Y. Hoekstra
Virtual water trade
P.Q. Hung September 2002
A quantification of virtual water flows between nations in relation to international crop trade
Value of Water
Research Report Series No.11
VIRTUAL WATER TRADE A
QUANTIFICATION OF VIRTUAL
WATER FLOWS BETWEEN NATIONS IN RELATION TO INTERNATIONAL CROP TRADE
A.Y. HOEKSTRA P.Q. HUNG
SEPTEMBER 2002
VALUE OF WATER RESEARCH REPORT SERIES NO. 11
IHE D ELFT
Contact author:
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A.Y. Hoekstra
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THE NETHERLANDS
E-mail
[email protected]
Contents
Summary...................................................................................................................................................................................7 1. Introduction .........................................................................................................................................................................9 1.1. The economics of water use........................................................................................................................................9 1.2. Virtual water trade......................................................................................................................................................10 1.3. The objective of this study........................................................................................................................................11 2. Method................................................................................................................................................................................ 13 2.1. Calculation of specific water demand per crop type ............................................................................................13 2.2. Calculation of virtual water trade flows and the national virtual water trade balance....................................14 2.3. Calculation of a nation’s ‘water footprint’.............................................................................................................15 2.4. Calculation of national water scarcity, water dependency and water self-sufficiency ...................................16 3. Data sources ...................................................................................................................................................................... 19 4. Specific water demand per crop type per country................................................................................................. 23 5. Global trade in virtual water....................................................................................................................................... 25 5.1. International trade in virtual water...........................................................................................................................25 5.1.1. Overview of international virtual water trade.............................................................................................. 25 5.1.2. Virtual water trade balance per country....................................................................................................... 28 5.1.3. International virtual water trade by product................................................................................................ 34 5.2. Inter-regional trade in virtual water.........................................................................................................................35 5.2.1. Inter-regional virtual water trade relations................................................................................................. 35 5.2.2. Virtual water trade balance per world region ............................................................................................. 40 5.2.3. Gross virtual water trade between countries within regions..................................................................... 50 5.3. Intercontinental trade in virtual water.....................................................................................................................51 5.3.1. Intercontinental virtual water trade relations.............................................................................................. 51 5.3.2. Virtual water trade balance per continent.................................................................................................... 53 5.3.3. Gross virtual water trade between countries within continents................................................................ 54 6. Virtual water trade of nations in relation to national water needs and availability..................................... 55 6.1. Water footprints, water scarcity, water self-sufficiency and water dependency of nations ..........................55 6.2. The relation between water scarcity and water dependency ...............................................................................60 7. Concluding remarks....................................................................................................................................................... 63 References .............................................................................................................................................................................. 65
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Appendices
I.
Crop water requirements (m3 /ha)
II.
Actual crop yields (ton/ha) in 1999
III.
Specific water demands (m3 /ton) in 1999
IV.
FAO guidelines on crop water requirements in mm [=10 m3 /ha]
Va.
Gross virtual water import per country for the years 1995-1999 (106 m3 )
Vb.
Gross virtual water export per country for the years 1995-1999 (106 m3 )
Vc.
Net virtual water import per country for the years 1995-1999 (106 m3 )
VI.
Classification of countries into thirteen world regions
VII.
Gross virtual water trade between and within regions (Gm3 )
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Summary The water that is used in the production process of an agricultural or industrial product is called the 'virtual water' contained in the product. A water-scarce country might wish to import products that require a lot of water in their production (water-intensive products) and export products or services that require less water (waterextensive products). This implies net import of ‘virtual water’ (as opposed to import of real water, which is generally too expensive) and will relieve the pressure on the nation’s own water resources. Until date little is known on the actual volumes of virtual water trade flows between countries.
The objective of this study is to quantify the volumes of all virtual water trade flows between nations in the period 1995-1999 and to put the virtual water trade balances of nations within the context of national water needs and water availability. The study has been limited to the quantification of virtual water trade flows related to international crop trade.
The basic approach has been to multiply international crop trade flows (ton/yr) by their associated virtual water content (m3 /ton). The required crop trade data have been taken from the United Nations Statistics Division in New York. The required data on virtual water content of crops originating from different countries have been estimated on the basis of various FAO databases (CropWat, ClimWat, FAOSTAT).
The calculations show that the global volume of crop-related virtual water trade between nations was 695 Gm3 /yr in average over the period 1995-1999. For comparison: the total water use by crops in the world has been estimated at 5400 Gm3 /yr (Rockström and Gordon, 2001). This means that 13% of the water used for crop production in the world is not used for domestic consumption but for export (in virtual form). This is the global percentage; the situation strongly varies between countries.
Considering the period 1995-1999, the countries with largest net virtual water export are: United States, Canada, Thailand, Argentina, and India. The countries with largest net virtual water import in the same period are: Sri Lanka, Japan, the Netherlands, the Republic of Korea, and China.
For each nation of the world a ‘water footprint’ has been calculated (a term chosen on the analogy of the ‘ecological footprint’). The water footprint, equal to the sum of the domestic water use and net virtual water import, is proposed here as a measure of a nation’s actual appropriation of the global water resources. It gives a more complete picture than if one looks at domestic water use only, as is being done until date. In addition to the water footprint, indicators are proposed for a nation’s ‘water self-sufficiency’ and a nation’s ‘water dependency’.
In studying global virtual water trade flows, it is recommended to start working on other products than crops as well, for instance livestock products such as meat. Another next step is to start interpreting the data and to study how governments can deliberately interfere in the current national virtual water trade balances in order to achieve higher global water use efficiency.
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8
1. Introduction 1.1. The economics of water use
Water should be considered an economic good. Ten years after the Dublin conference this sounds like a mantra for water policy makers. The sentence is repeated again and again, conference after conference. It is suggested that problems of water scarcity, water excess and deterioration of water quality would be solved if the resource ‘water’ were properly treated as an economic good. The logic is clear: clean fresh water is a scarce good and thus should be treated economically. There is an urgent need to develop appropriate concepts and tools to do so.
In dealing with the available water resources in an economically efficient way, there are three different levels at which decisions can be made and improvements be achieved. The first level is the user level, where price and technology play a key role. This is the level where the ‘local water use efficiency’ can be increased by creating awareness, charging prices based on full marginal cost and by stimulating water-saving technology. Second, at a higher level, a choice has to be made on how to allocate the available water resources to the different sectors of economy (including public health and the environment). Water is used for the production of several ‘goods’ and ‘services’. People allocate water to serve certain purposes, which generally implies that other, alternative purposes are not served. Choices on the allocation of water can be more or less ‘efficient’, depending on the value of water in its alternative uses. At this level we speak of ‘water allocation efficiency’. Water is a public good, so water allocation at the country or catchment level is principally a governmental issue. The question is here how all demands for water can best be met and where – in case of water shortage – supply should be restricted.
Beyond ‘local water use efficiency’ and ‘water allocation efficiency’ there is a level at which one could talk about ‘global water use efficiency’. It is a fact that some regions of the world are water-scarce and other regions are water-abundant. It is also a fact that in some regions there is a low demand for water and in other regions a high demand. Unfortunately there is no general positive relation between water demand and availability. Until recently people have focussed very much on considering how to meet demand based on the available water resources at national or river basin scale. The issue is then how to most efficiently allocate and use the available water. There is no reason to restrict the analysis to that. In a protected economy, a nation will have to achieve its development goals with its own resources. In an open economy, however, a nation can import products that are produced from resources that are scarcely available within the country and export products that are produced with resources that are abundantly available within the country. A water-scarce country can thus aim at importing products that require a lot of water in their production (water-intensive products) and exporting products or services that require less water (water-extensive products). This is called import of virtual water (as opposed to import of real water, which is generally too expensive) and will relieve the pressure on the nation’s own water resources. For water-abundant countries an argumentation can be made for export of virtual water. Import of water-intensive products by some nations and export of these products by others includes what is called ‘virtual water trade’ between nations.
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Global water use efficiency
virtual water trade between water-scarce and water-abundant regions
Water allocation efficiency
value of water in its alternative uses
Local water use efficiency
technology, water price, environmental awareness of water user
In summary, the overall efficiency in the appropriation of the global water resources can be defined as the ‘sum’ of local water use efficiencies, meso-scale water allocation efficiencies and global water use efficiency. So far most attention of scientists and politicians has gone to local water use efficiency. There is quite some knowledge available and improvements have actually been achieved already. More efficient allocation of water as a means to improved water management has got quite same attention as well, but if it comes to the implementation of improved allocation schemes there is still a long way to go. At the global level, it is even more severe, since basic data on virtual water trade and water dependency of nations are generally even lacking. This has been the incentive for this study.
1.2. Virtual water trade
For the production of nearly all goods water is required. The water that is used in the production process of an agricultural or industrial product is called the 'virtual water' contained in the product. For example, for producing a kilogram of grain, grown under rain-fed and favourable climatic conditions, we need about one to two cubic metres of water, that is 1000 to 2000 kg of water. For the same amount of grain, but growing in an arid country, where the climatic conditions are not favourable (high temperature, high evapotranspiration) we need up to 3000 to 5000 kg of water.
If one country exports a water-intensive product to another country, it exports water in virtual form. In this way some countries support other countries in their water needs. For water-scarce countries it could be attractive to achieve water security by importing water-intensive products instead of producing all water-demanding products domestically. Reversibly, water-rich countries could profit from their abundance of water resources by producing water-intensive products for export. Trade of real water between water-rich and water-poor regions is generally impossible due to the large distances and associated costs, but trade in water-intensive products (virtual water trade) is realistic. Virtual water trade between nations and even continents could thus be used as an instrument to improve global water use efficiency and to achieve water security in water-poor regions of the world.
World-wide both politicians and the general public increasingly show interest in the pros and cons of ‘globalisation’ of trade. This can be understood from the fact that increasing global trade implies increased
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interdependence of nations. The tension in the debate relates to the fact that the game of global competition is played with rules that many see as unfair. Knowing that economically sound water pricing is poorly developed in many regions of the world, this means that many products are put on the world market at a price that does not properly include the cost of the water contained in the product. This leads to situations in which some regions in fact subsidise export of scarce water.
1.3. The objective of this study
The objectives of this study are:
1.
To estimate the amount of water needed to produce crops in different countries of the world;
2.
To quantify the volume of virtual water trade flows between nations in the period 1995-1999;
3.
To put the virtual water trade balances of nations within the context of national water needs and water availability.
This report is primarily meant as a data report. We do not pretend to give an in-depth interpretation of the results. Besides, we limit ourselves to virtual water trade in relation to international crop trade, thus excluding virtual water trade related to international trade of livestock products and industrial products.
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2. Method 2.1. Calculation of specific water demand per crop type
Per crop type, average specific water demand has been calculated separately for each relevant nation on the basis of FAO data on crop water requirements and crop yields:
SWD[n, c] =
CWR[n, c] CY [n, c]
(1)
Here, SWD denotes the specific water demand (m3 ton -1) of crop c in country n, CWR the crop water requirement (m3 ha-1) and CY the crop yield (ton ha-1). The crop water requirement CWR (in m3 ha-1) is calculated from the accumulated crop evapotranspiration ETc (in mm/day) over the complete growing period. The crop evapotranspiration ETc follows from multiplying the ‘reference crop evapotranspiration’ ET0 with the crop coefficient Kc:
ETc = K c × ET0
(2)
The concept of ‘reference crop evapotranspiration’ was introduced by FAO to study the evaporative demand of the atmosphere independently of crop type, crop development and management practices. The only factors affecting ET0 are climatic parameters. The reference crop evapotranspiration ET0 is defined as the rate of evapotranspiration from a hypothetical reference crop with an assumed crop height of 12 cm, a fixed crop surface resistance of 70 s m-1 and an albedo of 0.23. This reference crop evapotranspiration closely resembles the evapotranspiration from an extensive surface of green grass cover of uniform height, actively growing, completely shading the ground and with adequate water (Smith et al., 1992). Reference crop evapotranspiration is calculated on the basis of the FAO Penman-Monteith equation (Smith et al., 1992; Allen et al., 1994a, 1994b; Allen et al., 1998):
ET0 =
900 U (e − e ) T + 273 2 a d ∆ + γ (1 + 0 .34U 2 )
0.408 ∆( Rn − G ) + γ
(3)
in which:
ET0
= reference crop evapotranspiration [mm day-1];
Rn
= net radiation at the crop surface [MJ m-2 day -1];
G
= soil heat flux [MJ m-2 day -1];
T
= average air temperature [°C];
U2
= wind speed measured at 2 m height [m s -1];
ea
= saturation vapour pressure [kPa]; 13
ed
= actual vapour pressure [kPa];
ea -e d
= vapour pressure deficit [kPa];
∆
= slope of the vapour pressure curve [kPa °C-1];
γ
= psychrometric constant [kPa °C-1].
The crop coefficient accounts for the actual crop canopy and aerodynamic resistance relative to the hypothetical reference crop. The crop coefficient serves as an aggregation of the physical and physiological differences between a certain crop and the reference crop.
The overall scheme for the calculation of specific water demand is drawn in Figure 1.1. This figure also shows the next step: the calculation of the virtual water trade flows between nations.
Climatic parameters
Ref. crop evapotransp. E0 [mm day-1]
Crop coefficient Kc [-]
Crop evapotranspiration Ec [mm day-1]
Crop water requirement CWR [m 3 ha-1]
Crop yield
Specific water demand
CY [ton ha-1]
SWD [m 3 ton-1]
Global crop trade
Global virtual water trade
-1
CT [ton yr ]
VWT [m 3 yr-1 ]
Figure 1.1. Steps in the calculation of global virtual water trade.
2.2. Calculation of virtual water trade flows and the national virtual water trade balance
Virtual water trade flows between nations have been calculated by multiplying international crop trade flows by their associated virtual water content. The latter depends on the specific water demand of the crop in the exporting country where the crop is produced. Virtual water trade is thus calculated as: VWT [n e , ni , c, t ] = CT [ne , n i , c, t ]× SWD[ne , c]
(4)
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in which VWT denotes the virtual water trade (m3 yr-1) from exporting country n e to importing country n i in year t as a result of trade in crop c. C T represents the crop trade (ton yr-1) from exporting country n e to importing country ni in year t for crop c. SWD represents the specific water demand (m3 ton -1) of crop c in the exporting country. Above equation assumes that if a certain crop is exported from a certain country, this crop is actually grown in this country (and not in another country from which the crop was just imported for further export). Although a certain error will be made in this way, it is estimated that this error will not substantially influence the overall virtual water trade balance of a country. Besides, it is practically impossible to track the sources of all exported products.
The gross virtual water import to a country n i is the sum of all imports: GVWI [ ni , t ] = ∑ VWT [n e , n i , c, t ]
(5)
ne ,c
The gross virtual water export from a country n e is the sum of all exports: GVWE [n e , t ] = ∑ VWT [n e , n i , c, t ]
(6)
n i ,c
The net virtual water import of a country is equal to the gross virtual water import minus the gross virtual water export. The virtual water trade balance of country x for year t can thus be written as: NVWI [x, t ] = GVWI [x, t ] − GVWE [x, t ]
(7)
where NVWI stands for the net virtual water import (m3 yr-1 ) to the country. Net virtual water import to a country has either a positive or a negative sign. The latter indicates that there is net virtual water export from the country.
2.3. Calculation of a nation’s ‘water footprint’
The total water use within a country itself is not the right measure of a nation’s actual appropriation of the global water resources. In the case of net import of virtual water import into a country, this virtual water volume should be added to the total domestic water use in order to get a picture of a nation’s real call on the global water resources. Similarly, in the case of net export of virtual water from a country, this virtual water volume should be subtracted from the volume of domestic water use. The sum of domestic water use and net virtual water import can be seen as a kind of ‘water footprint’ of a country, on the analogy of the ‘ecological footprint’ of a nation. In simplified terms, the latter refers to the amount of land needed for the production of the goods and services consumed by the inhabitants of a country. Studies have shown that for some countries the ecological footprint is smaller than the area of the nation’s territory, but in other cases much bigger (Wackernagel and Rees, 1996; Wackernagel et al., 1997). The latter means that apparently some nations need land outside their own territory to provide in their goods and services. 15
The ‘water footprint’ of a country (expressed as a volume of water per year) is defined as:
(8)
Water footprint = WU + NVWI
in which WU denotes the total domestic water use (m3 yr-1) and NVWI the net virtual water import of a country (m3 yr-1). As noted earlier, the latter can have a negative sign as well.
Total domestic water use WU should ideally refer to the sum of ‘blue’ water use (referring to the use of groundand surface water) and ‘green’ water use (referring to the use of precipitation). However, since data on green water use on country basis are not easily obtainable, we have provisionally chosen in this report to limit the definition of water use to blue water use. It should be noted that ‘net virtual water import’ as defined in the previous section includes both ‘blue’ and ‘green’ water.
2.4. Calculation of national water scarcity, water dependency and water self-sufficiency
At the start of this study we expected to find a relation between national water scarcity and net virtual water import. One would logically assume that a country with high water scarcity would seek to profit from net virtual water import. On the other hand, countries with abundant water resources could make profit by exporting water in virtual form. In order to check this hypothesis we need indices of both water scarcity and virtual water import dependency. Plotting countries in a graph with water scarcity on the x-axis and virtual water import dependency on the y-axis, would expectedly result in some positive relation.
As an index of national water scarcity we use the ratio of total water use to water availability:
WS =
WU ×100 WA
(9)
In this equation, WS denotes national water scarcity (%), WU the total water use in the country (m3 yr-1) and WA the national water availability (m3 yr-1). Defined in this way, water scarcity will generally range between zero and hundred per cent, but can in exceptional cases (e.g. groundwater mining) be above hundred per cent. As a measure of the national water availability WA we take the annual internal renewable water resources, that are the average fresh water resources renewably available over a year from precipitation falling within a country’s borders (see for instance Gleick, 1993). As noted in the previous section, total water use WU should ideally refer to the sum of blue and green water use, but for practical reasons we have provisionally chosen in this report to define water scarcity as the ratio of blue water use to water availability, which is generally done by others as well.
Next, we have looked for a proper indicator of ‘virtual water import dependency’ or ‘water dependency’ in brief. The indicator should reflect the level to which a nation relies on foreign water resources (through import
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of water in virtual form). The water dependency WD of a nation is in this report calculated as the ratio of the net virtual water import into a country to the total national water appropriation:
NVWI WU + NVWI × 100 WD = 0
if NVWI ≥ 0
(10)
if NVWI < 0
The value of the water dependency index will per definition vary between zero and hundred per cent. A value of zero means that gross virtual water import and export are in balance or that there is net virtual water export. If on the other extreme the water dependency of a nation approaches hundred percent, the nation nearly completely relies on virtual water import.
As the counterpart of the water dependency index, the water self-sufficiency index is defined as follows: WU WU + NVWI × 100 WSS = 100
if NVWI ≥ 0
(11)
if NVWI < 0
The water self-sufficiency of a nation relates to the water dependency of a nation in the following simple way:
WSS = 1 − WD
(12)
The level of water self-sufficiency WSS denotes the national capability of supplying the water needed for the production of the domestic demand for goods and services. Self-sufficiency is hundred per cent if all the water needed is available and indeed taken from within the own territory. Water self-sufficiently approaches zero if a country heavily relies on virtual water imports.
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3. Data sources Data on crop water requirements are calculated with FAO’s CropWat model for Windows, which is available through the web site of FAO (www.fao.org). The CropWat model uses the FAO Penman-Monteith equation for calculating reference crop evapotranspiration as described in the previous chapter (Clarke et al., 1998). The CropWat model calculates crop water requirement of different crop types on the basis of the following assumptions:
(1) Crops are planted under optimum soil water conditions without any effective rainfall during their life; the crop is developed under irrigation conditions. (2) Crop evapotranspiration under standard conditions (ETc), this is the evapotranspiration from disease-free, well-fertilised crops, grown in large fields with 100% coverage. (3) Crop coefficients are selected depending on the single crop coefficient approach, that means single cropping pattern, not dual or triple cropping pattern.
Climatic data The climatic data needed as input to CropWat have been taken from FAO’s climatic database ClimWat, which is also available through FAO’s web site. The ClimWat database contains climatic data for more than hundred countries. For many countries climatic data are available for different climatic stations. As a crude approach, the capital climatic station data have been taken as the country representative. For the countries, where the required climatic input data are not available in ClimWat, the crop water requirement is taken from the guideline of FAO as reported by Gleick (1993) (Appendix IV). Depending on the country, the authors made an estimate somewhere between the minimum and maximum estimate given in the FAO guideline. If still data were lacking, data were taken from a neighbouring country.
Crop parameters In the crop directory of the CropWat package sets of crop parameters are available for 24 different crops (Table 3.1). The crop parameters used as input data to CropWat are: the crop coefficients in different crop development stages (initial, middle and late stage), the length of each crop in each development stage, the root depth, and the planting date. For the 14 crops where crop parameters are not available in the CropWat package, crop parameters have been based on Allen et al. (1998).
Crop yields Data on crop yields have been taken from the FAOSTAT database, again available through FAO’s web site.
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Table 3.1. Availability of crop parameters. Crops for which crop parameters have been taken from FAO’s Crops for which crop parameters have been CropWat package taken from Allen et al. (1998) Banana
Maize
Sugar beet
Artichoke
Onion dry
Barley
Mango
Sugar cane
Carrots
Peas
Bean dry
Millet
Sunflower
Cauliflower
Rice
Bean green
Oil palm fruit
Tobacco
Citrus
Safflower
Cabbage
Pepper
Tomato
Cucumber
Spinach
Cotton seeds
Potato
Vegetable
Lettuce
Sweet potato
Grape
Sorghum
Watermelon
Oats
Groundnut
Soybean
Wheat
Onion green
Global trade in crops As a source for the global trade in crops, we have used the 1995-1999 data contained in the Personal Computer Trade Analysis System (PC-TAS), a cd-rom produced by the United Nations Statistics Division (UNSD) in New York in collaboration with the International Trade Centre (ITC) in Geneva. These data are based on the Commodity Trade Statistics Data Base (COMTRADE) of the UNSD. Every year individual countries supply the UNSD with their annual international trade statistics, detailed by commodity and partner country. These data are processed into a standard format with consistent coding and valuation. Commodities are classified according the Harmonised System (HS) classification of the World Customs Organization.
Link between two crop classifications Specific water demand is calculated for 38 crop types as distinguished by the FAO in CropWat. The Harmonised System (HS) classification used in the COMTRADE database is a much more detailed classification. For our purpose we therefore have to link the two classifications, which has been done as shown in Table 3.2.
Table 3.2. The link between FAO’s crop types and the Harmonised System classification. FAO crop types
Commodities in the Harmonised System classification
Artichoke
Global artichoke, fresh or chilled
Banana
Banana, including plantains
Barley
Barley
Bean dry
Bean dried Bean, small red, dried
Bean green
Bean, frozen
Cabbage
Cabbage lettuce, fresh or chilled
Bean, shelled or unshelled, fresh or chilled
Cabbages, konrabi Carrots
Carrot, fresh or chilled
Cauliflower
Cauliflower and headed broccoli, fresh or chilled
Citrus
Citrus fruit, fresh or dried Grapefruit, fresh or chilled
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FAO crop types
Commodities in the Harmonised System classification
Cotton seeds
Cotton seed, whether or not broken
Cucumber
Cucumber and gherkins provisionally preserved but not immediately consumption Cucumber and gherkins, fresh or chilled
Sorghum
Grain sorghum
Grape
Grape dried Grape fresh
Groundnut
Groundnut in shell whether or not broken Groundnuts in shell or roasted
Lettuce
Lettuce, fresh or chilled
Maize
Maize (corn)
Millet
Millet
Oats
Oats
Onion dry
Onion dried, but not further prepared
Onion green
Onion and shallots, fresh or chilled Onion, provisionally preserved
Oil palm fruit
Palm nut
Peas
Peas, dried, shelled Peas, frozen Peas, shelled or unshelled, fresh or chilled
Pepper
Pepper of the genius capsuis
Potato
Potato, fresh or chilled Potatoes, frozen
Sugar beet
Raw sugar beet
Sugar cane
Raw sugar can
Rice
Rice, broken Rice, husked, (brown) Rice, in the husk (paddy or rough)
Safflower
Safflower seed, whether or not broken
Soybean
Soybean
Spinach
Spinach, N-Z spinach orache spinach
Sunflower
Sunflower seed
Sweet potato
Sweet potatoes, fresh or dried
Tobacco
Tobacco, unmanufactured, not stemmed Tobacco, unmanufactured, partly or wholly stemmed
Tomato
Tomatoes, fresh or chilled
Vegetable
Vegetable, fresh or chilled vegetable, frozen
Wheat
Wheat Durum wheat Buck wheat
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4. Specific water demand per crop type per country The calculated crop water requirements for different crops in different countries are shown in Appendix I. The crop water requirements as calculated here refer to the evapotranspiration under optimal growth conditions (see Chapter 3). This means that the calculated values are overestimates, because in reality there are often water shortage conditions. On the other hand, the calculated values can also be seen as conservative, because they exclude inevitable losses (e.g. during transport and application of water) and required losses such as drainage. The calculated crop water requirements differ considerably over countries, which is mainly due to the differences in climatic conditions.
Data on actual crop yields in the year 1999 have been retrieved from the FAOSTAT database. The data, which are country averages, are shown in Appendix II. Where country specific crop yield data are lacking in FAOSTAT, regional averages have been taken. The values that have been assessed in this way are presented in grey-shadow cells in Appendix II. The differences between countries are here even larger than in the case of the crop water requirements. This is due to the impact of the human factor on the actual crop yields. Specific water demand (m3 /ton) per crop type has been calculated for different countries by dividing the crop water requirement (m3 /ha) by the crop yield (ton/ha). The results are shown in Appendix III. Because both crop water requirements and crop yields strongly vary between countries, specific water demands vary as well.
It is noted here that the specific water demand data for 1999 will be used to calculate the virtual water trade flows in the whole period 1995-1999 (see Chapter 5). This is acceptable because country crop yield data appear not to vary considerably over years.
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5. Global trade in virtual water 5.1. International trade in virtual water
5.1.1. Overview of international virtual water trade
The calculation results show that the global volume of crop-related virtual water trade between nations was 695 Gm3 /yr in average over the period 1995-1999. For comparison: the global water withdrawal for agriculture (water use for irrigation) was about 2500 Gm3 /yr in 1995 and 2600 Gm3 /yr in 2000 (Shiklomanov, 1997, p.61). Taking into account the use of rainwater by crops as well, the total water use by crops in the world has been estimated at 5400 Gm3 /yr (Rockström and Gordon, 2001, p.847). This means that 13% of the water used for crop production in the world is not used for domestic consumption but for export (in virtual form). This is the global percentage; the situation strongly varies between countries.
Considering the period 1995-1999, the top-5 list of countries with net virtual water export is: 1st. United States, 2nd. Canada, 3rd. Thailand, 4th. Argentina, and 5th. India. The top-5 list of countries in terms of net virtual water import for the same period is: 1st. Sri Lanka, 2nd. Japan, 3rd. Netherlands, 4th. Republic of Korea, and 5th. China. Top-30 lists are given in Table 5.1. The ranking lists do not considerably change if we look into particular years within the five-year period 1995-1999.
Net virtual water import, Gm3 -100- -800 -10- -100 -1- -10 0- -1 0- 1 1- 10 10- 50 50- 100 100- 500 No Data
Figure 5.1. National virtual water trade balances over the period 1995-1999. Green coloured countries have net virtual water export. Red coloured countries have net virtual water import.
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National virtual water trade balances over the period 1995-1999 are shown in the coloured world map of Figure 5.1. Countries with net virtual water export are green and countries with net virtual water import are red. Appendix V presents the complete set of calculated data with respect to gross import, gross export and net import of virtual water for all countries of the world for the years 1995 up to 1999.
Some countries have net export of virtual water over the period 1995-1999, but net import of virtual water in one or more particular years in this period (Table 5.2). There are also countries that show the reverse (Table 5.3).
Table 5.1. Top-30 of virtual water export countries and top-30 of virtual water import countries (over 1995-1999). Country
Net export volume (109 m3)
Country
Net import volume (109 m3)
United States
758.3
1
Sri Lanka
428.5
Canada
272.5
2
Japan
297.4
Thailand
233.3
3
Netherlands
147.7
Argentina
226.3
4
Korea Rep.
112.6
India
161.1
5
China
101.9
Australia
145.6
6
Indonesia
101.7
Vietnam
90.2
7
Spain
82.5
France
88.4
8
Egypt
80.2
Guatemala
71.7
9
Germany
67.9
Brazil
45.0
10
Italy
64.3
Paraguay
42.1
11
Belgium
59.6
Kazakhstan
39.2
12
Saudi Arabia
54.4
Ukraine
31.8
13
Malaysia
51.3
Syria
21.5
14
Algeria
49.0
Hungary
19.8
15
Mexico
44.9
Myanmar
17.4
16
Taiwan
35.2
Uruguay
12.1
17
Colombia
33.4
Greece
9.8
18
Portugal
31.1
Dominican Republic
9.7
19
Iran
29.1
Romania
9.1
20
Bangladesh
28.7
Sudan
5.8
21
Morocco
27.7
Bolivia
5.3
22
Peru
27.1
Saint Lucia
5.2
23
Venezuela
24.6
United Kingdom
4.8
24
Nigeria
24.0
Burkina Faso
4.5
25
Israel
23.0
Sweden
4.2
26
Jordan
22.4
Malawi
3.8
27
South Africa
21.8
Dominica
3.1
28
Tunisia
19.3
Benin
3.0
29
Poland
18.8
Slovakia
3.0
30
Singapore
16.9
26
Table 5.2. Countries with net export of virtual water in the period 1995-1999 that have however net import in particular years. A ‘minus’ indicates a negative virtual water trade balance (i.e. net export of virtual water). A ‘plus’ indicates a positive virtual water trade balance (i.e. net import of virtual water). Country
1995
1996
1997
1998
1999
Brazil
-
+
-
-
-
Syria
-
-
-
-
+
Greece
-
-
-
+
-
Sudan
-
+
+
+
-
United Kingdom
+
+
-
+
+
Burkina Faso
-
+
+
-
-
Benin
+
-
-
-
-
Slovakia
-
-
+
-
-
Ecuador
-
-
-
+
-
Bulgaria
-
+
+
-
-
Cuba
+
-
-
+
-
Finland
-
-
-
-
+
Yugoslavia
-
-
+
-
-
Uganda
-
-
+
+
+
Papua N. Guinea
-
-
+
-
+
Bahamas
+
-
-
-
-
Montserrat
-
-
-
-
+
Tajikistan
+
-
-
-
-
Cameroon
-
-
+
+
-
Martinique
-
+
+
+
+
Pakistan
-
-
+
-
+
Solomon Islands
-
+
-
+
+
Central Africa
-
+
-
+
-
Samoa
-
-
-
+
-
Wallis Island
-
+
+
+
+
Table 5.3. Countries with net import of virtual water in the period 1995-1999 that have however net export in particular years. A ‘minus’ indicates a negative virtual water trade balance (i.e. net export of virtual water). A ‘plus’ indicates a positive virtual water trade balance (i.e. net import of virtual water). Country
1995
1996
1997
1998
1999
St. Kitts & Nevis
-
+
-
+
+
Guinea Bissau
+
+
-
-
+
Burundi
+
+
-
+
+
Tonga
+
+
-
+
+
Mongolia
-
+
+
+
+
Nepal
+
+
+
-
+
Kyrgyzstan
+
+
-
-
-
27
Country
1995
1996
1997
1998
1999
Macedonia
-
+
+
+
+
Lithuania
+
+
+
-
-
Bermuda
+
+
+
-
-
Bahrain
+
+
+
+
+
Gambia
+
+
+
-
+
Bosnia
+
-
+
+
+
Madagascar
+
-
-
+
+
George
+
+
+
+
-
Croatia
-
-
+
+
+
Nicaragua
+
+
-
+
+
Uzbekistan
+
+
+
+
-
Czech Republic
-
+
+
+
-
Philippines
-
-
+
+
+
Russian Fed.
-
-
+
-
+
Mexico
+
+
-
+
+
5.1.2. Virtual water trade balance per country
In this section we present the virtual water trade balances of a few selected countries. For each country, we give the annual balances for the individual years 1995-1999 and the overall five-year balance. Figures 5.2-5.11 show the virtual water trade balances for the ten biggest net export countries: United States, Canada, Thailand, Argentina, India, Australia, Vietnam, France, Guatemala and Brazil. Figures 5.12-5.21 show the balances for the ten biggest net import countries: Sri Lanka, Japan, Netherlands, Korea Rep., China, Indonesia, Spain, Egypt, Germany and Italy. The Figures 5.22-5.29 show the balances for a few other countries which have been chosen a bit arbitrarily. For the balances of those countries that are not shown here, the reader is referred to the data in Appendix V.
It is not the intention of this report to make an in-depth analysis and interpretation of the calculated national virtual water trade balances. Instead, we limit ourselves here to make just a few observations. First, the data show that developed countries generally have a more stable virtual water trade balance than the developing countries. Peak years in virtual water export were for instance found for Thailand, India, Vietnam, Guatemala and Syria. The opposite, the occurrence of peak years with relatively high virtual water import, was found for Sri Lanka and Jordan.
Second, we see that countries that are relatively close to each other in terms of geography and development level can have a rather different virtual water trade balance. While European countries such as the Netherlands, Belgium, Germany, Spain and Italy import virtual water in the form of crops, France exports a large amount of virtual water. In the Middle East we see that Syria has net export of virtual water related to crop trade, but Jordan and Israel have net import. In Southern Africa, Zimbabwe and Zambia had net export in the period 199528
1999, but South Africa had net import. [It should be noted that the trade balance of Zimbabwe has recently turned due to the recent political and economic developments.] In the regions of the Former Soviet Union, countries such as Kazakhstan and the Ukraine have net export of virtual water, but the Russian Federation has net import.
It is hard to put the data presented here in the context of earlier studies, for the simple reason that few quantitative studies into virtual water trade between nations have been carried out. A few interesting studies have been done for the Middle East and Africa (Allan, 1997, 2001; Wichelns, 2001; Nyagwambo, 1998; Earle, 2001). One study was done by Buchvald for Israel and is available in Hebrew only. The main results of this study are cited in Yegnes-Botzer (2001). According to Buchvald’s estimation Israel exported 377 million m3 of virtual water in 1999 and imported more than 6900 million m3 . The current study calculates for Israel an export of 700 million m3 of virtual water in 1999 and an import of 7400 million m3 .
3.5E+11
1.0E+12 9.0E+11 8.0E+11
Export
Export 3.0E+11
Import
Import
2.5E+11
7.0E+11 6.0E+11
2.0E+11
5.0E+11 1.5E+11
4.0E+11 3.0E+11
1.0E+11
2.0E+11 5.0E+10
1.0E+11 0.0E+00
0.0E+00 1995
1996
1997
1998
1999
1995
Total
Figure 5.2. Gross virtual water import into and export 3 -1 from the United States in the period 1995-1999 (m yr ).
