Name : NADER MOHAMED SHAFIK MANSOUR. Date of birth. : Cairo , January 10th ...... when the level drops (39)Sadek Nahla ( 2002 ). An empirical equation.
AIN SHAMS UNIVERSITY FACULTY OF ENGINEERING IRRIGATION AND HYDRAULICS DEPARTMENT
STUDY OF EVAPORATION LOSSES IN LAKE NASSER BY NADER MOHAMED SHAFIK MANSOUR B.Sc. CIVIL ENGINEER ( 1991 ) AIN SHAMS UNIVERSITY Submitted for partial fulfillment of the requirements for the
DEGREE OF DOCTOR OF PHILOSOPHY IN CIVIL ENGINEERING Supervised by Prof. Dr. Abdelkawi M. Khalifa Professor of Hydraulics Irrigation and Hydraulics Department Faculty of Engineering Ain Shams University, Cairo.
Dr. Sonia Youssef El Serafy Assistant Professor Irrigation and Hydraulics Department Faculty of Engineering Ain Shams University, Cairo.
Dr. Karima Mahmoud Attia Assistant Professor Nile Research Institute National Water Research Center Ministry of Water Resources and Irrigation CAIRO - EGYPT 2004
إِﳕﱠَﺎ
ﻏَﻔُﻮٌر ﺻﺪق ﷲ اﻟﻌﻈﻴﻢ ﺳﻮرة )ﻓﺎﻃﺮ( آﻳﺔ )(28
STATEMENT This dissertation is submitted to Ain Shams University for the degree of Doctor of Philosophy in Civil Engineering.
The work included in this thesis was carried out by the author in the Department of Irrigation & Hydraulic, Ain Shams University, from August 1999, to August, 2004.
No part of this thesis has been submitted for a degree or a qualification at any other University or Institution.
Date
: 22 August 2004
Signature
: ……………………
Name
: NADER MOHAMED SHAFIK MANSOUR
C.V. Name : NADER MOHAMED SHAFIK MANSOUR Date of birth
: Cairo , January 10th, 1969
Present Position
: Assistant Researcher, Nile Research Institute, National Water Research Center.
Education
: From 1975 to 1980 Primary School From 1981 to 1983 Preparatory School From 1984 to 1986 Secondary School From 1987 to 1991Faculty of Engineering Ain Shams University.
Degree Awarded : B.Sc. In Civil Engineering, June 1991, Faculty of Engineering , Ain Shams University. M.Sc. In Civil Engineering, June 1998, Faculty of Engineering , Ain Shams University.
ACKNOWLEDGEMENTS
Firstly, and always , thanks to ALLAH I would like to express my thanks and obligation to whom helped me, that without their help the completion of this work was impossible. I gratefully acknowledge his indebtedness and appreciation to Prof. Dr. Abdel Kawi M. Khalifa, Professor of Irrigation and Hydraulics, Faculty of Engineering, Ain Shams University, Prof. Dr. M. El Niazi Hammad, Professor of Irrigation and Hydraulics, Faculty of Engineering, Ain Shams University, Dr. Sonia Youssef El Serafy, Assistant professor Irrigation and Hydraulics, Faculty of Engineering, Ain Shams University, Dr. Karima Mahmoud Attia, Assistant Professor, Nile Research Institute, National Water Research Center., for their supervision, advice and encouragement through the course of this work. It is a pleasure to express my thanks to my Father for his great support and advice. Also Deep thanks to my Family for their support and patience during the time of this research. For their true and sincere helps, deep thanks are presented to my colleagues and my professors specially Prof. Dr. M. El Motassem, Prof. Dr. Ahmed Fahmy and all my colleges in the Nile Research Institute.
ABSTRACT Title : Study of the evaporation losses in Lake Nasser. By: Nader Mohamed Shafik Mansour 1 Evaporation is defined as the transmission of water from any free liquid water surface to the atmosphere at a temperature below the boiling point of water. It represents one of the main components of water budget. Therefore, knowledge of which is indispensable for the solution of numerous water management problem. Reliable evaporation data are also necessary for planning and development of reservoirs. However, due to the interaction between many factors controlling the amount of water lost by evaporation, no universally recognized method is known for computation. In Egypt, due to limited water budget it is crucial that water must use in the most efficient way. As a result looking for water loss reduction methods comes to the top priority of the country. This research introduces computations of water lost by evaporation from water surface areas. Many alternatives to reduce evaporation are tried and evaluated. The study concluded that lake development by blocking the secondary channels is more efficient than cultivating the lake surface area by rice.
Key words: Reservoir, Lake Nasser, Evaporation, metrological data, evaporation reduction, water budget, reservoir development, losses computation. 1 - Assistant Researcher, Nile Research Institute
iv
TABLE OF CONTENTS CHAPTER I INTRODUCTION 1.1 Objective : 1.2 Available Water Resources in Egypt 1.2.1 Conventional water resource 1.2.2 Non-conventional Water Resources 1.3 Water Demands in Egypt 1.4 The Work Plan and Research Structure CHAPTER II LITRATURE REVIEW 2.1 Definitions : 2.2 Factors Affecting the evaporation phenomena: 2.3 Methods of evaporation estimation 2.3.1 Evaporation Empirical Formulae : 2.3.1.1 The atmometer: 2.3.1.2 Fitzgerald (1876 - 1887) : 2.3.1.3 Russel (1888): 2.3.1.4 Bigelow (1907 - 1910): 2.3.1.5 Meyer, A. F. and Freeman, J. R. (1917): 2.3.1.6 Folse (1929) 2.3.1.7 Carl Rohwer (1931) 2.3.1.8 Glen N. Cox (1938 - 1939) 2.3.1.9 Cummings and Richardson (1944) 2.3.1.10 Penman (1948) 2.3.1.10.1 The Energy Balance Condition: 2.3.1.10.2 The Sink Strength Condition: 2.3.2 Measurement of Evaporation : 2.3.2.1 The Weather Bureau Class A Land Pan: 2.3.2.2 The Sunken Screened Pan 2.3.2.3 Bureau of Plant Industry Pan: 2.3.2.4 The Flouting Pan: 2.3.2.5 The Colorado Sunken Pan: 2.3.2.6 Porous Porcelain Bodies: 2.3.2.7 Wet Paper Surfaces: 2.3.3 Estimation of reservoir evaporation : 2.3.3.1 Water budget determinations of reservoir evaporation :
2.3.3.2 Energy budget determination of reservoir evaporation : 2.3.3.3 Mass Transfer Determination of Reservoir Evaporation : 2.4 . Data Required : CHAPTER III DATA PRESENTATION 3.1 INTRODUCTION 3. 2 DATA COLLECTION 3. 2. 1 METROLOGICAL STATIONS 3. 2. 2 METROLOGICAL PARAMETERS 3. 2. 2. 1 Air Temperature 3.2.2.2 Water vapor pressure : 3.2.2.3 Wind Velocity : 3.2.2.4 Solar Radiation : 3.2.3 Geometric Data : 3.2.4. Remote Sensing : 3. 2. 4. 1 Definition 3. 2. 4. 2 Landsat Satellite Images 3. 2. 4. 3 Landasts 4 and 5 3. 2. 4. 4. Platform 3. 2. 4. 5. Mulispectral Scanner System 3. 2. 4. 6 REMOTE SENSING DATA 3. 2. 5 HYDROLOGICAL DATA 3.3 DATA PROCESSING 3. 3. 1 RECTIFICATION 3. 3. 2 MOSAIC 3. 3. 3 AREA COMPUTATIONS 3. 3. 4 DIGITAL ELEVATION MODEL 3. 3. 5 Field Survey Data : CHAPTER IV COMPUTATION OF EVAPORATION LOSSES 4.1 Introduction 4.1.1 Method ( I ) Evaporation Pan : 4.1.2 Method ( II ) Bulk Aerodynamic : 4.1.3 Method ( III ) Modified Bulk Aerodynamic: 4.1.4 Method ( IV ) Penman Method : 4.2 Data collected to enhance the evaporation estimation :
4.3 Calculating the volume of water lost by evaporation: 4.3.1 First ( The yearly average of the evaporation rate) : 4.3.2 Second ( The monthly average of the evaporation rate ) : 4.3.3 Third ( The monthly average of the evaporation rate for each station ) : CHAPTER V EVAPORATION REDUCTION 5.1 Introduction : 5.2 Deferent methods to decrease the evaporation losses from lake Nasser : 5.2.1 Decreasing the evaporation losses by changing the upstream levels of the HAD : 5.2.2.1 The advantages of changing the water level upstream HAD: 5.2.2.2 The disadvantages of changing the upstream HAD water level: 5.2.1.3 Conclusion: 5.2.2 Decreasing the evaporation losses by cultivating special crops on lake nasser surface: 5.2.2.1Environmental Requirements for Rice Cultivation 5.2.2.2 The suitable type of soil for rice: 5.2.2.3 The Proposed Cultivation Plan: 5.2.2.4 Conclusion: 5.2.3 Decreasing the evaporation losses by closure of secondary channels (khores): 5.2.3.1 Khore ( Klabsha ) : 5.2.3.2 Khore ( Allaqi ) : 5.2.3.3 Khore ( Sara ) : 5.2.3.4 Conclusion : CHAPTER VI SUMMARY CONCLUSIONS AND RECOMMENDATIONS 6.1 Summary : 6.2 Conclusions and recommendations: 6.3 Recommendations for the future studies: CHAPTER VII REFERENCES
LIST OF FIGURES
CHAPTER II Figure ( 2 – 1 ) : Porous Cup Atmometer of the Livingstone Type….20 CHAPTER III Figure ( 3 – 1 ) Figure ( 3 – 2 ) Figure ( 3 – 3 ) Figure ( 3 – 4 ) Figure ( 3 – 5 )
: Distribution of metrological station along EGYPT...40 : Location of Metrological Stations on Lake Nasser...41 : Satellite platform of landsats 4 and 5………………53 : Components of the platform of Landsats 4 and 5….54 : Daytime portion of orbits for landsats 1,2 and 3 for a single day……………………………………..55 Figure ( 3 – 6 a ) : Theme No. (44), Orbit No. (74) at 31 October 1987…………………………………56 Figure ( 3 – 6 b ) : Theme No. (44), Orbit No. (75) at 17 November 1987………………………………57 Figure ( 3 – 6 c ) : Theme No. (45), Orbit No. (75) at 17 November 1987………………………………57 Figure ( 3 – 7 a ) : Theme No. (44), Orbit No.(174) at 16 November 1998………………………………58 Figure ( 3 – 7 b ) : Theme No. (44), Orbit No.(175) at 23 November 1998………………………………59 Figure ( 3 – 7 c ) : Theme No. (45), Orbit No.(175) at 23 November 1998………………………………59 Figure ( 3 – 8 ) : The Name and Location of the surveyed cross sections………………………………………70 Figure ( 3 – 9 a ) : The identified object on the satellite image………..73 Figure ( 3 – 9 b ) : The same identified object on the paper map……...73 Figure ( 3 – 10a ): One theme of satellite image before rectification….74 Figure ( 3 – 10b ): The same theme of satellite image after rectification…………………………………...74 Figure ( 3 – 11 ) : The MOSAIC of the three themes of year ( 1987 )..75 Figure ( 3 – 12 ) : The MOSAIC of the three themes of year ( 1998 )..76 Figure ( 3 – 13 ) : The surface area of lake Nasser at water level ( 158.40m ) is ( 2972 Km2)………………………..79 Figure ( 3 – 14 ) : The surface area of lake Nasser at water level ( 181.22m ) is ( 6044 Km2 )………………….........80 Figure ( 3 – 15 ) : The 24 paper maps connecting together…………...83
Figure ( 3 – 16 ) : Contour levels ( 160m ) and ( 180m ) extracted from paper maps…………………………………...84 Figure ( 3 – 17 ) : The surface area of lake Nasser calculated from different griding methods………………………….86 Figure ( 3 – 18 ) : Comparison between the cross sections made from contour maps created by different griding methods and the field survey data for the same section………………………………………….......87 Figure ( 3 – 19 ) : The relation between the surface area of Lake Nasser and the water levels upstream HAD....88 Figure ( 3 – 20 ) : The comparison between the results of surface area equations………………………………….…..90 CHAPTER IV Figure ( 4 – 1 ) : The calculated evaporation according to different methods at Abo simble station………..…92 Figure ( 4 – 2 ) : The calculated evaporation at Abo simble station using the different methods ………...........100 Figure ( 4 – 3 ) : The calculated evaporation according to the different methods at Aswan station ………....100 Figure ( 4 – 4 ) : The division of the lake into four parts according to the location of each station…….…..114 Figure ( 4 – 5 ) : Part ( I ) of lake Nasser served by Aswan Station…………………………………...116 Figure ( 4 – 6 ) : The surface area of Part I of Lake Nasser for different water levels………………………...117 Figure ( 4 – 7 ) : Part ( II ) of lake Nasser serving Allaqi Station...118 Figure ( 4 – 8 ) : The surface area of Part II of Lake Nasser for different water levels………………………...119 Figure ( 4 – 9 ) : Part ( III ) of lake Nasser serving Wadi El Arab Station…………………………....120 Figure ( 4 – 10 ) : The surface area of Part III of Lake Nasser for different water levels………………………...121 Figure ( 4 – 11 ) : Part ( IV ) of lake Nasser serving Abo Simble Station……………………………...122 Figure ( 4 – 12 ) : The surface area of Part IV of Lake Nasser for different water levels…………………….…..123 Figure ( 4 – 13 ) : Comparison between the three methods of calculating evaporation losses for different years...128