1997
1998
1999
Total
Figure 5.3. Gross virtual water import into and export from Canada in the period 1995-1999 (m 3yr-1). 2.5E+11
3.0E+11 Export 2.5E+11
1996
Export
Import
2.0E+11
Import
2.0E+11 1.5E+11 1.5E+11 1.0E+11 1.0E+11 5.0E+10
5.0E+10 0.0E+00
0.0E+00 1995
1996
1997
1998
1999
1995
Total
1996
1997
1998
1999
Total
Figure 5.5. Gross virtual water import into and export from Argentina in the period 1995-1999 (m 3yr-1).
Figure 5.4. Gross virtual water import into and export 3 -1 from Thailand in the period 1995-1999 (m yr ).
29
2.0E+11 1.8E+11 1.6E+11
1.6E+11 Export
Export 1.4E+11
Import
Import
1.2E+11 1.4E+11 1.2E+11
1.0E+11
1.0E+11
8.0E+10
8.0E+10
6.0E+10
6.0E+10 4.0E+10 4.0E+10 2.0E+10
2.0E+10 0.0E+00
0.0E+00 1995
1996
1997
1998
1999
Total
1995
1.0E+11
8.0E+10
1997
1998
1999
Total
Figure 5.7. Gross virtual water import into and export from Australia in the period 1995-1999 (m 3yr-1).
Figure 5.6. Gross virtual water import into and export 3 -1 from India in the period 1995-1999 (m yr ).
9.0E+10
1996
1.6E+11 Export
Export 1.4E+11
Import
Import
1.2E+11 7.0E+10 6.0E+10
1.0E+11
5.0E+10
8.0E+10
4.0E+10
6.0E+10
3.0E+10 4.0E+10 2.0E+10 2.0E+10
1.0E+10 0.0E+00
0.0E+00 1995
1996
1997
1998
1999
Total
1995
1997
1998
1999
Total
Figure 5.9. Gross virtual water import into and export from France in the period 1995-1999 (m 3yr-1).
Figure 5.8. Gross virtual water import into and export 3 -1 from Vietnam in the period 1995-1999 (m yr ). 9.0E+10 8.0E+10
1996
1.8E+11 Export
1.6E+11
Import
Export Import
7.0E+10
1.4E+11
6.0E+10
1.2E+11
5.0E+10
1.0E+11
4.0E+10
8.0E+10
3.0E+10
6.0E+10
2.0E+10
4.0E+10
1.0E+10
2.0E+10
0.0E+00
0.0E+00 1995
1996
1997
1998
1999
Total
1995
Figure 5.10. Gross virtual water import into and export 3 -1 from Guatemala in the period 1995-1999 (m yr ).
30
1996
1997
1998
1999
Total
Figure 5.11. Gross virtual water import into and export from Brazil in the period 1995-1999 (m 3yr-1).
3.5E+11
5.0E+11 4.5E+11 4.0E+11
Export
Export 3.0E+11
Import
Import
2.5E+11
3.5E+11 3.0E+11
2.0E+11
2.5E+11 1.5E+11
2.0E+11 1.5E+11
1.0E+11
1.0E+11 5.0E+10
5.0E+10 0.0E+00
0.0E+00 1995
1996
1997
1998
1999
1995
Total
Figure 5.12. Gross virtual water import into and export 3 -1 from Sri Lanka in the period 1995-1999 (m yr ). 2.0E+11 1.8E+11 1.6E+11
1996
1997
1998
1999
Total
Figure 5.13. Gross virtual water import into and export from Japan in the period 1995-1999 (m 3yr-1). 1.2E+11
Export
Export
Import
1.0E+11
1.4E+11
Import
8.0E+10
1.2E+11 1.0E+11
6.0E+10
8.0E+10 4.0E+10
6.0E+10 4.0E+10
2.0E+10
2.0E+10 0.0E+00
0.0E+00 1995
1996
1997
1998
1999
Total
1995
Figure 5.14. Gross virtual water import into and export 3 -1 from the Netherlands in the period 1995-1999 (m yr ). 1.8E+11 1.6E+11
1996
1997
1998
1999
Total
Figure 5.15. Gross virtual water import into and export from the Korea Republic in the period 1995-1999 (m 3yr-1). 1.2E+11
Export
Export
Import
1.0E+11
Import
1.4E+11 1.2E+11
8.0E+10
1.0E+11 6.0E+10 8.0E+10 6.0E+10
4.0E+10
4.0E+10 2.0E+10 2.0E+10 0.0E+00
0.0E+00 1995
1996
1997
1998
1999
Total
1995
Figure 5.16. Gross virtual water import into and export 3 -1 from China in the period 1995-1999 (m yr ).
31
1996
1997
1998
1999
Total
Figure 5.17. Gross virtual water import into and export from Indonesia in the period 1995-1999 (m 3yr-1).
1.2E+11
9.0E+10 Export
1.0E+11
8.0E+10
Import
Export Import
7.0E+10 8.0E+10
6.0E+10 5.0E+10
6.0E+10 4.0E+10 4.0E+10
3.0E+10 2.0E+10
2.0E+10 1.0E+10 0.0E+00
0.0E+00 1995
1996
1997
1998
1999
Total
1995
Figure 5.18. Gross virtual water import into and export 3 -1 from Spain in the period 1995-1999 (m yr ). 1.4E+11
1997
1998
1999
Total
Figure 5.19. Gross virtual water import into and export from Egypt in the period 1995-1999 (m 3yr-1). 1.2E+11
Export 1.2E+11
1996
Export
Import
1.0E+11
Import
1.0E+11 8.0E+10 8.0E+10 6.0E+10 6.0E+10 4.0E+10 4.0E+10 2.0E+10
2.0E+10 0.0E+00
0.0E+00 1995
1996
1997
1998
1999
Total
1995
Figure 5.20. Gross virtual water import into and export 3 -1 from Germany in the period 1995-1999 (m yr ).
1997
1998
1999
Total
Figure 5.21. Gross virtual water import into and export from Italy in the period 1995-1999 (m 3yr-1). 2.5E+10
3.0E+10 Export 2.5E+10
1996
Export
Import
2.0E+10
Import
2.0E+10 1.5E+10 1.5E+10 1.0E+10 1.0E+10 5.0E+09
5.0E+09 0.0E+00
0.0E+00 1995
1996
1997
1998
1999
1995
Total
Figure 5.22. Gross virtual water import into and export 3 -1 from Syria in the period 1995-1999 (m yr ).
32
1996
1997
1998
1999
Total
Figure 5.23. Gross virtual water import into and export from Jordan in the period 1995-1999 (m 3yr-1).
3.0E+10
6.0E+10 Export
2.5E+10
Export
Import
5.0E+10
2.0E+10
4.0E+10
1.5E+10
3.0E+10
1.0E+10
2.0E+10
5.0E+09
1.0E+10
0.0E+00
0.0E+00 1995
1996
1997
1998
1999
Total
1995
Figure 5.24. Gross virtual water import into and export 3 -1 from Israel in the period 1995-1999 (m yr ).
1996
1997
1998
1999
Total
Figure 5.25. Gross virtual water import into and export from Saudi Arabia in the period 1995-1999 (m 3yr-1). 3.5E+09
4.0E+10 Export 3.5E+10
Import
Export 3.0E+09
Import
3.0E+10
Import
2.5E+09
2.5E+10 2.0E+09 2.0E+10 1.5E+09 1.5E+10 1.0E+09
1.0E+10
5.0E+08
5.0E+09 0.0E+00
0.0E+00 1995
1996
1997
1998
1999
1995
Total
Figure 5.26. Gross virtual water import into and export 3 -1 from South Africa in the period 1995-1999 (m yr ).
1997
1998
1999
Total
Figure 5.27. Gross virtual water import into and export from Zimbabwe in the period 1995-1999 (m 3yr-1). 4.5E+10
8.0E+10 Export 7.0E+10
1996
4.0E+10
Import
Export Import
3.5E+10
6.0E+10
3.0E+10
5.0E+10
2.5E+10 4.0E+10 2.0E+10 3.0E+10
1.5E+10
2.0E+10
1.0E+10
1.0E+10
5.0E+09
0.0E+00
0.0E+00 1995
1996
1997
1998
1999
1995
Total
Figure 5.28. Gross virtual water import into and export 3 -1 from the Russian Federation in the period 1995-1999 (m yr ).
33
1996
1997
1998
1999
Total
Figure 5.29. Gross virtual water import into and export from Kazakhstan in the period 1995-1999 (m 3yr-1).
5.1.3. International virtual water trade by product
The total volume of crop-related virtual water trade between nations in the period 1995-1999 can for 30% be explained by trade in wheat (Table 5.4). Next come soybeans and rice, which account respectively for 17% and 15% of global crop-related virtual water trade.
Table 5.4. Global virtual water trade between nations by product (Gm 3). Product
1995
%
1996
%
1997
%
1998
%
1999
%
Total
%
Wheat
181
32.35
215
26.49
254
32.01
203
29.00
197
32.73
1049
30.20
Soybean
103
18.37
108
13.28
125
15.79
122
17.47
135
22.45
593
17.07
Rice
81
14.57
198
24.35
71
8.95
119
16.95
65
10.78
534
15.36
Maize
58
10.40
56
6.93
67
8.51
65
9.22
61
10.14
307
8.85
Raw sugar
9
1.60
68
8.35
119
14.99
42
5.99
13
2.09
250
7.20
Barley
36
6.41
30
3.67
35
4.41
29
4.15
30
5.05
170
4.88
Sunflower
12
2.17
24
2.97
20
2.50
20
2.92
18
2.94
94
2.71
Sorghum
12
2.14
26
3.21
12
1.49
10
1.39
10
1.73
70
2.01
Bananas
11
1.88
16
2.00
15
1.95
15
2.15
11
1.83
68
1.97
Grapes
12
2.07
13
1.64
13
1.65
13
1.87
13
2.24
65
1.86
Oats
9
1.67
10
1.25
11
1.41
9
1.34
10
1.61
50
1.43
Tobacco
5
0.98
10
1.19
11
1.33
13
1.90
7
1.10
46
1.31
Ground-nuts
6
1.10
7
0.84
8
1.02
6
0.90
4
0.70
32
0.91
Peppers
4
0.80
5
0.62
9
1.12
6
0.84
6
1.02
30
0.87
Cotton seeds
5
0.83
5
0.56
5
0.64
6
0.92
7
1.24
28
0.81
Peas
3
0.46
4
0.48
4
0.57
5
0.67
2
0.31
18
0.50
Beans
3
0.47
6
0.68
3
0.35
2
0.36
2
0.38
16
0.45
Potatoes
2
0.40
2
0.26
2
0.31
2
0.33
2
0.37
11
0.33
Onions
2
0.28
3
0.33
2
0.19
2
0.35
1
0.25
10
0.28
Vegetables
1
0.14
1
0.10
1
0.12
4
0.50
1
0.17
7
0.20
Millet
1
0.23
1
0.14
1
0.16
1
0.17
1
0.22
6
0.18
Tomatoes
1
0.14
1
0.12
1
0.13
1
0.17
1
0.19
5
0.15
Palm nuts
1
0.12
1
0.12
1
0.07
1
0.08
0
0.08
3
0.09
Safflower
1
0.12
1
0.09
1
0.08
1
0.09
1
0.09
3
0.09
Cucumbers
0
0.06
1
0.12
1
0.07
0
0.06
0
0.07
3
0.08
Cauliflower
0
0.06
0
0.05
0
0.05
0
0.06
0
0.07
2
0.06
Cabbages
0
0.05
0
0.04
0
0.04
0
0.05
0
0.06
2
0.05
Carrots
0
0.04
0
0.03
0
0.03
0
0.04
0
0.05
1
0.04
Citrus
0
0.04
0
0.03
0
0.02
0
0.01
0
0.01
1
0.02
Artichokes
0
0.02
0
0.01
0
0.01
0
0.01
0
0.02
1
0.01
Lettuce
0
0.01
0
0.01
0
0.01
0
0.01
0
0.02
0
0.01
Sweet potato
0
0.02
0
0.01
0
0.01
0
0.01
0
0.01
0
0.01
Spinach
0
0.00
0
0.00
0
0.00
0
0.00
0
0.01
0
0.00
Grand total
559 100.00
813 100.00
793 100.00
34
700 100.00
601 100.00
3475 100.00
5.2. Inter-regional trade in virtual water
5.2.1. Inter-regional virtual water trade relations
In order to show virtual water trade between major world regions, the world has been classified into thirteen regions: North America, Central America, South America, Eastern Europe, Western Europe, Central and South Asia, the Middle East, South-east Asia, North Africa, Central Africa, Southern Africa, the Former Soviet Union, and Oceania. A list of countries per world region is given in Appendix VI.
The gross virtual water trade between and within regions in the period 1995-1999 is presented in Table 5.5. The details of the regional trade data are presented in Appendix VII. Net virtual water trade between regions in the period 1995-1999 is presented in Table 5.6 and Figure 5.30. In the figure the largest trade flows are indicated with arrows. The regions that have net import are marked in red colour and the regions that have net export are marked in green colour.
For each world region, a ranking has been made of the most important regions for gross import and gross export of virtual water (Table 5.7). Also a ranking has been made of the most important regions for net import and net export (Table 5.8).
Western Europe
FSU Eastern Europe
North America
Central and South Asia Middle East
Central America North Africa
Central Africa South America Net virtual water import, Gm3 -1030 -240 -140 -135 -45 -22 -5 12 20 151 222 380 833 No Data
Southern Africa
South east Asia
Oceania
Figure 5.30. Virtual water trade balances of thirteen world regions over the period 1995-1999. Green coloured regions have net virtual water export; red coloured regions have net virtual water import. The arrows show the largest net virtual water flows between regions (>100 Gm3).
35
1.65
0.25
3.53
0.02
0.79
0.13
2.87
0.81
0.01
0.73
1.63
1.81
2.00
14.60
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
Southern Africa
South America
South-east Asia
Western Europe
Total gross import
Central Africa
Central Africa
Exporter
Importer
167.30
2.26
2.14
7.16
0.68
0.33
0.40
153.24
0.15
0.13
0.15
0.67
4.62
0.00
981.76
59.53
226.63
62.29
5.38
8.00
83.26
395.21
2.46
11.56
2.82
100.40
124.52
0.11
60.16
18.97
2.56
7.83
0.50
13.06
0.07
9.51
1.14
2.54
20.40
3.07
0.78
0.12
Central Central & Eastern America South Europe Asia
205.35
20.20
25.76
20.26
0.37
29.26
9.47
63.77
3.74
25.65
10.37
21.64
0.43
0.07
Middle East
253.06
25.45
31.56
18.63
0.42
3.07
9.31
128.51
2.74
13.21
7.56
13.76
1.53
0.05
North Africa
87.62
5.08
12.97
13.37
1.74
0.96
2.69
82.78
4.18
2.35
0.56
3.32
40.37
0.05
North America
8.71
0.15
2.63
0.34
0.10
0.01
2.80
4.02
0.00
0.82
0.21
0.40
0.01
0.02
Oceania
45.53
3.89
5.98
4.85
0.26
48.68
0.06
9.65
0.22
1.21
5.23
9.88
4.29
0.01
FSU
40.11
2.03
11.81
2.75
2.78
0.00
2.84
9.84
0.43
0.03
0.12
9.44
0.17
0.64
107.24
1.59
3.45
146.73
1.31
0.06
3.66
88.67
4.61
0.48
0.08
0.87
2.45
0.00
203.03
1.78
87.20
16.50
1.21
0.40
31.56
82.80
0.16
2.72
0.55
64.89
0.41
0.05
523.28
250.46
11.08
191.21
7.66
35.00
4.41
170.27
13.79
18.37
37.42
17.77
14.33
1.99
Southern South South- Western Africa America east Asia Europe
Table 5.5. Gross virtual water trade between world regions in the period 1995-1999 (Gm 3). The grey-shaded cells refer to gross trade between countries within the regions.
2698
142.95
338.38
346.83
20.33
90.17
148.54
1118.38
30.99
54.21
65.09
149.25
189.52
3.11
Total gross export
-0.1
0.73
0.08
2.82
0.79
Eastern Europe
Middle East
North Africa
North America
Oceania
0.09
1.63
1.77
0.02
11.51
Southern Africa
South America
South-east Asia
Western Europe
Total net import
0
3.43
Central and South Asia
FSU
0.25
Central Africa
Central America
Central Africa
Exporter
Importer
-22.2
-12.07
1.73
4.71
0.51
-3.96
0.4
112.87
-1.38
-0.3
-0.62
-123.84
-0.25
832.49
41.76
161.74
61.42
-4.06
-1.89
82.86
391.89
-11.31
-10.08
-0.25
123.84
-3.43
-4.94
-18.44
2
7.75
0.38
7.83
-0.14
8.96
-6.42
-7.83
0.25
0.62
0.1
Central Central & Eastern America South Europe Asia
151.15
1.84
23.04
19.79
0.34
28.05
8.65
61.43
-9.47
7.83
10.08
0.3
-0.73
Middle East
-165.19
-69.84
-75.31
-8.1
-8.69
-1.33
-124.34
-61.43
-8.96
-391.89
-112.87
-2.82
-139.84
-4.26
-28.94
-3.32
-2.74
-0.04
1.33
-9.31
-8.65
0.14
-82.86
-0.4
-0.79
North Oceania America
222.08 -1030.77
11.66
31.41
14.02
-0.02
2.86
9.31
124.34
9.47
6.42
11.31
1.38
-0.08
North Africa
Table 5.6. Net virtual water trade between regions in the period 1995-1999 (Gm 3).
0
-44.65
-31.11
5.57
4.79
0.26
0.04
8.69
-2.86
-28.05
-7.83
1.89
3.96
FSU
19.76
-5.62
10.6
1.44
-0.26
2.74
8.1
0.02
-0.34
-0.38
4.06
-0.51
-0.09
-239.59
-189.62
-13.05
-1.44
-4.79
3.32
75.31
-14.02
-19.79
-7.75
-61.42
-4.71
-1.63
-135.33
-9.3
13.05
-10.6
-5.57
28.94
69.84
-31.41
-23.04
-2
-161.74
-1.73
-1.77
380.33
9.3
189.62
5.62
31.11
4.26
165.19
-11.66
-1.84
18.44
-41.76
12.07
-0.02
Southern South South- Western Africa America east Asia Europe
-380.33
135.33
239.59
-19.76
44.65
139.84
1030.77
-222.08
-151.15
4.94
-832.49
22.2
-11.51
Total net export
Central and South Asia
North America
South-east Asia
North America
North America
Central America
North America
North America
North America
Western Europe
South America
North America
Central and South Asia
North Africa
Southern Africa
South America
Central America
North America
Central Asia
Middle East
South-east Asia
Eastern Europe
Western Europe
Oceania
Russian Fed
North America
South-east Asia
North America
Russian Fed
Central and South Asia
Russian Fed
South-east Asia
Southern Africa
South America
North Africa
North America
South-east Asia
North America
South-east Asia
Middle East
Eastern Europe
North America
Oceania
South-east Asia
Central America
South-east Asia
Western Europe
South-east Asia
Central and South Asia
Western Europe
Western Europe
Eastern Europe
Central and South Asia
Middle East
South America
Southern Africa
Central and South Asia
Oceania
Western Europe
South-east Asia
Oceania
Oceania
South America
South-east Asia
Fourth
Western Europe
Central and South Asia
Central and South Asia
Western Europe
Central and South Asia
Western Europe
South-east Asia
Central and South Asia
Central and South Asia
Western Europe
Western Europe
Western Europe
Western Europe
First
Third
First
Second
Gross export to
Gross import from
Central Africa
Region
Table 5.7. Ranking of gross import and gross export regions for each of the thirteen world regions.
Middle East
South-east Asia
North Africa
Middle East
North Africa
North Africa
Middle East
Western Europe
North America
Central and South Asia
South and Central Asia
South America
Southern Africa
Second
Eastern Europe
Middle East
Middle East
North Africa
Middle East
Central and South Asia
Western Europe
Central America
Western Europe
Middle East
North America
North America
Eastern Europe
Third
Central and South Asia
North Africa
Eastern Europe
Russian Fed
North America
South-east Asia
North Africa
North Africa
Russian Fed
North Africa
South America
Middle East
Central and South Asia
Fourth
South America
North America
North America
Western Europe
Ocean
Russian Fed
South-east Asia
North America
Russian Fed
South America
Russian Fed
South America
Central America
Eastern Europe
South-east Asia
Ocean
Western Europe
Central and South Asia
Central and South Asia
Western Europe
Central and South Asia
North Africa
North America
South America
South America
Eastern Europe
Oceania
South-east Asia
North America
Central and South Asia
South-east Asia
Russian Fed
Oceania
Southern Africa
North America
Central America
South-east Asia
Western Europe
Western Europe
Middle East
South-east Asia
South America
Oceania
Central Africa
North Africa
North America
Central America
Oceania
Central and South Asia
Western Europe
Eastern Europe
North America
North America
South America
North America
South America
South America
Central and South Asia
South-east Asia
Southern Africa
South-east Asia
South-east Asia
Central and South Asia
North America
North Africa
North America
North America
Central and South Asia
Fourth
First
Third
First
Second
Net export to
Net import from
Central Africa
Region
Table 5.8. Ranking of net import and net export regions for each of the thirteen world regions.
Middle East
South-east Asia
North Africa
Middle East
North Africa
Central Africa
Middle East
Western Europe
Western Europe
Central and South Asia
Central America
Second
Eastern Europe
North Africa
Middle East
North Africa
Middle East
Southern Africa
North Africa
Russian Fed
Middle East
Eastern Europe
Third
North Africa
Middle East
Central Africa
Oceania
Southern Africa
Central Africa
Central Africa
North Africa
Middle East
Fourth
5.2.2. Virtual water trade balance per world region
The virtual water trade balances of the thirteen world regions are shown in Figures 5.31a and 5.31b. The former shows the gross import and export of virtual water for each region. The latter shows the difference between the two, the net import, which is positive in some cases and negative in others.
Regions with a significant net virtual water import are: Central and South Asia, Western Europe, North Africa, and the Middle East. Two other regions with net virtual water import, but less substantial, are Southern Africa and Central Africa. Regions with substantial net virtual water export are: North America, South America, Oceania, and South-east Asia. Three other regions with net virtual water export, but less substantial, are the FSU, Central America and Eastern Europe.
North America is by far the biggest virtual water exporter in the world, while Central and South Asia is by far the biggest virtual water importer. A further ranking of the world regions is given in Table 5.9.
1200 Export Import
1000 800 600 400 200 0 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
South America
South east Asia
Western Europe
Figure 5.31a. Gross virtual water import and export per region in the period 1995-1999 (Gm 3).
1000 500 0 -500 -1000 -1500 Central Africa
Central Central Eastern America and South Europe Asia
Middle East
North Africa
North America
Oceania
FSU
Figure 5.31b. Net virtual water import per region in the period 1995-1999 (Gm 3).
40
South Africa
South America
South east Asia
Western Europe
Table 5.9. Ranking of regions in terms of gross virtual water import and gross virtual water export. Gross virtual water import (1995-1999)
Ranking
Gross virtual water export (1995-1999)
Region
Gm 3
Central and South Asia
982
1
North America
1118
Western Europe
523
2
South America
347
North Africa
253
3
South-east Asia
338
Middle East
205
4
Central America
190
South-east Asia
203
5
Central and South Asia
149
Central America
167
6
Oceania
149
South America
107
7
Western Europe
143
North America
88
8
FSU
90
Eastern Europe
60
9
Eastern Europe
65
FSU
46
10
Middle East
54
Southern Africa
40
11
North Africa
31
Central Africa
15
12
Southern Africa
20
9
13
Central Africa
Oceania
Gm 3
Region
3
In the remaining part of this section, an overview will be given of the import and export of virtual water for each of the thirteen world regions. Figures 5.32a to 5.44a give the gross virtual water import and export of the thirteen world regions for the period 1995-1999. Figures 5.32b to 5.44b give the net virtual water import of the world regions for this period.
450 Export Import
400 350 300 250 200 150 100 50 0 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
Oceania
FSU
South Africa
South America
South east Asia
Figure 5.32a. Gross virtual water import and export of North America in the period 1995-1999 (Gm 3).
41
Western Europe
Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
Oceania
FSU
South Africa
South America
South east Asia
Western Europe
0 -50 -100 -150 -200 -250 -300 -350 -400 -450
Figure 5. 32b. Net virtual water import of North America in the period 1995-1999 (Gm 3).
180 Export Import
160 140 120 100 80 60 40 20 0 Central Africa
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
South America
South east Asia
Western Europe
Figure 5.33a. Gross virtual water import and export of Central America in the period 1995-1999 (Gm 3).
150 100 50 0 -50 -100 -150 Central Africa
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
South America
Figure 5.33b. Net virtual water import of Central America in the period 1995-1999 (Gm 3).
42
South east Asia
Western Europe
250 Export Import
200 150 100 50 0
Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
South east Asia
Western Europe
Figure 5.34a. Gross virtual water import and export of South America in the period 1995-1999 (Gm 3).
100 50 0 -50 -100 -150 -200 -250 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
South east Asia
Western Europe
Figure 5.34b. Net virtual water import of South America in the period 1995-1999 (Gm 3).
40 35
Export Import
30 25 20 15 10 5 0 Central Africa
Central America
Central and South Asia
Middle East
North Africa
North America
Oceania
FSU
South Africa
South America
South east Asia
Figure 5.35a. Gross virtual water import and export of Eastern Europe in the period 1995-1999 (Gm 3).
43
Western Europe
15 10 5 0 -5 -10 -15 -20 Central Africa
Central America
Central and South Asia
Middle East
North Africa
North America
Oceania
FSU
South Africa
South America
South east Asia
Western Europe
Figure 5.35b. Net virtual water import of Eastern Europe in the period 1995-1999 (Gm 3).
250 200
Export Import
150 100 50 0 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
South America
South east Asia
Figure 5.36a. Gross virtual water import and export of Western Europe in the period 1995-1999 (Gm 3).
250 200 150 100 50 0 -50 -100 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
Figure 5.36b. Net virtual water import of Western Europe in the period 1995-1999 (Gm 3).
44
South America
South east Asia
450 Export Import
400 350 300 250 200 150 100 50 0 Central Africa
Central America
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
South America
South east Asia
Western Europe
Figure 5.37a. Gross virtual water import and export of Central and South Asia in the period 1995-1999 (Gm 3).
450 400 350 300 250 200 150 100 50 0 -50 Central Africa
Central America
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
South America
South east Asia
Western Europe
Figure 5.37b. Net virtual water import of Central and South Asia in the period 1995-1999 (Gm 3).
70 Export Import
60 50 40 30 20 10 0 Central Africa
Central America
Central and South Asia
Eastern Europe
North Africa
North America
Oceania
FSU
South Africa
South America
South east Asia
Figure 5.38a. Gross virtual water import and export of the Middle East in the period 1995-1999 (Gm 3).
45
Western Europe
70 60 50 40 30 20 10 0 -10 -20 Central Africa
Central America
Central and South Asia
Eastern Europe
North Africa
North America
Oceania
FSU
South Africa
South America
South east Asia
Western Europe
Figure 5.38b. Net virtual water import of the Middle East in the period 1995-1999 (Gm 3).
250 Export Import
200 150 100 50 0 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
South America
Western Europe
Figure 5.39a. Gross virtual water import and export of South-east Asia in the period 1995-1999 (Gm 3).
100 50 0 -50 -100 -150 -200 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
Figure 5.39b. Net virtual water import of South-east Asia in the period 1995-1999 (Gm 3).
46
South America
Western Europe
140 Export Import
120 100 80 60 40 20 0 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North America
Oceania
FSU
South Africa
South America
South east Asia
Western Europe
Figure 5.40a. Gross virtual water import and export of North Africa in the period 1995-1999 (Gm 3).
140 120 100 80 60 40 20 0 -20 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North America
Oceania
FSU
South Africa
South America
South east Asia
Western Europe
Figure 5.40b. Net virtual water import of North Africa in the period 1995-1999 (Gm 3).
4.0 Export Import
3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
South America
South east Asia
Figure 5.41a. Gross virtual water import and export of Central Africa in the period 1995-1999 (Gm 3).
47
Western Europe
4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 -0.5 Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
South America
South east Asia
Western Europe
South America
South east Asia
Western Europe
Figure 5.41b. Net virtual water import of Central Africa in the period 1995-1999 (Gm 3).
14 Export Import
12 10 8 6 4 2 0
Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
Figure 5.42a. Gross virtual water import and export of Southern Africa in the period 1995-1999 (Gm 3).
12 10 8 6 4 2 0 -2 -4 -6 -8 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South America
Figure 5.42b. Net virtual water import of Southern Africa in the period 1995-1999 (Gm 3).
48
South east Asia
Western Europe
40 35
Export Import
30 25 20 15 10 5 0 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
South Africa
South America
South east Asia
Western Europe
Figure 5.43a. Gross virtual water import and export of the Former Soviet Union in the period 1995-1999 (Gm 3).
15 10 5 0 -5 -10 -15 -20 -25 -30 -35 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
South Africa
South America
South east Asia
Western Europe
Figure 5.43b. Net virtual water import of the Former Soviet Union in the period 1995-1999 (Gm 3).
90 Export Import
80 70 60 50 40 30 20 10 0 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
FSU
South Africa
South America
South east Asia
Figure 5.44a. Gross virtual water import and export of Oceania in the period 1995-1999 (Gm 3).
49
Western Europe
10 0 -10 -20 -30 -40 -50 -60 -70 -80 -90 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
FSU
South Africa
South America
South east Asia
Western Europe
Figure 5.44b. Net virtual water import of Oceania in the period 1995-1999 (Gm 3).
5.2.3. Gross virtual water trade between countries within regions
The virtual water trade flows between countries in each of the thirteen world regions are shown in Figures 5.45 and 5.46. The gross trade in virtual water within a region has been calculated by summing up all virtual water imports of the countries of the region that originate from other countries in the same region. Note that it yields the same result as if we would have added all virtual water exports of the countries in a region that go to other countries in the same region.
Western Europe is the region with the biggest internal trade in virtual water. Besides, the trade volume is rather stable here. South America is second in the ranking of internal trade volume. Central and South Asia is a rather unstable region if we look at the annual volume of virtual water traded between the countries of the region. Central and South Asia is the largest region in terms of population, so food demand is higher than in the other regions. This explains why the region is the biggest virtual water importer (see Figure 5.31b). The virtual water trade between countries within the region is also high, thus the countries within the region highly depend on both countries outside and countries within the region.
70 60 1995
50
1996
1997
1998
1999
Average
40 30 20 10 0 Central Africa
Central America
Central Eastern and South Europe Asian
Middle East
North Africa
North America
Oceania
FSU
South Africa
South America
South east Asian
Western Europe
Figure 5.45. Gross virtual water trade between countries within each region in the years 1995-1999 (Gm 3).
50
300 250 200 150 100 50 0 Central Africa
Central Central America and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South Africa
South America
South east Asia
Western Europe
Figure 5.46. Gross virtual water trade between countries within each region in the total period 1995-1999 (Gm 3).
5.3. Intercontinental trade in virtual water
5.3.1. Intercontinental virtual water trade relations
In the previous section the world was divided into thirteen ‘world regions’. In the current section, virtual water trade will be presented at the level of ‘continents’. The six continents – Africa, America, Asia, Europe, Oceania and the Former Soviet Union (FSU) – correspond to the world regions as indicated in Table 5.10.
The volumes of gross virtual water trade between continents in the period 1995-1999 are presented in Table 5.11. The gross virtual water trade between countries within the continents is given in the same table (the greyshaded cells). The net virtual water trade between continents is presented in Table 5.12.
Table 5.10. Correspondence between the six ‘continents’ and the thirteen ‘world regions’. Continent America Europe
Region North America
Central America
Eastern Europe
South America Western Europe
Asia
Middle East
Central and South Asia
South-east Asia
Africa
North Africa
Central Africa
Southern Africa
FSU
FSU
Ocean
Oceania
51
Table 5.11. Gross virtual water trade between continents in the years 1995-1999 (Gm 3). The grey-shaded cells refer to gross trade between countries within the continents. Importer Exporter Africa
Africa
America
Asia
Europe
Oceania
FSU
1995
1.874
0.442
4.204
5.980
0.029
0.005
1996 1997 1998 1999 Total 1995 1996 1997
2.201 1.560 2.060 1.873 9.568 32.655 31.882 33.980
1.651 1.106 3.121 6.393 12.713 83.598 107.887 115.344
3.247 2.071 2.463 1.542 13.527 136.725 146.857 227.862
4.708 3.967 5.380 5.154 25.188 78.196 73.898 77.621
0.018 0.022 0.020 0.024 0.113 1.239 0.755 1.023
0.115 0.094 0.130 0.145 0.488 1.523 3.028 2.640
1998 1999 Total
35.488 32.187 166.193
1995 1996 1997 1998
16.082 12.549 16.918 20.624
114.888 117.654 539.371 4.593 6.212 5.375 6.023
138.451 116.306 766.201 73.852 243.549 90.138 108.184
79.397 84.815 393.934 8.580 12.740 12.797 11.345
0.646 0.705 4.370 0.599 0.715 0.881 0.810
3.206 8.392 18.790 0.855 3.524 3.394 7.120
1999 Total
17.804 85.951
4.175 26.379
Europe
1995 1996 1997 1998 1999 Total
9.390 5.008 7.549 7.611 7.624 37.181
1.607 1.117 1.973 2.727 2.297 9.722
43.626 566.451 8.782 8.737 52.808 13.979 10.948 95.253
9.353 55.379 61.467 65.128 65.571 67.163 67.857 327.254
0.844 3.851 0.129 0.032 0.066 0.048 0.089 0.366
2.179 17.072 1.818 1.748 1.476 1.225 2.855 9.121
Oceania
1995 1996 1997 1998 1999 Total 1995
0.178 3.028 4.889 2.799 2.064 12.958 0.694
0.363 1.847 1.950 0.949 1.641 6.751 0.003
13.247 36.723 27.316 26.480 20.527 124.293 3.813
0.474 1.021 0.921 1.139 0.935 4.482 4.757
0.547 0.646 0.476 0.393 0.738 2.796 0.000
0.000 0.023 0.013 0.018 0.002 0.057 0.545
1996 1997 1998 1999 Total
0.575 0.776 0.673 0.365 3.082
0.547 0.416 0.308 0.076 1.350
7.066 5.533 13.261 7.985 37.659
14.002 12.495 11.171 5.644 48.066
0.000 0.013 0.000 0.000 0.013
9.740 11.843 10.695 15.862 48.682
America
Asia
FSU
Table 5.12. Net virtual water trade between continents in the period 1995-1999 (Gm 3). Importer Exporter Africa America Asia Europe Oceania FSU Total net import
Africa
America -153.48
153.48 72.42 11.99 12.84 2.59 253.32
-739.82 -384.21 2.38 -17.44 -1292.57
Asia -72.42 739.82 39.87 120.44 20.59 848.3
52
Europe -11.99 384.21 -39.87 4.12 38.94 375.41
Oceania -12.84 -2.38 -120.44 -4.12 -0.04 -139.82
FSU -2.59 17.44 -20.59 -38.94 0.04 -44.64
Total net export -253.32 1292.57 -848.3 -375.41 139.82 44.64 0
5.3.2. Virtual water trade balance per continent
Figure 5.47a shows the gross virtual water import and gross virtual water export for each continent for the whole period 1995-1999. Figure 5.47b shows the net import per continent. Net import is negative - this means there is net export – for America, Oceania and the Former Soviet Union. Net import is positive for Asia, Europe and Africa.
Table 5.13 ranks the continents according their gross import and gross export of virtual water. America is by far the largest export continent, with an average gross export of 270 Gm3 per year (over the period 1995-1999). The USA takes the largest share in this total export. Gross import to the American continent as a whole is only 11 Gm3 per year in average, which results in a net export of virtual water of 259 Gm3 per year. Asia is the largest importer of virtual water. Average gross import amounts to 207 Gm3 per year (over the years 1995-1999). Average gross export amounts to 38 Gm3 per year, resulting in an average annual import of 169 Gm3 .
1600 Export Import
1400 1200 1000 800 600 400 200 0 Africa
America
Asia
Europe
Oceania
FSU
Figure 5.47a. Gross virtual water import and export per continent in the period 1995-1999 (Gm 3).
1000 500 0 -500 -1000 -1500 Africa
America
Asia
Europe
Oceania
Figure 5.47b. Net virtual water import per continent in the period 1995-1999 (Gm 3).
53
FSU
Table 5.13. Ranking of continents in terms of gross virtual water import and gross virtual water export. Gross virtual water import (1995-1999) Continent
Rank Gm
Asia
3
Gross virtual water export (1995-1999) Gm 3
Continent
1037
1
America
Europe
527
2
Asia
189
Africa
305
3
Europe
152
America
57
4
Oceania
149
FSU
46
5
FSU
90
9
6
Africa
65
Oceania
1350
5.3.3. Gross virtual water trade between countries within continents
Data on gross virtual water trade between countries within continents are shown in Table 5.11 (the grey-shaded cells). Asia and America have the biggest internal gross virtual water trade (Figures 5.48-5.49). The virtual water trade between the American countries seems to be rather stable, which is not the case for the trade between the countries of the Asian continent. If compared to Asia and America, virtual water trade between countries within the area of the Former Soviet Union, within Africa and within Oceania is very small.
300 1995
1996
1997
1998
1999
Average
250 200 150 100 50 0 Africa
America
Asian
Europe
Oceania
FSU
Figure 5.48. Gross virtual water trade between countries within each continent in the years 1995-1999 (Gm 3). 600 500 400 300 200 100 0 Africa
America
Asia
Europe
Oceania
FSU
Figure 5.49. Gross virtual water trade between countries within each continent in the period 1995-1999 (Gm 3).
54
6. Virtual water trade of nations in relation to national water needs and availability 6.1. Water footprints, water scarcity, water self-sufficiency and water dependency of nations
Using the definition given in Section 2.3, a ‘water footprint’ has been calculated for each nation. Next, given the definitions in Section 2.4, indicators of national water scarcity, water self-sufficiency and water dependency have been calculated. The basic data on national water withdrawal and water availability have been taken from Raskin et al. (1997). The data on net virtual water import per country are taken from Appendix Vc. The results are shown in Table 6.1.
The level of water self-sufficiency has been classified into six categories: 0-20%; 20-50%; 50-70%; 70-90%; 90-99%; and 100%. Table 6.2 lists the countries in each of the categories.
Table 6.1. Water footprints, water scarcity, water self-sufficiency and water dependency of nations in 1995. Country
Afghanistan
Water withdrawal (106 m 3)
Water Net virtual 1 availability water import (106 m 3) (106 m 3)
Water footprint (106 m 3)
Water scarcity (%)
Water selfsufficiency (%)
Water dependency (%)
35704
50000
29
35733
71.4
99.9
0.1
Albania
356
21300
100
456
1.7
78.1
21.9
Algeria
5042
14300
9523
14565
35.3
34.6
65.4
Angola
628
184000
224
852
0.3
73.7
26.3
Argentina
35812
994000
-36742
-930
3.6
100.0
0.0
Armenia
4109
13300
308
4417
30.9
93.0
7.0
Australia
27312
343000
-13269
14043
8.0
100.0
0.0
2424
90300
-42
2382
2.7
100.0
0.0
17061
33000
158
17219
51.7
99.1
0.9
334
290
144
478
115.2
69.8
30.2
26467
2,357,000
12391
38858
1.1
68.1
31.9
Belarus
2979
73800
142
3121
4.0
95.4
4.6
Belgium
9237
12500
11730
20967
73.9
44.1
55.9
Benin
154
25800
97
251
0.6
61.4
38.6
Bhutan
23
95000
10
33
0.0
70.2
29.8
Bolivia
1557
300000
-1409
148
0.5
100.0
0.0
Bosnia/Herzeg.
1354
265000
83
1437
0.5
94.3
5.7
Brazil
46856
6,950,000
-1933
44923
0.7
100.0
0.0
Bulgaria
13576
205000
-1128
12448
6.6
100.0
0.0
Burkina Faso
412
17500
-10
402
2.4
100.0
0.0
Burundi
127
3600
2
129
3.5
98.8
1.2
Cambodia
660
498100
201
861
0.1
76.7
23.3
Austria Azerbaijan Bahrain Bangladesh
1
Data refer to the sum of internal and external water resources.
55
Country
Cameroon
Water withdrawal (106 m 3)
Water Net virtual 1 availability water import (106 m 3) (106 m 3)
Water footprint (106 m 3)
Water scarcity (%)
Water selfsufficiency (%)
Water dependency (%)
500
268000
-15
485
0.2
100.0
0.0
47246
2,901,000
-55330
-8084
1.6
100.0
0.0
Cape Verde
30
300000
40
70
0.0
43.0
57.0
Cent. African Rep.
85
141000
-1
84
0.1
100.0
0.0
Chad
218
43000
3
221
0.5
98.6
1.4
Chile
23203
468000
1509
24712
5.0
93.9
6.1
China
504315
2,800,000
42189
546504
18.0
92.3
7.7
6031
1,070,000
5604
11635
0.6
51.8
48.2
Comoros
13
1020
13
26
1.3
50.2
49.8
Congo
51
832000
636
687
0.0
7.4
92.6
Costa Rica
1464
95000
932
2396
1.5
61.1
38.9
Cote d'Ivoire
941
77700
578
1519
1.2
62.0
38.0
Croatia
1760
265000
-166
1594
0.7
100.0
0.0
Cuba
9585
34500
203
9788
27.8
97.9
2.1
Czech Rep.
2727
58200
-610
2117
4.7
100.0
0.0
Denmark
1210
13000
-1029
181
9.3
100.0
0.0
11
2300
102
113
0.5
9.7
90.3
Dominican R.
3483
20000
-1190
2293
17.4
100.0
0.0
Ecuador
6677
314000
-516
6161
2.1
100.0
0.0
55432
68500
15302
70734
80.9
78.4
21.6
1084
19000
918
2002
5.7
54.1
45.9
Eritrea
240
8800
27
267
2.7
90.0
10.0
Estonia
3220
17600
194
3414
18.3
94.3
5.7
Ethiopia
2156
110000
487
2643
2.0
81.6
18.4
33
28600
68
101
0.1
32.6
67.4
Finland
2243
113000
-431
1812
2.0
100.0
0.0
France
38570
198000
-18454
20116
19.5
100.0
0.0
Gabon
78
164000
64
142
0.0
55.0
45.0
Gambia
36
8000
150
186
0.5
19.3
80.7
Georgia
4054
65200
207
4261
6.2
95.1
4.9
Germany
47303
171000
12228
59531
27.7
79.5
20.5
Ghana
325
53200
229
554
0.6
58.7
41.3
Greece
7109
58700
-2989
4120
12.1
100.0
0.0
Guatemala
1501
116000
-883
618
1.3
100.0
0.0
22
27000
8
30
0.1
72.8
27.2
1501
241000
-14
1487
0.6
100.0
0.0
47
11000
364
411
0.4
11.4
88.6
Honduras
1656
63400
315
1971
2.6
84.0
16.0
Hungary
6678
120000
-5536
1142
5.6
100.0
0.0
Canada
Colombia
Djibouti
Egypt El Salvador
Fiji
Guinea-Bissau Guyana Haiti
56
Country
Water withdrawal (106 m 3)
Water selfsufficiency (%)
Water dependency (%)
Iceland
167
168000
56
223
0.1
74.9
25.1
607227
2,085,000
-24610
582617
29.1
100.0
0.0
Indonesia
83061
2,530,000
25256
108317
3.3
76.7
23.3
Iran
85608
117500
5494
91102
72.9
94.0
6.0
Iraq
52259
109200
51
52310
47.9
99.9
0.1
808
50000
675
1483
1.6
54.5
45.5
Israel
2277
2200
2021
4298
103.5
53.0
47.0
Italy
56362
167000
12706
69068
33.7
81.6
18.4
414
8300
271
685
5.0
60.4
39.6
91945
547000
55416
147361
16.8
62.4
37.6
907
1700
7629
8536
53.4
10.6
89.4
44138
169400
-658
43480
26.1
100.0
0.0
2454
30200
1667
4121
8.1
59.5
40.5
Korea (DPR)
16407
67000
561
16968
24.5
96.7
3.3
Korea (Rep.)
29558
66100
18964
48522
44.7
60.9
39.1
472
758000
472
944
0.1
50.0
50.0
12953
61700
143
13096
21.0
98.9
1.1
Laos
1260
270000
86
1346
0.5
93.6
6.4
Latvia
673
34000
224
897
2.0
75.0
25.0
1178
5600
727
1905
21.0
61.8
38.2
168
232000
67
235
0.1
71.5
28.5
Libya
4751
600000
610
5361
0.8
88.6
11.4
Lithuania
4416
24200
443
4859
18.2
90.9
9.1
847
265000
-32
815
0.3
100.0
0.0
23135
337000
447
23582
6.9
98.1
1.9
971
18700
-387
584
5.2
100.0
0.0
13058
456000
9983
23041
2.9
56.7
43.3
Mali
1746
100000
67
1813
1.7
96.3
3.7
Mauritania
1851
11400
161
2012
16.2
92.0
8.0
390
2200
250
640
17.7
60.9
39.1
Mexico
84209
357400
12432
96641
23.6
87.1
12.9
Moldova
3787
13700
-210
3577
27.6
100.0
0.0
Mongolia
657
24600
-27
630
2.7
100.0
0.0
11540
30000
6710
18250
38.5
63.2
36.8
655
216000
376
1031
0.3
63.5
36.5
Myanmar
4694
1,082,000
-1477
3217
0.4
100.0
0.0
Nepal
3284
170000
129
3413
1.9
96.2
3.8
Netherlands
8039
90000
29315
37354
8.9
21.5
78.5
New Zealand
1992
327000
845
2837
0.6
70.2
29.8
India
Ireland
Jamaica Japan Jordan Kazakhstan Kenya
Kuwait Kyrgyzstan
Lebanon Liberia
Macedonia Madagascar Malawi Malaysia
Mauritius
Morocco Mozambique
Water Net virtual 1 availability water import (106 m 3) (106 m 3)
57
Water footprint (106 m 3)
Water scarcity (%)
Country
Nicaragua
Water withdrawal (106 m 3)
Water Net virtual 1 availability water import (106 m 3) (106 m 3)
Water footprint (106 m 3)
Water scarcity (%)
Water selfsufficiency (%)
Water dependency (%)
1688
175000
168
1856
1.0
90.9
9.1
628
32500
106
734
1.9
85.5
14.5
Nigeria
4648
280000
628
5276
1.7
88.1
11.9
Norway
2077
392000
2548
4625
0.5
44.9
55.1
524
2103
1158
1682
24.9
31.1
68.9
Pakistan
278844
468000
-429
278415
59.6
100.0
0.0
Panama
1975
144000
68
2043
1.4
96.7
3.3
Papua New Guinea
120
801000
-81
39
0.0
100.0
0.0
Paraguay
541
314000
-6914
-6373
0.2
100.0
0.0
Peru
18726
40000
4789
23515
46.8
79.6
20.4
Philippines
49035
323000
-654
48381
15.2
100.0
0.0
Poland
12349
56200
4298
16647
22.0
74.2
25.8
7257
69600
6154
13411
10.4
54.1
45.9
226
195
49
275
115.9
82.2
17.8
25173
208000
-740
24433
12.1
100.0
0.0
116422
4,498,000
-4000
112422
2.6
100.0
0.0
809
6300
112
921
12.8
87.9
12.1
Saudi Arabia
5092
8760
10241
15333
58.1
33.2
66.8
Senegal
1702
39400
1282
2984
4.3
57.0
43.0
Sierra Leone
445
160000
324
769
0.3
57.9
42.1
Singapore
211
600
3599
3810
35.2
5.5
94.5
Slovakia
1818
30800
-1149
669
5.9
100.0
0.0
Slovenia
762
265000
1255
2017
0.3
37.8
62.2
Somalia
914
13500
138
1052
6.8
86.9
13.1
South Africa
14890
50000
6334
21224
29.8
70.2
29.8
Spain
30968
111300
17348
48316
27.8
64.1
35.9
Sri Lanka
10410
43200
1333
11743
24.1
88.6
11.4
Sudan
17800
154000
-5159
12641
11.6
100.0
0.0
518
200000
-31
487
0.3
100.0
0.0
Sweden
2990
180000
-220
2770
1.7
100.0
0.0
Switzerland
1146
50000
2045
3191
2.3
35.9
64.1
Syria
10907
53700
-8414
2493
20.3
100.0
0.0
Tajikistan
14950
101300
49
14999
14.8
99.7
0.3
Tanzania
1193
89000
606
1799
1.3
66.3
33.7
Thailand
35042
179000
-39010
-3968
19.6
100.0
0.0
Togo
115
12000
598
713
1.0
16.1
83.9
Trinidad & Tobago
163
5100
707
870
3.2
18.7
81.3
Tunisia
3391
9000
6048
9439
37.7
35.9
64.1
Turkey
36237
193100
1206
37443
18.8
96.8
3.2
Niger
Oman
Portugal Qatar Romania Russia Rwanda
Suriname
58
Country
Water withdrawal (106 m 3)
Turkmenistan
Water Net virtual 1 availability water import (106 m 3) (106 m 3)
Water footprint (106 m 3)
Water scarcity (%)
Water selfsufficiency (%)
Water dependency (%)
26186
72000
139
26325
36.4
99.5
0.5
UAE
657
797
2282
2939
82.4
22.4
77.6
Uganda
217
66000
-338
-121
0.3
100.0
0.0
UK
11929
71000
6390
18319
16.8
65.1
34.9
Ukraine
34623
231000
-1779
32844
15.0
100.0
0.0
Uruguay
4325
124000
-998
3327
3.5
100.0
0.0
492259
2,478,000
-168000
324259
19.9
100.0
0.0
Uzbekistan
91842
129600
434
92276
70.9
99.5
0.5
Venezuela
4446
1,317,000
4031
8477
0.3
52.5
47.5
30851
376000
-2596
28255
8.2
100.0
0.0
Yemen
3397
4902
1416
4813
69.3
70.6
29.4
Yugoslavia
4248
265000
-1
4247
1.6
100.0
0.0
Zambia
1759
116000
-38
1721
1.5
100.0
0.0
Zimbabwe
1527
20000
-340
1187
7.6
100.0
0.0
3696312
50547567
USA
Viet Nam
Grand total
Table 6.2. Countries categorised into different levels of water self-sufficiency (data for 1995). Level of water self-sufficiency 0-20% Congo Djibouti Gambia Haiti Jordan Singapore Togo Trinidad Tobago
20-50 %
50-70%
70-90%
90-99 %
100%
Algeria Belgium Cape Verde Fiji Kuwait Netherlands Norway Oman Saudi Arabia Slovenia Switzerland Tunisia UAE
Bahrain Bangladesh Benin Colombia Comoros Costa Rica Côte d'Ivoire El Salvador Gabon Ghana Ireland Israel Jamaica Japan Kenya Korea (Rep.) Lebanon Malaysia Mauritius Morocco Mozambique Portugal Senegal Sierra Leone Spain Tanzania UK Venezuela
Albania Angola Bhutan Cambodia Egypt Eritrea Ethiopia Germany Guinea-Bissau Honduras Iceland Indonesia Italy Latvia Liberia Libya Mexico New Zealand Niger Nigeria Peru Poland Qatar Rwanda Somalia Southern Africa Sri Lanka Yemen
Afghanistan Armenia Azerbaijan Belarus Bosnia Burundi Chad Chile China Cuba Estonia Georgia Iran Iraq Korea Kyrgyzstan Laos Lithuania Madagascar Mali Mauritania Nepal Nicaragua Panama Tajikistan Turkey Turkmenistan Uzbekistan
Argentina Australia Austria Bolivia Brazil Bulgaria Burkina Faso Cameroon Canada Central Africa Croatia Czech Rep Denmark Dominican R. Ecuador Finland France Greece Guatemala Guyana Hungary India Kazakhstan Macedonia
59
Malawi Moldova Mongolia Myanmar Pakistan Paraguay Philippines Papua/NG Russia Syria Slovakia Suriname Sweden Thailand Uganda Ukraine USA Vietnam Yugoslavia Romania Sudan Uruguay Zambia Zimbabwe
6.2. The relation between water scarcity and water dependency
One would expect that in general terms there is a positive relationship between water scarcity and water dependency, because high water scarcity will make it attractive to import virtual water and thus become water dependent. One would logically suppose: the higher the scarcity within a country, the more dependency on water in other countries. To test this hypothesis, all countries of the world have been plotted in a scarcitydependency graph. The result is shown in Figure 6.1. Surprisingly, there seems to be no relation as hypothesised. Let us for simplicity schematise the scarcity-dependency graph into four areas or ‘classes’. See Figure 6.2. In Table 6.3 we can see that most of the countries fall in class I.
100 90 80 70 60 50 0
10
20
30
40
60 *
50
70
80
90
100
110
120
40 30 20 10 0 Water scarcity
Figure 6.1. Water dependency versus water scarcity for all countries of the world (1995).
Water dependency 100 Class II
Class III
50
Class IV
Class I
0
100
50
Water scarcity Figure 6.2. Four classes in the scarcity-dependency graph. The grey-shaded areas refer to combinations of water scarcity and water dependency that can difficult be understood at first sight: high water scarcity but low water dependency, and low water scarcity but high water dependency.
60
Table 6.3. Position of countries in the scarcity-dependency graph. The grey-shaded countries fall in one of the grey-shaded areas of Figure 6.2. Class I
Class II
Class III
Class IV
Angola
Costa Rica
India
Mexico
South Africa
Algeria
Belgium
Afghanistan
Albania
Cote d'Ivoire
Indonesia
Moldova
Spain
Cape Verde
Jordan
Azerbaijan
Argentina
Croatia
Italy
Mongolia
Sri Lanka
Congo
Saudi Arabia
Bahrain
Armenia
Cuba
Iraq
Morocco
Sudan
Djibouti
UAE
Egypt
Australia
Czech Rep.
Ireland
Mozambique
Suriname
Fiji
Iran
Austria
Denmark
Jamaica
Myanmar
Syria
Gambia
Israel
Bangladesh
Dominican R.
Japan
Nepal
Sweden
Haiti
Pakistan
Belarus
Ecuador
Kazakhstan
New Zealand Tajikistan
Kuwait
Qatar
Benin
El Salvador
Kenya
Nicaragua
Tanzania
Netherlands
Uzbekistan
Bhutan
Eritrea
Korea (DPR)
Niger
Thailand
Norway
Yemen
Bosnia
Estonia
Korea (Rep.)
Nigeria
Turkey
Oman
Bolivia
Ethiopia
Kyrgyztan
Panama
Turkmenistan Singapore
Brazil
Finland
Laos
Papua/NG
Uganda
Slovenia
Bulgaria
France
Latvia
Paraguay
UK
Switzerland
Burkina Faso Gabon
Lebanon
Peru
Ukraine
Togo
Burundi
Georgia
Liberia
Philippines
Uruguay
Trinidad
Canada
Germany
Libya
Poland
USA
Tunisia
Cambodia
Ghana
Lithuania
Portugal
Venezuela
Cameroon
Greece
Macedonia
Romania
Vietnam
Madagascar
Central Africa Guatemala
Russia
Yugoslavia
Chad
Guinea-Bissau Malawi
Rwanda
Zambia
Chile
Guyana
Malaysia
Senegal
Zimbabwe
China
Honduras
Mali
Sierra Leone
Colombia
Hungary
Mauritania
Slovakia
Comoros
Iceland
Mauritius
Somalia
61
7. Concluding remarks This study was limited to virtual water trade related to crop trade between nations. Also other goods contain virtual water, for instance meat, diary products, cotton, paper, etc. In order to get a complete picture of the global virtual water trade flows, also other products than crops have to be taken into account. For instance, the virtual water trade balance of the Netherlands drawn in the current study suggests that this country has an incredibly high net import of virtual water, due to the large import of feed for the Dutch bio-industry. The balance will look quite differently if we would take into account the export of virtual water that relates to the export of meat from the Netherlands.
As stated in the introductory chapter, the current study is primarily a data report, aimed at disclosing the numbers. A next step is of course to interpret the results and ask the question why the global virtual water trade flows are as they are. What are the explanatory factors behind changes in national virtual water trade balances? What is for instance the relative importance of year-to-year fluctuations in agricultural yields, subsidies in agriculture, national water scarcity, the development of domestic demand for agriculture products? Another next step is to go beyond ‘explanation’ and to study how governments can deliberately interfere in the current national virtual water trade balances in order to achieve a higher global water use efficiency.
Knowing the national virtual water trade balance is essential for developing a rational national policy with respect to virtual water trade. But for some large countries it might be as relevant to know the internal trade of virtual water within the country. For China for instance, relatively dry in the north and relatively wet in the south, domestic virtual water trade is a relevant issue.
The method used for the calculation of the virtual water content of different types of crops has a few weak points. As explained, the crop water requirement estimates used in this study are conservative on the one hand (due to the water losses that are not taken into account), but they are overestimates on the other hand (because they are based on the assumption of optimal growth conditions, an assumption which is generally not met in reality). Improvements to the calculated figures can be made if we could make better estimates of actual specific water use per crop.
63
References Allan, J.A. (1997) ''Virtual water': A long term solution for water short Middle Eastern economies?' Occasional Paper 3, School of Oriental and African Studies (SOAS), University of London.
Allan, J.A. (2001) The Middle East water question: Hydropolitics and the global economy I.B. Tauris, London.
Allen, R.G., M. Smith, A. Perrier, and L.S. Pereira (1994a) An update for the definition of reference evapotranspiration ICID Bulletin 43(2): 1-34.
Allen, R.G., M. Smith, A. Perrier, and L.S. Pereira (1994b) An update for the calculation of reference evapotranspiration ICID Bulletin 43(2): 35-92.
Allen, R.G., L.S. Pereira, D. Raes, and M. Smith (1998) Crop evapotranspiration: Guidelines for computing crop water requirements, FAO Irrigation and Drainage Paper 56, FAO, Rome, Italy.
Clarke, D., M. Smith, and K. El-Askari (1998) CropWat for Windows: User guide, Version 4.2, www.fao.org.
Earle, A. (2001) 'The role of virtual water in food security in Southern Africa' Occasional Paper 33, School of Oriental and African Studies (SOAS), University of London.
Gleick, P.H. (ed.) (1993) Water in crisis: A guide to the world’s fresh water resources, Oxford University Press, New York, USA.
Nyagwambo, N.L. (1998) ''Virtual water' as a water demand management tool: The Mupfure river basin case' MSc thesis DEW 045, IHE Delft, the Netherlands.
Postel, S.L., Daily, G.C., and Ehrlich, P.R. (1996) ‘Human appropriation of renewable fresh water’ Science 271:785-788.
Rockström, J. and L. Gordon (2001) ‘Assessment of green water flows to sustain major biomes of the world: implications for future ecohydrological landscape management’ Phys. Chem. Earth (B) 26: 843-851.
Shiklomanov, I.A. (ed.) (1997) Assessment of water resources and water availability in the world, Comprehensive assessment of the freshwater resources of the world, World Meteorological Organisation, Geneva.
Smith, M., R.G. Allen, J.L. Monteith, A. Perrier, L.S. Pereira, and A. Segeren (1992) ‘Report on the Expert Consultation on revision of FAO methodologies for crop water requirements’, FAO, Rome, Italy, 28-31 May 1990.
65
Wackernagel, M., Onisto, L., Linares, A.C., Falfan, I.S.L., Garcia, J.M., Guerrero, I.S., and Guerrero, M.G.S. (1997) Ecological footprints of nations: How much nature do they use? - How much nature do they have? Centre for Sustainability Studies, Universidad Anahuac de Xalapa, Mexico.
Wackernagel, M. and Rees, W. (1996) Our ecological footprint: Reducing human impact on the earth New Society Publishers, Gabriola Island, B.C., Canada.
Wichelns, D. (2001) 'The role of 'virtual water' in efforts to achieve food security and other national goals, with an example from Egypt' Agricultural Water Management 49:131-151.
Yegnes-Botzer, A. (2001) 'Virtual water export from Israel: Quantities, driving forces and consequences' MSc thesis DEW 166, IHE Delft, the Netherlands.