CHAPTER V Figure ( 5 – 1 ) : Incoming annual water budget……………………132 Figure ( 5 – 2 ) : The current situation of water level management...135 Figure ( 5 – 3 ) : The suggestion of lowering the water level upstream HAD……………………………….........136 Figure ( 5 – 4 ) : Some of the khores in lake Nasser………………..146 Figure ( 5 – 5 ) : Diagram showing the method of partially filling the khores by terraces construction…….….147 Figure ( 5 – 6 ) : Satellite image for (Kalabsha khore) at November ( 1987 ) at water level ( 158.4m )…......149 Figure ( 5 – 7 ) : Satellite image for (Kalabsha khore) at November ( 1998 ) at water level ( 181.2m )…......150 Figure ( 5 – 8 ) : (Kalabsha khore) on the topographic maps with scale 1 : 50000………………………………….…151 Figure ( 5 – 9 ) : The developed contour map for khore ( Klabsha ) between levels 170 and 180m with interval 2.5m...152 Figure ( 5 – 10 ) : Surface area of khore (Klabsha) for different levels………………………………….…153 Figure ( 5 – 11 ) : Satellite image for (Allaqi khore) at November (1987) at water level of(158.4m)……...154 Figure ( 5 – 12 ) : Satellite image for (Allaqi khore) at November (1998) at water level of (181.2m)…….155 Figure ( 5 – 13 ) : (Allaqi khore) on the topographic map of scale 1 : 50000…………………………………....156 Figure ( 5 – 14 ) : The developed contour map for khore ( Allaqi ) between water levels 170 and 180m with an interval 2.5 m……………………………….….157 Figure ( 5 – 15 ) : Surface area of khore (Allaqi) at different water levels…………………………………….….158 Figure ( 5 – 16 ) : Satellite image for (Sara khore) at November (1987) at water level of (158.4m)……..159 Figure ( 5 – 17 ) : Satellite image for (Sara khore) at November (1998) at water level of (181.2m)……..160 Figure ( 5 – 18 ) : (Allaqi khore) on the topographic map of scale 1 : 50000………………………………….…161 Figure ( 5 – 19 ) : The contour map for khore ( Sara ) between levels 170 and 180m with contour interval of 2.5 m…………………………….…….162 Figure ( 5 – 20 ) : Surface area of khore (Sara) for different water levels……………………………………….163
LIST OF TABLES CHAPTER I Table ( 1 – 1 ) : Water demands in Egypt for years 1997 and 2025…….9 CHAPTER III Table ( 3 – 1 ) : Location and Operational Situation of the Metrological Stations on Lake Nasser………………..42 Table ( 3 – 2 ) : Table (3-2): Metrological Data for Aswan Station…...47 Table ( 3 – 3 ) : Ratio of actual to possible hours of sunshine (cloudiness ratio) At Aswan…………………….........48 Table ( 3 – 4 ) : Platforms and orbits of first and second generations of Landsat……………………………………............51 Table ( 3 – 5 ) : Characteristics of Landsat imaging system………….55 Table ( 3 – 6 ) : Daily water levels U.S. HAD and Monthly Average for year ( 1987 )……………………………61 Table ( 3 – 7 ) : Daily water levels U.S. HAD and Monthly Average for year ( 1995 )……………………………63 Table ( 3 – 8 ) : Daily water levels U.S. HAD and Monthly Average for year ( 2000 )……………………………65 Table ( 3 – 9 ) : Definition of Main Locations Surveyed during the Present Monitoring Program…………………………69 Table ( 3 – 10 ): The surface area of Lake Nasser Calculated from different griding methods for different water levels…………………………………………...86 Table ( 3 – 11 ): The results of the two equations of calculating the surface area of Lake Nasser from Remote Sensing Equation and Abu El-Ata equation…………………..89 CHAPTER IV Table ( 4 – 1 ) : The calculated evaporation rate ( mm/day ) for Aswan and Abo Simble stations using the four Methods………………………………………............99 Table ( 4 – 2 ) : Average monthly evaporation rate calculated from the floating station at Abo Simble(mm/day )…103 Table ( 4 – 3 ) : Average monthly evaporation rate calculated from the floating station at North Allaqi Khore ( mm/day )…104 Table ( 4 – 4 ) : Average monthly evaporation rate calculated from the ( Old ) floating station at Aswan ( mm/day )………..105
Table ( 4 – 5 ) : Average monthly evaporation rate calculated from the ( New ) floating station at Aswan ( mm/day )…………………………………..106 Table ( 4 – 6 ) : Average monthly evaporation rate calculated from The floating station at Wadi El Arab ( mm/day )…...106 Table ( 4 – 7 ) : The average monthly evaporation rate for each station ( mm / day )…………………………………108 Table ( 4 – 8 ) : Modified average monthly evaporation rate for each station ( mm / day )……………………………….....108 Table ( 4 – 9 ): Calculation of the yearly average of the evaporation rate ( mm / day )………………………..110 Table ( 4 – 10 ): The average monthly evaporation rate (mm / day)….112 Table ( 4 – 11 ): Surface are of part ( I ) of lake Nasser for each water level…………………………………………...116 Table ( 4 – 12 ): Surface are of part ( II ) of lake Nasser for each water level…………………………………………...118 Table ( 4 – 13 ): Surface are of part ( III ) of lake Nasser for each water level…………………………………………...120 Table ( 4 – 14 ): Surface are of part ( IV ) of lake Nasser for each water level…………………………………………...121 Table ( 4 – 15 ): Comparison between the three methods of calculating the evaporation losses…………………...128 CHAPTER V Table ( 5 – 1 ) : The average air temperatures recorded at the 5 metrological stations…………………………....….141 Table ( 5 – 2 ) : The water demand for rice and evaporation at Aswan……………………………………………..145 Table ( 5 – 3 ) : The water demand for rice and evaporation at Abo Simble…………………………………………..145 Table ( 5 – 4 ) : The surface area of khore ( Klabsha ) at different water levels calculated from the generated contours……………………………………………….152 Table ( 5 – 5 ) : Volume of water saved by partial closure of khore(Klabsha)……………………………………….153 Table ( 5 – 6 ) : The surface area of khore ( Allaqi ) at different water levels calculated from the generated contour….157 Table ( 5 – 7 ) : Volume of water saved by partial closure of khore (Allaqi)………………………………………...158
Table ( 5 – 8 ) : The surface area of khore ( Sara ) at different water levels calculated from the generated contour……….162 Table ( 5 – 9 ) : Volume of water saved by partial closure of khore (Sara)………………………………………...163
Chapter ( I ) INTRODUCTION In this chapter, the objectives of this study are revealed. The available water resources are cited. The water demand in Egypt is also discussed. Finally the work plan and research structure are given.
1.1. Study Objectives
Water is a crucial element for human beings and natural system. Rapid population growth, urbanization, deforestation, and industrialization have increased the demand and competition for water even under reasonable flood conditions. Egypt is one of the countries facing great challenges due to its limited water resources represented mainly by its fixed share of the Nile water and its aridity as a general characteristic. The limited water supply and the increased future demand necessitate the importance of better use of water resources, which might be obtained through reduction of water system losses.
This research is considered a base contribution to bridge the gab between limited water resources and the increasing demands. Thus main objectives of this research, are to compute the evaporation losses precisely and to introduce some alternatives to decrease the evaporation losses from Lake Nasser.
1
In this research, remote sensing technique is applied in computing the water surface area of Lake Nasser related to different flood issues. The computed areas are compared to the result of other researches. A relationship is developed to relate the upstream water level at Aswan High Dam and the lake area. Field data representing the hydrological and metrological conditions in the lake are used in different ways to compute the amount of water lost by evaporation.
1.2. Available Water Resources in Egypt
1.2.1. Conventional Water Resource
Water resources in Egypt are limited to the following resources of Nile River, rainfall and flash floods, groundwater in the deserts and Sinai and possible desalination of sea water.
Each resource has its limitation on use, whether these limitations are related to quantity, quality, space, time, or economic values.
Nile River Water: Egypt's main and almost exclusive resource of fresh water is the Nile River. The Nile River inside Egypt is completely controlled by the dams at Aswan in addition to a series of seven barrages between Aswan and the Mediterranean Sea. Egypt relies on the available water storage of Lake Nasser to sustain its annual share of water that is fixed at 55.5 billion m3 annually by an agreement with Sudan since 1959. The agreement 2
allocated 18.5 billion m3 to Sudan annually assuming 10 billion m3 as evaporation losses from Lake Nasser each year based on an average annual inflow of 84 billion m3/year. This average was estimated as the annual average river inflow during the period 1900 till 1959.
Rainfall and Flash Floods: Rainfall on the Mediterranean coastal strip decreases eastward from 200 mm/year at Alexandria to 75 mm/year at Port Said. It also declines inland to about 25 mm/year near Cairo. Rainfall occurs only in the winter season in the form of scattered showers. Therefore, it can not be considered a dependable source of water.
Flash floods due to short-period heavy storms are considered a source of environmental damage especially in the Red Sea area and southern Sinai. Many studies have been made to determine possible measures to avoid hazards caused by flash floods. This water could be directly used to meet part of the water requirements or it could be used to recharge the shallow groundwater aquifers. It is estimated that about 1 billion m3 of water on average can be utilized annually by harvesting flash floods.
Groundwater: Groundwater is found in the western desert in the Nubian sandstone aquifer that extends below the vast area of the New Valley governorate and the region east of Owaynat. It has 3
been estimated that about 200,000 billion m3 of fresh water are stored in this aquifer. However, groundwater exists at great depths and the aquifer is generally non-renewable. Therefore, the utilization of such water depends on pumping costs and its depletion rate versus the potential economic return on the long run.
Groundwater in Sinai is mainly encountered in three different water-bearing formations; the shallow aquifers in northern Sinai, the valley aquifers; and the deep aquifers. The shallow aquifers in the northern part of Sinai are composed of sand dunes that hold the seasonal rainfall, which helps to fix these dunes. The aquifers in the coastal area are subject to salt-water intrusion. The total dissolved solids in this water range from 2,000 to 9,000 ppm which can be treated to reach a suitable salinity level for use to irrigate certain crops.
The total groundwater abstraction in the western desert in 1995/96 was estimated to be about 0.48 billion m3 while it is only 0.09 billion m3/year in Sinai.
Desalination of Sea Water: Desalination of seawater in Egypt has been given low priority as a source of water. That is because the cost of treating seawater is high compared with other sources, even the unconventional sources such as drainage reuse. The average cost of desalination of one cubic meter of seawater 4
ranges between 3 to 7 L.E (Egyptian pound). In spite of this, sometimes it is feasible to use this method to provide domestic water especially in remote areas where the cost of constructing pipelines to transfer Nile water is relatively high.
Nevertheless, brackish groundwater, having a salinity of about 10,000 ppm, can be desalinated at a reasonable cost providing a possible potential for desalinated water in agriculture.
The amount of desalinated water in Egypt now is in the order of 0.03 billion m3/year.