66
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium-Luxembourg Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Bahrain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Côte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
Banana 6800 6610 13690 9400 5840 11380 9760 6570 7120 8970 7120 7120 8130
Barley Bean dry Bean green 3770 3850 3540 5420 3970 4250 3420 8040 4260
Grapes Groundnut 6470 3890 12640 3790 14360 7370
Maize 3340 2160 6860
Mango 12680 21660
3400 5520 4510 3640 3560 4030 3560 3560 3790
2390 5920 5010 4140 2700 5290 2700 2700 4420
2500 4200 3390 2120 2200 2670 2200 2200 2760
6780 12510 10200 6530 3970 9030 3970 3542 7790
3550 7290 6060 3540 3180 5930 3180 3180 5240
3290 6780 5640 3250 3170 4380 3170 3170 4890
11400 21190 17430 11450
7050 9250 7120 3520 7010 16700 7260
3520 4180 3560 2780 3270 3420 3490
3450 4620 2700 2700 3450 3500 4200
3260 3190 2200 2120 2500 2740 2460
7640 10110 3970 2690 7410 9400 6290
4600 5570 3180 3400 4280 4450 4940
3350 5180 3170 3120 3980 4110 4620
13060 17000
5940 3520 18840 12510 7730
2960 2780 4310 2870 4220
2350 2700 2950 7180 3970
2470 2120 3570 3510 2250
7260 3110 11120 13010 7640
3430 3400 4200 6140 4830
3170 3120 3850 5700 3480
7120 13690 16810 7070 7410 13330 18060 7120 19640 9860 7930 22850 5580 5180 6560 18380 14340
3560 3420 4440 3620 3580 2870 5140 3560 4600 4520 4110 5210 2540 4100 3120 4290 3220
2700 8040 4110 3050 3660 2860 5600 2700 4830 5050 4000 5740 2620 4330 3040 3450 2910
2200 4260 3480 3470 2740 2290 3760 2200 3540 3400 3200 4120 2270 4120 2460 3580 2630
3970 14360 9130 8570 7690 7470 9170 3970 10680 10360 8340 15070 8270 5200 7390 10550 8110
3180 7370 5440 5690 4650 3660 7150 3180 6150 6080 5110 7150 3740 4960 3940 4690 3830
3170 6860 5060 4470 4330 3390 6690 3170 5720 5660 4760 6610 2510 3500 3660 4330 3540
6300 16280 5530 9430 8670 7120 7120 22760 9480 9481 6290 9680 8720 14100 7120 19170 2050
3880 3480 4350 4270 5050 3560 3560 6250 4330 4270 3050 5620 3930 3040 3560 4080 1030
4000 3310 3330 4900 5200 2700 2700 6230 4840
7000 9220 5770 9790 7650 3970 3970 12020 10020
4080 4280 5370 5820 6530 3180 3180 8060 5820
2970 3960 2460 5410 6060 3170 3170 7520 5410
2680 4520 4080 3100 2700 4470 1230
3000 2830 3530 3190 4180 2200 2200 4660 3260 3260 2480 4200 3090 2400 2200 3170 1040
7440 10250 11080 7890 3970 10550 3600
3680 6930 5060 3960 3180 5600 1880
3410 4490 4690 3670 3170 5190 1410
7120 7120 8380 11930 21520 7120 7120 16280 6610
3560 3560 4300 2630 4130 3560 3560 3480 5420
2700 2700 3730 2570 5220 2700 2700 3310 3970
2200 2200 3430 2100 3110 2200 2200 2830 4250
3970 3970 8870 6680 11750 3970 3970 9220 12640
3180 3180 5220 3320 6230 3180 3180 4280 3790
3170 3170 4860 3070 5860 3170 3170 3960 2160
8520 6300 15280 17740
3940 3880 3000 3450
4320 4000 3200 3950
2980 3000 2390 2690
8910 7000 8600 9880
5260 4080 4020 4880
4890 2970 3710 4520
Appendix I - p.1
17370
13820
12540 11530 11650 11350 16950 19570 13810
21660 15300 14130 13030 12080 16590 17880 17680 13970 21320 12250 10760 12110 16600 12980
10940 14730 16830
20810 17080 11880 20110 16630 12780 17430 6630
14620 10810 19580
14730
15200 10940 13840 16100
Millet 4580 2160 5530
Palm 11910
3360 4800 3820 2500 3690 4210 3690 3690 2580
10560 19600 16130 10550
3370 3910 3690 2720 2810 3680 1850
19630
15920 5140 12740 12190 15770 5140 11600 14100 10670
2380 2720 3050 4580 2940
10520 15700 17700 12780
3690 5530 4190 3010 2990 2980 5680 3690 4990 3860 4090 6070 2140 2930 3130 3560 3030
19630 14080 13190 12020 11230 15220 5140 16560 16360 13000 22720 11480 9980 11210 15370 12050
2000 3460 3050 3530 5100 3690 3690 6340 3720
12250 13700
3390 4210 4250 3230 3690 4670 2210
11000 18570 14570 11890
3690 3690 3810 2680 5510 3690 3690 3460 2160 3330 2000 3380 4170
15580
19130 15830
16210 4590
7080 13450 10040 18310 7080 13700
14060 12250 12920 15040
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Réunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Banana 7960 8230 6300 7120 7120 8510 8640 13070 14920 7120 13070 5530 9500 5400 8740 7720 8600 16780
Barley Bean dry Bean green 4120 3590 3270 3900 4270 2930 3880 4000 3000 3560 2700 2200 3560 2700 2200 3780 5510 5190 4180 3920 3020 8800 4160 1880 8530 3280 3560 2700 2200 8800 4160 4350 3330 3530 4400 4880 3310 3650 3070 2980 1910 5120 2470 3700 3510 3380 3200 2672 3370 3090 2800
Grapes Groundnut 8180 5020 8470 5220 7000 4080 3970 3180 3970 3180 11320 6930 9680 5010 13240 5980 14990 6180 3970 3180 13240 5980 5770 5370 9800 5910 5100 4620 9060 4340 8890 5340 3970 9680 4020
Maize 4680 4860 2970 3170 3170 4720 4850 6350 5710 3170 6350 2460 5500 3160 4030 4470 6420 3710
Mango 13620 14590 10940
Palm 12510 13460 12250 5140
15140
Millet 3420 3110 2000 3690 3690 5180 4160 3960 4400 3690 3960 3050 3610 2910 3220 3530 3180 3260
19720 15710 24940 21620 24940 16820 10540 13550 14730
18460 14500 22610 19300 7080 22610 9740 15550 9500 12240 13710 14120
6500
2460
3870
2980
5290
3370
2190
9880
3560
9230
17850 6840 7120 7560 13510 14220 10520 7120 7120 7010 20580 12380 14430 7810 8440 23300
3000 3040 3560 1710 2960 3120 2550 3560 3560 3020 5130 3430 3520 3560 4250 4270
8170 3170 2700 4300 2400 3100 6140 2700 2700 3820 4340 3880 2600 3640 3770 4900
4510 2960 2200 2040 2690 2470 3200 2200 2200 2560 4170 2490 2980 3180 3560 3380
18220 7650 3970 7840 8250 7940 11000 3970 3970 6420 11550 6270 8230 8720 9880 13140
8210 4520 3180 3590 2500 3980 5540 3180 3180 3660 5850 4900 3670 4950 5850 6010
7620 3670 3170 3330 2280 3690 5150 3170 3170 2270 4530 4590 3350 4250 5100 5560
24720 12770
23960 11880
11140 18650 11380 13030 14460 16200 21100
5980 3170 3690 2670 2300 3230 4150 3690 3690 3770 4450 3950 2670 3690 3860 5190
8530 12530 15160 5820
3820 6630 3120 3170
4210 6310 2370 3880
3000 5830 2710 2920
9270 14400 8970 6330
5160 9240 3250 4580
4790 8620 2980 3430
15560 23750 13620 12060
3600 7350 2490 3190
14420 22090 12670 11130
7120
3560
2700
2200
3970
3180
11160 7560 15170 7410 19090
5120 2400 3460 3580 4350
5710 4150 2520 3660 3000
3860 2570 2970 2740 3780
11720 8080 8880 7690 11290
6880 4300 3510 4650 4260
3170 4200 6400 4010 3230 4330 3910
8340 7120
3330 3560
4380 2700
4040 2200
8170 3970
4970 3180
6570 9130 23300 23110
3640 3900 4270 4440
4140 4420 4900 4620
2120 3020 3380 3660
6530 10710 13140 14500
2200 11130 11900 7320
3970 4490 4520 4460
3180 5960 7100 3380
3170 4300 4760 2820
7000 7880 8170 7840 7120 9000 12520 8530 15310 7120 7120
3530 4000 4170 3380 3560 3590 2870 4020 3560 3560 3560
3150 2460 3450 3860 2700 3650 7180 4330 8430 2700 2700
15610 12420
4050
3900
11780 12080 12900 16580
10650 11200 11980 15020
10290 17200 10460 12030 13430 15050 19750
3690 20000 12510 13660 13030 17160
4380 3300 2610 2990 3090
18510 11420 12660 12020 15900
2960 3170
14580
4060 3690
13670 7080
3540 5200 6010 5780
3250 4820 5560 5310
11450 17660 21100 22660
2500 4230 5190 4950
10550 16470 19750 21240
3600 12450 9900 9340
3690 7040 4540 4670
4010 6560 2430 4520
8340 19810 18370 15160
3290 5490 6490 3470
3520 18230 17150 13460
2630 3560 3400 3320 2200 2960 3510 3040 4420 2200 2200
8040 11140 9200 8250 3970 4280 13010 8740 15980 3970 3970
4390 4180 4940 4630 3180 4340 6140 5340 7750 3180 3180
4140 3850 4590 3630 3170 4270 5700 4970 7200 3170 3170
13070 16420 14800 14020
3290 3650 3390 3800 3690 3610 4580 3250 5770 3690 3690
12090 15290 13650 13040
3180
9070
5070
4710
15010
3990
13860
Appendix I - p.2
19570 14980 24010
17700 13840 21730 7080
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org). Banana Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
9540 14220 19050 14220 7810 7580 7352
Barley
5640 3120 4560 3120 3560 3570
Bean dry
4080 3100 4450 3100 3640 3470
Bean green
3600 2470 3580 2470 3180 3000
Grapes
10060 7940 10490 7940 8720 8550
Groundnut
6390 3980 5780 3980 4950 4800
Maize
4120 3690 5370 3690 4250 4240 4240
Mango
18500 12900 17310 12900 14460 14070
Millet
3940 3230 4580 3230 3690 3570
Palm
16850 11980 16010 11980 13430 13040 12000
23110 8970 6230 8970 7520 15800 8740 7120 7120 9540 15340 16780 12440 8390 15440 9430 8110 7880 6700
4030 3450 5590 3080 5750 4400 3560 3560 5640 1740 3370 2440 4700 3160 4270 3710 1260 5150
5290 4200 5640 3620 8280 3950 2700 2700 4080 8790 3090 2180 4370 3130 4900 3950 4790 3820
2670 2450 4570 3030 5620 3490 2200 2200 3600 3270 2800 2050 4260 2550 3190 2860 1900 3500
9030 7430 8280 8060 17110 9260 3970 3970 10060 15350 9680 7260 8780 8760 9790 8890 8030 7330
5930 4090 6870 4480 9250 5400 3180 3180 6390 6240 4020 2850 5740 4000 5820 4860 3500 4390
4380 3800 6640 3690 8620 5030 3170 3170 4120 5760 3710 2620 4460 3700 5410 4520 3240 1540
16780 18360 9540 7120 7120 6570 5600
3370 3730 5640 3560 3560 3640 2760
3090 3600 4080 2700 2700 4140 2430
2800 3040 3600 2200 2200 2120 2580
9680 9070 10060 3970 3970 6530 8840
4020 5070 6390 3180 3180 3540 2690
3710 4270 4120 3170 3170 3250 2450
15140 16590 18500
6560 7410 7050 9840
3120 3580 3390 4570
3040 3660 3180 5060
2460 2740 3160 3440
7390 7690 8170 10180
3940 4650 5020 6140
9900 9310 5570 14220 18070 18470
3110 3590 4100 3150 4900 4060
5410 4810 4190 2960 3710 2750
3230 3340 3400 2550 4050 3570
10570 10160 4390 8010 10150 10990
5450 5490 4930 3850 5180 3910
Appendix I - p.3
17370 12130 13540 25900 15340
18500 22000 15140 11210 16870 13970 16830 14880 11730 12980
4210 3380 5620 3630 7180 3880 3690 3690 3940 4410 3260 2290 3950 3290 3530 3470 2530 2400
15920 11350 12580 24750 14130
16850 19600 14120 10460 15450 13020 15580 13800 10520 11760
11450 12590
3260 3770 3940 3690 3690 2500 2890
14120 15460 16850 5140 6340 10550 11780
3660 4330 4110 5720
12110 13030 13550 17440
3130 2990 3190 3800
11210 12020 12620 16120
5060 5100 4890 3570 4800 3580
16380 16130
4170 4270 4130 3080 3760 2860
14950 14810
12880 16380 16590
11960 15050 15400
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium-Luxembourg Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Bahrain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Côte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
Pepper 4200 3240 3520
Potato Sorghum Soybean Sugarbeet Sugarcane Sunflower Tobacco 2960 4450 5300 6960 12740 6300 5790 6640 5230 6870 8190 11640 6040 5730 6920 7550 5520 5710 23310 9100 5280
Tomato Vegetable 7640 4040 7700 4900 8350 4230
3690 5740 4570 4050 3130 5790 3130 3130 3120
4130 6880 5630 5290 3290 4680 3290 3290 4740
3260 5030 4070 4210 2600 4880 2600 2600 3830
4230 6660 5400 6020 3400 5810 3400 3400 3780
4850 8960 7530 6700 3990 5780 3990 3990 6550
11620 21000 17970 12850 12830 18520 12830 12830 14160
3710 6800 5770 3770 2990 5550 2990 2990 5050
3550 5710 4660 4090 2830 5350 2830 2830 3420
4610 8600 7280 4490 3740 6330 3740 3740 6320
3160 5480 4600 2430 2450 4490 2450 2450 3760
3420 4680 3130 3110 3370 4940 2250
3520 4070 3290 2610 5230 4230 4360
3270 3000 2600 2670 4280 3880 2890
5210 3970 3400 3450 5660 5730 2570
5270 5360 3990 3970 6930 6640 6180
13450 12930 12830 6670 17490 15540 11950
4030 3980 2990 2990 5370 4210 4730
4280 3440 2830 2840 4860 4620 4030
4830 5050 3740 3740 6810 6330 5860
3360 4560 2450 2440 3280 3550 3110
3520 3110 6570 3300 4400
4000 2610 4260 5750 4980
3150 2670 3010 6530 3920
4330 3450 6290 4570 5330
4980 3970 7770 5640 6170
12070 6670 17270 21130 14250
3280 2990 3360 8100 4120
3520 2840 5380 4340 4210
4080 3740 5940 6990 5120
2480 2440 5230 3460 3160
3130 3520 4360 3790 3830 3880 3410 3130 5090 4630 4820 7850 4610 4070 3790 5830 4310
3290 6920 5400 4650 3780 3570 7000 3290 6000 5650 5050 6880 5410 4320 3940 4690 3780
2600 7550 3830 2920 2950 3060 5140 2600 4900 4180 3980 6540 4290 4450 3090 3490 3050
3400 5520 4430 5460 3780 4400 4340 3400 5830 5550 5190 9500 5740 5580 4020 5840 4650
3990 5710 5340 4710 4580 5140 4530 3990 6770 7570 6040 10880 6640 6530 4790 7100 5510
12830 23310 16240 14300 13320 12470 18070 12830 18780 18190 14500 22930 13830 9870 12690 17120 13400
2990 9100 4560 3490 3590 3380 6200 2990 5580 5830 4550 7010 4330 4730 3550 3940 3390
2830 5280 3610 4470 3360 3560 3000 2830 4640 4810 4280 7590 3740 4650 3240 4900 3810
3740 8350 5030 4350 4620 4860 5450 3740 6830 7370 5690 10680 5250 6220 4510 5930 4970
2450 4230 3620 2890 3080 2850 2950 2450 3860 4720 3770 5440 3120 3710 2920 4600 3270
2380 4920 2590 4240 6000 3130 3130 5200 4470
3580 4200 5500 5350 6300 3290 3290 7280 5410
2980 3560 4340 3950 4950 2600 2600 5810 4100
2790 5460 5600 5250 6150 3400 3400 5620 5440
3320 6430 6720 7290 7790 3990 3990 6620 7250
8600 15150 10920 17240 14790 12830 12830 22320 17540
3530 3910 4940 5670 5700 2990 2990 6930 5600
3000 4460 4730 4630 5390 2830 2830 4430 4730
4280 5890 6300 7160 7330 3740 3740 6940 7080
2620 3640 4070 4630 4630 2450 2450 4350 4610
3730 4570 5060 4110 3130 5170 1730
4060 4730 4910 3860 3290 5410 2400
3190 4790 4550 3280 2600 4840 2470
4280 7790 5980 4630 3400 6250 2780
5000 7580 6230 5420 3990 7150 3060
12570 21420 17210 13230 12830 18090 5660
3490 7380 4770 3640 2990 5320 2420
3440 6110 4990 3760 2830 4940 1910
4380 5890 6110 5100 3740 7280 3550
2760 5170 4320 3000 2450 3720 960
3130 3130 3970 3470 5680 3130 3130 4920 3240 4400 3990 2380 4510 5020
3290 3290 4210 3250 6010 3290 3290 4200 6640
2600 2600 3290 2710 5940 2600 2600 3560 5230
3990 3990 5250 4530 8340 3990 3990 6430 8190
2830 2830 4390 3130 5830 2830 2830 4460 5730
3740 3740 4740 4240 9000 3740 3740 5890 7700
2450 2450 3060 2680 3670 2450 2450 3640 4900
3570 2980 3640 4490
12830 12830 14890 11200 20220 12830 12830 15150 11640 12000 15650 8600 14160 16540
2990 2990 3710 3050 6390 2990 2990 3910 6040
4920 3580 3880 4690
3400 3400 4500 3860 7500 3400 3400 5460 6870 4730 4730 2790 5420 6240
4980 3530 3900 4820
4110 3000 4350 4950
6290 4280 6030 7140
4020 2620 3130 3420
6500 3320 6220 7080
Appendix I - p.4
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Réunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Pepper 3600 3730 2380 3130 3130 4720 5150 6170 2310 3130 6170 2590 4330 2790 2100 4140 2600 5430
Potato Sorghum Soybean Sugarbeet Sugarcane Sunflower Tobacco 3740 2920 3980 4670 13740 3370 4080 4870 3260 4340 6440 15040 4890 3780 3580 2980 2790 3320 8600 3530 3000 3290 2600 3400 3990 12830 2990 2830 3290 2600 3400 3990 12830 2990 2830 4920 5030 6910 8250 20300 6490 6870 5170 4030 4890 6180 16480 4440 3980 4780 3450 5820 6380 24710 9270 7000 5590 7840 3690 5460 23840 10210 3900 3290 2600 3400 3990 12830 2990 2830 4780 3450 5820 6380 24710 9270 7000 5500 4340 5600 6720 10920 4940 4730 5500 3860 5130 7330 17320 5610 4470 2410 2500 4580 5260 10100 4130 3940 4050 4670 3140 3680 14640 5770 3030 4680 3420 5400 5450 15170 4080 4420 2610 3400 3990 2990 4120 3940 3470 6000 7070 15400 3890 4950
2360
2300
3460
4270
5610
10600
4480
3350 3580 3130 2010 5230 4100 2700 3130 3130 3410 6040 3300 4630 4220 4720 6950
7550 3860 3290 3360 2600 3900 5200 3290 3290 2480 5850 4790 3670 4480 5350 5750 4200 4890 9070 3250 4260
8070 3080 2600 3860 2680 3280 5720 2600 2600 3660 4170 3630 2540 3580 3740 5730
5400 4740 3400 2680 4810 4600 4130 3400 3400 3830 5950 4180 4430 5110 5700 8610
6760 4900 3990 3470 6080 5390 4470 3990 3990 5720 7270 4370 5470 5640 5900 9790
3870 6890 2600 3620
5110 8940 5440 4550
6370 7980 6620 4700
27860 13180 12830 12750 12130 13360 17810 12830 12830 12010 19500 12380 13460 15020 16470 21490 15672 16050 24430 13760 12300
12150 3680 2990 4840 3480 3650 6940 2990 2990 4350 4860 4340 3200 4190 4350 6050 5670 4870 7290 2960 3980
2600
3400
3990
12830
5350 2570 5150 3830 6770
3290 3200 6400 4110 3550 3780 4330
4730 4000 2590 2950 3000
6270 3560 5030 3780 6370
8550 3570 6170 4580 7930
3320 3130
3100 3290
3930 2600
6490 3400
4050 5080 6950 8130
5290 4900 5750 5560
4210 5000 5730 5620
3400 4880 4360 5940
3990 6810 2640 6130
4110 5400 4210 3780 3130 4220 3300 3900 3940 3130 3130 4490
4310 6920 5400 4250 3130
Tomato Vegetable 4320 2830 6160 3810 4280 2620 3740 2450 3740 2450 7470 5460 5830 3620 8700 4400 7130 2880 3740 2450 8700 4400 6300 4070 7080 4450 5270 2810 4940 2400 5040 3380 6200 6250 3920
3550
5060
3790
7000 5460 3890 2830 2530 4250 3730 3950 2830 2830 3150 4950 3360 3740 4180 4680 6880
9410 4530 3740 4090 4110 5100 6280 3740 3740 5290 6270 3900 4390 5240 5490 9630
4170 3050 2450 2020 4190 3050 3160 2450 2450 3620 4960 2560 3800 3460 3590 4630
4370 7580 4620 3840
6180 10290 5210 5270
4090 6590 4060 3510
2990
2830
3740
2450
20580 13270 13960 13320 17490
6580 4720 3020 3590 3380
5440 3240 4270 3360 5500
8320 4850 4870 4620 6090
5330 2680 4070 3080 5360
6490 3990
15050 12830
5160 2990
5370 2830
5850 3740
4350 2450
6020 6590 8610 9130
6700 6580 9790 11160
12850 18050 21490 22830
3770 5250 6050 5810
4090 5660 6880 7870
4490 6740 9630 10360
2430 4990 4630 5490
7000 5990 6300 4830
2990 6300 8140 5870
2830 6440 10230 7200
4580 20790 19660 16670
2450 6810 8180 5620
2990 5520 6540 3540
3740 7900 9330 6960
4680 6920 4500
4380 6720 4640 3840 3290 4440 5750 5010 7240 3290 3290
3190 5330 3640 3680 2600 3500 6530 3380 8210 2600 2600
4240 7550 4690 5290 3400 4590 4570 4490 5720 3400 3400
4950 8480 5810 5870 3990 5400 5640 6560 6640 3990 3990
13630 18060 15340 14600 12830 8680 21130 15470 29090 12830 12830
3450 5620 4570 4340 2830 3820 4340 3890 5460 2830 2830
4650 6110 4970 5400 3740 5060 6990 6250 8810 3740 3740
2950 3460 3130 3720 2450 3300 3460 3870 4350 2450 2450
5000
3790
4760
5670
15770
3590 5020 3940 4460 2990 4030 8100 4960 10090 2990 2990 5810 4400
3880
5330
3530
Appendix I - p.5
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org). Pepper Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Potato
Sorghum
Soybean
Sugarbeet Sugarcane
Sunflower
Tobacco
Tomato
Vegetable
5420 4100 5230 4100 4220 4230
4820 3900 5680 3900 4480 4480 4480
4680 3280 4410 3280 3580 3460
6910 4600 5610 4600 5110 4820
6900 5390 6660 5390 5640 5420
18270 13360 18150 13360 15020 14620 13564
6360 3650 5080 3650 4190 3980
6120 3730 4560 3730 4180 3940
7020 5100 6290 5100 5240 5060
4630 3050 4200 3050 3460 3280
5790 3960 6600 3890 6370 4350 3130 3130 5420 2130 5430 4210 5200 4700 4240 4160 1470 4210
4680 4140 6930 3900 8910 4510 3290 3290 4820 5630 3940 3000 5310 3900 5350 4630 3200 4390
4880 3280 5460 3520 8110 3520 2600 2600 4680 8100 3470 2450 4120 3460 3950 3760 4200 5160
5810 4230 5100 4900 8150 5030 3400 3400 6910 3590 6000 4550 6330 5330 5250 4870 2260 5210
5780 4660 8450 5560 8820 5550 3990 3990 6900 5380 7070 5410 6990 6230 7290 6000 3030 5330
18520 12170 15790 14110 27190 15700 12830 12830 18270 24320 15400 11350 17390 14320 17240 15340 12850 12030
5550 3700 6270 4170 9430 4080 2990 2990 6360 10610 3890 2640 5540 3760 5670 4590 5370 5450
5350 3680 5920 4010 7190 4440 2830 2830 6120 3870 4950 3800 5150 4340 4630 4250 2290 5650
6330 4540 7910 5150 10400 5190 3740 3740 7020 7210 6250 4600 5950 5770 7160 5840 4020 5970
4490 3390 5140 3450 6060 3390 2450 2450 4630 2810 3920 3020 4600 3400 4630 3930 1740 3950
5430 5800 5420 3130 3130 4050 4500
3940 4520 4820 3290 3290 5290 5730
3470 3950 4680 2600 2600 4210 4550
6000 6430 6910 3400 3400 6020 6430
7070 7570 6900 3990 3990 6700 7210
15400 16960 18270 12830 12830 12850 14260
3890 4290 6360 2990 2990 3770 4190
4950 5290 6120 2830 2830 4090 4410
6250 6790 7020 3740 3740 4490 5030
3920 4180 4630 2450 2450 2430 2780
3790 3830 3760 4550
3940 3780 4300 5710
3090 2950 3090 4000
4020 3780 5040 5300
4790 4580 4950 7600
12690 13320 13910 17990
3550 3590 3700 5810
3240 3360 4120 4590
4510 4620 4570 7320
2920 3080 3060 4570
3460 4020 4810 4220 5240 6630
5200 5300 5070 3790 5250 3970
5130 4720 4010 3120 3380 2890
4550 4960 5240 4620 4840 6420
5090 5430 6160 5450 6030 7910
17430 16990 9200 13310 17220 16800
6130 5480 4610 3460 4040 3170
4100 4300 4370 3770 4050 5510
6150 6170 5770 5000 5010 6470
3400 3660 3770 3180 4580 5150
Appendix I - p.6
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium-Luxembourg Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Bahrain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Côte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
W.melon 5600 6130 6250
Wheat Cotton seed Cabbage 4350 7410 2700 8010 5900 6060 2930
3660 6630 5600 4670 2990 5750 2990 2990 4910
3540 5480 4440 3030 3740 4730 3740 3740 3120
5470 8960 7180 5110
3240 1180 3740 3020
8710 3880
3200 1600 1800 2780
3980 3880 2990 3000 5150 4960 4660
4260 4660 3740 3540 3270 4560 2470
6360 7380
3770 3000 5440 5190 4530
2920 3540 3830 4890 3320
6090
2990 6250 3830 3470 3450 3810 3420 2990 5040 5640 4490 8230 4240 4990 3430 5060 4030
3740 5900 3800 4260 3440 3520 4620 3740 5180 4570 4250 7770 3720 4040 3310 4070 3520
3280 4730 5020 5450 5780 2990 2990 4850 5400
2300 4180 6540 4340 8400 3740 3740 5530 4480
11020 7080
3680 6740 4580 4000 2990 5410 2170
3170 6380 4910 3690 3740 5450 1240
6000 11430 7900 5900 3880 8520 3730
2990 2990 4490 3340 6500 2990 2990 4730 6130
3740 3740 3470 3060 6810 3740 3740 4180 8010
6680 4910 10070 5600 3880 6440 10168
4830 3280 4690 5400
3900 2300 4350 5250
6280 4280 6310 7710
4970
5290 6840 4330
5940 5680 6660
6060 7400 6290 5480 5500 9710 4872 8920 7300 6590 11280 7660 6780 5670 6670 5620
4280 6440 6770
3660 1960 1800 2790 3500 2550 3200 1800 5150 2540 4000
Carrots
Cauliflower Cucumber
2470 3620 2790 3460 3960 2020 1720 4980 3610 3130 4580 3790 2970
Oats
Onion green
3000
6730
6100
4360
4150
5740
5330
6730 3760
6100 3410
5010 3000 4600 4860
4150 2300 3120
5740 3220
5330 2980 3200
3760 3760
3410
2220 3220
2980 2980
3000 3000
2300
4440
6120
5400
1960 2930 3960 3200 2860 3660 1642 4080 3760 3870 5270 3440 2250 2940 4640 3320
Lettuce
3670 3000
3190
4410
3850
3220
3000
5040
4840
2300
2980
4220
4720
5280
4110
5790
4450
3180 4560 4660
5090 4640 4910
3980 4410 3390
3730 3440 2860
5450 5470 3760
4860 4610 3600
3410
2670
3540
2160
2590
2590
3410
3000
2300
3220
2980
3410 3410
5620 3000 3000
4430 2300 2300
3220 3220
5040 2980 2980
3600 3600 5790
3100 4200
3410 3760 3760
4250 3860
3000
6240 5290
3890 5570
3220
3800 1760 1800 1960 3970 2610 3670 1960 1940 3620 3100 3290 3800 2300 3060 3360
3760 3600
4540 4540
3790 3790
3110 3110
3510 3510
3450 3450
3600
4540
3790
3110
3510 3510
3450
5510
6150
5670
3550
6500
5010
5080
5460
4200
3830
4020
5760
Appendix I - p.7
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Réunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
W.melon 4120 4780 3280 2990 2990 6390 4410 6860 5110 2990 6860 5020 5450 4170 3660 4040 5190
Wheat Cotton seed Cabbage 3180 6000 3690 3570 5840 3150 2300 4280 3740 1960 3740 6910 9190 3660 3950 7080 4080 6100 13080 3210 4780 4590 1560 3740 1960 6100 11920 4200 6540 8752 2800 4220 6810 3600 3760 6510 2700 3450 3690 1650 4330 6930 6440 3880 1800 4310 6210 3770
4400
3820
7020
6860 3640 2990 3030 4160 3980 4700 2990 2990 4390 5150 3410 3840 4150 4320 7450
6440 3840 3740 2850 3490 3710 4430 3740 3740 3380 4490 3320 2970 4150 4550 6950
6250 6210
4710 8080 4700 3930
4200 7650 3370 4030
6770 10440 4860 6270
2990 6360 3690 4350 3450 5510
3740 6460 5160 3480 3200 3440 3750
8270 4210 5020 5480 5970
5080 2990
5440 3740
8730 5600
4670 4910 7450 8300
3030 5450 6950 7220
5110 8180 9730 9540
6090 7240 3950
3672 5760 7040 5160
7660 10500 7290
3570 6220 4770 4410 2990 4040 5190 4850 6550 2990 2990
3410 4200 3600 4370 3740 5200 4890 3690 6170 3740 3740
5860 9910 7300 7410
4110
3960
7130
3470 3490 5920 4660
6620 8080 6760 5020 6930 7350 9730
Carrots
Cauliflower Cucumber
4540
4570 3790
3570 3110
6160
5090 5600 6260
6120 4390 8000
6010 3530 3920
6570 4910
4720
3790 6250 4720 5480 3990 5350
3110 2540 3870 4630 3310 4450
3510
4220 4680 6380 5450 4470 5820
5770 4860 5990
5200
3672
4590
4230
2530 1800
4220
4600
5150 2400 3890 3878
Oats
3600
4220
1720 1520 3950 3060 2200 1960 1960
Lettuce
3580
3510
5010 5720
4960
3600
4720
5480
5240
4620 3450 4400 4980 5780 4330 3450 4210 4300 5670 4230 5580
5600
3450 5100
4910
4590
3450 3220
6110
Onion green
3670
3000 3000
3510
5230
3940
4200
3700
3450 4760
6630 3450 3450 6030
4790
4460
4390 2590 3430 6030 3830 3280
4220
1960
6790 5680 6090 6790
5200
6780
4720
3000
2440 4110
5790
3190 5550 3450
4270 4350 4020 3200 5210
3800
4450
4030
3780
1960
3600
3410
3000
2300
3220
2980
2600 3020
6730
6100
4360
4150
5740 5120
5330 4480 8940 5130
6130
5570 5460
6200
5080 1960 4070
2300 4840
3780 6550 8650
4320
5150 4140 1960 2230 3300 3110
3760 4710
1960 1960 3730
Appendix I - p.8
4720 4650
3760
3790 3220
3000 3830
3150
3510 3980
3570 4410 4630 2980 3850
3000 3600
2300
3510 3510
2980 3570
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org). W.melon Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Wheat
Cotton seed Cabbage
6450 3980 4850 3980 4150 3950
5650 3710 4660 3710 4150 3890
8830 5920 8210 5920 6930 6560
5750 3650 6270 4130 7980 4540 2990 2990 6450 5140 5190 3940 5280 4610 5450 4430 2910 5880
4730 3450 8730 4020 7540 3830 3740 3740 5650 4810 4310 3100 5140 4110 4340 4090 2730 4270
8710 5090
5190 5560 6450 2990 2990 4670 5000
Cauliflower Cucumber
5400
5120
6200
3060 4026 1960 1960
5320 3670 3760
4850 4720
3000
4560 3440 3950
5960 4390
3040 4120
1960
3670
8830 4390 6210 4400 8010 6140 6770 6540 2750 8720
3650 1960 2840 3690 3320
4310 4740 5650 3740 3740 3030 3430
6210 7070 8830
4010 2660 3650 1960 2100 4050 2430
3430 3450 3670 5650
3310 3440 4020 4360
5670 5480 6350 7110
3030 3200 3760
4670 4740 4620 4000 4190 5560
4400 4480 5730 3580 3560 3800
5630 6310
2800 3270 2390 3210 4950 4990
6830 10140 6920
6210 5110 8640
5690 6860 5640
3650 4240
Carrots
Lettuce
Oats
5290 5840
4570
3410
4410 3510
4200 2980
5990 4210
3860 4960 3570
5100 6770
4460 6350 4350 6240
4720
3000
2300
3510
2980
4150 3670
4410
4150
4030
6020
5080
5110
4580 3430
5570
4620 2980 3950 4550
5210 4010
3460 2260 2150 2080
Onion green
4900 4140
5490 4200
2640
5610 6260
5940 3670 5400 3670 4220
6200 4720 5390
3670 5410 5080
5280 5490 3000 5280
3510 3110 4110
3510 6370 6110
4600 4400 5240
4030
5060
3920 3620
4160
4870 5220 5380 2980 5340 2980 5600 3450 4450 3450 2980 4280 3780
5410 4200
5570
Appendix I - p.9
4000
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org). Onion dry Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium-Luxembourg Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Bahrain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Côte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
Peas
Safflower
Spinach
Sweet potato
Artichoke
Citrus 8660
Rice 5900
14490
6620
4490
5970
6620 3970
4490 2730
5970 3370
7780 3000 11180 7680
6430 3700 2330
6430 3500
10850 4680
7680
8600 6200 8600 5900 5900
9400 3670 5480 3970
2730 2730 3600
3370
2330
3500
11630 4680
7670 4910 11420 13020 9400
2730
6530
4100
3970
2730
4910 8550 10380 7870
5760
6700 8200 8950 5900 5900 6780 7200 6570 6800
7600 5900
10300 8200 3000 5920
3400
8260 11190 6120
3280
6200
3430
12190 2570 9570 16780 8390 7360 8230 11220 8840
3350
3000
8770
3970
2730
3970 3970
5180 2730 3780
6670 5580
4020 4170 4020
5490 5680
3900
3370
2330
3370 3370
4400 2330 2330
3780 5260 6720 6800
4210 5420 4020
4960
3500
11370 9370 10940
4680
3500 3500
4680 4680
6810
3780 3780
5900 5900 14040 11660
10710 13800
3780 4020
5590 5590
7340 8450 5900
11500 9740
6940
6800
7340 6800 7200
8050 13650 11390 8740
6870 9600 8200 5900
11960 3320 4680 4680
3610 3610
4370 4370
7490 7490
4020 5590
3780
4680