1.2.2. Non-Conventional Water Resources
Other sources of water, that can be used to meet part of the water requirements, exist. These sources are called non-conventional sources, which include the renewable groundwater aquifer in the Nile basin and Delta, the reuse of agricultural drainage water and the reuse of treated sewage water.
These recycled water sources cannot be considered independent resources and cannot be added to Egypt's fresh water resources. These sources need to be managed with care and their environmental impacts should be evaluated to avoid any deterioration in either water or soil quality.
5
The renewable Groundwater Aquifer in the Nile Valley and Delta: The total available storage of the Nile aquifer was estimated at about 500 billion m3 but the maximum renewable amount (the aquifer safe yield) was estimated to be only 7.5 billion m3. The existing rate of groundwater abstraction in the Valley and Delta regions is about 4.5 billion m3/year, which is still below the potential safe yield of the aquifer.
Reuse of Agricultural Drainage: The amount of water that returns to drains from irrigated lands is relatively high (about 25 to 30%). This drainage flow comes from three sources; tail end and seepage losses from canals; surface runoff from irrigated fields; and deep percolation from irrigated fields (partially required for leaching salt). None of these sources is independent of the Nile River. The first two sources of drainage water are considered to be fresh water with relatively good quality.
The agricultural drainage of the southern part of Egypt returns directly to the Nile Rive where it is mixed automatically with Nile fresh water which can be used for different purposes at the downstream. The total amount of such direct reuse is estimated to be about 4.07 billion m3/year in 1995/96. In addition, it is estimated that 0.65 billion m3/year of drainage water is pumped to El-Ibrahimia and Bahr Youssef canals for further reuse. Another 0.235 billion m3/year of drainage water is reused in Fayoum while about 0.65 billion m3/year of Fayoum is drained to 6
Lake Qarun. Moreover, drainage pumping stations lift about 0.60 billion m3/year of Giza drainage from drains to the Rossetta Branch just downstream of the delta barrages for further downstream reuse.
Drainage water in the delta region is then emptied to the sea and the northern lakes via drainage pump stations. The amount of drainage water pumped to the sea was estimated to be 12.41 billion m3 in 1995/96. This amount decreased and will continue to decrease in the future according to the development of the reuse of agricultural drainage water.
Reuse of Treated Waste Water: One way of augmenting the irrigation water resources is to reuse treated domestic wastewater for irrigation with or without blending with fresh water. The increasing demands for domestic water due to population growth, improvement in living standards and the growing use of water in the industrial sector due to the future expansion of industry will increase the total amount of wastewater available for reuse.
Wastewater treatment could become an important source of water and should be considered in any new water resource development policy. However, proper attention must be paid to the associated issues with such reuse. The major issues include public health and environmental hazards as well as technical, institutional, sociocultural and sustainability aspects. 7
1.3. Water Demands in Egypt
Demands for water can be categorized in four main classes:
Crop Consumptive Use: The average annual consumptive use for 1995/96 was estimated to be 40.82 billion m3. In that year, about 7.8x106 feddans were irrigated with an average water consumptive use per feddan of about 5100 m3/year. This amount represents only the crop evapotranspiration and does not include conveyance losses in the irrigation network or seepage and deep percolation loses at the farm level.
Municipal Water Requirements: The total municipal water use was estimated to be 4.54 billion m3 in 1995/96. A portion of that water is actually consumed and the rest returns to the system, either through the sewage collection system or by seepage to the groundwater. There are regions like Alexandria, the Suez Canal, and desert areas where the discharge cannot be recovered.
Industrial
Water
Requirements:
The
estimated
water
requirement for the industrial sector during the year of 1995/96 was in the order of 7.5 billion m3/year. A small portion of the diverted water for industrial requirement is consumed through evaporation during industrial processes while most of the water returns to the system. 8
Navigational Requirements: The river Nile main stream and part of the irrigation network are used for navigation. Water demand specifically for navigation occurs only during the winter closure period (about 3 weeks in January and February), when the discharges, to meet agriculture demands, are too low to provide the minimum draft required by ships.
Table 1.1 shows the water requirements by year 2025, as compared by the actual requirements in year 1997. * Winter closure and evaporation from irrigation network
Table (1 – 1): Water demands in Egypt for years 1997 and 2025 Usage Sector
Year 1997
Year 2025
( milliard m3 )
( milliard m3 )
Irrigation
48.0
64.0
Domestic use
4.5
7.30
Industry
7.5
9.50
Others *
3.0
2.20
Total requirements
63.0
83.0
Available
65.0
65.0
Difference
+ 2.0
- 18.0
In summary the aforementioned water resources balance indicates that the actual resources currently available for use are 55.5 billion m3/year, whereas water demands for all the sectors are in the order of 63 billion 9
m3/year. Recycling and better management nearly overcomes some gap between water needs and demands. Currently groundwater abstraction is about 4.8 billion m3/year. An amount of 4.3 billion m3/year of drainage water is now re-used. Another 0.4 billion m3/year of treated wastewater is re-used for irrigation at present however, small deficit is still found between demand and supply. That means that in the future, the water demands will exceed the water resources, this highlights the significance of looking for new sources of fresh water. Better use of water resources represents high priority, which might be obtained through reduction of water system losses.
1.4. The Work Plan and Research Structure
In order to achieve the study objectives, several sets of data and techniques are utilized. Satellite images for Lake Nasser, collected by the LANDSAT 5, were used. The images represented high and low floods issues. Remote Sensing techniques are promoted to analyze the satellite images. Many sets of old and recent field data, related to hydrological and metrological information, are obtained and utilized.
The research structure is restricted to seven chapters summarized as follows:
Chapter (I) introduces problem definition, study objectives, scope of work and the study structure. The Literature Review is given in chapter
10
(II). It summarized the previous studies related to the study subject and the used techniques.
Chapter (III), represents the collected metrological and hydrological data as well as the image data. This chapter focuses on the used techniques and programs. The work procedure is discussed and presented. The evaporation losses computation is given in chapter (IV). It illustrates the methodology and the calculation of the precise amount of water lost by evaporation from the Lake since the construction of the dam. Developed relation is shown and compared to literature. In chapter (V), alternatives to reduce evaporation losses are proposed, discussed and evaluated. Chapter (VI) gives the reached conclusion and recommendation for future work. Finally, references are given.
11
Chapter ( II )
LITERATURE REVIEW In this chapter, some terms are defined. The factors affecting evaporation are cited. Also, the methods of measuring or estimating it are given. Finally, the required data for the estimation of evaporation are listed.
2.1. Definitions :
Evaporation is defined as the transmission of water from any free liquid water surface to the atmosphere at a temperature below the boiling point of water
2.2. Factors Affecting the Evaporation Phenomena:
(51) Varshney R.S. ( 1977 ) The main factors causing evaporation are temperature (particularly of the water body), the humidity of the surrounding atmosphere, wind, insolation and atmospheric pressure.
(A)
In studies utilizing available metrological data, air temperature is used to determine losses by evaporation instead of water temperature. In some investigations,
the
observed
water
body
temperature in summer were found to be higher 13
than air temperature, and also the difference may become greater as the size of water body increases. Air is cooled by the loss of heat through radiation at night, and is heated during the day by absorbed radiant energy from the sun, and from the earth itself.
(B)
The amount of heat, received at a given point on the earth varies with the latitude of the place, the season of the year, the moisture in the air, the dust in the atmosphere, and the cloudness.
(C)
Except, where there are great changes in altitude with corresponding differences in barometric pressure the density of the atmosphere has little effect on evaporation, under natural conditions. However, it has been confirmed by observations, however, that evaporation is greater at higher elevations.
(D)
Considering the heat utilized to vaporize water, the difference between the heat received and the heat lost by radiation and conduction to surrounding media, should be the amount of heat required to supply the latent heat of vaporization. This takes into consideration insolation1 and does 14
not consider wind, as such approach do not require that wind effect be included. Insolation is the ultimate source of atmospheric heat. Its effect on evaporation is caused through the rising of the temperature of the water, since radiation from the sun is the primary main source of heat or purposes on the earth. Radient heat received by a water surface, but not reflected, is absorbed directly by the water and operates to raise its temperature without affecting the air temperature.
2.3. Methods of Evaporation Estimation :
Many methods for the estimation of evaporation are available. Among them are:
2.3.1 Evaporation Empirical Formulae
Most of the known evaporation empirical formulae, were based on the Dalton’s law (1802), with modifications for factors affecting evaporation. Dalton discovered that the rate of evaporation from a free water surface, depended upon the difference between the vapor pressure at saturation for the temperature of the water, and the vapor pressure actually existing in the air above the water surface. Starting with this premise, many other investigators have derived formulae to express 15
mathematically the rate of evaporation in terms of the meteorological elements causing or affecting it.
2.3.1.1 The atmometer, devised by Piche, is a glass tube, 29 cm long and 1 cm in diameter, which is sealed at one end. In use, the tube is filled with distilled water, and a disc of white filter paper is clamped across the open end. The instrument is then suspended open and downwards, and as evaporation takes place, the moist paper disc, the consumption of water may be read off from graduated marks on the tube. One of the main disadvantages of the instrument, is its sensitivity to wind speed. This instrument is no longer used, as it gives approximate results.
2.3.1.2 (11)Fitzgerald (1876 - 1887), made a careful and complete series of observations under controlled laboratory conditions and under natural conditions, and proposed the following formula:
E = ( 0.4 + 0.199 w ) * ( e (s).e (d) )
Equ.(2.1)
in which: E
: the evaporation in incnes/24 hours
W
: the wind speed in miles/hour
e(s)
: the vapor pressure of the saturated air in inches of mercury at the temperature of the water surface, and
e(d)
: the mean vapor pressure of air in inches of mercury above the water surface. 16
It is to be noted that altitude effect is not accounted for.
2.3.1.3 (25)Russel (1888), made a study of evaporation measured by Piche evaporimeter at 18 stations of the Weather Bureau, over the United States, and prepared the following formula:
E = ( ( 1.96 e(w) + 43.88 ) * ( e(w).e (d) ) )
Equ.(2.2)
in which: e(w)
: the vapor pressure in inches of mercury for the mean wet bulb temperature
e(d)
: the mean vapor pressure of air in inches of mercury above the water surface, and
B
: the mean barometric reading in inches of mercury at 32°F.
2.3.1.4 (25)Bigelow (1907 - 1910), made an extensive series of experiments for the Weather Bureau. The suggested formula has the form:
E = 0.138 [ e(s) / e(d) ] * [ de/ds ] * [ 1 + 0.07 w ]
Equ.(2.3)
in which the derivative de/ds is the rate of change of the maximum vapor pressure with temperature and the other symbols as designated above.
17
2.3.1.5 (25)Meyer, A. F. and Freeman, J. R. (1917), developed independently the formula:
E = ( 0.5 + 0.05 w ) * [ e(s).e (d) ]
Equ.(2.4)
approaching the problem of evaporation from a considerably different angle, where the indicated symbols w, e(s), and e(d), are the same as defined before.
2.3.1.6 (25)Folse (1929), published earlier the results of detailed investigations made on evaporation and runoff of the Great Lakes (Superior, Michigan, and Hurm). The suggested evaporation formula was:
e * E(1) + e[(W/100).x ] * E(2) ] + l = V
Equ.(2.5)
in which: e
: the mean differences for the lake between (1), the saturation vapor pressure corresponding to the mean air temperature for two days ending at midnight on the day to which the observation pertains, and (2), the mean actual vapor pressure for the 24 hours
E(1)
: the portion of the evaporation which is proportional to the vapor pressure potential,
W
: the average speed in miles per 24 hours of the wind for the 2-days ending at midnight of the day of observation,
x
: the speed of the wind, below which it has an 18
inappreciable effect on the evaporation, E(2)
: the portion of evaporation proportional to the product of the vapor pressure potential and the wind velocity. is the net change in the surface elevation of the lake due to net inflow from the lake above the runoff from the adjacent land, precipitation on the lake and outflow into the next lake below, and evaporation, and
V
: the residual due to discrepancies between the observed "I" and the fall in surface elevation of the lake due to evaporation
From the observed data of the vapor pressure potential, wind, and changes in elevation of the lake surface, the factors "E(1), E(2), and "x", were evaluated as Constants. The final equation form was as:
E(w) = 0.319 e + 1.49 [ e { (w/100).2.6 } ]
Equ.(2.6)
where E(w)
: the total evaporation expressed in hundredths of inches per day, and
W
: the wind speed in miles per day
2.3.1.7 (25)Carl Rohwer (1931), puplished the Fort Collins experiments on evaporation, which included observations under different conditions, principally on the Colorado Sunkon Pan, 19
Weather Bureau Land Pan, Floating Pan of the U. S. Geological Survey, 85 foot tank, and a small reservoir. Out of these experiments, there was developed a formula for evaporation:
E = 0.771(1.465-0.0186 B)*( 0.44 + 0.118 W )*(e(s).e(d)) Equ.(2.7)
in which the nomeclature is the same as shown above.
2.3.1.8 (25)Glen N. Cox (1938 - 1939), published the following evaporation formula:
E =[e(a).e(d)+0.0016 T.D]/[0.564+0.051T.D+( W/300 )]
Equ.(2.8)
in which: E
: the evaporation in inches per day,
e(a)
: the saturated vapor pressure at air temperature,
e(d)
: the actual vapor pressure,
T.D
: the difference between mean air temperature and that of water, and
W
: the wind speed in miles/day
2.3.1.9 (25)Cummings and Richardson (1944), proposed the formula:
E = ( H.S.C ) / 2.54 L ( 1 + R )
20
Equ.(2.9)
in which: H
: the net radiation received in calories per sq. cm.,
S
: the heat stored in a unit column of water in calories,
C
: a correction factor for interchange of heat between the wails and the water,
L
: the latent heat of the water in calories, and
R
: the Bowen’s Ratio, between the heat carried away by convection and the heat carried off by vapor.
2.3.1.10 (33)Penman (1948), presented a theory and a formula for the estimation of evaporation from weather data, which allows to compute the evaporation from a free water surface using readily available standard meteorological data only. The following meteorological elements are required: a
: the mean air temperature " t(c) "
b
: the mean atmospheric humidity " h " ,expressed as fraction "h"= e/e.a "
c
: the mean wind speed "U(2) in m/sea, measured at (or reduced to) a height of 2 ms. above the ground, and
d
: the relative duration of bright sunshine expressed as the ratio " n/D ", where " n " is the actual number of hours of sunshine per day, and "D" is the maximum possible number of hours of sunshine per day.
The extreme values of " n/D " are: * " n/D " = 0 , when cloudy sky, and 21
* " n/D " = 1 , when cloudless sky or clear weather.
The theory is based on the two essential conditions that must be satisfied before evaporation can takes place. These conditions are:
The Energy Balance Condition: There must be a supply of energy, as evaporation requires latent heat of vaporization. For water the latent heat is about 600 gramme-calories per gramme at ordinary temperature. This means that for the evaporation of 1 mm of water over 1 cm2., an energy of 60 gramme-calories should be supplied.
During daylight hours, sun and sky light provide a certain measurable amount of short wave radient energy, the intensity of which varies with latitude, season, time of day and cloudiness. The amount of energy that would reach the earth at a given place at a given time, if there were clouds and no atmosphere, is given by Angot, and will be indicated as " R(A) ". The amount " R(C) " that penetrate the atmosphere and reaches the ground is much less than "R(A)". It can be estimated by the formula:
R(C) = R(A) * (0.2 + 0.48(n/D) )
Equ.(2.10)
A part of this energy is reflected as short wave radiation. 22
The net amount :
R(I)
= R(C) * ( 1 - r ) =R(A) * ( 1 - r ) * (0.2 + 0.48(n/D) ) Equ.(2.11)
where r is the reflection coefficient or albedo. For open water r = 0.05, and for green vegetation r = 0.25 . A small part, about 0.5 percent of R(C) is used in photo-synthesis, but this can be neglected in the balance. Some of the net incoming short wave radiation ‘R(I), is re-radiated day and night as long wave radiation R(B), and the process is most rapid when skies are cloudless and the air is dry: R(B)="segma"[T(a)4*(0.47-0.077(e)0.5)*(0.20+0.80(n/D)] Equ.(2.12)
in which " segma " is a constant and equals 117.4x109g.cal./cm2 day.
The net amount of energy which finally remains at the surface and which is available for various sinks is called the heat budget ‘H’, and is given by;
H = R(I) - R(B)
i.e.
H = R(C).r * R(C) - R(B) = R(A ) * ( 1 - 0.06) ( 0.20 - 0.48 (n/D)) 23
-117.4(10)^(9) * T(a)4 *(0.47-0.066(e)0.5)*(0.2+0.8(n/D))
Equ.(2.13)
The Sink Strength Condition: There must be a removal of the vapor once it is produced. To provide the potential difference needed to maintain the evaporation current, there must be a difference of vapor pressure between the evaporation surface and the air above it: E(a) = 0.35 (e(a) - e(d) ) * (1 + (u/100) )
Equ.(2.14)
where e(a)
: the saturation vapor pressure of water at the mean air temperature,
e(d)
: the actual vapor pressure at the mean air temperature,
u
: the wind speed in miles/day at a height of two meters above the ground surface.
Combining the two equations for " H " and " E(a) " to give:
E(o)=[("delta"*(H + x)*E(a))/("delta"+x)]
Equ.(2.15)
where "delta"
: the slope of the saturation vapor pressure curve for water at the mean air temperature in mm.Mg/Fo, and
E(o)
: the constant of the wet and dry bulb 24
psychrometer. In the equation for " H ", if " r " is given the value 0.25, "E(o)" will represent potential evaporation from an extended short green crop, whereas, if " r " is given the value 0.05, " E(o) " will represent evaporation from an extended sheet of open water.
To overcome the computational labor, involved in solving the Penman equation, a nomogram has been designee by P. J. Rijkeert of the Royal Meteorological institute, Netherlands, which enables rapid evaluation to be made, and it Is possible to write the penman formula in the following forms
E(o) = E(1) * { t,(n/D) } + E(2) { t, R(A),(n/D) } + E(3) { t,(n/D),h } + E(4) { t, U(2),h }
Equ.(2.16)
where E(1), E(2), E(3) and E(4), can be found directly from the nomogram as functions of t, n/D, R(a), h, and U(2). Summation of E(1) up to and including E(4), gives E(o), which is the evaporation of a free water surface.
2.3.2 Measurement of Evaporation.
(52)R.S.Varshney ( 1977 ) Evaporation has been measured by a diverse assortment of instruments and methods. Some of the smaller instruments that have been used are the Piche 25
evaporimeter, the evaporation scale of H Wild and porous clay bulbs of various designs, called atmometers.
All these
instruments measure evaporation from very small amounts of water, micro-scopic when compared to volumes considered in engineering hydrology.
In the past, main reliance has been placed on pans of various sorts, dimensions and conditions of exposure, to secure information on evaporation for engineering purposes. In a few notable cases, attempts have been made to determine rates of evaporation from natural bodies of water by measuring and estimating closely the inflow and out flow and attributing the difference to losses by subterranean seepage and evaporation. The more commonly used types of evaporation pans, are 1
- the U.S. Weather Bureau class A land Pan
2
- the Sunken Screened Pan
3
- the Bureau of Plant Industry Pan
4
- the Floating Pan
5
- the Colorado Sunken pan Of these, the U S. Weather Bureau pan is increasingly being adopted in India. Piche Evaporimeter is also quite in use in India.
2.3.2.1 The Weather Bureau Class A Land Pan
Most commonly used pan for measuring evaporation from water surfaces is of unpainted galvanized iron and is 1.2 meter in dia. 26
250 mm. deep and is set on a 150 mm high wooden grillage so as to raise the water surface a little more than 300 mm above the ground level. The water is kept about 25 mm below the rim of the pan.
It is thus exposed to air on all sides. Evaporation is
measured by means of a pointer gauge located in a stilling well. The equipments of a station, measuring evaporation include instruments to observe con-commitant meteorological conditions including temperature, precipitation, wind and humidity.
Because of the protection afforded by the rim and the surrounding objects, the water in the Weather Bureau pan is not subject, to the effect of wind to the same extent as the open water in a lake or a reservoir. On the other hand, the amount of water contained in the pan is small so that much more of the sun's energy heats the water surface, causing evaporation and less is stored in the water. There is also substantial heating of the metal in the rim above the water. All these factors tend to give the water in the class A pan a higher temperature during the daylight hours than the water of a nearby lake or reservoir. At night, conditions are reversed and the class A pan will cool to a lower temperature than the adjacent large body of water. The evaporation from these pans however remain higher than from a reservoir under similar climatic conditions and the values of evaporation as measured with a class A pan have to be multiplied by a coefficient for obtaining probable values of evaporation from reservoirs. The value of this coefficient has been found to range from 0.60 in summer to 0.82 in winter, but 27
for calculation of the annual evaporation loss, an average coefficient 0.70 has been accepted and is found to give reasonably accurate figures of evaporation.
2.3.2.2 The Sunken Screened Pan
In the screened evaporation pan, water in the pan is shaded by a 6 mm mesh galvanized wire screen, which intercepts some of the heat energy, thus reducing water loss from the pan to approximately that from a large water area.
Based on
experiments conducted over a period of 10 years. The annual coefficient of the screened pan is found practically to be 1.0, but monthly coefficient is somehow greater than 1.0 in the winter and somehow less than 1.0 in summer.
2.3.2.3 Bureau of Plant Industry Pan
The U.S. Bureau of Plant Industry Pan is 180 cm in diameter 60cm deep and buried in the ground within 10 cm of the top and water is maintained approximately at ground level. Evaporation is measured by means of a pointer gauge in a well outside the pan. This pan normally gives evaporation about 5% greater than reservoir evaporation.
2.3.2.4 The Flouting Pan
28
The floating pan, widely known as the U. S. Geological Survey pan, has been employed by that agency and others for the determination of evaporation from extensive water surfaces with a view to obtain results under conditions identical with large bodies of water. The pan is 91.5 cm square 45 cm deep and is mounted on a raft floating on a relatively large body of water. Baffles are provided within the pan to prevent surging. Evaporation is measured by replacing the water lost by means of a special cup holding a volume equal to that formed by a depth of 0.25 mm over the area of the pan. The wetting of the sides of the pan (because of rocking due to wave action) results in a variable increase in evaporation. The coefficient adopted for obtaining reservoir evaporation is 0.80, while the range of the coefficient is 0.70 to 0.82.
2.3.2.5 The Colorado Sunken Pan
The Colorado Experiment station, Fort Collins, Colorado utilizes a square pan, 92 cm on the side and 46 to 92 cm deep. It is set in the ground so that 5 to 15 cm extend above the surface. The water surface in the pan is maintained at approximately the elevation of the ground surface; a deviation of only 2.5 cm upward or downward is permitted. Evaporation is measured by means of a pointer gauge. The coefficient to be applied for obtaining reservoir evaporation is 0.78 while the range of variation is 0.57 to 0. 86. 29
2.3.2.6 Porous Porcelain Bodies
Porous porcelain spheres, cylinders, or blocks are commonly by plant
physiologists
for
measuring
evaporation
because
evaporation from their surfaces is considered to be quite representative of that from plant. The living stone sphere which is frequently used in botanical investigations is about 5 cm. in diameter and about 2.5 mm. in thickness. It is filled with distilled water and connected to a supply reservoir so that atmospheric pressure on the water surface in the container acts to keep the sphere full. Since the characteristics of the porous material cannot be absolutely controlled, each sphere must be compared with a standard and a correcting coefficient determined. For field use a valve must be provided to prevent intake of rainwater.
30
Figure ( 2 - 1 ) : Porous Cup Atmometer of the Livingstone Type
2.3.2.7 Wet Paper Surfaces
The Piche evaporimeter is probably the best known of the wetpaper type. It consists of a graduated glass tube about 22.5 mm in length and 1 cm. internal diameter with one end closed and with a disk of filter paper held against the open end by a spring and metal disk. The tube is filled with distilled water. After the filter and disk are in place, it is inverted.
31
Measuring the evaporation losses from pan accurately requires attention to the minutest details. Films of dust blown in from nearby streets or fields; the oily secretions of insects alighting on the water in the pans; birds bathing in the pans; partial or irregular shading of pans by nearby fences, trees, buildings; or screens to keep out birds and the unknown increase in surface salinity due to use of hard water, are causes of errors or irregularities in evaporation from pan observations.