3610
8190
5550
6820
4710
3370
5680
4370 5090
7490 11040
4250 9820 7380 13580 4250 10060 8370 10230 11940
5900 5900 6250 9600 5900 5900 9200 7820 9120 7650
9530 11120
Appendix I - p.10
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org). Onion dry Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Réunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
5590 6400
Peas
4130 3780 6020 3680 8210
5590 5170 6760
3780 8120 4190
5710
3560 5420
Safflower
Spinach
Sweet potato
Artichoke
4680
3610
4370
7490
8080 4850
7100 5670
18410
3190
3870 4260 3210
5620 4030 6820 5050
9200 5640
9550
Citrus 9130 9920 8260
Rice 8820
13600 12400 16300
9880 9300 10210
14800 7360 11460 7060 9010
3970 4570 6190
3760
3860
3570
13920
3520
3960
3970
4020 3780 3780
7030
4170
6220
4570 3900
5860
10290
5900 12000 6400 7600 8210
10370
6200 9230
6880
6570
17640 7600
3970
7920 6200
7820 8120 8810 11080
6200 8720 5900 5900
5900 5900
3320
12560 7710 8760 10100
5450
11200
8900
14610 7450
6000
4020 4800
6200
3260
10700
10620 16330 9250 10230
6410 7980
3790
5140
4200 5670 3670
3370
3000
13640 8450 9230
4810
12000 7620 8720
11560
3970
2730
3370
6620
4490
5970
8920
5500 5490
2930
3500 6430
6300
2730 6040
4680
3910 7680 12170 15680
13440 9530
5490 4970 3970 5450
4180
3970 3970
2730 3790
3790 4300
7580
6180
4550
5860 3500 4860
3120
11110 9960
5870 10180 16000
10420 12300 12600 5900 11670 10970 7620
7840 8230 8720 5900 6800
5900 5900
3370 10160
Appendix I - p.11
9800 5900
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org). Onion dry Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Peas
Safflower
Spinach
Sweet potato
5640 6140
16480
5740 3970
4600 3790
4520
6570
4010 5330 6200
5210 4200
8710
Artichoke
4830
5630 4600
11060 13790
6690
3790
7120 3970
8410
7140
3270 4640
7100 7910
3850 4800 4860
11600 10600
9570
8720 5900 5900
11750 8330 10520
3370
7260 8350 7600 12600 8900 5900
18830
5080
Rice
12400 11740
18220 10340
5320 3970
Citrus
3840
5860
14410 7670 11400 9570
12000 6200 6800 9600 7230
10170 7740 8610
9200 7200 7680
11360
9850 6200 9340 5900 8600 7680 6200
5300
7120 3790 4630
4500 3780 6200 3790 4750 4770
10170 6640
6130
6070
6800
2680 3620
6860
4910 7260 8560
3970
5140
5220
3770 3670
8830 9270 11870
4810
11000 10900 10520 8780 10940 11210
3490 4370 4490
Appendix I - p.12
7680 8720
8670 8960 9000 10340
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Banana Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Bahrain Brazil Brunei Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, D Congo, R Cook Islands Costa Rica Côte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
3.2
Barley Bean dry Bean green 1.2 1.8 1.1 1.2 0.9 0.5 3.7
2.5 9.7 11.0 2.6 19.7
2.2 9.3 14.3 5.6 24.0 18.8 5.2 16.5 11.2
16.0 4.3
2.3 1.3 1.9 4.7 1.0 0.9
1.6 2.5 0.9 1.3 2.7
0.6
0.7
1.5 7.4
0.9 3.4 1.0 0.7
1.0 1.0 0.6 2.6
1.0 2.0
2.3
0.7
2.6
0.8
4.6 14.4
0.4 0.9 3.2
3.7 2.5 2.2 0.6
1.0 12.3 33.2 37.5 1.8 4.5 15.9
2.0
0.6 1.6 1.4 1.3
2.1 3.9 5.2
3.6 7.0 5.1 12.3
0.6
16.6
3.3 1.4
1.2 0.9
4.4
1.0 1.6 0.6
3.7
0.7
0.5
1.0 2.5 2.6 12.2 2.1 1.1 4.1 1.6 2.2 3.9 0.3
15.8
1.8
2.8
7.4
3.3
1.0 1.0 0.8
3.8 1.4 1.1
5.0
4.3 18.9 7.2
7.6 3.6
3.0 2.0 4.0 24.5 29.3 3.8 9.5
2.5
0.9
1.1
1.2 1.0 1.1 1.0 4.0 1.1 1.1
3.4 0.4 1.5 1.3 1.3
14.0 5.0 8.0
0.8 0.5 2.6 0.9
6.2 1.5 12.5 2.9
12.0 12.0 4.0 19.2 11.0
1.2 0.7 3.5 1.0
2.2 0.8
4.6
3.3 4.0
1.1 1.3
12.0 1.7
1.0
2.5 4.1 9.0 0.8 1.7 1.5 2.2 6.7 1.4 9.3 1.0
5.8
0.6 0.9 1.3 2.7 1.0 0.7
2.3 11.2 11.1
7.2 9.3
5.2 1.7 8.5 8.2 11.1 2.9
3.5 16.4 9.3
3.0
Appendix II - p.1
1.1 1.0 1.1 0.3 1.1 1.3 2.9
0.9 1.3 1.2
1.8 1.4 1.0
14.1
0.7
8.7
9.9
1.1
2.2
1.2
16.7
4.8 4.9
1.0 0.4
8.0
12.5 12.7
1.7
14.7 19.2
16.8
0.6
5.0 12.5
45.0
6.3
1.6
11.2
8.3 0.3
6.3
11.2 11.4
0.7 1.1
3.0
11.4 12.4 12.9
1.5
0.2
1.4
1.6 0.7 8.5 4.9 1.8 2.4 0.8 0.7
11.4
0.9
6.2 1.0
1.1 1.0 2.0 3.0 1.4 1.0 0.8 1.1
Palm
9.4
1.3 6.9
1.9 0.8 5.6 2.9 4.1 6.6 12.0 1.6 1.4 1.2 1.3 8.9 2.5
2.3
5.9 5.2
1.6 1.9
7.0 7.0 7.2 7.0 5.9 6.4 6.0
6.2 6.4 1.8 6.2
1.1 2.3 1.0 1.0
0.8 0.6
7.6 2.6 6.2
1.6 0.9
9.0
1.7 0.7 2.1
0.5
7.3
6.3 11.2
Millet 0.8
5.7 9.0
1.5
0.8
4.0
Mango
1.7 5.2 4.0 5.3 9.6 3.6 2.2
11.8 7.3 13.3 7.6 3.4 3.2 2.6
4.7
0.5 0.8 0.5
2.9 11.7 43.5
0.3
4.0
1.0
12.0 2.8 31.2 5.9 3.7 1.4 3.3 54.0 14.7
Maize 1.5 3.7 2.2
0.4
5.1
12.0 3.0 1.3 6.5
Grapes Groundnut 6.9 13.9 0.6 3.9 1.1
27.0 1.4 1.5
0.6 3.6
16.9 9.6
34.3 2.0 1.6 1.0 7.8 1.5 9.8 6.7
15.1 1.6 0.9 15.0 1.0 0.8 0.9
12.0 0.8
11.4
4.7
0.9
8.0 1.0
8.0
0.9
3.8
11.4 8.8 8.8
1.0 0.7 1.8 6.4
0.8 0.9
21.3 2.7 8.6
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Réunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Banana 6.8 6.4 38.6
Barley
3.1 31.2 12.5 26.1
51.8 26.7 8.1 4.4 21.6
5.5 5.2 4.2
1.9 1.4 0.5 6.7 1.5 3.8 4.0 0.7
Bean green
0.7 0.5 1.3
2.9 2.9 8.4
0.4 1.7 1.6 1.0 4.6
2.7 5.9 2.3 2.3 1.0 9.0 8.8
2.0 1.2 1.8
1.3 2.4
0.9
2.0 4.4 2.5 2.0
0.8 1.9
11.0 25.7
Bean dry
Grapes
Groundnut 0.9 0.9 6.0 1.0 5.8 0.9
7.0 9.6 7.1 2.8
2.9 6.2
1.6 0.6
3.2 1.5
9.0
2.0 1.8
15.7 8.1
13.3 13.3 0.6 2.5
2.5 3.9 23.0 5.3 2.4
1.6
4.3 9.9
6.9 1.1 1.2 2.3
1.0 1.3
5.4
0.9
3.3
5.3
0.7
0.9
11.4
0.5 0.6
6.0
7.0
0.9 3.6
1.8 2.1
5.6 4.8
0.6 2.3
6.0
11.4
0.4 0.6
8.3
2.3 0.9 1.7 2.0 12.0 4.4
1.0
1.7
0.8 2.1 1.5
0.6 4.5 2.6 1.2 2.8 3.3 1.9 0.4 1.8 1.7 0.5
1.2 0.9 0.9
5.0
12.2 0.5 19.8 2.5 0.8
5.8 1.0
4.4
0.9 2.2
0.6
3.5 6.5
1.7 0.7
0.8
3.0
3.2
0.7
0.6
11.9
7.1 6.3
10.0 12.4
1.9 0.6 1.1 0.6
1.2
0.7
1.0 6.3
0.6 2.9
8.7
6.7
1.1
5.7
1.3 0.7 0.7
7.6 3.0 7.0
9.1
9.0
0.4 9.4
0.7
8.8 8.3
0.5 6.7 7.3
1.1 3.0 0.4 1.5
1.7 7.1 4.2 1.1 1.2 1.3 1.4
6.0
1.1 1.8 0.8 1.1
12.0 4.0 1.5 1.6
2.7 9.9 6.7
0.8 0.9 1.8 0.9 1.3 2.5
5.4 2.3 2.4 1.7 5.8 5.3 4.0 12.5 6.8 3.6 2.0 0.8
2.0
1.0
11.4 16.9 11.4
1.0 1.0
8.0 0.9
1.6
21.4 14.1
11.4 11.4 11.4 1.0
5.0 4.4 8.5
0.6 1.7 1.1
0.8 0.6
Palm
7.5
3.0 1.0 3.0
2.9
0.7
11.2
0.5 1.8 2.5
28.7
44.0 7.0
12.3 5.1 8.8
1.6 2.4 0.3
3.4
4.5 32.0 6.5
1.7 2.7 6.2 1.9 12.0 12.6 9.7 1.2 2.4 11.9
0.8 1.8 2.3 3.8
Millet
1.4
0.9 1.4 2.4 0.8
5.9
19.9 24.4 5.2
Mango 6.3 7.3 6.7
23.5 7.5 8.9 5.9 7.0 16.3 1.7 7.9 11.8 2.8
1.6
5.1 17.6 2.5 6.0
Maize 1.2 0.8 1.2 6.4
1.3 0.6 0.7 0.2
11.4
1.1 0.8
11.4
0.4 1.6
11.4 26.5 10.5 2.7
2.0 14.0 3.6 39.5
3.5 0.8 1.2
0.6 0.6 0.5 0.5
7.8
7.0
7.9 6.0
8.4 6.8 6.7
0.4 14.3 20.0 22.0 2.0 29.2 21.1 20.0 8.3 23.0 23.0
1.5 1.2 3.7 1.3
0.7 0.9 0.9 1.9 0.5 0.6
1.8 3.0 2.8 2.8 2.0 8.4
3.0 2.5 1.4
0.7 1.6 0.8 0.6
1.4 4.4
17.8 9.5 4.4 4.3 4.4 3.2 1.0 4.4 4.3
1.0
0.9 1.1 0.6 0.9
9.6 14.8 9.6 26.0 12.5
7.5 17.6 6.2
2.9 12.5 0.8 0.9 0.8 7.5
Appendix II - p.2
0.5
11.4
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Banana 1.0 4.5 6.9
Barley
Bean dry
4.7 17.2 4.9 25.0 22.0 21.3 2.9 16.1 15.4 44.7 33.0 33.9 21.4 4.2 22.0 4.1 8.4 12.8 1.7 1.5 5.1 26.9
0.6
1.7 3.0 3.2
0.9 2.4
3.8 5.3 0.4 0.9 2.3 0.7
0.9 1.9 0.4
1.8 8.0
11.9 19.4 15.6
Grapes
3.0 7.9
13.7
3.0 3.4
7.5 3.5 6.6
Groundnut 1.0
Maize 3.3
4.0 1.7
2.1 1.6 0.9
Mango 5.7 8.4
Millet
Palm
12.8 6.8
0.8 1.6 1.1
1.2 8.0 6.0 6.9
1.6
0.7 1.7 2.3 0.6 0.7 1.4 1.4 1.1
0.7 2.2 9.5 1.9 0.6 2.3 1.8 9.2 9.2 3.2 3.5 1.4 3.4 2.0
7.2 11.4
2.9
6.6
2.0 0.6 1.0 0.9 1.9 1.5
1.0 8.3 16.5
16.0
4.6
17.7 21.0
3.0 1.5 2.5
Bean green
5.6 3.2 2.2 0.8 1.1 0.9
0.3 1.2 1.1 0.5 1.9
5.0 12.9 4.8 5.0 1.6
1.2 1.8 1.6 0.8 0.8 0.3
8.7 8.2 7.0 7.0 4.0
13.5 4.7 7.9 11.0
11.2 11.2 5.5 1.2 5.2 16.5
5.4 6.3 5.8
0.5 1.4
6.8 8.3
0.4 2.0 0.6 1.3 2.0 0.6
7.0 13.2 13.3 5.6 2.9
2.5 1.7 1.7 15.8 14.0 3.4
0.8 0.7
3.0 5.2
13.3 6.2
2.7 1.1 0.6 1.5 0.5 0.5 1.1 2.6
0.7 1.1 1.1 3.0 0.5 1.9 1.0 1.8 1.3
3.3 2.5
0.6 2.4 0.7 0.3
10.5 14.1 10.5 2.8
0.6 1.0 0.9 0.4
13.8 17.6 8.8
3.7 0.8
1.7
12.4
1.2 2.5 4.0 8.0 8.4 4.9 2.2 0.5 3.0 2.6
1.6 0.9 1.0 1.0 1.9 1.2 3.5
3.5
5.5
1.2 1.0
16.9 4.8
15.5 7.2
0.9
14.1 14.1
12.1 11.4
6.0 5.7
9.3
2.9 4.8
1.1 2.6
1.5 1.3
5.7 4.2
6.9 3.6
1.3
1.5 4.8
1.0 1.6
0.8
7.1 7.1
7.0 7.1
0.4 0.6
1.4 1.6
Appendix II - p.3
4.1
4.7
0.6 0.6 0.7 0.2
10.5
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Pepper Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Bahrain Brazil Brunei Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, D Congo, R Cook Islands Costa Rica Côte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
1.2 1.2 0.6
1.2 0.6 0.6 0.8 0.3
Potato Sorghum Soybean Sugarbeet Sugarcane Sunflower Tobacco 16.8 14.3 19.0 1.4 3.7 1.7 1.9 14.2 0.9 1.7 15.4 2.7 0.5 1.0 1.0 5.5 37.8 0.6 1.0
29.5 12.9 32.1 3.7 9.5
4.4 3.2 0.2
14.0 11.4
1.6
11.2 45.1
9.2
5.5 23.7 13.6 6.5 8.5
0.8
2.1
2.4 2.0 2.0 2.7 1.3
1.2 0.8 0.7 0.8 0.7 1.3 2.2
26.0
68.4 0.5
21.6 7.3
6.7
1.8
95.9 12.0
1.2 2.6
25.0
1.2
39.9 58.1 22.0 22.0 48.2 34.5 31.2 46.4
0.2 3.0 0.4
6.8 0.3 0.6
1.2 1.5 1.2
3.8 0.5 0.5 0.8 0.5 0.5 1.0
0.9 0.4 1.8
1.8 3.4 1.0 0.8
5.2 11.5
1.5 0.9 1.6
12.4 7.8
2.4
28.0
68.1
0.8
1.8
5.4
1.9 6.0 2.4
0.6 1.0 0.8
17.7
73.0 1.0 64.8
1.3
0.8 1.2
1.3 0.5 1.0
15.4 11.3
2.9
1.4
1.8 0.6
27.3 16.7
2.9
2.8
2.6 6.2 16.5 13.9 17.0 14.4 6.3 8.9
1.3 0.7 4.0 3.3 3.2
1.6 1.8 2.5
0.6
0.5
47.2 2.0
1.2 1.2 2.5
85.9 67.9
42.8
1.5
0.3 4.1 1.0
7.3 95.5
1.5 1.6
61.9 29.2 26.0
4.3 12.0 45.6 56.3
6.3 47.4
13.0 7.3
1.3
3.2 3.6
22.0
0.7 0.9 0.5 0.5
8.0 19.8 39.0
3.0 6.2
2.7
75.0 94.8
1.5 2.0
1.7 34.1 73.0 73.0
2.0 43.7 67.7 118.5 68.6
2.2 1.2
1.5 2.3
1.2 115.8
34.5 74.2
1.5 1.2
0.7 1.4
39.5 73.0 36.0 7.7 58.3
2.3
1.0 13.7 38.9 11.5 18.2
9.4
2.8
7.0 1.7 2.0
1.2 0.7 0.9
0.6 2.6 2.0 1.2
0.7 2.5
56.6 56.7
2.8
Appendix II - p.4
25.5 63.0 44.0 39.9 9.8 51.2 27.5
1.5
4.5
11.6 0.8 4.9 8.5 9.1 6.3 7.5
1.1 1.3 2.2 1.2 1.8
1.0 36.4 9.4 36.9 28.8
1.1 0.7
44.2 12.6
6.8 2.7
0.8 0.9 2.8
9.3 28.2 28.2 28.8
8.0 25.3 12.1 15.0 6.6 4.8 16.7 2.0
1.0 0.8 1.4 2.9 1.8 1.8 1.2 0.5 0.4 0.7 1.9 0.5 1.5 0.7 4.2 2.0 1.9
1.2 1.2 2.8 0.6 2.8
2.2 0.9
77.9 20.0 27.0
5.7 12.8 18.7 36.5 26.1 16.6 8.8 3.5 5.4 1.0 14.3 4.0 6.1 6.6 1.5 2.6 5.1 4.6 4.5
25.7 12.5 9.0 8.6 9.5 2.0 17.7 9.0 7.0 5.4 7.0 1.0 13.6 8.2 7.1 5.0 7.0 1.9 23.0 5.8 1.2 12.9 6.7 17.4 13.8
15.6
22.3 11.5 24.7 23.7 19.6 39.5
27.6 1.0
1.8 2.6 2.4
0.6
1.9 1.1
1.6
2.5 1.4 5.8 1.3
0.5 0.7 1.0 1.0
0.9
7.8 3.2 27.7 46.1 43.0 18.1 17.8 28.5 6.9 7.6 14.4 32.9
16.4
1.0 1.9 9.4 21.5 5.7
1.2
1.7 1.0 2.5 2.4 1.2
Tomato Vegetables 9.5 3.2 8.6 17.3 6.6 7.8 3.7 7.3
65.5 23.9 21.7 9.0 7.4 7.5 5.0 25.9 1.0 11.5 4.8 11.1 17.7 43.0
1.5 41.6 1.2 44.3 8.6 16.4 28.3
23.8 1.0 11.5 8.6 4.0 5.1
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Pepper Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Réunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Potato
0.7
Sugarbeet Sugarcane Sunflower Tobacco 65.2 0.9 58.8 1.4 2.1 32.0 81.8 0.5 2.4 44.6 1.5 2.0 1.2 1.1 24.0 72.1 0.6 1.5 1.2 68.9 0.6 1.6 29.8 86.2 0.7 1.1 1.3 22.4 21.3 1.3 1.0 5.7 1.2 1.1 1.2 1.2 70.0 1.3 1.0 3.5 46.3 2.7 2.8 63.2 1.5 1.7 54.3 67.5 1.0 2.6 0.2
1.8 3.8
0.6 0.8
1.3 1.2
1.0 1.4
1.1 1.3
0.4
1.2 0.9 0.9
1.2
7.6 24.5 22.3 15.0 6.6 15.9 19.8
0.5 0.7
7.8 14.1 12.4
1.3
0.4
5.9
0.5
1.2
0.8 1.8
11.0 15.0
0.7
0.9 1.0
0.5 1.2 0.5 0.8 1.2 0.5
12.2 1.0 21.3 12.9 18.8 14.7 21.3 14.4 31.9 38.7 24.2 15.8 3.3 25.9
0.8 0.7 0.8
0.5 0.5 0.4 0.7 0.8
Sorghum 0.8 0.9 2.3 0.8 1.2 1.2 0.3 4.2 7.7 6.4
Soybean
1.7 1.1
17.2 13.0
2.3 29.2 47.5
0.8
28.4 39.4
1.3
2.0 1.2 1.0 1.1
1.7
1.2 1.5 2.0 2.0
9.2 44.9 13.7 41.7 13.3 1.0 6.4 23.7 21.9 16.6 16.0 21.9 4.2 6.0 11.3 12.1 15.7 15.7 9.3 18.0 14.4 9.7 6.0 14.7
8.4 29.5
0.8 1.4
2.3 1.1 1.3
1.0 13.2 7.6 18.4
22.0
1.0 68.9
1.6
18.0
75.0 24.0 62.9 63.0 59.7 63.9
0.9
16.6
1.0
62.0
0.4 3.2 2.5 2.6
0.6 0.8 0.9 0.3
8.0 1.4
0.8
0.8 1.8
1.9 0.2 1.1
1.6 2.2 0.8 0.7
3.0 0.6 2.4
1.2 1.2 0.8
4.0 1.4 4.6
8.0
12.0
0.9
9.2
8.3
0.9 0.8
8.8 17.5
0.8
37.3 65.9 16.5
8.3 13.6 15.0 5.3 12.5 12.7 6.4 17.3 7.7 11.7 1.3 8.2 6.5 17.4 6.2 13.4 4.5 7.5 8.9 39.4 1.8 23.6 7.6 8.0 6.9 6.7 22.9 14.4 13.8 12.0 19.7 16.2 6.2 15.0 8.6 19.6 18.8
33.3
1.2
5.0 7.4 3.5 18.3 12.5 1.4
1.3
1.2 36.7 70.0 24.4
2.8 1.4 1.2 1.5 2.5
46.0
1.8 0.8 0.5
14.3 12.4
1.4 2.6 1.5 2.4 5.4
7.4 48.3 64.5 15.8
33.8 6.6
1.0
0.8
0.7 0.8 1.6 1.9
35.0
1.3
1.2
76.5 18.0 44.2
0.7 0.6 0.8 0.8
1.0 1.7 1.7
36.6 42.0
66.2 23.3 28.4 26.0 16.0 26.5
0.5 1.0
53.8 47.0 118.8 63.4 63.0 8.0 3.8
21.7 18.6
0.8
Appendix II - p.5
34.0 47.6 52.8
14.2 6.7 48.7 8.8
0.9 1.0
42.6
0.9
1.5 1.4 0.8 0.4
47.0 1.8 16.3 7.0
1.1 4.5 1.9 1.6
32.3 22.7 2.0 12.3 53.3 4.3 37.5 24.4 8.6 15.4 66.6 12.9 31.9 12.2 16.6 12.3
1.2 20.0 47.8 53.2
9.5 29.3
1.2
1.3 1.0
1.4
1.1 0.7
69.3 1.5 1.0 0.8
1.7 2.2
1.2
1.0
1.2
1.2 2.3
15.9 8.9 14.5 11.9 31.9 56.9 14.7 5.7 22.5 18.4 6.8 5.0 11.6 2.4 15.7
1.2
2.3
0.8 1.7
0.5 0.6
62.0
0.4
5.0 18.5 22.3
86.7
Tomato Vegetables 4.2 6.8 15.5 5.7 1.5 1.0 28.4 14.2 41.7 15.7 1.0 7.4 7.5 27.2 16.7 11.4 6.1 7.0 1.4 17.4 53.2 15.7 17.9 1.7 56.5 26.3 36.5 14.9
1.2 0.8 1.0
1.2 1.6 1.2 1.2 2.9 2.6 1.0 1.0 1.3 0.9 1.3
1.8 7.6 1.8 15.3 7.4 6.7 7.1
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Pepper Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Potato
Sorghum
Soybean
0.5 1.7 1.2
25.9 17.1
1.8 2.0
14.0 14.3 19.7
1.2 2.0 0.6
26.6 24.7 12.5 7.3
1.3 0.6 0.8 1.2 2.4
0.3 2.3 5.0 0.8 0.6
0.8 2.0 1.5
2.8
1.0 1.8
2.0 3.2 35.2 23.2 13.2 6.9 7.8
22.0 12.8 25.9 5.6
Sugarbeet Sugarcane Sunflower 25.0 13.0 23.0 19.8
1.2 1.5
1.3 2.2 1.0 1.2 0.9
12.0 4.8 43.2
16.0 6.5
0.6
0.6 1.0 0.9 1.6 0.7
3.3 0.8 1.4 0.4 1.5
46.0 68.0 45.4
16.0
1.1 0.3 1.6
0.7 1.4 1.2 2.0 2.0 1.6 1.2
7.2 8.2 19.5 4.2 4.2 16.4 13.6
1.5 1.2
1.2 1.2
18.4 11.8
2.6
1.2 4.4 3.6 2.6
2.1
1.2 1.2 1.5 2.7 2.5 1.9 1.1
42.6 43.9
7.0 22.0 16.0 35.0 67.2 76.8 55.2 7.1 5.0 18.8
55.0 96.8 56.7 28.0 48.4 40.0 32.0
13.3 15.4 17.4 57.8 49.5
63.0 44.0 79.7 51.6
11.8
0.8 1.1
61.5 5.6
Tobacco 1.2 3.4 1.3 1.1
0.9 1.3 1.7
1.3 0.7
0.7 0.8 1.5 0.9 0.3 2.1 2.6 1.3
0.8 1.2 1.0 2.8 1.8 0.4 1.1
0.6 1.5
0.6 1.0 0.9 1.4 1.2 1.7 1.4
1.6 1.5 2.6 0.8 1.4 0.5 1.2 0.8 0.9 2.5 1.3 0.8 12.6 2.0 2.2 3.3 1.9 1.9 1.9
Tomato Vegetables 7.5 6.7 5.8 24.3 21.8 19.5 18.0 6.1 7.8 9.9 6.3 23.0 17.1 19.9 7.7 27.0 16.4 6.4 31.9 14.2 59.5 21.3 7.5 1.0 12.0 7.8 8.4 15.8 12.5 8.2 32.9 21.0 36.7 23.3 38.7 8.9 19.9 18.0 7.9 6.8 9.1 7.4 4.0 5.0 14.7 1.3 12.6 9.0 37.2 12.5 41.7 15.9 11.6 11.0 7.5 6.5 7.4 13.4 8.3 68.2 25.7 36.6 3.1 48.5 31.8 18.2 8.3 34.0 4.6 15.8 2.6 17.5 12.9
2.0
1.2 1.5
12.7 8.2
1.7 4.7
2.7
0.7 0.9
10.0 15.8
0.7 0.6
2.3 2.1
35.2
Appendix II - p.6
13.1 18.3
2.4
1.5
2.1 1.7
12.7 8.3
8.9 7.6
0.6 0.7
1.9 2.2
1.0 6.7
6.4 6.9
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Bahrain Brazil Brunei Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, D Congo, R Cook Islands Costa Rica Côte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
W.melon 11.5 15.3
13.9 21.7 15.9 9.2
Wheat Cotton seed 1.2 1.1 2.5 1.0 0.8 0.6 1.3
1.0
2.5 1.9 2.3 5.4 1.9
0.1 1.0 2.0 3.6 2.0 1.3
2.3
1.3
6.5
1.7 8.3
Cabbage
9.0
Carrots
13.7
Cauliflower Cucumber
11.2
Lettuce
12 13.1783
Oats 1.6 0.8
1.0 5.0 15.0 22.6 30.9 46.5 13.1 14.0 20.4 10.3 7.5 17.1 19.1
4.0 26.3 17.1 37.3 31.4 8.3 15.2 6.0 16.5 45.1
50.0 9.2 18.0
10.8 7.6
18.1
7.6923 11 13.3333 15.60005 72.242 8.40215 12 10.0091 4.1111 7.6471 12.9354 65
18.0 22.6 27.9 23.0
2.1 1.4 2.0 4.1 0.8
22.0
1.7 3.4
23.0 9.6
1.2
7.6
1.9
2.2
12.8
2.7 0.8
1.1 1.7 0.9
27.1
1.3
1.4 1.9
18.3 15.0
2.6
1.2
9.6 15.0
16.4 26.3 12.0
22.0 20.0 22.0
19.8 4.9 10.3 64.6
0.9 1.5 1.5 0.9 3.1 1.7
Onion green
22.0
9.2 6.6
7.2
6.9091 30
9.6
0.9 2.4
26.0
15.0
11
19.0
1.1
22.0
12.9
10.8
15.82375
8.1
1.4
9.1 17.0
21.7 24.0
36.6 24.0
16.3 12.0
32.1399 15.3333
27.5 16.0
2.5
22.0
21.0 22.9 12.9
23.1579 15.83625 17.8759
13.8 21.7 13.8
3.3 1.9 1.4
22.0 23.7 22.0
4.07145
31.3
1.8
22.0
7.4
2.6
20.0
10.0 7.6 25.0
1.2 3.1 5.1
6.2 20.0 20.0
0.7 0.7 1.2
5.1 12.0
10.3 7.4
2.5
16.9
12.9
0.5 0.8
2.1 3.5 3.9 2.2
3.8 3.0
27.0 20.3 4.6
27.0 17.8 31.9
1.3
0.4
20.8
2.8
1.0 1.1
7.4
10.0
10.3
4.5
9.0 10.0 38.0 20.6 42.7
16.8
6.6323 2.883 90.78945 11.2232 328.5714
6.0
18.5
3.3
56.3
2.6 4.6 7.2
14.0 15.6 36.7 34.9 27.7
0.7 6.3 2.3
0.7 2.4 1.8
10.0 14.5 9.1 29.2 8.0
10.0 10.0 8.0 26.2
5.7 23.4
1.3 1.1
2.0 1.6
11.8 14.6
12.8
3.5
19.0 22.7 15.1
31.6 42.2
9.2 12.1
7.6 51.6
8.3 44.4
26.7
23.5 10.0 9.0 11.5
31.4 5.3 9.0 10.0
9.8 29.3 18.6
23.4 16.5 9.6
1.0 32.8
2.0 7.2
6.1901 31.25 12.7875 13.81505 10
10.0 14.7 7.1 25.9
32.2937
14.2857 75.2621 116.9438 21.7353
24.0 27.5
1.6 1.0
10.0
2.5 4.4
20.0 19.1
0.3 14.1
42.8
2.3 7.5 1.8 2.3
19.0 25.0
2.0
2.0 0.8 2.8 0.3 2.0 1.3 1.2
Appendix II - p.7
19.4
11.5
8.54165 40.76265 10 82.1579 10 34.49035 4.5
24.0 18.7 7.0 19.9 16.7
0.6 4.8 0.7 1.9
24.2
1.2
22.0
19.1
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
W.melon Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Réunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Wheat
9.7 17.3
0.7 3.6
13.2
2.6 0.8 1.8 0.5 8.8 1.5 3.2
21.3 1.5 22.6 33.8 19.9 33.6 38.1
Cotton seed 0.4 2.0
0.7 1.3 2.0 1.5 3.6 0.9
3.5 0.2
Cabbage 5.7 6.0 30.8 27.4 34.6 18.3 24.0 18.0 16.2 34.0 29.3 19.4 15.8 39.2 25.7
Carrots
11.7 25.9 32.0 14.5 15.9 10.0 24.4 73.2 48.1 13.9 28.9 36.7
Cauliflower Cucumber
8.0 22.7273 18.2 23.7472 12.0 120.40475 17.3 6.6434 16.0 8.31485 11.0 19.33925 11.3 7.55 9.8 166.6667 26.0 65.625 20.9 27.2059 12.6 14.2105 10.5 49.5831 17.2 81.94265
Lettuce
Oats
2.8 14.4 23.5
2.6
6.6 17.0
1.5 1.2
11.7 24.0 36.6 19.3 12.4 23.5 29.2
0.8 6.1 0.4 2.5 1.8 1.4
Onion green
16.0 15.0 18.0 18.0 12.0 12.1 20.0 31.8 20.0 11.5 21.2 12.3
9.7
1.3 1.4
1.8 0.4
11.5 22.0
11.5 0.0
0.0 0.0
8.0847
0.0 10.0
0.4 1.1
12.0 12.0
19.9 27.2 24.3 15.9
3.0 3.7 1.5 2.4
1.8
0.0 0.0 42.6 0.0 0.0 0.0 23.9
11.9811 53.08535 42.03475 14.97915 0 11.7219 31.3329
21.2 21.2 50.2 0.0 0.0 0.0 123.7
13.1 25.2
2.2
12.0
2.4 2.4 1.2
25.9 25.9 38.4 15.9 0.0 9.1 21.3 0.0 0.0 3.9 14.1 8.6
1.4
26.0
15.6 58.3 44.3 16.1 0.0 14.8 26.0 0.0 0.0 16.9 22.6 18.4
1.7 1.3 1.3
20.0 12.0
9.8 15.4
15.1923 16 20
0.0 2.0 1.3
17.1 20.0 20.0
4.3409
2.6
2.9
24.88095
17.0
12.0
21.1111
31.2
15.33025 26.5625
13.9 19.0
16.2 14.5
21.7
1.2 2.7 3.3 2.5
1.6
18.5
3.7
12.4
0.8 0.8
0.8
2.3 5.0
1.7
2.9
10.0 38.5 0.0 0.0 44.0 15.0 0.0 17.6 34.1
0.0 16.0 0.0 0.0 0.0 5.0 0.0 14.6 23.0
0.0 16.0 0.0 0.0 16.2 0.0 0.0 18.8 12.3
0.9 2.0 0.5 0.7 1.4
13.3 0.0 0.0 20.6 0.0 0.0 0.0
10.9 0.0 6.1 22.4 0.0 0.0 0.0
10.0 0.0 0.0 19.2 0.0 0.0 0.0
0.9
0.0 33.4
0.0 33.4
0.0 10.6
2.8 1.3 0.7
37.5 1.5 0.0 0.0
73.3 0.0 0.0 8.7
45.0 0.0 0.0 0.0
35.4 22.0 15.2 13.6
29.3 20.0 18.4 7.5
14.2 16.0 18.5 0.0
0.0 13.2 11.6 39.6 17.5 5.6 15.5 14.7 22.5 18.6
12.1 16.4 0.0 29.7 32.2 0.0 12.0 20.0 0.0 16.5
0.0 12.0 0.0 20.1 18.7 0.0 12.0 20.0 0.0 6.1
1.0
1.0
22.7
4.9
4.4
2.3 0.6
21.1
1.0
0.8 1.1 1.1 5.6 1.7 8.3 1.8 7.1 2.0 2.1
2.0 22.2 12.8 1.0 5.2 2.3 15.5 6.7 9.5 2.3 4.8
2.5 2.9
4.5 2.3 2.2 1.9 0.7 1.8 1.3 3.5 1.6
1.9
1.2 1.7 0.9 1.8
2.4 2.8 1.6 0.8
0.9
0.4
Appendix II - p.8
1.9
7.833 7.32145 1 28.09645 16
664.2857
127.3375 12 12.5 3.8016
11.27695 4.0357 13.48725 23.3333 15.0265 17.47915 10.0344
0.0 0.0 0.0 0.0 0.0 0.0 0.0 28.7
1.4
20.0 22.9
1.6
20.0
0.7
14.4 12.0
5.0
20.0
36.0 0.0 0.0 0.0
4.0 1.2
45.2 22.0 6.8 20.0
22.8 0.0 1.4 13.2
4.1 0.8
31.3 20.0 12.5
0.0 13.5 0.0 0.0 21.1 0.0 12.9 17.0
1.2 1.0 2.6 0.6
7.2 22.0 5.0 20.0 18.7
1.6 1.2
16.0 20.0 20.0
23.0
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
W.melon Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
11.9 12.9
2.0 22.9 11.9 14.5 37.8 28.6 12.5
22.3 4.8 14.5 8.4 12.5 13.0 29.2 12.8
4.4 2.3 26.3 14.0 11.7 15.4 11.5
Wheat
Cotton seed
4.3
Cabbage
22.0
Carrots Cauliflower Cucumber 10.0
13.8
18.0
Onion green
12.0 23.0
21.0 26.4 32.8
12.0 16.1 21.6
10.0 10.5
33.1 28.8 13.4
24.5 51.3 11.5
24.6 20.9
0.3 2.4 3.0
0.4 1.3 3.8
1.2
0.9
1.5 6.2 5.4 1.7 1.1 1.4 0.6 1.2
0.7
3.8 1.0 0.4 1.5 1.0
22.7 0.0 43.0 22.9 22.1 7.1 0.0 11.9 22.0
4.6 1.5 2.0 3.2
1.5 2.9 1.9
20.5 11.4 22.3 6.2
7.3 21.1 18.3
11.5 13.4 56.1 38.7 11.1 36.3
11.24215
13.18185 63.4612 9.3333
17.0 8.2
2.5 2.6
12.0 20.0
14.2 27.9
1.0 1.8
12.5 21.0 20.0 12.0
61.6 61.6 15.8 12.0 12.5 12.0
10.6771 53.7 40.4 13.8 11.0
21.9 17.0 21.9
54 88.2353 11.41915 3.58335
24.0 24.9 20.9
3.6 5.7 1.2 0.5
12.0
6.9
8.33945
16.7 17.0
1.5
6.6 20.0 18.3
11.579 22 28.67225 4.75
5.2 0.0 17.4
10.3859 55.00105 410 16.4046
13.0 19.7 27.4 33.4
1.8 2.3 0.4 8.6 2.9 1.9 2.7
0.3
2.4
14.4 36.2 28.4 23.0 8.4 53.2
0.4
0.8 1.0
30.0 23.0
28.9 12.0
1.6 3.3
1.4
9.2 13.4
8.7 7.5
7.5 5.6
1.3 1.0
1.7
Oats
22.65995
1.0
1.2 4.1 3.8
Lettuce
18.5 10.0 35.0 13.3 17.5
0.1 1.9
1.4 6.0 2.2 1.0
10 16.4 17.2
14.03265 16
24.3
17.11075 7.36665
4.5
1.2
22.0 21.2 10.5 12.0 12.0 20.0 16.5 13.0 20.0 22.0 20.0 22.0 12.5
22.7 13.5 13.6
1.9
12.0 20.0
1.6
12.0
7.0
Appendix II - p.9
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Onion dry Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Bahrain Brazil Brunei Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, D Congo, R Cook Islands Costa Rica Côte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
14.5
Peas Safflower 7.1875 2.5263 6.78635
Spinach
Sweet potato
Artichoke
Citrus
Rice 2.25 2.3 1.5
8.1 8.5
7.9 27.4 18.0 38.9 51.9 10.6 5.5 29.9 4.0 13.3 7.5 26.7 0.0 9.9
24.26765 7.1699 20.4492 41.07015 4.4309
5.8 18.0
0.776 0.77925
15.2 11.6
17.1 11.0
18.7
5.4
14.4
12 5
5.2566 3.2 9.5518 6.2 4.62185
4.2 8 2.125 30.12615 4.5
1.2
4.8
9.4 8.5
19.1
14.0
9.7
15.5
5.0 11.3
7.5 7.5 14.5
5.8239 5.1704
4.3
12.4
8.9022
10.2 5.2
7.8
21.9422
5.7
6
33.5 27.5
11.11915
3 3.076 3.2 2.3 6.2 2.0167 2.08705 3.2 1.6667 1.79305
15.5
5.5 6.2
4 2.7941 1.6519 3.0691 1.9259 3.12495
3.4 7.2
1.86585 3.25195
5.4
7.2
1.5
5.8
5.7 5.3 3.5
20.0 36.5 20.6 16.7
25.81115 7.97325 14
5.9
6
23.5
4.5
7.9 6.6 37.5 15.5 30.4
0.8375
2.16665
14.0 6.8
2.5 7.0 20.3
7.5 4.0 14.0
2.6 3.7 7.5 28.0 11.0 3.0
6.8 12.4 6.8
11.2
5.82635 4.2 6.25 4.523 14.69855
1.2
9.3 11.5 10.0
14 7.7 9.0 23.8 8.2
5.0724 9.3316 14
4.4 10.0
14 5
17.2 40.2
9.5 19.56075
18.0 38.4 7.7 19.1
6 12.074 15.3646 0 7.40965
8.0 6.3
5.2
0.6
18.9
19.0 14.0
9.7
4.0 4.1 3.7 24.0 6.5 2.5
13.5 18.0
5.1 8.8
1.46155 1.48545 4.02985 6.34365 4.89515 1.2143 0.755 0.8571 4.30975 1.57235 5.2 2.77285 5.3 5.2
5.3 17.5
4.43805 3.36425 8.75905 6.07815 5.2
0.52145
8.1 9.5
1.2
0.0 17.2
14.2
6.2
5.4
9.7
5.4
10.0
12 7.8
1.8
15.9 13.4
14.0 1.4 20.0 2.7 10.5
1.2 6.1
Appendix II - p.10
5.1
1.37705 5.2 5.95475 2.6919 2 1.68265 3.2 5.2 1.5491 7.63025 3.2 2.41405 1.50935 1.51415
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Onion dry Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Réunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
4.7 5.7 24.4
Peas
Safflower
Spinach 13.3
6.5 5.36845
11.4 7.3 25.2 8.8 31.0 30.3 28.2 8.7 50.7 15.1
7.38065 8.5 9.9121 4.91935 9.5 16.6805 20.11925
13.6 5.6
2.5966 5.7143
11.9 58.9 25.9 16.5
9.6154 10.3224
1.2 0.6 0.8
Sweet potato
17.5
3.0 3.3 11.0
2.0
8.5 9.5
Artichoke
Citrus
3.2 9.7 7.8 7.5
16 12.4 8.5
6.1 0.8
22.13145 4.0192
56.3 13.2 7.6 12.5 20.2
33.4 12.6 16.1 23.8
20.0
9.5
14.7 14.7 41.5
12.9 21.2
9.7 10.0 10.0
7.4 11.5 6.8 20
0.4347 11.0
6.1
19.29555
19.0 8.6 8.0
8.10715 6.3 13.2863
8.5
1.83335
7.2 8.2 0.5 29.0 12.6 0.0 0.0 22.1 12.4
5.2 8.5
14.9
4.5
4.00865 6.50645
12
2.4424 2.81975 3.2 2.8
16.0
10.0
6 6.2204
1.2916 5.2 5.03615
5.5
12.0
1.48765
7.9 0.0 3.0 21.5 5.7 8.2
10.6394 6 10
0.8
36.0
22.3658
1.2
20.0 2.2 24.5
42.5
11.7
2.0916 7.3 5.5
11.1 0.2 4.6 8.9 1.0 11.7 19.0 5.9
7.1 9
12.0
7.1
12.0
9
9.7
5.4
1.85515 2.9122 2.24415 3.2 0 4.54265 3.3 4.6435 1.125
4.3423 2.0 15.9 6.9 4.6
20.5 6.7
6 6
14.0 4.3 15.2
5.2108 7.4 12.94155
6.7 22.0 6.8 21.5 25.3
6.93335 6.2485
11.6
4.07495 8.8916
16.5
0.75
10.9
4.7 7.8 14.8 4.2 14.0 7.3 5.9
3.3 5.2059 1.07465 3.1844
2.4335 5.2
3.30695 2.71135 1.549 5.2 3.9 2.9837 2.75565
18.0
3.2
1.7857 3.9396 6.0153 2.8226 5.2 6.0007
4.5 2.6
1.04165
4.4
11.0
9.8 9.58715 2.92515
10 6.8
6.1 5.0 17.9
0.0 15.1 13.2 19.7
25.9 0.0 10.1 10.6
3.0116 2.6238
12.4
5.6 8.6 18.8
Rice 4.1243 1.99 2.4201 3.00945 5.2 2.94915 4.22555 4.25235 1.8642 5.2 5.5 6.214 1.49105 6.31655 2.3
25.0 4.9 4.6 10.9
Appendix II - p.11
2 2.8352 2.88645 1.864
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Onion dry Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Peas Safflower 4.0865
12.3 20.3
7.5 5
12.0 11.0 20.2
7.4 16.8 4.9055
Spinach
Sweet potato Artichoke 1.5
12.0
Citrus
Rice
6.2
4.6 2.7
20.6 42.3 7.8 7.1
21.62995 16.1121 8
29.4
12.9167 38.36145 9.0304
19.0 7.7 3.0 14.7
16.1 21.6 6.5
6 12
4.5 4.156 9.828
0.8
12.5 4.5
1.49405
17.1
14.5 10.0 3.9 16.2 5.5 13.4 11.7 1.8
12.0 14.0
5.6 12
11.0
24
1.2
3.3 2.6106 1.15665 3.3 5.2 5.2 3.9679 1.6667 2.26925 7.30225 3.264 0.8598 3.7621 6.83335 5.2
12.0
0.9
12.0
1.0286
15.2 9.6
1.7 15.4 7.2 12.2 6.7 16.0
5.1 3.8 4.5 8.2 8.2 11.5
11.6
4.2
4.28635 2.53045 1.53665 2.372 1.92265 2.9244 2.3 4.75415 0.8975
4.0 7.9 12.0 36.0 44.0 8.1 27.0
5.2 3.2409 8 10.1948 33.6443 9.6311 2.928
25.6 3.0
5.3 8
9.1 6.3
7 15.5
4.8423 4.03165
14.0 5.5
2.7895 5.57055
10.0
3.7 15
2.1 2.3
15.2 14.4
6 1.9986
14.8 2.1
5
0.80885 2
1.676
109.6 12.0 16.3
14.0 16.5 10.0
9.7 12.5
14.2 15.5 24.8 6.8
0.9272
Appendix II - p.12
1.40165 2.96635 3.3 5.2 6.46125 5.80615 2.44815
3
Appendix III. Specific water demands (m /ton) in 1999. Source: calculated on the basis of Appendices I and II. Banana Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Brahain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Côte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
2066
Barley Bean dry Bean green 3142 2990 3470 3542 3910 14897 1151
3760 604 887 2538 454
3726 0 492 1665 147 374 3212 440 529
483 0
1599 2789 2069 753 3622 4211
2656 1069 5640 2077 1012
5982
4759
2445 377
3087 796 3588 5251
3490 0 5148 1089
2368 1372
1823
5846
1392
3557
1613 929
8366 3329 1098
679 1640 1437 5367
9480 768 190 258 4929 3102 1207
1377
9912 1646 3145 2417
939 303 520 178
5172
128
660 3043
4346 2306 6458
3533
4730
8400
3350 2072 1205 256 1885 3692 1127 0 1459 803 15400
485
2701
1261
1878
1220
3209 7729 7139
839 4900 4521
4332
923 142 1029
952 861
2998
299 440 275
4382 2619
0 5028 1772 4621
526 1671 336 1066
835 0 1866 533 1007
0 5605 1953 5060
2920 4417
1241 5647
689
1191 2638
2891 4345
264 3015
0
0 773 354 6287 1783 4030 1444 476 2733 232 0
2547
1158
1984 577 2178
4565
8700 2907 2077 1492 0 5797
943 196 308
551 426
598 1308 333 516 268 1034
1134 243 1363
2333
Appendix III - p.1
2891 3320 5495 11357 2891 3370 1327
4372 3136 4109
1678 2734 4520
1286
308
2941 4331
4090 13683
1625
864 951
1680
681 584
773
5303
2415 0
397
612
1627
3075
381 17162
3468 4309 4882 5820 1633 2891 2891
4916
5122
1060
476
365
2607
2763
1287
1700
1257
353 3540
726 418 572
1421 451
7681 3732
10069 1745
362 366
1710
16424
2706 1750
3059 9228 295 708 2088 1840 4431 0
929
0
6110 6353
4645 7405 1870 1676 2769 4690 4923 0
Palm
1211
830
983 12994 3575 2023 2077
1353 1867
2132 2210
314
0
5427 3305 0 347 215 4075 1863
4140 2476 3180 3400
1528 4855 443 1840 1478 478 264 4628 3929 0 2627 506 1893
1352 572
6328
3952
3801 3533
1000 1317 796 1399 1294 623 662
2375 904 680
Millet 5621
3084 1272
2405
5484
530
Mango
3375 627 799 829 330 888 2258
555 543 680 522 1057 2434 0
700
5379 0 8433
1524 804 199
11845
615
4157
465 1839 211 3115 3837 0 0 117 1110
Maize 2227 577 3066
6710
3281
593 6547 7754 1215
Grapes Groundnut 941 908 6317 3717 6611
0 7718 9820
5421 847
724 1432
491 1845 2306 17080 0 8141 2046 2494
4678
0 6965 14230 971 11890
4613 5468 0 4613
621
4137
5849
1255 18310
1841
3790
3814
621 1564 0
0 20326 7504 2504
4092 4527
576 4826 1755
3
Appendix III. Specific water demands (m /ton) in 1999. Source: calculated on the basis of Appendices I and II.
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Réunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Banana 1177 1277 163
Barley
Bean dry
1140 272 690 500
252 207 1169 1229 404
3051 0 1548
2008 6176 3775 535 5867 1160 924 2796
294
6134 8359 2117
1010 1034 263
13775 2346 2609 8626 588
1899 511 0 1399 2200 0 402
1697 4094 1740
2403 1415
0
1230 0 0 1520
4561 0
622
Bean green
Grapes
Groundnut 5622 5952 1167 4080 686 3533
428 256 376 991
1392 1561
0 6395
2027 2473
331
1685 0
0 557
398 0 0 7303
880 0 0 1428 1555
1284
923 792
873 4882 4747 1977
8210 3450
2807
4684
1270
2179
8087
5056
1630
4895 6067
530
1246
4003 1386
1891 2013
2338 3044
8167 0
563
833
7146 5335
1532
1452 2423 7090 2622 264 722
6225
3304
11550 1525 3121
13431 667 1338 0 1121 1273 3413 9733 1779 2523 8389
3568 4100 4341
4220
1407 5207 678 1544 6262
0 3000
3554
7514 1453
6084
785 451
2099 0
3204
733
1259
3370
6413
216
1134 1410
897 510
2209 6359 4060 6816
2983
5330
3335 566
6826 933
254
595
2891
635
3185 6774 7000
279 1007 483
715
1611
17719 1277
4785
1440 1336
7410 3000 1859
3218 1749 13819 3973
1764 445 0 2861 4176 4170 3845
3792
3355 3911 6034 4245
334 1640 1608 2906
7429 1853 2248
5488 4564 2762 4881 2446 1736
764 1680 1922 2092 551 809 1425 399 1059 874 1608 0
0
4270
1619 857 1983
3560 0
275 2405
2225
573 365
621 1983 854 2910
2200 902 469
6633 3190 2891
4752 7968
Palm
2254
2055 2700 907
1228
7177
2227
5270 2015 1438
297
208 3329
1600 3065 2839
2254 702 11341
0
2455 236 2327
2852 1821 1019 3008 264 502 252 4497 1317 338
8318 2806 2563 1640
Millet
2553
3631 1929 1792 3012
3495
763 239 0
Mango 2171 1995 1641
482 1291 1488 2533 567 811 3447 1241 430 3285
9141
2810 444 3376 3883
Maize 3925 5832 2425 494
2593 4108 4454 17934
1054
3565 4613
621
12393 3024
925 622 1881 7965
0 795 3294 185
1123 5613 3930
5300 9933 14727 7310
409
514
603 470
1172 1374 0
0 490 394 371 4007 309 592 427 1837 310 310
2667 3492 959 2784
3287 3903 4371 1388 6657 12207
1461 1187 1233 1172 1100 351
1340 1448 2492
11802 1646 3240 0
3069 505
627 966 1856 923 971 2760 15980 892 931
12420
8396 2891 0 5704
1402 819 1599 525 1046
2189 841 2272
6826 1921 4428 3941 0 0
Appendix III - p.2
13056
621
3
Appendix III. Specific water demands (m /ton) in 1999. Source: calculated on the basis of Appendices I and II. Banana Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Barley
Bean dry
Bean green
Grapes
Groundnut 0
0 0 0 1212 827 3908 312 345 345 0 1433 581 139 272 222 739 2098 324 2309 2009 969 4840 10406 1839 293
5167
2094 1191 0
4514 1442
926 674 14462 2042 1438 3718
1060 886
1163 2455 0
1598 2383
0 2501 3931
Millet
Palm
0 0 0 1886
4871 3094 4364
2983 531 707 611
7970
0 4511 3753 11011 1887
0 3434 1804 10768 6482 6607 3900 2891
0 1966 401 3500 6325 3775 2760 345 346 1299 1646 2663 776 2266
0 1519
537 189 957 606 3434
3191 1519 2572 3946 2798 15885
252 437 467 400 515
670 1594 1048 733
354 354 1816 13276 1862 439
2388 5673 6302 1884 10548 7750
2019 5667 3383 4100 1909 0
11980 1448 814
1193 638 1118 1670 3266 2836 3978
7315 3340
424 228
1653 1275 1264
6891 1800 6800 2077 1367 6727
400 272 166 391 742
3699 6016 2382 251 466 2621
3985 5413
820 527
556 1240
4418 1361
5751 4609 2891 1064 7080 1388 0 2167 3621
0 5320
7655 1394 7566 12347
1516 805 1198 8736
6964 3284 2544 9037
1025 594 1747
878 1878
1476
848
3222 1693 1030 396 377 664 1089 0 1220 1695
2023 4113 3940 3690 1985 2083 826
4034
1839 4064 658 13205
2018
0 338 476
734
Mango 0
750
3636
402 313
1213 2379 0
1200 314
Maize
1800
12449 11210
2544
1096 0
781 1805
3322
365 450
925 1054
2907 0
1003
6325 3829
3159 1599
3131 3136
589 816
1462 1237
3944
3451 1009
4945 2538
3587
570 503
1450 1548
13214 6517
3338 2238
Appendix III - p.3
3892
3530
6700 6883 5159 14300
1433
3
Appendix III. Specific water demands (m /ton) in 1999. Source: calculated on the basis of Appendices I and II. Pepper Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Brahain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Côte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
3375 4825 5217
2850 7800 5183 4213 19760
Potato Sorghum Soybean Sugarbeet Sugarcane Sunflower Tobacco 176 487 671 4528 467 5627 4007 2218 3579 3022 451 2796 18200 5349 0 753 308 5771 3668
179 254 146 879 345
960 1515 15205
0 308
2012
293 58
290
769 184 0 611 309
4706
1488
2458 1700 2933 1261 2720
2875 7075 8206 3213 0 3450 1601
258
58 7586
184 545
1910
2137
193 1069
4531 1133
566
4208
337 222 583 303 363 450 0 260
16209 1470 0
566 14413 5217
3842 2678 3158
619 9840 5180 7500 6260 6260 4470
3489 7645 1833
1617 826 4860 6035
1209 510
0 3830 1746
329 478
2244
220
209
5351
2295
954
1746 1153 2214
6120 5520 5696
226
176 23310 251
2231
9609 3192
2197 10560 3610
243 742
1239
2235
2048 7774
121 360
897
1227
1978 1118 329 311 232 325 605 0
3096 9997 1073 1339 973
3588 3119 1616
4697
9627
284 0
2325 4550 2213
100 223
93
1935
10304 1055 3950
1989 240
2220 2125
107 224 184
1556 608 88 71
788 160
253 745
3756
1063 1750
181
7821 0 6260 6260
411 166 108
0 419
1277
132 134
2887 2385
2866 505 203 176
8770 0 186 181 251
1345 2492
2379 3218
2492 156
116 54
2615 4733
5040 2575
0 176 356 1942 192
1279
6114 240 84 365 364
379
1006
371 2132 2615
2569 4959 4835
5832 1303 3435 3942
4428 1173
71 144
985
Appendix III - p.4
595 185 273 392 875 277 601
4166
1076
273 0 501 498 396 491 382
4810 5632 5241 1279 2585 1779 4083 8150 0 0 1622 8920 3054 6936 1295 1415 1489
80 260 208 662 674 0 0 165 5890 547 1486 660 212 87
4300 0 1550 5092 2722
7080 0 464 159 212
2573 7101
85 580
359 1366
0 3144 1013
0 133 133 164
0 97 202 204 404 757 147 1225
4858 2387 999 7493 2032
1356 4833
48 342 273
805 191 131 123 94 148 430 0 625 4560 171 617 536 542 2073 0 484 526 1151
95 309 524 441 571 1560 210 324 657 610 0 0 193 446 570 926 661 1302 107 757 3756 0 414 297 314
1202
160 478 217 266 168 83
483 12470
2361 2954 2492
3867
1574 2718
2467
0 2355 824 3509
6260 7443 3240 4400
4659
929 1389 135 137 87 206 356 0 698 660 260 114
305
5410 0 433 220 855
3808
2460 2979 2125 1194 2358
Tomato Vegetables 426 2415 568 483 638 0 1257 431
2493 90 4757 174 0 383 151
206 0 348 306 783 668
3
Appendix III. Specific water demands (m /ton) in 1999. Source: calculated on the basis of Appendices I and II. Pepper Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Réunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Potato
6839
Sugarbeet Sugarcane Sunflower Tobacco 211 4533 256 2749 1302 104 105 6048 1395 89 1966 1450 2492 6077 344 281 10449 4535 4031 239 6303 3741 214 287 13484 6146 2795 244 1122 7735 4070 2833 705 2492 2573 4850 353 6931 7000 1586 145 1843 1693 274 2918 2646 97 150 4130 1507 15667
1416 1047
0 4101
2615 5000
3460 0
3768 0
18050
4500 5492 3778
1675
304 0 0 505 585 207 169
6260 4471
663 233 264
2000
13591
985
8340
4958
5788 2411
334 299
3810
4922 5110
6260 5142 5180 5413 2325 4200
398 3580 155 256 262 351 224 389 103 123 227 348 724 156
3250 8145 2950
4760 6260 13371 7894 7713
Sorghum 4238 3466 1134 6087 3358 2875 23086 619 449 677
Soybean
2316 2405
232 544
2899 137 73
4250
140 101
1977
1565 3375 5080 7391
2922
3508 2520 1565 2110
335 73 0 127 368 5750 875 169 311 159 383 0 1051 1121 412 317 209 283 537 402 228 339 0 341
447 138
3738 2136
1685 2573 2211
5100 474 495 204
1069
5351
682
595
4068 5225
500 299
8791
258 0 374
456 255 240 868 0 321 1036 235 456 0 1838 0 820 154 656 230 1179 0 487 62 0 103 654 579 794 0 0 325 503 375 0 182 556 209 435 125 176
585
256
13460 218
434 504
2462 0 4667 2229 716
686 0 0 594
5942 4190
1146 0 1010
2780
261
287 653 255 388 230 192
3977
241
367
2269
2279
6436 3355 3278 10949
3560
58
173 777 301
7225 5096 4265 4507
3240 2491 1988
3592
664 435 1829 224 285 2628
1953
10125 359 183 523
2369 2235
10766
5779
2608
2492 2119
0 439 0 319 0 0 284 531 109 110 617 610 272 1032 156
4767
1792
6750 2550
6115 6224
171
11500
1814 176 191
178
15659
325 0
4517
8394 1889
2694 24989 4991
3763 3008 10763 13990
1997 10216 1989
5250 6593 7631
799 3767 799
438
2664 3238 4342 2267 1836
87
411 305
272 921 803 109 403 386
118 818
5670
4776
6243 9475 2863 1973
551 180 264
254 385 129 230 204 1085 5603
6072 2830
88
6456
2727 3945 8220 18819
96 3769 593 1485
2718 1239 3444 2213
116 349 4748 564 0 1085 163 204 624 242 76 544 196 725 226 304
6063 5620
3591
2718 5841
420 1700 2690 0
1848 4112 0
184 215
0
Appendix III - p.5
377 0 298
1248 100 553
2492
2042 1040 411 313
Tomato Vegetables 1037 416 397 667 2788 2620 132 172 90 476 5460 785 486 320 264 624 470 534 6378 253 118 259 396 2596 93 107 135 161
2405 3586 5810
2875 3555 3691 3652 965 1450 4340 5460 2098 2997 0
2116 573 1336 160 0 529 0
3
Appendix III. Specific water demands (m /ton) in 1999. Source: calculated on the basis of Appendices I and II. Pepper Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Potato
Sorghum
Soybean
0 3188 3417
186 227
2344 2115
320 313 227
4825 1980 10319
176 167 553 538
3565 5085 4271 2983 1461
0 2157 656 7020 6241
7963 1565 3613
1504
4240 817
2296 1030 93 208 426 572 386
243 362 123 781
Sugarbeet Sugarcane Sunflower 0 0 794 676
4258 3308
4337 1927 5228 4083 9056
470 1136 0
361 714
5867
8255 8100 4073 1557 5962
1023 8692 2564 16438 3048
87 59 152
338
4773 11281 2625
7602 4143 4517 1565 1565 2531 3750
551 549 248 792 778 323 422
2286 3185
3158 3227
214 321
1188
2167 595 1178 1776
1055
4902 5415 4607 1259 1380 3225 5845
141 69
1909 683 848 0 276 158 286 1981 5448 837
332 159 200 621 357 384 402
1155 490 397 69 81
290 292 161 249
609
4738 3322
206 2373
Tobacco 0 0 4708 3391
4656 3028 0
4144 5428
5595 5225 2552 0 0 2498 1390 4709
5213 5992 4440 1070 3497 8683 2400
7344 3625
6483 4337 3322 2115 3151 2444 2470
1786 4005 1491 5940 2653 10300 3858 5196 2554 2260 3714 6496 487 1415 1264 1258 2327 1722 1805
Tomato Vegetables 0 0 0 288 212 262 169 1026 540 514 484 228 202 255 426 0 0 0 198 317 76 160 1057 5140 429 444 1236 384 415 412 114 117 102 105 181 519 363 156 795 574 504 410 1488 920 393 2720 570 514 157 314 96 110 515 359 0 962 533 507 504 103 180 102 784 77 77 247 295 148 607 0 1716 167 239
8995
3350 3207
418 621
2711 861
1925
7336 7367
526 251
4630 4817
2124 3057
175
Appendix III - p.6
1312 918
1919
3107
2021 2646
487 697
413 496
7319 4529
2158 2505
5010 966
720 746
3
Appendix III. Specific water demands (m /ton) in 1999. Source: calculated on the basis of Appendices I and II.
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Brahain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Côte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
W.melons 485 408
336 138 362 324
Wheat Cotton seed Cabbage 3528 6736 3210 0 7222 9774 325 2655
5470
1218 1954 2082 688 1928
49347 5292 0 2402 1940 0
1890
4947
0
2159 424
Carrots
Cauliflower Cucumber
0
0
Lettuce
Oats
250 0
Onion green 0 0 0
748 201 0 104 34 138 199 0 0 488 115 94
0 256 0 181 120 0 0 0 228 83
0 661 189
0 0
189
0 396 0 321 42 547 405 0 0 0 232 46
231 184 82 136
2690 0 2902 794 0
242
1297 957
130 310
0 0 0 36
7339 1647 0 3338 1130 2298
5083
596
1706
3095
234
1370 4841
0 3536 8605
140
2640
4005 2919
164 336
1441
4060
394 200
258 189 287
3634 1053 1024 1525 2739
242 149 145
202
311 243
0 0
0
531 100
332
0 1363
235
360
401
203
4592
220
0
0
190
0
1607
328 0
76 170
115 0
290 0
164 0
149 0
2328
202
1769 1893
127 111 644
118 256 146
242 202 381
172 278 190
271 158 207
1632 2887 2686
221 195 164
15637
159
0
0
0
4280 5724
334
341
259
787
1439
118
0 341 0 183 88
203
452 0 62 267 9
313
1244
149
443 301 92
0 1034 630
817 149 149
0 115 282 419 0
0 0 437 162
0 8914 4408
764 464
2351
116
222
13874 14879
0
271
1983
103
3246 805 518
199 222 108 58 62
4465 1005 2135
8075 4811 4514
361 0 343 157 474
0 0 0 147
745 0
2796 4881
1940 5389
0 261
0
0
95 86 263
119 85
493 374
257 38
0 81
170
132 329 423 200
175 0 0 508
374 230 246
0 206 356
0 91
1884 516
93
0 50 32 0
130 113
1953 0
0
1391 798
173 181
30213 211
143
1609 498 2322 3440
254 131
1150
1940 7854 3641 0 2140 5048 6361
Appendix III - p.7
317
474
0 93 0 69 0 0 933
129 190 0 0 230
5565 725 0 3411
3350
181 207
262
3
Appendix III. Specific water demands (m /ton) in 1999. Source: calculated on the basis of Appendices I and II. W.melons Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Réunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Wheat
339 173
3450 1040
486
2675 4938 3330 9560 427 4067 2016
323 3348 304 148 273 124 96 0
1088 15245
Cotton seed Cabbage 647 13626 525 2140 0 72 0 13402 200 5507 170 6540 178 3115 97 58 3332 143 9724 145 228 69 64
Carrots
Cauliflower Cucumber
0 139 0 0 388 0 173 64 133 391 154 159
0 250 0 294 350 569 0 483 0 276 0 464 348
201 160 0 921 528 414 0 23 95 173 386 80 65
5005 3193
2198 17060
157 171
368
221 0 0 433
1273 0 0 2652
3981
235 0 57 112
177 0 0 265
117
1550 1169 2819
117 58
0 287
3748 1386 1143
130 87 107
0 255 0
0 306
0 188 150
290 207
192
0 130 69 201 374 141 152
0 572 0 2019 3178 0
0
0
207
0 0
169 0 0
30
244 277 482 358 173 132 215 493 200 455
13264 0
288 425
3437
351 0
0
288
1856 0 0
173 397
1791 0
387 173 173
1205
1539
2097
3713 5188
6077
389 101
343
328
169
218
372
2998 0
5837 0 229
0
0
0
218 96
0 183
0 423
0 255
175 216
148
0
472
0
0 0
0
383 0 0 155
1597 10540
174
4143 2880 3092 675 3208 449 0 426 3475 3406
628
4380 4092
0
680
508 2807
913 208
289 230
0
824
606
1371
278
173
1187 2049 284
0 247 132
643
353 0 0 307
Onion green
4918
7650
3045 327 310 0
Oats
1796
8080
4670
2485 2148
Lettuce
810 2469 3245 2716 0 2319 2782 1056 3154
2143
9021 2105 10482 8083 4148
6222
2975 7784 12871
5461
8142 4263 8246 3772
1566 1338 2384 0
0
0
1363
4233
160 243
0
173
0
308
252
59
108
321
69 1963
92
136
5
315
80
644
149
115
1428 4267
118 204 1315 257
0 6050
121 328 692
0 55 185 0 318
313 0 49 127 584 201 0 87 105
0 307 0 0
391 341 0
0 517 0 0
101
0 0
0
278
3158 3220
127 146
235 248
0 0 222 164
149
1349 6682
498 200 926 149 206
0 0
0 0
0
0 0 2211 2980
0 149 179
0
19609
Appendix III - p.8
0
172 359
0 0
100
3
Appendix III. Specific water demands (m /ton) in 1999. Source: calculated on the basis of Appendices I and II. W.melons Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Wheat
Cotton seed Cabbage
Carrots
Cauliflower Cucumber
Lettuce
Oats
Onion green
0
544 309
1975 0 0 396 96 145 638
289 1071 271 550 436 342 100 458
1259 2759 114 334 426 222 299
1329
166
391
284
274
6187
3458 941 0 0 1951 1155
0 6875 1342
3295
7962
2553 600 696 3365 4314 3002 4960 4283
10563
192 74 60
443 228 174
485 449
104 137 0
243 86 0
123 197
177
943 2678 1382 1347
381 254
267
0 94 451
201 0
1394 0
271 178
5100 3855
357 302 218 520
48 0 293 248 316 379
0
2325 4399 14800 2933 8158
46 0 165 274
68 0 301 334
215 0 201
56 0 363 0
96 0 193
962 0 0 0
310 151
502
735
613
275 202
3713
169 198 97 335
0 196 0
0 0 0
423 0 191 884
0
4360 933 4639
319 404 65 109 0 101
2351 2067 13697 435 1302 1578 1250
23523
3642
184 101 69 91 483 46
8323
6675 5580
101 139
187 423
2812 1743
4576
355 178
585 0
476 679
5142 5726
3551
350 149
321 0 177 355 308
508 100 7 322
151
50495 3211
0 0 114 123
2482
0 252
0
3667
0 491
866
588 2948 6110
460 0 305
221 247 512 248 445 149 339 265 223 157 149 195 302
0 352 340
2188
451 210
0
333
796
Appendix III - p.9
3
Appendix III. Specific water demands (m /ton) in 1999. Source: calculated on the basis of Appendices I and II. Onion dry Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Brahain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Côte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
0
Peas
Safflower
Spinach
Sweet potato
0 0 0
Artichoke
Citrus
Rice 0 2565 0
0 0
0 241 0 170 76 0 0 0 0 0 0 149
185 0 220 66 0
0 356
7693 7661
244 202
375 318
0
1422
753
640 0
459 1285 91 800
2808
0
0 645
122
250
482
317
0 0
0 0 0
0 528
0
528
461
565 0
512
124
0
500
177 0
306
156 523 287
0
572
143
667
317
0 0
0 2720 0 1922 0 0
0 0
4395 0
1741
0
4080
569
1088
2622
278 0
0 0 244
1516 2343 781
0 0 0 0 0 0
1234 594 1210
0
469 0 829 604 257
2808
471 203 233
270 0 584 282 827
830 581 287
0 0
270 804
326 139
398 193
11333
0
0 250
482
1735 0 0 283 0 0
793 767
2255 1107
1703 5374 1135 0
1519 780
0 2042 1096 1349 1135
0
0
3900
210
308
1208
787
772
787
1104
698 1312
0 670 0 246
227
749
353
648
0 0 1821 1072 1471 0 0 0
1113 1135
0
0 0
2233 2666 2797 2565 952 3362 3450 2053 0 3792
0 0
0 183 271 0
0 146 0 428
1636 1938 900 952 1277
0
0
505 0 0 257 131
0
312 3707 0 0 0
4733 0
Appendix III - p.10
1869
0 1135 991 0 3125 5705 1844 1135 5939 1025 2850 3169 0 0
3
Appendix III. Specific water demands (m /ton) in 1999. Source: calculated on the basis of Appendices I and II. Onion dry Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Réunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
0 0 229
Peas
Safflower
Spinach
Sweet potato 0
635 704
562 0 0 0 180 171 240 0 113 0
816 433 828 0 398 487 208 161 1349
293 0
0 800
518 0 0 241
401 0
3900 13467 6063
207
0 0 397
1600
838 595
Artichoke
Citrus
2581 0 2360 0
850 1000 1918
0 11500
0 293 563 257 0
168 320 424 212
179
0
239 0 0
0 0
0 0 955
2000 640 1685 353
0 1265
1700
205
0 0 494
496 600 285
824
2275
0 759 0 0 0
879 459
0
1302
1639 0
633
2538 3092 1844 2107
643
0
0
277
670 772
0
873
0 0 0 629
395 945 367
6013
110
122
2808
331 0 365
106
0 249 730 185 216
4168
278
143 0
0
0
0 669
0
930 484
189
0 0 0 0 0
250 0 424
0 1180
892
1441
250
939
482
724 768 1790
0 793 0 1384 250 663 0
0 3056 0 2328 0 1942 1719 0
3636 0 7091 2738
4027 1135
3151 4536 8134 1135 2992 3677 2765
0
3113
0 1990 1368 3089 1135 1133
3556 0
0
3564
0
0 285 1296
1200 1836
0 1270 0
0 393 373
5355
491 0 0
0 0 0 0
917 915 524 816 0
0 1135 1172
0 485
0 0 0
2059 3518
555
0 0 0
Rice 2139 0 3273 2060 0 3350 2201 2401 0 1135 2182 1030 0 1203 3570
135 0 0 0
Appendix III - p.11
0 2081 2044 0
3
Appendix III. Specific water demands (m /ton) in 1999. Source: calculated on the basis of Appendices I and II. Onion dry Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Peas
Safflower
Spinach
Sweet potato Artichoke 0
0
0 0
752 1228
478 361 0
622 226 0
1373
Citrus
2000
0 0
0 155 0 1227
185 331 775
135
293 0 931
374 516 0 487
442 366 0
545 387
856 1155 495
5650
766 0
2811
283
0 0 1448 285 0 0 456 0
922 985
1488 877
1712
600
2808
Rice
3515 4060 0 2642 1135 1135 0 0 3199 1143 2328 14655 2366 0 1135
0
5644
320
6455
0 0
0 381 0 435 0 383
1504 3000 2127 1240 1240 0
742
0
2800 2450 4425 4047 3760 3146 3130 1615 0
0 0 593 105 105 0 147
865 1166 775 372 141 495 0
0 1732
711 459
0 0
1261 598
1586 2163
0 946
0 627
0
2946 701
4129 3896
0 0
728 2247
0 0
2242
11127 5170
4057
0 223 222
0 415 0
0 0
0 317 293 1259
0
Appendix III - p.12
7027 2090 2830 1135 1331 1323 2533
Appendix IV: FAO guidelines on crop water requirements in mm [=10 m3/ha] FAO guidelines
Crop Min
Max
Bananas
700
1700
Beans
250
500
Corn (Maize)
400
750
Cotton
550
950
Dates
900
1300
Grains
300
450
Grapefruit
650
1000
Groundnut
500
700
Onions
350
600
Potato
350
625
Rice
590
950
Sorghum
300
650
Soybean
450
825
Sugar beet
450
850
Sugarcane
1000
1500
Sweet potato
400
675
Tobacco
300
500
Tomato
300
600
Wheat
450
650
Source: Gleick (1993, p.282-283)
Appendix Va: Gross virtual water import per country for the years 1995-1999 (106 m3) Country AFGHANISTAN ALBANIA ALGERIA ANDORRA ANGOLA ANGUILLA ANTIGUA BARB ARGENTINA ARMENIA ARUBA AUSTRALIA AUSTRIA AZERBAIJAN BAHAMAS BAHRAIN BANGLADESH BARBADOS BELARUS BELGIUM-LUX BELIZE BENIN BERMUDA BHUTAN BOLIVIA BOSNIA HERZG BRITISH INDIAN OCEAN TER BR.VIRGIN IS BRAZIL BRUNEI DAR. BULGARIA BURKINA FASO BURUNDI CAMBODIA CAMEROON CANADA CAPE VERDE CAYMAN ISLDS CENT.AF.REP CHAD CHILE CHINA COCOS ISLNDS COLOMBIA COMOROS CONGO CONGO, D.R. COOK ISLANDS COSTA RICA COTE DIVOIRE CROATIA CUBA CYPRUS CZECH REP DENMARK DJIBOUTI DOMINICA DOMINICAN RP ECUADOR EGYPT EL SALVADOR EQ.GUINEA ERITREA ESTONIA ETHIOPIA FAEROE ISLDS FALKLAND ISL FIJI FINLAND FR.GUIANA FR.POLYNESIA FRANCE GABON GAMBIA
1995
1996
1997
1998
1999
Total
59.9 105.7 9523.3 2.8 223.9 2.3 7.0 328.0 307.9 2.8 1433.0 863.1 158.1 51.2 144.2 12427.3 86.1 186.0 13948.1 22.1 717.7 235.2 9.8 346.8 88.4 0.0 24.6 16261.0 177.7 102.7 29.6 1.9 266.3 161.2 3982.1 39.8 48.6 0.1 3.2 2735.6 47926.2 0.0 6352.3 13.0 22.8 645.6 4.1 1510.8 754.3 458.5 1052.0 965.6 1136.4 1181.8 102.2 3.1 642.9 1171.1 15892.2 1006.4 0.0 26.8 233.6 512.7 1.0 0.0 68.4 667.4 1.9 8.7 8721.1 63.7 275.8
76.9 665.9 5683.6 1.9 230.5 3.5 9.1 297.1 220.6 6.5 949.1 1413.6 117.3 16.9 114.6 7349.0 81.6 95.1 14172.0 22.0 304.7 69.6 46.5 575.1 154.3 0.1 80.7 26101.0 217.5 657.0 41.8 1.5 85.9 90.0 4565.6 40.6 137.3 2.1 0.0 3316.0 36450.2 1.8 8178.9 43.7 25.3 628.1 0.0 2956.3 322.7 448.6 1248.9 1208.5 1267.0 1234.5 95.4 1.2 578.6 1176.5 16736.0 942.0 0.5 87.5 146.9 257.4 0.5 0.0 125.4 888.4 0.0 17.2 10242.3 113.6 511.5
107.0 240.2 11328.1 3.0 92.4 0.2 15.4 3598.7 510.8 8.2 905.2 1325.0 132.5 23.8 47.3 4940.4 168.8 244.4 15308.7 21.8 269.6 437.4 43.0 668.1 284.6 0.0 187.4 22776.5 287.6 353.7 81.9 0.0 74.8 241.6 5310.6 34.3 188.3 0.0 2.9 2933.7 21541.0 7.5 7905.1 32.7 95.9 140.8 0.0 1688.5 400.8 886.6 869.8 1360.8 1380.4 1270.9 56.5 3.5 791.6 1524.6 17371.4 1308.7 0.1 69.9 1376.6 160.3 1.3 3.1 270.6 1021.0 0.0 16.1 9369.8 83.9 380.3