The kind of metal used in the construction of the pan, the color and depths of the pan, the rim height, the exposure, the character and moisture content of the soil surrounding burned pans, and the inability to secure accurate records on days of rainfall or high wind are all factors which affect the accuracy and dependability of pan evaporation records.
A black evaporation pan exposed in Tennessee, evaporated about 10% more than a white pan, and 3% more than a galvanized iron pan; a pan 60 cm deep evaporated about l0% more than one 15 cm deep. A 25 mm evaporation pan exposed in California with 240 cm depth of water evaporated about 15% more than one with 15 cm of water, and about 30% more than one with 5 cm of water in it; a copper pan evaporated slightly more than a black enamel pan. Little difference was found in the evaporation from a 32
galvanized pan, an aluminum pan, a dark blue pan and a green enamel pan, although white enamel pan lost 17% less water than a galvanized pan.
2.3.3 Estimation of Reservoir Evaporation Estimation of evaporation in reservoir can be determined by the following three methods:
2.3.3.1.
Water
Budget
Determinations
of
Reservoir
Evaporation
The direct measurement of evaporation under field conditions is not feasible, at least not in the sense that one is able to measure river stage, discharge etc. As a consequence, a variety of techniques has been evolved for determining or estimating vapor transport from water surfaces. The most obvious approach involves the maintenance of a water budget. Assuming that the storage S, surface inflow I, surface outflow 0, subsurface seepage 09 and precipitation P can be measured, evaporation E can be computed form,
E = ( S1 - S1 ) + I + P.O.O g
Equ.(2.17)
This approach is simple in theory but application rarely produces reliable results, since all errors in measuring inflow, outflow and
33
change in storage are directly reflected in. the computed evaporation.
2.3.3.2 Energy Budget Determination of Reservoir Evaporation:
The energy budget approach, like the water budget employs a continuity equation and solves for evaporation as the residual required to maintain the balance. Although the continuity equation in this case is one of energy, an approximate water budget is required as well, since inflow, outflow and storage of water represent energy values which must be considered in conjunction with the respective temperatures.. Application of the energy budget has been attempted by numerous investigators. With cases selected so as to minimize the effect of terms that could not be evaluated. However Lake Hefner experiment is believed to constitute the first test of the method with adequate control. The energy budget for a lake or a reservoir may be expressed as
Q s.Q r.Q b.Q n.Q e = Q F.Q v
Equ.(2.18)
Where Qs
: sun and sky radiation incident at the water surface
Qr
: reflected radiation
Qb
: net energy lost by the water body through exchange of long wave radiation with the atmosphere
Qn
: sensible heat transfer (conduction) to the atmosphere 34
Qe
: energy used for evaporation
QF
: the increase in the energy stored in the water body
Qv
: net energy adverted into the water body (net energy content of inflowing and outflowing water is termed adverted energy).
All are in calories per sq. cm. Letting ( H v )represent the latent heat of vaporization and ( R ) the ratio of heat loss by conduction to heat loss by evaporation (i.e Bowen Ratio), equation (2.18) becomes :
E
Qs Qr Qb Qv Q Hv(1 R)
Equ.(2.19)
where E
: the evaporation in cm and
r
: density of water
The Bowen ratio can be computed from the equation
R
0.61Ts Ta P es ea 1000
Equ.(2.20)
where P
: the atmospheric pressure;
Ta and e s
: the temp. and vapor pressure of the air;
Ts
: the water surface temperature
ea
: the saturation vapor pressure corresponding to Ta.
35
All temperatures and pressures are in degree °C and millibars.
Sensible heat transfer cannot be readily observed or computed and the Bowen ratio was conceived as a means of eliminating this term from the energy budget equation. The validity of the constant in equation (2.20) has been the subject to much discussion. Bowen found limiting values of 0.58 and 0.66 depending on the stability of the atmosphere and concluded that 0.61 was applicable under normal atmospheric conditions. Using an independent approach; Pritchard derived, values of 0.57 and 0.66 for smooth and rough surfaces respectively. At lake Hefner, Oklahoma, monthly values of the ratio, computed from equation (2.20) were found to vary from.0.33 in February to 0.25 in November, while the annual value was 0.03. It is obvious that one need not be concerned over variations in the constant of equation (2.20) for annual computations. If the correct value is assumed to. have been one of the limits determined by Bowen, the extreme error in m6nthly evaporation at Lake Hefner would be only about 4%.
In the application of equation (2.19) it is important that the radiation exchange be accurately evaluated. Most routine observations
from
established networks of phytometers provide measurements of. incident short-wave radiation only and prior to the development of radio-meters, radiation exchange was necessarily estimated from empirical relation. Radiometers can be designed to measure either the total incoming or "net radiation" i.e. the algebraic sum of incident and reflected sun and sky
36
shortwave radiation; incident and reflected atmospheric long wave radiation and long wave radiation emitted by the water body.
The energy adverted and storage terms (Q s.Q F) of equation (2.19) are computed from an approximate water budget and temperatures of the respective water volumes Eqn. (2.17) can be written as
S2 - S1 = I + P . O . Og . E
Equ.(2.21)
Variations in density are neglected and all terms are expressed in cubic cm. The energy content per gm of water is the product of its specific heat and temperature.
Assuming unity for values of density and specific heat,
Qv Q
1 IT1 PT p OTo Og Tg ETe S1T1 S 2T2 A
Equ.(2.22)
where T1, Tv etc. are temperatures (°C) of the respective volumes of water and. the surface area of the lake. A = Is introduced to convert energies to units of calories per sq. cm.
Equation (2.21) must be balanced before solving equation (2.22) although approximate values of individual terms will suffice. The temperature of precipitation can be taken as the wet-bulb temperature; 37
seepage temperature as that at the lowest levels of the lake and TB as the lake surface temperature. Adverted energy and change in energy storage tend to balance for most lakes; particularly over long periods of time and are frequently assumed to cancel when considering annual or mean annual evaporation.
2.3.3.3Mass
Transfer
Determination
of
Reservoir
Evaporation:
Assuming an adiabatic atmosphere and logarithmic distribution of wind speed and moisture in the vertical, and based on the theory of turbulent mass transfer, an equation has been derived which gives
E
343K 2 e1 e s V2 V1 5T 3974.6 ln Z 2 Z1
2
Equ.(2.23)
where E
: evaporation in cm/hour
k
: Von-Karman's constant ~ 0.4
e
: Vapor pressure in gm/cm2
V
: wind speed in km per hour
T
: mean temperature in degrees °C of the layer between the lower layer Z1 and the upper layer Z2
38
Since the computed evaporation is proportional to small differences in wind and vapor pressure at two levels near the surface, instrument requirements are not easily satisfied under field conditions.
2.4 . Data Required for Evaporation Loss Estimation:
the data required to calculate the evaporation losses are either metrological data or geometric data.
Metrological data : Several metrological parameters must be available to calculate the evaporation rate. On the other hand, geometric data covering the area of Lake Nasser must be available. Unfortunately, this area was calculated in different ways but the precision of this calculations is very poor. By using a new technique ( Remote Sensing ) and satellite images the area of the lake will be calculated.
39
CHAPTER (III)
DATA ACCUMULATING AND PROCESSING In Egypt the amount of water lost by evaporation from Lake Nasser is used to be estimated by using traditional methods. The estimation of this loss is about 10 milliard m3/year. The objective of this chapter is to describe and represent different sets of data used to compute the precise amount of water lost by evaporation from Lake Nasser. The chapter also focuses on the techniques and programs used in these computations.
3.1. Data Accumulating For precise computations of evaporation losses, it is necessary to collect reliable data pertaining to this process. However, due to the interaction between many factors controlling the amount of water lost by evaporation, many related data should be obtained. The collected data are processed and treated by different computer programs and software. Examples of the collected data are summarized in the following subsections.
3.1.1. Metrological Stations The Egyptian Metrological Authority (EMA) operates a network of metrological stations comprises of about 100 stations covering the entire area of Egypt, Figure (3 – 1) shows the distribution of these stations. 39
Figure (3 – 1): Distribution of Metrological Stations along Egypt
Six metrological stations are distributed on the lake surface area. These stations are operated either by the weather authority or the High Aswan Dam Authority. The location of these stations with respect to the Lake boundaries is illustrated in Figure (3 – 2). The location and the operational situations of the six stations are presented in table (3 – 1). The actual data of these stations will be presented in this chapter and will be used for the computation of the amount of water lost by evaporation from the lake.
40
Figure (3 – 2): Location of Metrological Stations on Lake Nasser
41
Table (3 – 1): Location and Operational Situation of the Metrological Stations on Lake Nasser Station No. Station Type Location
1 Floating U.S. HAD
2 Land U.S. HAD
3 Floating Abo Simble
4 Floating U.S. HAD
Distance from HAD ( km ) Operation started year Current Status
2
2
280
1974
1978
Doesn't work since 1990 NRA EMA
Owner Operational Responsibility
2
5 Floating North of Allaqi Khour 75
6 Floating West of Wadi El Arab 170
1986
1995
1995
2000
Working
Working
Working
Working
Under test
NRA EMA
HADA EMA
HADA HADA
HADA HADA
HADA HADA
Source: Egyptian Metrological Authority Note that: N R A: Nile River Authority. E M A: Egyptian Metrological Authority HADA: High Aswan Dam Authority
3.1.2. Metrological Parameters
Evaporation from water surface is a continuous process affected by many metrological parameters usually used in the computation of the amount of water lost by evaporation. The rate of evaporation per unit area depends on the properties of the overlaying air and the supply of temperature and heat to the water surface. The factors have direct influence to this process will be discussed in the following subsections. 42
3.1.2.1 Air Temperature
The evaporation rate is highly affected by air and water temperatures. The change in temperature mainly occurrs by the effect of the heat supply from the solar radiation by the sun. This process is activated in large reservoir fed by incoming and outcoming rivers. Also the saturation of the vapor pressure depends on temperature.
The daily average temperature is computed by two different methods according to the degree of the station. For the first degree station, the daily average is equal to the mathematical average of the 24 hours measurements. For the second degree station, the daily average temperature is equal to the mathematical average of the maximum and average reading during 24 hours. The results obtained from the second degree stations are higher than the first degree stations by (+ 0.90 °).
3.1.2.2. Water Vapor Pressure
In case that the other parameters are constant, the evaporation rate is affected by the difference between the pressure of the saturated vapor at the water temperature and the vapor pressure of the air. The water vapor can be expressed as follows:
43
ed = ea * Rh
Equ.(3.1)
Where: ed
: water vapor pressure
ea
: saturated water vapor pressure
Rh
: relative humidity
ea is calculated from a special designed table depending on the temperature. Rh is calculated using two methods: a–
First degree stations: The daily average is equal to the mathematical average of the measured R.H. along the 24 hours.
b–
Second degree stations: The daily average is the mathematical average of the R.H. measured at 8:00 am, 12:00 am and 8:00 pm (This average indicates an error of about 5% with respect to the value from the first degree station).
3.1.2.3. Wind Speed
Wind affects evaporation by bringing fresh air in contact with the evaporating surface. However, the rate of evaporation does not increase after a certain speed for the wind for the same metrological conditions. For large water surface areas, the limiting wind speed pertaining maximum rate of evaporation 44
mainly depends on the stability of the air mass overlaying the water surface and it may vary between 20 and 25 miles per hour (Horton, 1917 and Houk, 1951). The value of wind speed is measured at a certain height above the water surface. This height is estimated to vary between 2 and 20 m, depending on the condition of the station. In the current research, the average of the wind speed is calculated using two different procedures which can be expressed as follows:
a–
First degree station: The daily average is considered as the mathematical average of the measured wind speed during the 24 hours.
b–
Second degree station: The daily average is considered as the mathematical average of the maximum and minimum wind speed during the day. As a base, the height of the measured speed, to estimate the evaporation rate, should be taken at height of 2 m other speeds should be modified using Slater and Mcroy equation developed in 1961. This equation can be expressed as follows:
1
U2 2 7 Uz Z
Equ.(3.2)
Where: U2
: wind velocity at height of 2 m above water surface
Uz
:
wind velocity at height equal to Z m above water surface 45
3.1.2.4. Solar Radiation
The solar radiation is considered the principle source of heat. However, the changes in the amount of heat added or removed to water surface are not reflected totally to the changes in evaporation. The heat effects will be considered for evaluating of the net radiation utilized for evaporation. The solar radiation is measured in a limited number of stations. But it can be calculated from the Angeshtrom equation which is expresses as follows:
RG = (a + b n/N) RA
Where: RG
: solar radiation
RA
: solar radiation out of the atmosphere (comes from a certain table depending on the latitude and longitude)
n
: actual hours of sunshine
N
: possible hours of sunshine
a ,b
: constants depending on the latitude, longitude (a = 0.25 & b = 0.50 for the lake)
46
Equ.(3.3)
Table (3 – 2) contains the data from the Aswan floating station which will be used to calculate the evaporation. Table (3 – 3) contains the data of the sunny hours measured in Aswan floating station. Table (3-2): Metrological Data for Aswan Station Item Ta Rh cl.c Jan. 15.5 35 0.7 Feb. 17.8 26 0.6 March 22 18 1.6 April 26.9 14 1.5 May 30.5 13 1.6 June 33.4 13 0.5 July 33.5 16 0.2 August 33.3 18 0.1 Sept. 31.1 20 1 Oct. 27.9 22 0.7 Nov. 21.8 33 0.2 Dec. 17 37 1 Ta : average air temperature (°C)
U 2.58 2.71 2.93 3.00 2.84 2.90 2.64 2.64 2.74 2.64 2.61 2.51
Rh
: average air relative humidity
cl.c
: average of cloudiness
U
: wind velocity above 2m (km/hour)
RG
: solar Radiation ( Calories / cm2 )
sh.h
: actual number of sunshine hours (hour / day)
47
RG 17 19.9 22.4 25.3 26.2 27.7 28.2 27 24 20.8 18 16
sh.h 9.6 9.8 10.3 10.6 11.1 12 12.2 11.6 10.5 10 9.9 9.2
Table (3 – 3): Ratio of actual to possible hours of sunshine (cloudiness ratio) At Aswan Item Jan. Feb. March April May June July Aug. Sept. Oct. Nov. Dec. Annual Average
Actual (hours/day) 9.6 9.8 10.3 10.6 11.1 12 12.2 11.6 10.5 10 9.9 9.2
Possible (hours/day) 10.7 11 12.4 12.6 13.3 13.3 13.3 12.7 12 11.2 10.7 10.3
%
10.6
12
88
89 89 83 84 83 90 92 91 87 89 92 87
3.1.3. Geometric Data
The present study is based on several sets of field data representing the lake. Topographical maps for the lake representing 20 m interval contour are used to extract the lake surface area at different levels. The same maps are used to rectify the remote sensing data because they have very clear landmarks. These maps are scanned and digitized to the computer with the emphasis on the contour lines between 160 and 180 m and the spots in between which represent the low and high water levels 48
respectively. These data are jointed with the data from the satellite image to create the Digital Elevation Model for the Lake (DTM). These maps are produced by the Egyptian Survey Authority (ESA) in 1991. They are compiled from aerial photography of 1988. Field survey were conducted for verification and compilation in 1990. The scale of the maps is 1: 50000 with contour interval of 20 m starting with contour level 160 m). They are referenced to Ellipsoid (Helmert 1906) and their projection is Transverse Mercator with specific parameter. The number of maps covering the area of the Lake Nasser is 24 maps.
Each year a field trip is made to survey 26 cross sections along the lake. This survey is made mainly for the monitoring of the sediment transportation in the lake. Figure ( 3 –15 ) shows the locations of the cross sections of lake Nasser.
3.1.4. Remote Sensing
Remote sensing is broadly defined as collecting and interpreting information about a target without being in physical contact with the object. Aircraft and satellites are the common platforms for remote sensing observations. The term remote sensing is commonly restricted to methods that employ electromagnetic energy (such as light, heat, and radio waves) as the means of detecting and measuring target characteristics. This definition of remote sensing excludes electrical, magnetic, and gravity surveys 49
that measure force fields rather than electromagnetic radiation. Magnetic and radioactivity surveys are frequently made from aircraft but are considered airborne geophysical surveys rather than remote sensing. Aerial photography is the original form of remote sensing and remains the most widely used method. Aerial photography analyses have played major roles in the discovery of many oil and mineral deposits around the world. These successes, using the visible portion of the electromagnetic spectrum, suggested that it might be possible to obtain comparable results by using other wavelength regions. In the 1960s, technologic developments enabled the acquisition of images at other wavelengths, including thermal infrared (IR) and microwave. The development and deployment of manned and unmanned earth satellites began in the 1960s and provided an orbital vantage point for acquiring images of the earth. For a review of the history of remote sensing, see Fischer and others (1975).
3.1.4.1. Landsat Satellite Images
Landsat is an unmanned system that prior to 1974 was called ERTS (Earth Resources Technology Satellite). Initially NASA operated Landsat, but in 1983 responsibility for operating the system transferred to the National Oceanic and Atmospheric Administration (NOAA).
50
In 1985, operation of Landsat transferred to the EOS AT Company, a private corporation. The science of remote sensing and the acquisition of images from satellites predated Landsat by many years, but the Landsat program is largely responsible for the growth and acceptance of remote sensing as a scientific discipline.
Landsat satellites have been placed in orbit using Delta rockets launched from Vandenberg Air Force Base on the California coast between Los Angeles and San Francisco. The five Landsats belong to two generations of technology with different platforms and orbital characteristics (Table 3 – 4 ). Table (3 – 4): Platforms and Orbits of First and Second Generations of Landsat Description
Altitude Orbits per day Number of orbits ( paths ) Image side lap at equator Crosses 40°N Latitude at ( Local sun time, approximate) Operational from On-board data storage Imaging Systems: Multispectral Scanner Return-beam Vidicon, panchromatic Thematic mapper
Landsats 1,2, and 3
Landsats 4 and 5
1st generation
2nd generation
918 km 14 251 14 % 9:30 a.m.
705 km 14.5 233 7.6 % 10:30 a.m.
1972 to 1984 Yes
1982 till now No
Yes Yes ( Landsat 3 )
Yes No
No
Yes
51
3.1.4.2. Landasts 4 and 5 The second generation of Landsat consists of two satellites launched July 16, 1982, and March 1, 1984. Landsat 4 is in orbit but not functioning because of problems with the power supply and data transmission systems. Landsat 5 is performing as planned.
3.1.4.3. Platform
Landsats 4 and 5 Figure (3 – 3) are larger and more complex than their predecessors. Their most conspicuous features are a single large solar array and a microwave antenna mounted on a mast for communication with other satellites. The major components, shown in Figure (3 – 4), include an MSS imaging system and a new system, the thematic mapper (TM).
Only a few of the existing receiving stations have recording equipment adequate to handle the very high volumes of image data transmitted from TM. Tracking and Data Relay Satellites (TDRSs) are placed in geostationary orbits; when all the planned TDRSs are deployed, Landsat will always be in communication with a ground station via a TDRS. Image data are transmitted to TDRS, which relays them to the ground station at White Sands, New Mexico, which then relays the data via Domestic Communication Satellite (DOMSAT) to the Goddard Space Flight Center (GSFC), at Greenbelt, Maryland. GSFC converts the TM data into master film negatives and computer compatible tapes that it forwards to EDC for distribution to users. There have been problems in 52
deploying TDRS platforms, which has hampered the acquisition of TM data. When all TDRS platforms are fully operational, TM images can be acquired on a worldwide basis. Landsats 4 and 5 also have direct access antennas (Figure 3 – 4) that can transmit TM data to suitably equipped ground receiving stations when the satellite is within receiving range. All MSS data are transmitted directly to ground receiving stations. Because of the lower altitude of Landsats 4 and 5, only 233 orbits and 16 days are required to cover the earth. The smaller number of orbits and their wider spacing reduces the sidelap between adjacent image swaths to only 7.6 percent at the equator in contrast to 14 percent for Landsats 1,2, and 3. The orbit paths for Landsats 4 and 5 are parallel, but not coincident, with those of their predecessors shown in Figure (3 – 5).
Figure (3 – 3): Satellite platform of landsats 4 and 5 53
Figure (3 – 4): Components of the platform of Landsats 4 and 5
Figure (3 – 5): Daytime portion of orbits for landsats 1, 2 and 3 for a single day 54
3.1.4.4. Mulispectral Scanner System
The three imaging systems deployed on various Landsats, listed in the order of improving spatial resolutions, are MSS, RBV, and TM. Table (3 – 5) lists their significant characteristics. All five landsats, carried MSS, which has produced the vast majority of images.
Table (3 – 5): Characteristics of Landsat Imaging System Description
Multispectral scanner (MSS)
Returnbeam vidicon (RBV)
Thematic mapper (TM)
Spectral region: Visible and reflected IR
0.5 to 1.1 mm
Thermal IR (TM band 6)
---
0.5 to 0.75 mm ---
4
1
0.45 to 2.35 mm 10.5 to 12.5 mm 7
185 km 185 km
99 km 99 km
185 km 170 km
0.087 mrad
0.043mrad
0.43 mrad
---
---
0.17 mrad
79 * 79 m
40 * 40 m
30 * 30 m
---
---
120 * 120m
7.6 x 10 6
6.1 x 10 6
39 x 10 6
30.4 x 10 6
6.1 x 10 6
273 x 10 6
Spectral bands Terrain coverage: East-west direction North-south direction Instantaneous field of view: Visible and reflected IR Thermal IR (TM band 6) Ground resolution cell: Visible and reflected IR Thermal IR (TM band 6) Number of picture elements: Single band All bands
55
3.1.4.5 Remote Sensing Data
Two sets of satellite images from the satellite LANDSAT TM with 7 bands are brought for the purpose of this study. Each set consists of 3 themes covering the area of lake Nasser from latitude 20° N to 24° N.
The first set of images represent the lower flood of November 1987, the water level at that time was (158.40 m). The themes of this set are:
Orbit No. (74), Theme No. (44) at 31 October 1987.
Orbit No. (75), Theme No. (44) at 17 November 1987.
Orbit No. (75), Theme No. (45) at 17 November 1987.
Figure (3–6 a, b, and c) show the three themes of the first set as a raw data.
Figure (3 – 6 a):Theme No. (44), Orbit No. (74) at 31 October 1987 56
Figure (3 – 6 b): Theme No. (44), Orbit No. (75) at 17 November 1987
Figure (3 – 6 c): Theme No. (45), Orbit No. (75) at 17 November 1987 57
The second set of images resembles a high flood year of November 1998; the water level at that time was (181.20 m). The themes of this set are:
Orbit No. (174), Theme No. (44) at 16 November 1998.
Orbit No. (175), Theme No. (44) at 23 November 1998.
Orbit No. (175), Theme No. (45) at 23 November 1998.
Figure (3 – 7 a, b, and c) show the three themes of the second set as a raw data.
Figure (3 – 7 a): Theme No. (44), Orbit No. (174) at 16 November 1998 58
Figure (3 – 7 b): Theme No. (44), Orbit No. (175) at 23 November 1998
Figure (3 – 7 c): Theme No. (45), Orbit No. (175) at 23 November 1998 59
These themes are in pixel units so that it is impossible to extract any kind of geometric data from them. To be able to extract geometric data from the images, rectification or geo-referencing processes should be conducted. These processes are adjusting the images to have a geodetic Datum, Projection and coordinate system. Computer software, ERDAS IMAGIN 8.4, is used to formulate these processes with the aid of field data.
3.1.5 Hydrological Data The water levels upstream the dam is collected in order to develop a relationship between the water level and the lake surface area. The developed equation is compared to the previous existing relation between resemble parameters. Tables (3-6), (3-7) and (3-8) show the collected daily water levels upstream HAD for the years 1987, 1995 and 2000, respectively.