5.3 256.3 10687.4 2.0 164.6 0.2 0.5 1735.4 182.2 14.0 777.2 1452.3 2112.6 12.0 294.1 15034.2 126.7 2208.3 14878.1 25.4 562.5 28.7 33.0 738.9 409.6 17.2 58.8 25724.2 569.8 155.6 154.9 5.4 132.1 194.0 4882.8 37.9 1.3 6.6 0.1 2983.3 23307.6 0.0 8485.7 46.7 160.1 110.9 0.0 1707.5 1271.6 623.3 1304.4 1192.5 1372.7 1681.0 111.2 0.8 695.7 2460.3 17799.3 923.5 5.4 177.6 823.0 387.9 1.5 0.1 248.4 1047.6 0.0 13.7 9523.1 93.1 367.7
43.4 120.3 11504.2 1.3 157.9 0.1 11.9 1475.5 359.3 3.0 990.4 1352.4 2501.4 18.1 86.6 1772.2 135.2 3545.7 13755.1 21.2 508.4 24.4 0.0 1045.3 242.0 0.0 1.3 24945.1 366.5 167.0 35.0 9.5 91.4 189.8 5331.0 69.3 106.6 0.0 0.7 4344.2 23529.5 0.9 6755.1 60.5 162.9 73.8 0.0 1875.2 1118.3 415.3 937.2 1164.6 1072.1 1544.9 182.2 5.2 950.1 1638.7 16886.5 1530.9 0.3 12.3 574.9 427.4 1.8 0.0 160.5 970.3 0.0 12.2 9025.3 149.3 61.4
292.4 1388.3 49053.2 11.0 869.4 6.4 43.9 7434.7 1580.8 34.6 5055.0 6404.9 5022.0 122.0 686.9 41523.0 598.4 6279.5 72061.9 112.5 2362.8 795.3 132.3 3374.2 1190.0 17.3 352.9 115807.8 1619.1 1441.8 343.2 18.3 650.4 876.6 24072.1 221.8 482.0 8.9 6.8 16312.8 152752.2 10.3 37677.0 196.6 467.0 1599.3 4.2 9738.3 3867.7 2849.3 5412.3 6318.3 6228.6 6913.1 547.5 13.8 3658.8 7971.2 84685.3 5711.5 6.4 374.1 3154.9 1745.7 6.2 3.3 873.0 4594.7 1.9 68.0 46881.6 503.6 1596.6
Appendix Va - p.1
Appendix Va: Gross virtual water import per country for the years 1995-1999 (106 m3) Country GEORGIA GERMANY GHANA GIBRALTAR GREECE GREENLAND GRENADA GUADELOUPE GUATEMALA GUINEA GUINEABISSAU GUYANA HAITI HONDURAS HONG KONG HUNGARY ICELAND INDIA INDONESIA IRAN (ISLM.R) IRAQ IRELAND ISRAEL ITALY JAMAICA JAPAN JORDAN KAZAKHSTAN KENYA KIRIBATI KOREA D P RP KOREA REP. KUWAIT KYRGYZSTAN LAO P.DEM.R LATVIA LEBANON LIBERIA LIBYA LITHUANIA MACAU MACEDONIA, TFYR MADAGASCAR MALAWI MALAYSIA MALDIVES MALI MALTA MARSHALL IS. MARTINIQUE MAURITANIA MAURITIUS MEXICO MICRON, F.ST MOLDOVA REP. MONGOLIA MONTSERRAT MOROCCO MOZAMBIQUE MYANMAR N.CALEDONIA N.MARIANA NAURU NEPAL NETH.ANTILES NETHERLANDS NEW ZEALAND NICARAGUA NIGER NIGERIA NORFOLK ISLD NORWAY OMAN
1995
1996
1997
1998
1999
Total
206.8 20653.3 320.2 0.5 2740.6 1.0 29.7 49.4 851.9 93.4 14.7 81.2 363.9 528.8 3182.6 452.6 57.0 595.7 25841.8 5904.1 50.8 813.1 2314.5 19087.4 414.6 55326.2 7731.2 16.4 1998.6 0.1 563.0 19013.1 472.4 270.1 89.0 235.8 767.5 66.9 647.1 588.3 122.7 21.3 547.2 42.4 10337.4 25.4 77.3 306.9 2.9 10.3 160.8 489.5 16237.9 8.8 202.8 16.9 0.0 6838.3 445.8 9.2 14.7 16.1 1.0 128.6 48.3 33476.2 931.3 478.7 206.4 1010.8 0.0 2551.2 1263.4
501.8 23907.8 617.4 0.4 3193.6 0.4 49.7 0.0 1209.5 53.5 14.0 59.1 321.6 625.1 3344.2 539.1 59.7 1517.0 24063.7 5393.2 172.7 877.6 5270.7 19275.5 423.9 60193.5 1196.9 74.6 635.5 0.2 440.1 22870.1 356.0 494.6 127.0 470.8 824.2 168.0 669.6 757.7 124.0 149.6 163.5 13.4 11549.1 14.0 29.7 325.6 2.0 0.0 442.6 658.4 25277.9 14.0 86.7 6.1 0.0 6391.8 219.0 4.9 13.5 0.4 0.0 64.1 94.4 35300.6 971.8 684.4 242.4 4410.2 1.8 2085.8 1097.1
259.3 21815.3 657.0 0.8 3093.2 1.3 30.7 0.0 1120.2 33.4 3.1 71.9 305.2 846.7 3119.5 987.2 66.1 4084.9 18687.4 8339.0 1669.0 886.6 5798.8 20528.5 375.3 63662.0 7585.9 40.6 612.4 0.4 1084.1 23638.2 621.4 84.5 169.4 319.4 635.3 60.5 1273.8 578.1 118.1 294.8 228.6 12.3 12024.4 12.0 35.3 306.9 2.4 0.0 517.3 469.1 22053.6 10.7 21.1 27.7 0.0 6433.2 247.5 31.2 42.6 1.9 0.0 26.6 42.7 37646.8 1144.2 446.7 422.7 7711.9 1.7 1872.5 1198.2
392.1 24692.0 727.2 12.1 3584.7 1.7 32.7 0.0 1186.3 63.0 0.4 47.0 376.3 996.6 3046.2 599.2 68.9 4449.0 28330.4 5144.5 1985.9 1090.5 4895.4 20113.9 368.1 60148.1 3695.0 51.2 922.9 0.4 674.0 23933.4 379.6 54.2 61.5 290.1 560.5 20.9 822.5 394.6 4.3 211.3 265.1 2.8 12571.0 2.0 196.3 294.5 1.9 0.0 676.4 566.9 27729.9 8.0 50.3 41.3 0.2 3743.7 499.9 33.4 14.0 2.8 0.0 18.3 32.2 32509.4 770.4 621.6 658.9 9038.5 0.0 1832.7 1138.5
181.9 25206.0 1034.5 40.6 2977.2 1.8 52.4 0.0 1607.5 167.2 9.4 80.4 578.2 998.4 2864.2 599.8 72.3 1418.6 9907.7 7997.4 1618.1 1061.1 7424.9 19123.8 382.3 58830.0 1425.3 29.2 681.5 0.1 453.6 23458.2 570.2 59.0 23.9 191.1 758.0 21.0 532.5 183.8 115.8 67.7 395.6 58.5 11059.7 4.7 60.6 353.2 1.4 0.0 81.6 639.4 30507.5 5.6 53.1 31.2 0.0 3632.1 272.6 26.8 13.9 4.1 0.0 0.5 42.3 35994.6 1188.8 686.9 17.2 6810.9 0.0 2731.3 1407.1
1541.9 116301.9 3356.2 54.4 15607.0 6.2 195.1 49.4 5975.4 410.5 41.5 339.6 1945.2 3995.5 15556.7 3177.9 324.1 12065.2 106831.0 33115.7 5503.3 4728.9 25940.3 98129.1 1964.2 298159.8 22680.1 209.1 4850.8 1.3 3214.9 112913.0 2488.8 962.3 470.9 1507.0 3880.8 337.3 3945.6 2502.1 484.9 744.8 1600.0 129.4 57541.6 58.1 399.2 1587.2 10.6 10.3 1878.6 2823.4 121806.7 47.1 413.9 123.2 0.2 28089.0 1684.8 105.5 98.7 25.3 1.1 238.1 259.8 175011.7 5003.2 2918.2 1547.6 28982.2 3.5 11073.4 6140.4
Appendix Va - p.2
Appendix Va: Gross virtual water import per country for the years 1995-1999 (106 m3) Country PAKISTAN PALAU PANAMA PAPUA N.GUIN PARAGUAY PERU PHILIPPINES PITCAIRN POLAND PORTUGAL QATAR REUNION ROMANIA RUSSIAN FED RWANDA S.AFR.CUS.UN S.VINCENT-GR SAMOA SAO TOME PRN SAUDI ARABIA SENEGAL SEYCHELLES SIERRA LEONE SINGAPORE SLOVAKIA SLOVENIA SOLOMON ISLS SOMALIA SPAIN SRI LANKA ST.HELENA ST.KITTS NEV ST.LUCIA ST.PIER.MIQU SUDAN SURINAME SWEDEN SWITZ.LIECHT SYRIA A. R. TAIWAN (POC) TAJIKISTAN TANZANIA, U.R THAILAND TOGO TOKELAU TONGA TRINIDAD TBG TUNISIA TURKEY TURKMENISTAN TURKS CA.ISL UGANDA UKRAINE UNTD ARAB EM UNTD KINGDOM URUGUAY US MSC.PACIFIC USA UZBEKISTAN VANUATU VENEZUELA VIET NAM WALLIS FUT.IS YEMEN YUGOSLAVIA ZAMBIA ZIMBABWE Grand Total
1995
1996
1997
1998
1999
Total
2517.0 6.4 422.9 47.1 224.9 4912.5 3712.4 0.0 4579.4 6469.1 48.9 380.5 798.4 2422.6 112.4 8609.4 58.4 0.3 2.6 12240.6 1304.3 17.3 325.9 3889.2 245.2 1266.1 0.6 170.0 21848.7 1404.4 0.0 3.2 1.3 0.0 258.6 30.2 514.7 2224.7 1011.0 7331.2 50.8 719.4 2718.4 599.4 0.0 1.0 805.0 6082.4 6494.9 139.0 0.1 171.8 349.8 2658.5 11994.1 618.7 57.4 23579.1 435.7 0.0 5158.6 173.6 0.0 1421.4 43.9 29.0 121.2 558839.1
2335.3 3.4 520.9 65.0 388.5 5723.8 9576.3 0.0 6740.0 6700.8 36.2 0.0 1086.5 15072.4 119.8 7072.8 54.7 0.9 7.9 14016.2 2721.0 11.5 18.7 3910.3 401.3 1132.8 0.3 334.9 18177.9 206708.4 0.0 5.3 0.9 0.3 561.3 32.4 738.1 2088.1 715.9 7553.6 52.6 924.0 3215.1 388.8 0.0 0.2 842.4 2885.5 11644.9 121.3 0.1 134.0 359.6 1380.1 14326.6 809.4 12.7 26513.8 981.3 0.1 5315.8 100.2 0.0 1947.1 647.3 68.8 49.2 812513.7
4091.0 8.0 595.6 68.9 265.4 5788.4 10949.5 0.2 3099.2 6365.3 55.5 0.0 757.1 17122.9 28.3 6058.6 67.6 0.5 4.2 6480.1 2244.3 20.0 29.7 3785.8 709.7 909.4 0.1 285.4 20299.2 173081.4 0.0 4.1 1.5 0.1 752.0 21.5 729.1 2057.0 672.8 7431.2 60.3 1905.0 4232.1 856.8 0.0 0.0 823.5 3725.7 11974.8 20.5 0.1 69.6 375.3 1710.8 15143.9 670.7 5.6 36844.1 586.7 0.0 5786.9 113.1 0.0 1138.5 715.0 5.9 124.7 792869.1
2125.6 1.2 671.3 48.7 284.4 6215.4 12125.7 0.0 3834.9 7373.0 123.6 0.0 966.1 15768.6 116.1 7186.8 57.2 1.1 0.6 14225.7 3327.1 74.6 23.5 3316.5 325.4 956.5 0.6 557.4 24763.4 52171.3 3.5 17.0 1.6 0.2 1014.1 23.3 851.1 2034.5 648.0 7155.4 59.0 1385.2 4564.2 1223.6 0.0 12.2 593.4 3401.1 12108.4 4.8 0.2 325.0 904.5 2184.9 15099.5 1022.0 1.7 27793.3 607.5 0.1 8063.7 176.6 0.0 1374.4 269.9 12.3 52.6 699989.7
1666.5 1.1 488.5 14.9 551.6 5191.5 4562.2 0.0 2797.6 6882.0 32.2 0.0 740.6 22286.2 88.4 5710.5 43.4 0.6 1.9 5063.8 3805.2 15.5 18.3 4294.7 251.6 1049.7 1.3 151.1 25533.8 3269.8 4.0 6.7 0.7 0.0 220.4 30.4 853.4 2090.4 1375.0 6524.2 10.7 1124.2 5760.1 1189.2 0.0 5.3 333.8 2932.1 9264.8 1.5 0.3 343.6 355.1 2241.9 14454.6 988.2 14.5 31591.3 52.7 0.1 6928.9 205.1 0.0 1363.0 87.6 57.9 231.1 600677.0
12735.3 20.1 2699.2 244.5 1714.9 27831.6 41033.6 0.2 21050.6 33790.2 296.4 380.5 4388.4 72672.6 465.0 34638.1 281.3 3.4 17.1 56566.6 13401.9 138.9 416.2 19196.2 1933.2 5314.4 3.0 1498.7 110623.1 436635.3 7.5 36.4 6.1 0.6 2806.3 137.7 3686.4 10494.6 4422.7 35995.5 233.4 6057.7 20489.8 4257.8 0.0 18.7 3398.1 19625.6 51487.8 287.1 0.9 1043.9 2344.3 10546.8 71020.6 4109.0 91.9 146321.5 2663.7 0.3 31253.9 768.8 0.0 7244.5 1763.6 173.9 578.9 3474587.7
Appendix Va - p.3
Appendix Vb. Gross virtual water export per country in the years 1995-1999 (106 m3) Country AFGHANISTAN ALBANIA ALGERIA ANDORRA ANGOLA ANGUILLA ANTIGUA BARB ARGENTINA ARMENIA ARUBA AUSTRALIA AUSTRIA AZERBAIJAN BAHAMAS BAHRAIN BANGLADESH BARBADOS BELARUS BELGIUM-LUX BELIZE BENIN BERMUDA BHUTAN BOLIVIA BOSNIA HERZG BRITISH INDIAN OCEAN TER BR.VIRGIN.IS BRAZIL BRUNEI DAR. BULGARIA BURKINA FASO BURUNDI CAMBODIA CAMEROON CANADA CAP VERDE CAYMAN ISLDS CENT.AF.REP CHAD CHILE CHINA COCOS ISLNDS COLOMBIA COMOROS CONGO CONGO, D.R. COOK ISLANDS COSTA RICA COTE DIVOIRE CROATIA CUBA CYPRUS CZECH REP DENMARK DJIBOUTI DOMINICA DOMINICAN RP ECUADOR EGYPT EL SALVADOR EQ.GUINEA ERITREA ESTONIA ETHIOPIA FAEROE ISLDS FALKLAND ISL FIJI FINLAND FR. GUIANA FR.POLYNESIA FRANCE GABON GAMBIA
1995
1996
1997
1998
1999
Total
31.4 6.2 0.2 0.0 0.0 0.0 0.0 37070.2 0.0 0.0 14702.5 918.1 0.0 38.8 0.0 36.7 8.3 43.6 2218.1 50.4 620.9 36.8 0.0 1755.6 5.8 0.0 0.0 18204.4 0.0 1230.6 39.2 0.4 65.5 176.3 59311.3 0.0 1.2 1.0 0.0 1227.0 5703.9 0.0 752.3 0.1 5.1 9.8 0.0 560.2 173.0 624.7 849.4 262.6 1746.2 2211.0 0.0 662.6 1833.0 1684.2 590.3 88.4 0.0 0.0 39.7 26.0 0.0 0.0 0.0 1098.7 0.0 0.0 27178.3 0.0 125.6
122.1 11.4 25.2 0.0 0.0 0.0 0.0 45187.6 0.1 0.0 43171.3 649.6 34.7 57.8 0.0 5162.7 15.0 6.0 1978.1 55.2 1031.0 4.5 0.0 1977.2 283.9 0.0 0.0 20261.8 0.0 413.2 8.6 0.5 23.7 190.2 58122.6 0.0 0.0 0.4 0.0 1266.4 4456.6 0.0 794.0 0.0 2.7 9.0 0.0 1007.0 47.1 621.0 1322.9 278.3 418.5 1707.3 0.0 801.1 2823.0 2285.9 1457.3 78.4 0.0 0.0 16.1 39.3 0.0 0.0 0.0 972.2 0.0 0.0 24851.6 0.0 165.0
979.7 37.1 0.4 0.0 0.0 0.0 0.0 40267.0 2.1 0.0 35407.8 978.2 21.9 135.9 0.0 1017.0 30.7 6.9 2836.2 107.3 1160.3 0.4 0.0 1781.7 14.0 0.0 0.0 38566.1 0.0 226.1 46.2 0.0 31.2 157.5 71206.1 0.0 18.1 0.5 0.0 1188.1 12851.5 0.0 900.2 0.0 10.5 3.6 0.0 573.2 33.7 115.4 1770.5 131.9 173.0 1923.1 0.9 738.0 4581.4 2872.0 648.8 106.9 0.0 1.2 96.7 24.7 0.0 0.0 0.0 1343.6 0.0 0.0 26509.0 0.3 88.3
154.3 12.6 5.5 0.0 0.0 0.0 0.0 59010.8 23.4 0.0 31600.0 1189.0 26.7 104.6 0.0 6592.4 23.9 64.7 2671.9 60.5 1753.0 55.1 0.0 1481.9 13.7 0.0 0.0 40859.8 0.0 815.9 2628.3 0.3 2.5 163.3 56989.1 0.0 0.0 0.8 0.0 1189.6 15344.9 0.0 883.0 0.0 5.7 1.6 0.0 637.3 112.7 227.6 1170.5 143.0 338.7 1840.1 0.0 334.7 2700.5 1835.9 1099.5 77.0 0.0 0.0 276.5 9.5 0.0 0.0 0.0 1221.9 0.0 0.0 26532.0 3.1 440.6
150.1 4.9 3.3 0.0 27.5 0.0 0.0 52241.1 2.2 0.0 25782.5 1145.4 66.8 36.3 1.2 4.1 9.5 54.0 2780.8 265.4 823.9 25.4 0.0 1664.2 1.4 0.0 0.0 42916.8 0.1 1113.0 2144.5 0.0 15.4 252.5 50913.0 0.0 0.0 11.8 0.0 1184.7 12217.5 0.0 996.4 0.0 10.1 0.7 0.0 672.2 51.3 141.2 1406.8 178.6 1129.7 1536.7 0.0 568.5 1381.5 2244.1 711.9 122.4 0.0 0.0 73.1 14.0 0.0 0.0 0.0 822.5 0.0 0.0 30186.4 0.0 1.6
1437.6 72.2 34.6 0.0 27.5 0.0 0.0 233776.8 27.7 0.0 150651.5 4880.3 150.1 373.3 1.2 12813.0 87.3 175.2 12485.1 538.9 5389.1 122.2 0.0 8660.5 318.8 0.0 0.0 160808.8 0.1 3798.7 4866.8 1.3 138.4 939.7 296542.0 0.0 19.3 14.5 0.0 6055.8 50574.4 0.0 4325.8 0.1 34.1 24.7 0.0 3450.0 417.7 1729.8 6520.0 994.4 3806.1 9218.2 0.9 3104.9 13319.5 10922.1 4507.8 473.1 0.0 1.3 502.1 113.4 0.0 0.0 0.0 5459.0 0.0 0.0 135257.2 3.5 821.1
Appendix Vb - p.1
Appendix Vb. Gross virtual water export per country in the years 1995-1999 (106 m3) Country GEORGIA GERMANY GHANA GIBRALTAR GREECE GREENLAND GRENADA GUADELOUPE GUATEMALA GUINEA GUINEABISSAU GUYANA HAITI HONDURAS HONG KONG HUNGARY ICELAND INDIA INDONESIA IRAN (ISLM.R) IRAQ IRELAND ISRAEL ITALY JAMAICA JAPAN JORDAN KAZAKHSTAN KENYA KIRIBATI KOREA D P RP KOREA REP. KUWAIT KYRGYZSTAN LAO P.DEM.R LATVIA LEBANON LIBERIA LIBYA LITHUANIA MACAU MACEDONIA, TFYR MADAGASCAR MALAWI MALAYSIA MALDIVES MALI MALTA MARSHALL IS. MARTINIQUE MAURITANIA MAURITIUS MEXICO MICRON, F. ST MOLDOVA REP. MONGOLIA MONTSERRAT MOROCCO MOZAMBIQUE MYANMAR N.CALEDONIA N.MARIANA NAURU NEPAL NETH.ANTILES NETHERLANDS NEW ZEALAND NICARAGUA NIGER NIGERIA NORFOLK ISLD NORWAY OMAN
1995
1996
1997
1998
1999
Total
0.0 8425.5 91.4 0.0 5728.8 0.0 32.0 31.3 1735.4 21.5 6.4 95.3 0.0 209.9 241.7 5988.5 0.9 25203.5 730.8 409.7 0.0 137.6 271.5 6380.9 143.3 128.7 102.3 674.0 331.6 0.0 1.7 48.8 0.2 126.7 2.7 11.5 40.5 0.0 36.7 145.7 0.9 53.1 97.7 429.7 350.7 0.0 9.9 20.9 0.0 59.5 0.0 242.1 3804.7 0.0 412.5 44.0 55.8 128.4 69.4 1486.4 0.0 0.0 0.0 0.0 0.0 4164.9 86.1 310.4 100.1 190.6 0.0 13.5 105.0
1.7 10269.3 95.6 0.0 5235.5 0.0 0.5 0.0 1658.0 19.5 6.2 101.2 0.0 343.0 840.8 2501.5 0.2 85625.4 738.8 1221.6 0.1 154.1 644.3 7035.1 163.1 40.2 7.1 8164.1 320.4 0.0 1.7 38.9 0.1 245.2 0.8 18.7 39.2 0.0 25.6 130.7 0.6 146.4 176.2 926.6 2579.4 0.0 7.5 114.5 0.0 0.0 0.2 317.7 11384.8 0.0 205.0 0.0 104.6 88.7 103.0 1141.4 0.0 0.0 0.0 1.7 0.0 4204.1 92.2 330.8 137.8 777.6 0.0 20.6 93.2
82.7 8246.2 172.9 0.0 5486.3 0.0 0.9 0.0 69278.5 27.5 8.8 250.3 0.0 438.4 16.2 3897.5 6.8 28994.7 772.4 504.7 0.1 298.6 651.9 6948.7 143.4 79.7 122.6 10937.1 52.7 0.0 7.3 35.3 0.0 93.9 0.6 101.1 14.2 0.0 31.3 329.5 0.9 122.0 245.4 883.0 1313.1 0.0 16.8 39.0 0.0 0.0 2.9 271.5 32768.8 0.0 213.1 0.0 32.8 95.8 67.6 12430.4 0.0 0.0 0.0 2.7 0.0 5069.3 131.2 462.6 137.4 127.4 0.0 7.9 122.9
239.1 13410.9 364.6 0.0 3571.3 0.0 0.2 0.0 2527.4 52.7 5.5 351.8 0.2 328.7 38.6 6388.1 0.0 29101.4 2538.3 1259.0 16.2 287.3 682.3 6751.3 126.1 498.0 31.3 8188.2 69.0 0.0 0.4 80.5 0.0 133.2 0.9 37.9 44.9 8.7 66.4 513.7 0.0 121.8 72.3 849.2 621.3 0.0 39.2 27.2 0.0 0.0 0.0 291.6 24973.8 0.0 323.6 0.0 7.3 51.1 130.9 2044.7 0.0 0.0 0.0 90.5 0.0 6546.6 153.0 251.0 163.6 194.2 0.0 8.2 141.6
191.3 8004.7 362.8 0.0 5418.0 0.0 2.1 0.0 2483.5 83.1 0.0 334.4 0.0 338.7 77.8 4104.6 0.1 4136.6 915.6 622.1 0.0 131.8 699.3 6694.4 110.5 195.5 11.6 11416.4 74.6 0.0 0.0 141.5 0.0 127.0 3.5 97.5 8.3 0.0 67.0 800.1 0.1 46.1 67.1 844.7 1415.3 0.0 0.9 26.8 0.0 0.0 0.0 251.7 3941.3 0.0 1123.3 9.0 0.0 72.8 54.5 403.7 0.0 0.0 0.0 0.0 0.0 7328.3 103.1 310.8 0.7 3382.4 0.0 5.2 135.2
514.8 48356.6 1087.3 0.0 25439.8 0.0 42.7 31.3 77682.8 204.4 26.9 1132.9 0.2 1658.7 1215.1 22948.1 7.9 173061.6 5695.9 4017.1 16.4 1009.3 2949.3 33810.3 686.5 942.0 275.0 39379.8 848.3 0.0 11.1 345.1 0.3 726.1 8.6 266.8 147.0 8.7 227.0 1919.7 2.5 489.3 658.6 3933.2 6279.7 0.0 74.3 228.5 0.0 59.5 3.1 1374.6 76873.4 0.0 2277.5 50.7 200.5 436.8 425.3 17506.6 0.0 0.0 0.0 95.0 0.0 27313.0 565.6 1665.5 539.7 4672.1 0.0 55.4 597.9
Appendix Vb - p.2
Appendix Vb. Gross virtual water export per country in the years 1995-1999 (106 m3) Country PAKISTAN PALAU PANAMA PAPUA N.GUIN PARAGUAY PERU PHILIPPINES PITCAIRN POLAND PORTUGAL QATAR REUNION ROMANIA RUSSIAN FED RWANDA S.AFR.CUS.UN S.VINCENT-GR SAMOA SAO TOME PRN SAUDI ARABIA SENEGAL SEYCHELLES SIERRA LEONE SINGAPORE SLOVAKIA SLOVENIA SOLOMON ISLS SOMALIA SPAIN SRI LANKA ST.HELENA ST.KITTS NEV ST.LUCIA ST.PIER.MIQU SUDAN SURINAME SWEDEN SWITZ.LIECHT SYRIA A. R. TAIWAN (POC) TAJIKISTAN TANZANIA, U.R THAILAND TOGO TOKELAU TONGA TRINIDAD TBG TUNISIA TURKEY TURKMENISTAN TURKS CA.ISL UGANDA UKRAINE UNTD ARAB EM UNTD KINGDOM URUGUAY US MSC.PACIFIC USA UZBEKISTAN VANUATU VENEZUELA VIET NAM WALLIS FUT.I YEMEN YUGOSLAVIA ZAMBIA ZIMBABWE Grand Total
1995
1996
1997
1998
1999
Total
2945.8 0.0 357.8 17.1 7138.7 123.2 4366.0 0.0 281.6 315.8 0.1 68.7 1538.0 6422.8 0.7 2275.5 0.0 1.7 0.0 1999.5 21.8 0.0 2.1 291.4 1394.0 11.1 1.3 32.3 4459.8 71.3 0.0 5.8 1254.2 0.0 5417.3 60.9 735.7 186.2 9486.6 259.8 1.5 109.9 41728.1 0.9 0.0 0.0 98.3 34.4 5217.1 0.0 0.0 510.0 2128.8 376.8 5614.5 1617.1 0.0 191579.1 1.6 0.0 1125.8 2770.0 1.4 5.5 45.4 67.0 461.6 558839.1
2756.1 0.0 314.3 22.2 8439.5 111.7 9633.0 0.0 218.4 272.3 0.0 0.0 3647.7 16476.2 0.0 3487.6 0.0 1.4 0.0 123.9 65.4 0.0 0.2 301.4 449.3 9.3 0.3 36.0 6038.5 3052.5 0.0 4.8 1335.7 0.0 511.8 130.1 1352.5 124.5 2610.1 208.0 69.0 141.8 90840.7 208.9 0.0 0.0 167.2 61.4 4154.0 0.2 0.0 647.8 6624.3 246.4 6313.7 5672.3 0.0 195159.6 103.7 0.0 2831.3 62568.1 0.0 11.4 1312.3 79.2 708.7 812513.7
1862.2 0.0 392.7 21.2 11766.6 129.9 8821.6 0.0 357.9 718.0 0.0 0.0 1744.5 12951.4 0.0 2537.4 0.0 1.1 0.0 14.8 57.8 0.0 0.2 712.4 515.3 16.4 3.1 31.0 5945.0 2613.8 0.0 9.1 884.0 0.0 381.4 147.5 1922.6 133.4 10175.2 102.1 124.5 358.4 37361.8 1.7 0.0 0.1 116.1 86.8 4430.0 1.5 0.0 35.5 6344.1 409.7 52929.6 3413.9 0.0 172422.8 296.5 0.0 969.2 3048.8 0.0 0.0 223.1 199.0 806.4 792869.1
3585.7 0.0 292.1 21.5 5593.9 263.9 8950.6 0.0 444.7 489.8 0.0 0.0 2620.5 17448.4 0.0 1597.9 0.0 0.6 0.0 32.8 42.2 0.0 0.2 695.8 1160.7 45.7 3.7 14.0 5661.1 2411.4 0.0 6.8 899.5 0.0 946.0 135.5 2091.1 176.2 3949.5 151.5 143.4 391.2 44381.4 428.0 0.0 0.0 44.9 98.4 9058.6 0.8 0.0 190.1 9397.9 507.1 6408.6 2668.7 0.0 165017.7 118.5 0.0 1228.9 21001.7 0.0 40.5 707.5 212.6 663.2 699989.7
1634.3 0.0 298.7 20.0 10901.7 89.0 4438.9 0.0 959.4 853.6 0.0 0.0 3955.3 7104.9 0.0 2893.3 0.0 0.9 0.0 4.8 30.6 0.0 0.5 174.9 1367.6 26.4 1.3 0.0 6000.8 19.5 0.0 5.1 837.5 0.0 1305.2 98.5 1783.9 192.0 94.5 112.3 80.2 415.9 39504.7 434.3 0.0 0.0 26.5 7.8 8717.4 0.4 0.0 90.5 9668.0 550.5 4606.1 2744.5 0.0 180442.5 98.2 0.0 470.7 1539.9 0.0 0.0 153.2 106.9 526.4 600677.0
12784.2 0.0 1655.6 102.1 43840.4 717.7 36210.1 0.0 2262.1 2649.5 0.1 68.7 13506.1 60397.9 0.8 12791.7 0.0 5.7 0.0 2175.9 217.9 0.0 3.2 2175.8 4887.0 109.0 9.7 113.4 28105.2 8168.6 0.0 31.7 5210.9 0.0 8561.7 572.5 7885.8 812.3 26315.8 833.7 418.6 1417.3 253816.7 1073.9 0.0 0.1 453.0 288.8 41222.2 2.8 0.0 1473.8 34163.1 2090.5 75872.5 16116.4 0.0 904621.7 618.5 0.0 6625.9 90928.5 1.4 57.3 2441.5 664.6 3166.4 3474587.7
Appendix Vb - p.3
Appendix Vc. Net virtual water import per country in the years 1995-1999 (106 m3) Country AFGHANISTAN ALBANIA ALGERIA ANDORRA ANGOLA ANGUILLA ANTIGUA BARB ARGENTINA ARMENIA ARUBA AUSTRALIA AUSTRIA AZERBAIJAN BAHAMAS BAHRAIN BANGLADESH BARBADOS BELARUS BELGIUM-LUX BELIZE BENIN BERMUDA BHUTAN BOLIVIA BOSNIA HERZG BRITISH INDIAN OCEAN TER BR.VIRGIN.IS BRAZIL BRUNEI DAR. BULGARIA BURKINA FASO BURUNDI CAMBODIA CAMEROON CANADA CAP VERDE CAYMAN ISLDS CENT.AF.REP CHAD CHILE CHINA COCOS ISLNDS COLOMBIA COMOROS CONGO CONGO, D.R. COOK ISLANDS COSTA RICA COTE DIVOIRE CROATIA CUBA CYPRUS CZECH REP DENMARK DJIBOUTI DOMINICA DOMINICAN RP ECUADOR EGYPT EL SALVADOR EQ.GUINEA ERITREA ESTONIA ETHIOPIA FAEROE ISLDS FALKLAND ISL FIJI FINLAND FR. GUIANA FR.POLYNESIA FRANCE GABON GAMBIA
1995
1996
1997
1998
1999
Total
28.5 99.5 9523.2 2.8 223.9 2.3 7.0 -36742.2 307.9 2.8 -13269.4 -55.0 158.1 12.5 144.2 12390.5 77.9 142.4 11730.1 -28.3 96.8 198.4 9.8 -1408.7 82.5 0.0 24.6 -1943.3 177.7 -1127.9 -9.6 1.5 200.8 -15.1 -55329.2 39.8 47.3 -0.9 3.2 1508.6 42222.3 0.0 5600.0 12.9 17.7 635.9 4.1 950.6 581.3 -166.2 202.6 703.0 -609.8 -1029.3 102.2 -659.5 -1190.1 -513.1 15301.9 918.0 0.0 26.8 193.9 486.7 1.0 0.0 68.4 -431.4 1.9 8.7 -18457.2 63.7 150.2
-45.2 654.4 5658.4 1.9 230.5 3.5 9.1 -44890.5 220.5 6.5 -42222.2 764.0 82.6 -40.9 114.6 2186.3 66.7 89.1 12193.9 -33.2 -726.3 65.1 46.5 -1402.1 -129.6 0.1 80.7 5839.2 217.5 243.8 33.2 1.0 62.1 -100.1 -53557.0 40.6 137.3 1.7 0.0 2049.6 31993.6 1.8 7384.9 43.7 22.6 619.1 0.0 1949.4 275.7 -172.4 -73.9 930.2 848.5 -472.8 95.4 -799.9 -2244.4 -1109.4 15278.7 863.6 0.5 87.5 130.8 218.1 0.5 0.0 125.4 -83.7 0.0 17.2 -14609.3 113.6 346.5
-872.8 203.2 11327.7 3.0 92.4 0.2 15.4 -36668.3 508.8 8.2 -34502.6 346.9 110.6 -112.1 47.3 3923.4 138.0 237.5 12472.4 -85.5 -890.7 437.1 43.0 -1113.6 270.6 0.0 187.4 -15789.6 287.6 127.6 35.7 0.0 43.6 84.2 -65895.5 34.3 170.2 -0.5 2.9 1745.5 8689.5 7.5 7004.9 32.7 85.5 137.2 0.0 1115.3 367.1 771.2 -900.6 1228.9 1207.5 -652.2 55.6 -734.5 -3789.8 -1347.4 16722.6 1201.9 0.1 68.7 1279.9 135.6 1.3 3.1 270.6 -322.6 0.0 16.1 -17139.2 83.6 292.0
-149.0 243.7 10681.9 2.0 164.6 0.2 0.5 -57275.4 158.8 14.0 -30822.8 263.3 2085.9 -92.6 294.1 8441.8 102.8 2143.6 12206.2 -35.1 -1190.6 -26.4 33.0 -742.9 395.9 17.2 58.8 -15135.6 569.8 -660.3 -2473.4 5.1 129.6 30.7 -52106.3 37.9 1.3 5.9 0.1 1793.7 7962.6 0.0 7602.7 46.7 154.4 109.3 0.0 1070.2 1159.0 395.7 133.9 1049.5 1034.0 -159.0 111.2 -333.9 -2004.8 624.4 16699.8 846.5 5.4 177.6 546.5 378.5 1.5 0.1 248.4 -174.3 0.0 13.7 -17008.9 89.9 -72.9
-106.7 115.4 11500.9 1.3 130.3 0.1 11.9 -50765.7 357.0 3.0 -24792.1 206.9 2434.6 -18.2 85.3 1768.0 125.7 3491.7 10974.3 -244.2 -315.5 -1.0 0.0 -618.9 240.6 0.0 1.3 -17971.8 366.3 -946.0 -2109.5 9.5 76.0 -62.7 -45582.0 69.3 106.6 -11.8 0.7 3159.5 11312.0 0.9 5758.7 60.5 152.8 73.1 0.0 1203.0 1067.0 274.2 -469.6 986.0 -57.6 8.2 182.2 -563.3 -431.5 -605.5 16174.5 1408.5 0.3 12.3 501.8 413.3 1.8 0.0 160.5 147.8 0.0 12.2 -21161.0 149.3 59.8
-1145.2 1316.2 49018.6 11.0 841.8 6.4 43.9 -226342.0 1553.0 34.6 -145596.6 1524.6 4871.8 -251.3 685.6 28710.0 511.0 6104.3 59576.8 -426.3 -3026.3 673.1 132.3 -5286.3 871.2 17.3 352.9 -45001.1 1619.0 -2357.0 -4523.6 17.1 512.0 -63.0 -272470.0 221.8 462.7 -5.6 6.8 10256.9 102177.8 10.3 33351.2 196.5 433.0 1574.6 4.2 6288.4 3450.0 1119.5 -1107.6 5323.9 2422.5 -2305.1 546.6 -3091.1 -9660.7 -2950.9 80177.5 5238.4 6.4 372.9 2652.9 1632.2 6.2 3.3 873.0 -864.3 1.9 68.0 -88375.7 500.1 775.5
Appendix Vc - p.1