60
Table ( 3 – 6 ) : Daily water levels U.S. HAD and Monthly Average for year ( 1987 ) Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Average
Jan. 161.66 161.63 161.61 161.6 161.58 161.57 161.56 161.55 161.54 161.53 161.52 161.5 161.49 161.48 161.47 161.46 161.45 161.44 161.44 161.44 161.44 161.44 161.44 161.42 161.39 161.35 161.31 161.28 161.26 161.24 161.22 161.46
Feb. 161.2 161.19 161.18 161.16 161.12 161.09 161.06 161.03 161 160.97 160.94 160.9 160.82 160.82 160.76 160.71 160.73 160.76 160.61 160.62 160.6 160.57 160.55 160.52 160.44 160.4 160.46 160.36
160.81
March 160.32 160.29 160.27 160.25 160.23 160.21 160.17 160.13 160.09 160.05 160.02 160 159.98 159.95 159.91 159.88 159.86 159.84 159.82 159.8 159.77 159.73 159.69 159.65 159.61 159.56 159.52 159.48 159.43 159.4 159.36 159.88 61
April 159.32 159.28 159.25 159.21 159.17 159.17 159.09 159.05 159.02 158.98 158.95 158.92 158.9 158.87 158.85 158.83 158.81 158.79 158.76 158.73 158.7 158.67 158.64 158.61 158.58 158.55 158.52 158.49 158.46 158.43 158.85
May 158.4 158.37 158.34 158.31 158.28 158.25 158.22 158.19 158.16 158.13 158.1 158.07 158.04 158.01 157.98 157.95 157.98 157.89 157.86 157.84 157.81 157.79 157.77 157.75 157.71 157.69 157.66 157.63 157.59 157.55 157.5 157.96
June 157.45 157.4 157.33 157.26 157.18 157.1 157.02 156.94 156.86 156.74 156.7 156.65 156.58 156.5 156.42 156.43 156.27 156.21 156.14 156.07 156.03 156 155.94 155.9 155.87 155.83 155.79 155.74 155.69 155.65 156.46
Table ( 3 – 6 ) : Daily water levels U.S. HAD and Monthly Average for year ( 1987 ) (con.)
Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Average
July 155.61 155.58 155.54 155.5 155.46 155.42 155.39 155.37 155.35 155.33 155.3 155.26 155.21 155.18 155.15 155.12 155.08 155.05 155.02 154.99 154.95 154.92 154.89 154.86 154.83 154.8 154.77 154.74 154.71 154.68 154.65 155.12
Aug. 154.62 154.59 154.58 154.57 154.54 154.52 154.5 154.5 154.5 154.5 154.5 154.5 154.52 154.53 154.56 154.61 154.64 154.66 154.7 154.75 154.82 154.87 154.96 155.05 155.12 155.18 155.28 155.4 155.55 155.75 155.95 154.82
Sep. 156.1 156.24 156.38 156.52 156.65 156.77 156.92 157.07 157.2 157.32 157.45 157.57 157.68 157.87 157.84 157.92 157.97 158.04 158.07 158.12 158.14 158.18 158.19 158.2 158.2 158.2 158.2 158.2 158.2 158.18 157.59 62
Oct. 158.16 158.15 158.13 158.11 158.1 158.1 158.09 158.08 158.09 158.08 158.07 158.08 158.06 158.08 158.08 158.09 158.1 158.1 158.14 158.12 158.14 158.14 158.14 158.15 158.2 158.23 158.26 158.27 158.31 158.33 158.35 158.15
Nov. 158.37 158.4 158.4 158.42 158.44 158.48 158.44 158.47 158.47 158.46 158.47 158.48 158.49 158.48 158.46 158.46 158.46 158.46 158.44 158.44 158.46 158.46 158.44 158.43 158.43 158.43 158.43 158.43 158.42 158.41 158.44
Dec. 158.41 158.4 158.39 158.37 158.34 158.32 158.3 158.3 158.29 158.28 158.29 158.28 158.24 158.22 158.21 158.2 158.21 158.2 158.2 158.2 158.16 158.13 158.13 158.1 158.18 158.07 158.05 158.02 157.99 157.97 157.95 158.21
Table ( 3 –7 ) : Daily water levels U.S. HAD and Monthly Average for year ( 1995 ) Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Average
Jan. 176.93 176.93 176.93 176.93 176.93 176.93 176.93 176.93 176.93 176.93 176.93 176.92 176.92 176.91 176.9 176.9 176.89 176.88 176.86 176.84 176.82 176.81 176.8 176.79 176.78 176.76 176.74 176.72 176.71 176.7 176.69 176.86
Feb. 176.68 176.68 176.68 176.68 176.67 176.66 176.65 176.64 176.63 176.62 176.6 176.58 176.55 176.52 176.5 176.49 176.48 176.47 176.45 176.43 176.41 176.39 176.37 176.35 176.34 176.34 176.33 176.31
176.52
March 176.29 176.27 176.26 176.26 176.26 176.26 176.23 176.2 176.17 176.14 176.11 176.09 176.07 176.05 176.03 176.02 176.01 176 175.99 175.97 175.95 175.93 175.9 175.87 175.84 175.8 175.76 175.73 175.72 175.72 175.71 176.02 63
April 175.7 175.69 175.67 175.63 175.59 175.55 175.53 175.52 175.51 175.5 175.47 175.44 175.41 175.4 175.4 175.39 175.37 175.35 175.31 175.27 175.23 175.21 175.19 175.18 175.17 175.16 175.15 175.13 175.11 175.09 175.38
May 175.07 175.05 175.01 174.99 174.98 174.96 174.95 174.91 174.89 174.88 174.88 174.87 174.86 174.84 174.82 174.8 174.77 174.74 174.74 174.73 174.72 174.7 174.69 174.67 174.64 174.6 174.57 174.54 174.51 174.47 174.45 174.78
June 174.41 174.37 174.32 174.28 174.24 174.2 174.15 174.1 174.06 174.02 173.98 173.93 173.89 173.85 173.82 173.79 173.75 173.71 173.66 173.63 173.58 173.52 173.47 173.42 173.39 173.36 173.33 173.28 173.25 173.21 173.8
Table ( 3 – 7 ) : Daily water levels U.S. HAD and Monthly Average for year ( 1995 ) (con.) Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Average
July 173.16 173.12 173.08 173.04 172.99 172.95 172.9 172.86 172.82 172.78 172.74 172.69 172.64 172.61 172.59 172.56 172.54 172.52 172.5 172.48 172.48 172.48 172.48 172.48 172.48 172.48 172.47 172.45 172.41 172.37 172.34 172.66
Aug. 172.32 172.32 172.32 172.32 172.32 172.32 172.33 172.35 172.38 172.43 172.5 172.56 172.64 172.72 172.82 172.9 172.99 173.03 173.17 173.26 173.35 173.44 173.52 173.61 173.71 173.8 173.9 174.02 174.14 174.23 174.29 173.03
Sep. 174.41 174.5 174.56 174.63 174.69 174.77 174.85 174.93 175.02 175.1 175.1 175.2 175.27 175.33 175.4 175.48 175.54 175.6 175.67 175.73 175.78 175.83 175.88 175.92 175.94 175.96 175.98 176 176.03 176.07 175.37 64
Oct. 176.09 176.1 176.11 176.11 176.11 176.11 176.11 176.11 176.12 176.13 176.15 176.16 176.16 176.18 176.2 176.22 176.23 176.24 176.25 176.25 176.25 176.25 176.25 176.26 176.26 176.27 176.27 176.27 176.27 176.27 176.27 176.19
Nov. 176.27 176.27 176.26 176.25 176.23 176.21 176.2 176.17 176.14 176.11 176.09 176.08 176.08 176.08 176.08 176.08 176.08 176.08 176.07 176.06 176.05 176.04 176.03 176.02 176.01 176 175.99 175.98 175.97 175.96 176.1
Dec. 175.96 175.96 175.96 175.96 175.96 175.96 175.96 175.96 175.96 175.96 175.95 175.95 175.95 175.94 175.94 175.94 175.94 175.93 175.92 175.92 175.92 175.92 175.91 175.91 175.9 175.9 175.9 175.89 175.89 175.88 175.88 175.93
Table ( 3 – 8 ) : Daily water levels U.S. HAD and Monthly Average for year ( 2000 ) Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Average
Jan. 180.93 180.91 180.9 180.88 180.88 180.87 180.84 180.83 180.79 180.79 180.7 180.67 180.65 180.62 180.6 180.58 180.56 180.54 180.52 180.5 180.49 180.47 180.45 180.43 180.4 180.38 180.35 180.34 180.32 180.28 180.27 180.6
Feb. 180.25 180.23 180.21 180.2 180.19 180.17 180.14 180.12 180.1 180.09 180.07 180.06 180.05 180.02 179.99 179.96 179.93 179.91 179.89 179.88 179.87 179.85 179.83 179.8 179.78 179.76 179.73 179.71 179.68
179.98
March 179.66 179.64 179.62 179.6 179.58 179.55 179.52 179.49 179.46 179.44 179.41 179.38 179.35 179.32 179.3 179.28 179.27 179.26 179.24 179.21 179.18 179.15 179.12 179.09 179.06 179.04 179.01 178.99 178.96 178.94 178.92 179.29 65
April 178.9 178.89 178.88 178.86 178.84 178.83 178.82 178.79 178.75 178.75 178.69 178.68 178.67 178.66 178.65 178.64 178.63 178.62 178.61 178.59 178.55 178.53 178.51 178.5 178.49 178.47 178.45 178.44 178.42 178.42 178.65
May 178.41 178.4 178.38 178.36 178.34 178.3 178.26 178.22 178.19 178.17 178.15 178.13 178.1 178.08 178.06 178.04 178.02 178 177.98 177.95 177.91 177.86 177.82 177.77 177.74 177.73 177.7 177.66 177.61 177.58 177.53 178.01
June 177.52 177.5 177.49 177.48 177.37 177.32 177.29 177.26 177.24 177.21 177.19 177.16 177.13 177.09 177.07 177.05 177.02 176.98 176.93 176.87 176.8 176.75 176.72 176.69 176.66 176.62 176.57 176.54 176.51 176.48 177.02
Table ( 3 – 8 ) : Daily water levels U.S. HAD and Monthly Average for year ( 2000 ) (con.) Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Average
July 176.45 176.42 176.38 176.34 176.31 176.27 176.24 176.22 176.2 176.17 176.14 176.13 176.1 176.08 176.05 176.02 176 175.97 175.95 175.94 175.93 175.92 175.91 175.89 175.87 175.86 175.85 175.84 175.84 175.84 175.84 176.06
Aug. 175.85 175.85 175.85 175.86 175.88 175.9 175.95 176.02 176.08 176.12 176.15 176.2 176.25 176.3 176.38 176.47 176.53 176.6 176.65 176.72 176.8 176.89 176.98 177.08 177.19 177.3 177.41 177.51 177.62 177.73 177.85 176.58
Sep. 177.96 178.07 178.19 178.3 178.41 178.5 178.6 178.69 178.77 178.86 178.96 179.07 179.13 179.18 179.25 179.28 179.31 179.37 179.46 179.5 179.55 179.6 179.65 179.69 179.75 179.8 179.84 179.87 179.9 179.93 179.15 66
Oct. 179.97 180.01 180.04 180.08 180.12 180.13 180.15 180.15 180.16 180.18 180.19 180.19 180.19 180.23 180.27 180.31 180.35 180.39 180.43 180.47 180.5 180.5 180.51 180.51 180.53 180.53 180.54 180.54 180.57 180.57 180.57 180.32
Nov. 180.57 180.58 180.58 180.59 180.6 180.6 180.6 180.6 180.61 180.62 180.62 180.62 180.62 180.62 180.62 180.62 180.63 180.63 180.63 180.63 180.62 180.61 180.6 180.59 180.57 180.55 180.54 180.54 180.54 180.54 180.6
Dec. 180.53 180.53 180.53 180.52 180.51 180.5 180.49 180.48 180.47 180.46 180.45 180.44 180.43 180.41 180.4 180.39 180.38 180.37 180.35 180.32 180.29 180.25 180.24 180.23 180.22 180.21 180.2 180.19 180.18 180.17 180.15 180.36
3.1.6 Field Survey Data :
The first mission to gather data concerning the sediment deposition in Lake Nasser was assigned, to High Aswan Dam Authority (HADA) incorporation with Nile Research Institute (NRI), to gather data concerning the sediment deposition in Lake Nasser. The main goals of this survey program were designed to conduct hydrographic survey, measure flow currents, and collect suspended matters and bed material samples at a certain transect lines (cross sections) along the lake inside the Sudanese and Egyptian borders. The equipment used in conducting the hydrographic survey were theodolites and primary echosounders. Accordingly, the topographic and the shape of the cross sections were obtained. Also a mechanical sieve analysis was done for bed material samples to determine the percentage of sand, silt and clay as the main components of the sediment deposition. The number of the cross sections surveyed during the first missions was seven cross sections inside Sudanese borders and seven cross sections within the Egyptian borders. Year after year, the number of the cross sections increased to be 15 and 14 cross sections within the Sudanese and Egyptian borders, respectively. By comparing the cross section profiles, for successive years, the sediment deposition volumes were estimated in addition to the longitudinal profile of the lake bottom. The cross sections appellations and locations are listed in Table (3-9).