Appendix Vc. Net virtual water import per country in the years 1995-1999 (106 m3) Country GEORGIA GERMANY GHANA GIBRALTAR GREECE GREENLAND GRENADA GUADELOUPE GUATEMALA GUINEA GUINEABISSAU GUYANA HAITI HONDURAS HONG KONG HUNGARY ICELAND INDIA INDONESIA IRAN (ISLM.R) IRAQ IRELAND ISRAEL ITALY JAMAICA JAPAN JORDAN KAZAKHSTAN KENYA KIRIBATI KOREA D P RP KOREA REP. KUWAIT KYRGYZSTAN LAO P.DEM.R LATVIA LEBANON LIBERIA LIBYA LITHUANIA MACAU MACEDONIA, TFYR MADAGASCAR MALAWI MALAYSIA MALDIVES MALI MALTA MARSHALL IS. MARTINIQUE MAURITANIA MAURITIUS MEXICO MICRON, F. ST MOLDOVA REP. MONGOLIA MONTSERRAT MOROCCO MOZAMBIQUE MYANMAR N.CALEDONIA N.MARIANA NAURU NEPAL NETH.ANTILES NETHERLANDS NEW ZEALAND NICARAGUA NIGER NIGERIA NORFOLK ISLD NORWAY OMAN
1995
1996
1997
1998
1999
Total
206.8 12227.8 228.8 0.5 -2988.3 1.0 -2.4 18.1 -883.5 71.9 8.2 -14.1 363.9 319.0 2940.9 -5535.9 56.0 -24607.8 25111.0 5494.4 50.8 675.5 2043.0 12706.5 271.3 55197.5 7628.9 -657.7 1667.0 0.1 561.3 18964.3 472.2 143.4 86.3 224.3 727.0 66.9 610.3 442.6 121.9 -31.8 449.6 -387.4 9986.7 25.4 67.5 285.9 2.9 -49.3 160.8 247.4 12433.2 8.8 -209.7 -27.1 -55.8 6709.9 376.4 -1477.2 14.7 16.1 1.0 128.5 48.3 29311.3 845.2 168.3 106.3 820.2 0.0 2537.7 1158.5
500.1 13638.5 521.8 0.4 -2041.9 0.4 49.2 0.0 -448.6 34.0 7.8 -42.1 321.6 282.1 2503.4 -1962.4 59.6 -84108.3 23324.8 4171.6 172.6 723.5 4626.4 12240.5 260.7 60153.3 1189.8 -8089.5 315.0 0.2 438.5 22831.2 355.8 249.4 126.2 452.1 785.1 168.0 644.0 627.0 123.4 3.3 -12.7 -913.1 8969.7 14.0 22.3 211.2 2.0 0.0 442.4 340.8 13893.1 14.0 -118.4 6.1 -104.6 6303.1 116.0 -1136.5 13.5 0.4 0.0 62.4 94.4 31096.6 879.6 353.6 104.5 3632.5 1.8 2065.3 1003.9
176.7 13569.1 484.1 0.8 -2393.1 1.3 29.9 0.0 -68158.3 5.9 -5.7 -178.3 305.2 408.2 3103.4 -2910.3 59.3 -24909.9 17915.1 7834.3 1669.0 588.0 5146.9 13579.9 231.9 63582.2 7463.3 -10896.5 559.6 0.4 1076.8 23602.8 621.4 -9.4 168.8 218.3 621.1 60.5 1242.5 248.6 117.2 172.8 -16.8 -870.7 10711.3 12.0 18.4 267.8 2.4 0.0 514.4 197.6 -10715.2 10.7 -192.0 27.7 -32.8 6337.4 179.9 -12399.3 42.6 1.9 0.0 24.0 42.7 32577.5 1013.0 -15.9 285.3 7584.5 1.7 1864.6 1075.4
153.0 11281.1 362.7 12.1 13.4 1.7 32.4 0.0 -1341.1 10.2 -5.1 -304.8 376.1 667.9 3007.6 -5788.9 68.9 -24652.4 25792.0 3885.5 1969.8 803.2 4213.1 13362.6 242.0 59650.2 3663.7 -8137.0 853.9 0.4 673.6 23852.9 379.6 -79.0 60.6 252.2 515.7 12.2 756.2 -119.1 4.3 89.5 192.8 -846.3 11949.8 2.0 157.1 267.3 1.9 0.0 676.4 275.2 2756.1 8.0 -273.3 41.3 -7.1 3692.6 369.1 -2011.3 14.0 2.8 0.0 -72.2 32.2 25962.8 617.4 370.6 495.3 8844.3 0.0 1824.5 996.9
-9.4 17201.3 671.7 40.6 -2440.8 1.8 50.3 0.0 -876.0 84.0 9.4 -254.0 578.2 659.7 2786.4 -3504.8 72.2 -2718.0 8992.2 7375.3 1618.1 929.4 6725.6 12429.4 271.8 58634.5 1413.7 -11387.2 606.9 0.1 453.6 23316.7 570.2 -68.1 20.5 93.6 749.7 21.0 465.5 -616.3 115.7 21.7 328.5 -786.3 9644.4 4.7 59.6 326.4 1.4 0.0 81.6 387.7 26566.2 5.6 -1070.2 22.2 0.0 3559.3 218.1 -376.9 13.9 4.1 0.0 0.5 42.3 28666.4 1085.7 376.1 16.5 3428.5 0.0 2726.1 1271.9
1027.2 67945.3 2268.9 54.4 -9832.8 6.2 152.5 18.1 -71707.4 206.1 14.5 -793.3 1945.1 2336.8 14341.7 -19770.2 316.2 -160996.4 101135.1 29098.6 5487.0 3719.6 22991.0 64318.7 1277.7 297217.8 22405.1 -39170.8 4002.5 1.3 3203.8 112567.9 2488.5 236.3 462.4 1240.2 3733.8 328.6 3718.6 582.4 482.4 255.5 941.4 -3803.8 51261.8 58.1 325.0 1358.6 10.6 -49.3 1875.6 1448.7 44933.3 47.1 -1863.6 72.5 -200.3 27652.1 1259.5 -17401.1 98.7 25.3 1.1 143.1 259.8 147698.7 4437.6 1252.7 1007.9 24310.1 3.5 11018.1 5542.5
Appendix Vc - p.2
Appendix Vc. Net virtual water import per country in the years 1995-1999 (106 m3) Country PAKISTAN PALAU PANAMA PAPUA N.GUIN PARAGUAY PERU PHILIPPINES PITCAIRN POLAND PORTUGAL QATAR REUNION ROMANIA RUSSIAN FED RWANDA S.AFR.CUS.UN S.VINCENT-GR SAMOA SAO TOME PRN SAUDI ARABIA SENEGAL SEYCHELLES SIERRA LEONE SINGAPORE SLOVAKIA SLOVENIA SOLOMON ISLS SOMALIA SPAIN SRI LANKA ST.HELENA ST.KITTS NEV ST.LUCIA ST.PIER.MIQU SUDAN SURINAME SWEDEN SWITZ.LIECHT SYRIA A. R. TAIWAN (POC) TAJIKISTAN TANZANIA, U.R THAILAND TOGO TOKELAU TONGA TRINIDAD TBG TUNISIA TURKEY TURKMENISTAN TURKS CA.ISL UGANDA UKRAINE UNTD ARAB EM UNTD KINGDOM URUGUAY US MSC.PACIFIC USA UZBEKISTAN VANUATU VENEZUELA VIET NAM WALLIS FUT.I YEMEN YUGOSLAVIA ZAMBIA ZIMBABWE Grand Total
1995
1996
1997
1998
1999
Total
-428.9 6.4 65.1 30.0 -6913.9 4789.3 -653.6 0.0 4297.7 6153.3 48.8 311.8 -739.5 -4000.2 111.7 6333.9 58.4 -1.4 2.6 10241.1 1282.5 17.3 323.8 3597.8 -1148.8 1254.9 -0.8 137.7 17388.9 1333.1 0.0 -2.6 -1252.8 0.0 -5158.7 -30.8 -221.1 2038.5 -8475.6 7071.4 49.3 609.5 -39009.7 598.5 0.0 1.0 706.7 6048.0 1277.8 139.0 0.1 -338.3 -1778.9 2281.6 6379.6 -998.4 57.4 -168000.0 434.2 0.0 4032.8 -2596.4 -1.4 1415.9 -1.5 -37.9 -340.4 0.0
-420.9 3.4 206.6 42.8 -8050.9 5612.1 -56.7 0.0 6521.6 6428.5 36.2 0.0 -2561.2 -1403.8 119.8 3585.2 54.7 -0.5 7.9 13892.3 2655.6 11.5 18.6 3608.9 -48.0 1123.5 0.0 298.9 12139.4 203655.9 0.0 0.5 -1334.8 0.3 49.6 -97.7 -614.4 1963.5 -1894.2 7345.6 -16.3 782.2 -87625.6 179.9 0.0 0.2 675.3 2824.1 7491.0 121.1 0.1 -513.8 -6264.7 1133.7 8012.9 -4862.9 12.7 -168645.8 877.6 0.1 2484.4 -62467.8 0.0 1935.7 -665.0 -10.4 -659.5 0.0
2228.8 8.0 202.9 47.6 -11501.1 5658.4 2127.9 0.2 2741.4 5647.3 55.5 0.0 -987.4 4171.4 28.3 3521.2 67.6 -0.6 4.2 6465.3 2186.5 20.0 29.5 3073.4 194.4 892.9 -2.9 254.4 14354.2 170467.6 0.0 -5.0 -882.5 0.1 370.5 -126.0 -1193.5 1923.6 -9502.4 7329.1 -64.3 1546.5 -33129.7 855.1 0.0 0.0 707.4 3639.0 7544.8 18.9 0.1 34.1 -5968.8 1301.1 -37785.8 -2743.2 5.6 -135578.8 290.2 0.0 4817.7 -2935.6 0.0 1138.5 491.9 -193.1 -681.7 0.0
-1460.2 1.2 379.2 27.2 -5309.5 5951.6 3175.1 0.0 3390.2 6883.3 123.6 0.0 -1654.4 -1679.8 116.1 5588.9 57.2 0.4 0.6 14192.9 3285.0 74.6 23.3 2620.7 -835.4 910.8 -3.1 543.3 19102.3 49759.9 3.5 10.2 -897.9 0.2 68.1 -112.2 -1240.0 1858.3 -3301.5 7003.9 -84.5 994.0 -39817.2 795.6 0.0 12.2 548.5 3302.7 3049.8 4.1 0.2 134.9 -8493.4 1677.8 8690.9 -1646.7 1.7 -137224.4 489.0 0.1 6834.8 -20825.0 0.0 1333.9 -437.6 -200.3 -610.6 0.0
32.2 1.1 189.8 -5.2 -10350.0 5102.5 123.3 0.0 1838.2 6028.4 32.2 0.0 -3214.8 15181.3 88.3 2817.2 43.4 -0.3 1.9 5058.9 3774.6 15.5 17.8 4119.8 -1116.0 1023.3 0.0 151.1 19533.0 3250.2 4.0 1.6 -836.8 0.0 -1084.9 -68.1 -930.5 1898.3 1280.5 6411.9 -69.6 708.3 -33744.6 754.9 0.0 5.3 307.2 2924.3 547.4 1.1 0.3 253.1 -9312.9 1691.4 9848.5 -1756.3 14.5 -148851.2 -45.5 0.1 6458.2 -1334.8 0.0 1363.0 -65.6 -49.0 -295.3 0.0
-48.9 20.1 1043.6 142.4 -42125.5 27113.9 4823.5 0.2 18788.6 31140.7 296.3 311.8 -9117.7 12274.7 464.3 21846.4 281.3 -2.3 17.1 54390.7 13184.0 138.9 413.0 17020.4 -2953.8 5205.4 -6.7 1385.4 82517.9 428466.7 7.5 4.7 -5204.8 0.6 -5755.3 -434.7 -4199.5 9682.3 -21893.2 35161.9 -185.3 4640.5 -233326.9 3183.9 0.0 18.6 2945.1 19336.8 10265.6 284.3 0.9 -430.0 -31818.9 8456.2 -4852.0 -12007.5 91.9 -758300.2 2045.2 0.3 24628.0 -90159.7 -1.4 7187.1 -677.8 -490.7 -2587.5 0.0
Appendix Vc - p.3
Appendix VI. Classification of countries into thirteen world regions Central Africa BURUNDI CAMEROON CENT.AF.REP COMOROS CONGO CONGO, D.R. EQ.GUINEA GABON KENYA RWANDA SAO TOME PRN SEYCHELLES TANZANIA, U.R UGANDA Central America ANGUILLA ANTIGUA BARB ARUBA BAHAMAS BARBADOS BELIZE BR.VIRGIN.IS CAYMAN ISLDS COSTA RICA CUBA DOMINICA DOMINICAN RP EL SALVADOR GRENADA GUADELOUPE GUATEMALA HAITI HONDURAS JAMAICA MARTINIQUE MEXICO MONTSERRAT NETH.ANTILES NICARAGUA PANAMA S.VINCENT-GR ST.KITTS NEV ST.LUCIA TRINIDAD TBG TURKS CA.ISL US.MSC.PAC
Central and South Asia AFGHANISTAN BERMUDA BHUTAN CHINA HONG KONG INDIA JAPAN KOREA D P RP KOREA REP. MACAU MALDIVES MONGOLIA NEPAL PAKISTAN SRI LANKA TAIWAN (POC) Eastern Europe ALBANIA BOSNIA HERZG BULGARIA CROATIA CYPRUS CZECH REP ESTONIA GREECE HUNGARY LATVIA LITHUANIA MACEDONIA, TFYR POLAND ROMANIA SLOVAKIA SLOVENIA YUGOSLAVIA Middle East BAHRAIN IRAN (ISLM.R) IRAQ ISRAEL JORDAN KUWAIT LEBANON OMAN QATAR SAUDI ARABIA SYRIA A. R.
TURKEY UNTD ARAB EM YEMEN North Africa ALGERIA BENIN BURKINA FASO CAP VERDE CHAD COTE DIVOIRE DJIBOUTI EGYPT ERITREA ETHIOPIA GAMBIA GHANA GUINEA GUINEABISSAU LIBERIA LIBYA MALI MAURITANIA MOROCCO NIGER NIGERIA SENEGAL SIERRA LEONE SOMALIA SUDAN TOGO TUNISIA North America CANADA ST.PIERRE & MIQUELON USA,PR,USVI Oceania AUSTRALIA BR.IND.OC.TR COCOS ISLNDS COOK ISLANDS FIJI FR.POLYNESIA KIRIBATI MARSHALL IS. MICRON, F. ST N.CALEDONIA N.MARIANA
NAURU NEW ZEALAND NORFOLK ISLD PALAU PAPUA N.GUIN PITCAIRN SAMOA SOLOMON ISLS TOKELAU TONGA VANUATU WALLIS FUT.I FSU ARMENIA AZERBAIJAN BELARUS GEORGIA KAZAKSTAN KYRGYZSTAN MOLDOVA REP. RUSSIAN FED TAJIKISTAN TURKMENISTAN UKRAINE UZBEKISTAN South Africa ANGOLA MADAGASCAR MALAWI MAURITIUS MOZAMBIQUE REUNION S.AFR.CUS.UN ST.HELENA ZAMBIA ZIMBABWE South America ARGENTINA BOLIVIA BRAZIL CHILE COLOMBIA ECUADOR FALKLAND ISL FR. GUIANA GUYANA PARAGUAY
PERU SURINAME URUGUAY VENEZUELA South east Asia BANGLADESH BRUNEI DAR. CAMBODIA INDONESIA LAO P.DEM.R MALAYSIA MYANMAR PHILIPPINES SINGAPORE THAILAND VIET NAM Western Europe ANDORRA AUSTRIA BELGIUM-LUX DENMARK FAEROE ISLDS FINLAND FRANCE GERMANY GIBRALTAR GREENLAND ICELAND IRELAND ITALY MALTA NETHERLANDS NORWAY PORTUGAL SPAIN SWEDEN SWITZ.LIECHT UNTD KINGDOM
Appendix VII. Gross virtual water trade between and within regions (Gm3) Year 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total
Importer Central Africa Exporter Central Africa 0.4976 Central Africa 0.6567 Central Africa 0.0344 Central Africa 0.2755 Central Africa 0.1884 Central Africa 1.6526 Central America 0.0169 Central America 0.0013 Central America 0.0762 Central America 0.1474 Central America 0.0114 Central America 0.2534 Central & South Asia 1.7603 Central & South Asia 0.8645 Central & South Asia 0.1941 Central & South Asia 0.5200 Central & South Asia 0.1939 Central & South Asia 3.5329 Eastern Europe 0.0004 Eastern Europe 0.0071 Eastern Europe 0.0009 Eastern Europe 0.0007 Eastern Europe 0.0079 Eastern Europe 0.0170 Middle East 0.2902 Middle East 0.0604 Middle East 0.1064 Middle East 0.0377 Middle East 0.2996 Middle East 0.7944 North Africa 0.0108 North Africa 0.0066 North Africa 0.0715 North Africa 0.0323 North Africa 0.0083 North Africa 0.1296 North America 0.5246 North America 0.3987 North America 0.6078 North America 0.7213 North America 0.6205 North America 2.8728 Oceania 0.0004 Oceania 0.1183 Oceania 0.1549 Oceania 0.4262 Oceania 0.1086 Oceania 0.8083 FSU 0.0000 FSU 0.0000 FSU 0.0084 FSU 0.0000 FSU 0.0001 FSU 0.0084 Southern Africa 0.0659 Southern Africa 0.0148 Southern Africa 0.0187 Southern Africa 0.1619 Southern Africa 0.4690 Southern Africa 0.7302 South America 0.3406 South America 0.1454 South America 0.2371 South America 0.4825 South America 0.4284 South America 1.6341 South-east Asia 0.2849 South-east Asia 0.3131 South-east Asia 0.3588 South-east Asia 0.4478 South-east Asia 0.4075 South-east Asia 1.8121 Western Europe 0.1380 Western Europe 0.1505 Western Europe 1.3653 Western Europe 0.1932 Western Europe 0.1574 Western Europe 2.0044
Central America 0.0000 0.0002 0.0002 0.0001 0.0000 0.0005 0.7178 1.1950 1.0331 0.5410 1.1329 4.6198 0.0218 0.0327 0.1746 0.1800 0.2623 0.6714 0.0189 0.0995 0.0030 0.0229 0.0064 0.1507 0.0705 0.0119 0.0161 0.0173 0.0189 0.1346 0.0000 0.1341 0.0021 0.0109 0.0000 0.1471 22.4680 31.4015 28.0958 33.2296 38.0402 153.2352 0.0033 0.0684 0.1207 0.1274 0.0829 0.4026 0.0000 0.0605 0.1986 0.0587 0.0081 0.3259 0.0774 0.4304 0.0987 0.0191 0.0507 0.6763 0.5553 1.8655 1.7136 1.9114 1.1105 7.1563 0.4551 0.5623 0.0492 0.9822 0.0892 2.1381 0.4339 0.3463 0.4891 0.4562 0.5373 2.2629
Central & South Asia 0.0147 0.0101 0.0035 0.0559 0.0218 0.1060 0.9242 7.9984 93.3307 21.5666 0.6962 124.5161 3.4605 61.7172 20.8937 8.4108 5.9164 100.3962 0.0750 0.0634 0.4984 1.4679 0.7169 2.8216 0.1083 2.3403 2.8098 4.5177 1.7832 11.5591 0.8781 0.6628 0.2092 0.1301 0.5750 2.4551 97.3939 86.3532 77.3522 65.2549 68.8541 395.2083 7.3305 26.9375 18.0507 15.8428 15.0996 83.2610 0.1686 0.5679 0.5140 4.2047 2.5405 7.9956 1.1837 1.8448 1.2787 0.6378 0.4311 5.3761 4.6692 16.1354 11.0835 16.3524 14.0544 62.2949 19.1315 135.8150 29.3716 32.0168 10.2948 226.6296 3.1199 1.3676 47.1093 6.6849 1.2506 59.5323
Appendix VII - p.1
Eastern Europe 0.0148 0.0175 0.0218 0.0369 0.0274 0.1185 0.1236 0.2523 0.1892 0.1490 0.0615 0.7756 0.2895 1.2141 0.6079 0.5264 0.4313 3.0692 4.7491 3.6900 3.2317 5.0361 3.6283 20.4032 0.4875 0.3581 0.4086 0.3684 0.4666 2.5394 0.1254 0.2632 0.2079 0.2822 0.2611 1.1398 1.7263 2.8439 1.8298 1.4994 1.6147 9.5140 0.0133 0.0344 0.0074 0.0051 0.0141 0.0743 2.2567 3.7433 3.1474 2.8446 1.0728 13.0635 0.0846 0.1097 0.1043 0.0777 0.1200 0.4963 1.0516 1.6227 2.2029 1.5771 1.3799 7.8342 0.4550 0.3038 0.8805 0.4792 0.4391 2.5578 2.6850 5.2138 4.5064 3.3835 3.1859 18.9746
Middle East
North Africa
North America
0.0008 0.0000 0.0315 0.0248 0.0122 0.0694 0.0234 0.0938 0.2159 0.0729 0.0242 0.4304 4.6034 7.1493 3.5783 5.6039 0.7064 21.6413 1.9467 2.4611 1.2022 2.0765 2.6796 10.3661 7.2631 1.0893 5.9675 3.0537 1.2827 25.6536 1.6840 0.3597 0.3088 1.0650 0.3208 3.7382 12.1025 13.4897 15.8272 9.8012 12.5528 63.7734 0.5766 1.6820 1.7365 3.0403 2.4344 9.4698 3.6448 6.4979 4.8750 8.8628 5.3805 29.2610 0.0013 0.0181 0.0237 0.2207 0.1049 0.3687 2.5608 2.0701 6.2214 5.9081 3.5032 20.2636 5.0358 4.7795 4.4413 5.8334 5.6713 25.7613 3.0802 4.4753 3.4981 3.1953 5.9554 20.2044
0.0051 0.0155 0.0051 0.0156 0.0099 0.0512 0.3731 0.1906 0.4837 0.0967 0.3849 1.5290 2.2978 2.3960 2.8211 4.3142 1.9312 13.7603 2.5848 1.5212 0.9695 1.3279 1.1580 7.5614 3.9026 0.5779 2.5509 2.6701 1.5322 13.2090 0.3373 0.7116 0.5386 0.8993 0.2485 2.7353 25.7962 25.4160 24.3203 26.5783 26.4031 128.5138 0.0882 1.7303 4.3002 1.9581 1.2312 9.3081 0.6938 0.5752 0.7675 0.6726 0.3649 3.0740 0.0635 0.0506 0.1691 0.0474 0.0844 0.4150 1.4886 3.0895 6.3842 5.2614 2.4084 18.6321 2.4177 4.8298 7.0455 7.5120 9.7584 31.5634 6.0055 2.9264 4.8419 5.6990 5.9736 25.4465
0.0039 0.0045 0.0112 0.0050 0.0266 0.0512 5.8659 7.7870 13.0115 7.3844 6.3168 40.3656 0.4308 0.9847 1.0028 0.4401 0.4600 3.3184 0.0692 0.0804 0.1540 0.1353 0.1162 0.5551 0.4917 0.5697 0.4971 0.4200 0.3671 2.3456 0.0037 0.1016 0.0035 0.1869 3.8797 4.1754 15.6483 14.5063 19.1281 15.9503 17.5477 82.7806 0.1710 0.4404 0.4029 0.5164 1.1563 2.6870 0.0026 0.4862 0.1581 0.2491 0.0684 0.9644 0.1302 0.5077 0.4175 0.3441 0.3402 1.7397 2.0551 2.6493 3.4523 2.5408 2.6677 13.3652 2.1945 2.5216 2.8520 2.7838 2.6162 12.9680 0.4943 0.4402 1.0670 1.7203 1.3596 5.0814
Appendix VII. Gross virtual water trade between and within regions (Gm3) Year 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total 1995 1996 1997 1998 1999 Total
Importer Exporter Central Africa Central Africa Central Africa Central Africa Central Africa Central Africa Central America Central America Central America Central America Central America Central America Central & South Asia Central & South Asia Central & South Asia Central & South Asia Central & South Asia Central & South Asia Eastern Europe Eastern Europe Eastern Europe Eastern Europe Eastern Europe Eastern Europe Middle East Middle East Middle East Middle East Middle East Middle East North Africa North Africa North Africa North Africa North Africa North Africa North America North America North America North America North America North America Oceania Oceania Oceania Oceania Oceania Oceania FSU FSU FSU FSU FSU FSU Southern Africa Southern Africa Southern Africa Southern Africa Southern Africa Southern Africa South America South America South America South America South America South America South-east Asia South-east Asia South-east Asia South-east Asia South-east Asia South-east Asia Western Europe Western Europe Western Europe Western Europe Western Europe Western Europe
Oceania
FSU
0.0016 0.0032 0.0037 0.0039 0.0028 0.0152 0.0021 0.0012 0.0016 0.0012 0.0008 0.0068 0.0828 0.0968 0.0857 0.0671 0.0705 0.4030 0.0128 0.0243 0.0550 0.0384 0.0830 0.2134 0.1463 0.1621 0.1582 0.1627 0.1916 0.8209 0.0001 0.0000 0.0003 0.0000 0.0000 0.0005 1.1661 0.6804 0.9599 0.5791 0.6364 4.0219 0.5475 0.6456 0.4756 0.3933 0.7380 2.7964 0.0000 0.0000 0.0128 0.0000 0.0000 0.0128 0.0273 0.0152 0.0182 0.0157 0.0213 0.0977 0.0711 0.0738 0.0618 0.0662 0.0681 0.3409 0.3702 0.4566 0.6372 0.5804 0.5823 2.6266 0.1166 0.0082 0.0113 0.0099 0.0064 0.1523
0.0000 0.0000 0.0004 0.0030 0.0095 0.0128 0.0705 0.7957 0.6464 1.4570 1.3183 4.2878 0.6171 2.7256 2.4983 2.7169 1.3252 9.8831 1.2859 1.0543 0.7011 0.7832 1.4087 5.2331 0.0583 0.2322 0.2314 0.3683 0.3229 1.2131 0.0045 0.0852 0.0362 0.0845 0.0078 0.2182 1.1577 1.7920 0.9510 0.5480 5.2041 9.6527 0.0002 0.0233 0.0126 0.0182 0.0025 0.0568 0.5451 9.7397 11.8430 10.6950 15.8625 48.6822 0.0000 0.0297 0.0575 0.0426 0.1274 0.2573 0.2946 0.4403 1.0428 1.2015 1.8700 4.8491 0.1799 0.5666 0.6638 4.0351 0.5305 5.9759 0.5322 0.6934 0.7744 0.4420 1.4464 3.8883
Southern Africa 0.2974 0.2296 0.0689 0.0110 0.0372 0.6440 0.1234 0.0135 0.0038 0.0252 0.0000 0.1660 2.0879 1.7244 1.9615 2.8054 0.8581 9.4374 0.0097 0.0436 0.0047 0.0334 0.0270 0.1184 0.0132 0.0039 0.0028 0.0053 0.0039 0.0291 0.2438 0.0988 0.0079 0.0111 0.0715 0.4330 2.9580 2.2324 1.4799 1.7857 1.3884 9.8444 0.0897 1.1791 0.4342 0.4143 0.7245 2.8418 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.3526 0.4171 0.6457 0.6061 0.7558 2.7772 1.0340 0.3949 0.3870 0.3896 0.5423 2.7477 3.0271 1.7790 1.8766 2.3113 2.8190 11.8129 0.6521 0.3595 0.3661 0.3563 0.2997 2.0337
South America 0.0000 0.0000 0.0000 0.0006 0.0019 0.0024 0.5349 0.4109 0.4511 0.8466 0.2027 2.4461 0.2170 0.4307 0.0725 0.1390 0.0133 0.8725 0.0045 0.0180 0.0184 0.0310 0.0087 0.0807 0.0841 0.0303 0.1068 0.1177 0.1395 0.4784 0.0007 0.0003 0.0013 2.5338 2.0780 4.6141 14.2710 19.8020 19.1690 18.7479 16.6849 88.6748 0.1887 1.3382 1.4269 0.3051 0.4021 3.6611 0.0000 0.0007 0.0592 0.0000 0.0000 0.0599 0.2259 0.4718 0.5718 0.0209 0.0160 1.3063 21.4816 28.2697 29.2891 33.7365 33.9501 146.7270 0.6281 1.0685 0.6033 0.9429 0.2086 3.4514 0.5863 0.1325 0.2419 0.3617 0.2690 1.5914
Appendix VII - p.2
South-east Asia 0.0135 0.0035 0.0052 0.0203 0.0031 0.0456 0.0227 0.0020 0.0662 0.1215 0.1966 0.4090 16.4929 12.9263 8.6227 22.0534 4.7938 64.8891 0.2588 0.0936 0.0984 0.0356 0.0671 0.5536 1.8071 0.1687 0.0653 0.2319 0.3430 2.7234 0.0003 0.0001 0.0794 0.0752 0.0007 0.1556 15.5146 18.5889 19.2247 16.0199 13.4565 82.8046 5.3400 8.1038 7.5285 7.5973 2.9925 31.5618 0.0000 0.0001 0.1445 0.1935 0.0642 0.4024 0.4280 0.3477 0.1307 0.2332 0.0726 1.2123 3.5136 2.1257 4.5405 3.3530 2.9675 16.5003 15.9496 17.5632 14.3879 26.4621 12.8347 87.1976 0.3013 0.2755 0.4019 0.5186 0.2778 1.7752
Western Europe 0.2956 0.3720 0.4330 0.3726 0.5153 1.9884 3.3923 3.2256 3.0797 2.1573 2.4711 14.3330 2.3568 4.8867 5.0332 3.7352 1.7571 17.7689 8.0978 6.5557 6.6503 6.4511 9.6622 37.4171 3.2920 3.5465 3.5249 3.7930 4.0939 18.3654 4.3878 2.4037 1.7243 3.2199 2.0517 13.7874 40.1633 35.7772 34.6834 31.2913 28.3520 170.2672 0.4606 0.9863 0.9140 1.1343 0.9212 4.4077 2.5000 10.2587 9.3471 8.3268 4.5710 35.0022 1.0714 1.5414 1.4755 1.3904 2.1788 7.6575 31.7385 30.1766 35.6362 42.7230 50.9358 191.2102 1.6990 2.4310 2.3415 2.4427 2.1644 11.0786 45.9353 49.6688 51.1823 52.2922 51.3804 250.4589
Value of Water Research Report Series 1. Exploring methods to assess the value of water: A case study on the Zambezi basin. A.K. Chapagain − February 2000 2. Water value flows: A case study on the Zambezi basin. A.Y. Hoekstra, H.H.G. Savenije and A.K. Chapagain − March 2000 3. The water value-flow concept. I.M. Seyam and A.Y. Hoekstra − December 2000 4. The value of irrigation water in Nyanyadzi smallholder irrigation scheme, Zimbabwe. G.T. Pazvakawambwa and P. van der Zaag – January 2001 5. The economic valuation of water: Principles and methods J.I. Agudelo – August 2001 6. The economic valuation of water for agriculture: A simple method applied to the eight Zambezi basin countries J.I. Agudelo and A.Y. Hoekstra – August 2001 7. The value of freshwater wetlands in the Zambezi basin I.M. Seyam, A.Y. Hoekstra, G.S. Ngabirano and H.H.G. Savenije – August 2001 8. ‘Demand management’ and ‘Water as an economic good’: Paradigms with pitfalls H.H.G. Savenije and P. van der Zaag – October 2001 9. Why water is not an ordinary economic good H.H.G. Savenije – October 2001 10. Calculation methods to assess the value of upstream water flows and storage as a function of downstream benefits I.M. Seyam, A.Y. Hoekstra and H.H.G. Savenije – October 2001 11. Virtual water trade: A quantification of virtual water flows between nations in relation to international crop trade A.Y. Hoekstra and P.Q. Hung – September 2002
Acknowledgement The work underlying this report has been sponsored by the National Institute of Public Health and the Environment (RIVM), Bilthoven, the Netherlands. The research is part of the research programme of Delft Cluster. We would like to thank Ton Bresser (RIVM) and Huub Savenije (IHE) for their valuable inputs.
IHE Delft P.O. Box 3015 2601 DA Delft The Netherlands
Website www.ihe.nl Phone +31 15 2151715
National Institute for Public Health and the Environment
Delft Cluster
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