Since 1990, HADA and NRI had been executing these survey missions using the state-of-the art techniques in implementing hydrographic 67
survey. Using such real time data acquisition systems, such as MiniRanger systems (Falcon IV), allowed the surveying of more areas of the lake around the existing cross sections. Since 1998, differential global positioning system (DGPS) has been used as a positioning system, in addition to digital echosounders for depth measurements. Hence, estimation of sediment deposition volumes, become more accurate. The need for hydrographic survey in sediment deposition studies is crucial as well as the hydrological variable measurements.
Figure (3-8) shows the name and location of the cross sections along Lake Nasser in Egypt and Sudan.
68
Egyptian Borders
Sudanese Borders
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29
EL-Daka Okma Malek EL-Nasser EL-Dowaishat Ateere Semna Kajnarity Morshed Gomai Madeek Amka Amka Second Cataract Abdel-Qader Doghame Dabrosa Arkin Sara Adendan Abu-Simbel Toushka Ibreem Korosko Wadi- Alarab* EL-Madeek Garf Hussien* Morwaw Kalabsha Dahmeet High Dam*
23 19 16 13 10 8 6 3 D 28 27 26 25 24 22 21 20 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
Location U.S. AHD (km)
Cross Section Number
Cross Section Name
Serial No.
Region
Table (3-9): Definition of Main Locations Surveyed during the Present Monitoring Program Observation year
487.000 466.000 448.000 431.000 415.500 403.500 394.000 378.500 372.000 368.000 364.000 357.000 352.000 347.000 337.500 331.100 325.000 307.000 282.000 256.000 228.000 182.500 171.000 130.000 90.000 60.000 41.000 30.000 0.500
from
to
1977 1977 1977 1977 1977 1977 1977 1977 1977 1987 1977 1987 1988 1977 1977 1987 1977 1987 1978 1978 1994 1994 1978 1994 1978 1994 1978 1994 1980
2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003
N/A means not available (No cross section number is given). 69
* Only water quality variables are measured.
Dahmeet Merwaw Garf Husin Almadik
Masmas
Abrim
Koresko
Toshka Abo Simble Adindan
na
lka
de
r
y than l Al
ma Aldekka
ge
anda
Alg
y Atir K
d-E
rit y
t
a sh ay
Ok
Ab
SemnaAldw
Malek Naser
Sar DeArkina bro Do sa gee m Am Gom ka ay Madek AmMka orsh ed
Figure (3 – 8): The Name and Location of the surveyed cross sections
70
3.2 Data Processing
In order to extract information from the satellite images, a processing approach must be done.
3.2.1 Rectification The raw data of the satellite images are in pixel units which mean that the information in raster format and it is impossible to extract any kind of data related to the real world. To be able to extract data from these themes it should be passed through a rectification or geo-referencing processes. These types of processes change the raster data to vector data which indicate relationship to real world. That means that the image will have a geodetic Datum, Projection and coordinate system. The most common used datum in in Egypt is Helmert 1906 with the projection of Egyptian Transverse Mercator which is considered a modified version of the Transverse Mercator projection. This projection has a coordinate system of the following parameters:
False Easting = 615000 m False Northing= 810000 m Latitude of origin
= 30° N
Longitude of central meridian = 31° E Scale factor
= 1.0
71
A computer software [ERDAS IMAGIN 8.4] is used to georeference the images. Field Data or Maps (vector data) are utilized to achieve this process. The topographic maps of scale 1: 50000 which were produced in 1991 by the Egyptian Survey Authority were used to rectify the satellite images. These maps have the Egyptian Transverse Mercator projection and geodetic datum Helmert 1906. The rectification process is to verify the raster data of the satellite image using defined and known object in the field data set to coincide similar object in the two sets of data. The coordinate of the defined object will be determined with a suitable accuracy by the use of topographic maps. Figure (3-9 a) and (3-9 b) show the satellite image and the topographic map. The selected object to start the rectification process is the intersection of two roads (Aswan-Abo Simble road and Aswan – Cairo road). To rectify a theme accurately, at least 12 rectification points are defined with a good distribution in order to represent the entire theme. According to the number of rectification points and there distribution the software work out the rectification processes. Figure (3-10 a) and (3-10 b) show the same theme before and after the rectification.
72
Figure (3 – 9 a): The identified object on the satellite image
Figure (3 – 9 b): The same identified object on the paper map
73
Figure (3 – 10 a): One Theme of Satellite Image Before Rectification
Figure (3 – 10 b): The Same Theme of Satellite Image After Rectification 74
3.2.2 Mosaic
After rectifying the 3 themes in each set of data, the themes must be collected together in one theme. This operation is called [MOSAIC]. It means that the software will connect the three themes together in one theme. The sidelap of adjacent orbit swaths and the 10 percent forward overlap of consecutive images greatly facilitate mosaic compilation. The uniform scale and minimal distortion of landsat images also make mosaic compilation more accurate. The area of overlap between the themes must be very smooth. Figure (3 – 11) shows the three themes of the first data set of year (1987) after MOSAIC, also figure (3 – 12) shows the three themes of the second data set of year (1998) after MOSAIC.
75
Figure (3 – 11): The MOSAIC of the three themes of year (1987)
Figure (3 – 12): The MOSAIC of the three themes of year (1998)
3.2.3 Area Computations
After rectification and mosaic, the final image is used to calculate the area of the lake to represent the lake surface area in low and high floods. To enable these calculations, a process of land use classification is carried out.
Land use describes how a parcel of land is used (such as for agriculture, residences, or industry), whereas land cover describes the materials (such 76
as vegetation, rocks, or buildings) that are present on the surface. The land cover of an area may be evergreen forest, but the land use may be lumbering, recreation, oil extraction, or various combinations of activities. Accurate, current information on land use and cover is essential for many planning activities
Classification systems should recognize both activities (land use) and resources (land cover). Such a classification system that utilizes orbital and aircraft remote sensing data should meet the following criteria (Anderson and others, 1976): 1-
The minimum level of accuracy in identifying land-use and land-cover categories from remote sensing data should be at least 85 percent.
2-
Accuracy of interpretation for all categories should be approximately equal.
3-
Repeatable results should be obtainable from one interpreter to another and from one time of sensing to another.
4-
The system should be applicable over extensive areas. 5.The system should be usable for remote sensing data obtained at different times of the year.
6-
The system should allow use of subcategories that can be derived from ground surveys or from larger scale remote sensing data.
7-
Aggregation of categories should be possible.
8-
Comparison with future land-use data should be possible.
9-
Multiple land uses should be recognizable.
77
Through this process the remote sensing specified software is used to identify pixels have similar properties such as pixels represent water, vegetations, ect. Each type of pixels having similar characteristics will be isolated in separate layer. The satellite image used in this study consists of 7 wave bands. The bands ( 1, 2, and 3 ) represent the visible wave length ( blue, green and red ), while Bands ( 4,5,7 ) represent infra red wave lengths and band ( 6 ) resembles the thermal wave length. Each object on the earth or on the real world will reflect the sun radiations in different wavelength. This is attributed to that each object absorbs some of the sun radiation and reflect the other radiations. Each pixel in this satellite image has 7 values representing the reflected wavelengths of each band. These values depend on the object on the earth surface, for example for water areas water surface will absorb most of the radiations, then these areas will appear in dark blue, in case of silty water it will appear in light blue .etc. Each of the isolated layers will represent the same type of characterizes. The water layer will be used to calculate the water area of the lake which has direct relationship with the amount of water lost by evaporation processes.
Figure (3 – 13) shows the selected water area of the year (1987) and the computed surface area of the lake at this water level (158.40m) is 2972km2.
78
Figure (3 – 13): The surface area of Lake Nasser at water level (158.40m) is 2972 km2 Figure (3 – 14) shows the isolated water pixel of the year (1998) and the calculated surface area of the lake at this water level (181.22m) is 6044km2.
79
Figure (3 – 14): The surface area of Lake Nasser at water level (181.22m) is 6044 km2
80
3.2.4 Digital Elevation Model
To construct a digital elevation model (DTM) for the Lake, another source of data is used. These data are topographic maps (24 maps) covering the lake area. They are produced by the Egyptian Survey Authority (ESA) in 1991. These maps are compiled from aerial photography taken in 1988. Field verification and compilation are conducted in 1990. the scale of these maps is 1: 50000 with contour interval of 20 m a part. The starting contour line is 160 m which represents low water level. They are referenced to Ellipsoid (Helmert 1906) and there projection is Transverse Mercator with specific parameter can be expresses as follows: False Easting = 615000 m False Northing = 810000 m Latitude of Origin = 30 ° N Central Meridian = 31 ° E Scale Factor = 1 Figure (3 – 15) indicates the entire set of the 24 maps collected together as one map. These maps are used to rectify the satellite images as mentioned previously because they have very clear landmarks. These maps are also used to extract the contour levels (160 m) and (180 m) as well as the spots in-between. They are joined with the data from the satellite image to create the DTM of the lake. 81
Two techniques are used for processing the data of the maps into digital format as follows:
By using the digitizing table the contour lines on the paper maps are traced and converted to vector format. In the AutoCAD computer soft ware this vector can be converted to spots with a coordinates and elevations so that it can be use to create the DTM.
By scanning the 24 map and transfer them into a raster format then by the help of AutoCAD computer software, it can be converted to spots with a coordinates and elevations.
Figure (3 – 16) contains the spots of the two contour levels (160 m) and (180 m).
82
Dabood
Adindan
Armenia
Toshka
Hondl
Koresko
Abo Sembil
Wadi Armenia
Wadi Toshka
Wadi Koresko
Gabal Merwaw
Kalabsha
Om Hebal
Gazar
Hoor
Marya
Dekka
Koshtoma
Nogadeeb
Sayala
Karar
Sobo
Kostol
Figure (3 – 15): The 24 paper maps connecting together
83
Allaqi
Contour line for level 180m Contour line for level 160m
Figure (3 – 16): Contour lines for levels (160 m) and (180 m ) extracted from paper maps
84
The entire digital format data representing different sources are used with the help of computer software [SURFR 8] to produce a digital elevation model (DTM) for the lake Nasser by using a different griding methods. Each grid method gives a different result. From the DTM created from different griding method a contour map is created by using the same computer software. Each contour map is covering the contour lines between levels of 160m and 180m with an interval of 2 m. The surface area of each contour can then be calculated.
Table (3 – 10) illustrates the surface area of the lake for the different water levels calculated from the developed contours for each griding method. By using these data a relationship is developed between the surface area of the lake and various water levels as shown in Figure (3 – 17).
In order to choose the suitable curve for the relation between the water level and the surface area, the field data can be used to verify the calculated areas. by using the contour maps which were created before, cross sections can be made at the same location. Figure ( 3 – 18 ) shows one of the cross sections created by the different griding method and the same surveyed cross section.
85
Table (3 – 10): The surface area of Lake Nasser Calculated from different griding methods for different water levels
158.4 160 162 164 166 168 170 172 174 176 178 180 181.2
inverse Distance 3096.59 3212.43 3503.31 3741.91 3947.69 4170.34 4367.29 4577.29 4804.18 5054.52 5351.22 5794.30 6365.78
kriging 3096.59 3276.04 3579.02 3813.30 4029.11 4222.34 4433.30 4704.92 4899.92 5151.37 5456.09 5857.55 6365.78
local polynomial 3096.59 3204.89 3400.72 3660.29 3905.19 4138.39 4403.96 4689.38 4937.48 5237.09 5604.17 5965.94 6365.78
Minimum Distance 3096.59 3201.01 3377.11 3605.29 3822.37 4042.05 4282.50 4579.14 5005.37 5357.53 5636.18 6001.64 6365.78
Nearest Neighbor 3096.59 3682.95 3830.54 3968.31 4112.99 4259.41 4425.36 4589.14 4747.43 4922.28 5071.91 5253.42 6365.78
Triangulation 3096.59 3254.31 3489.75 3730.67 3960.28 4183.24 4409.89 4676.54 4890.27 5156.74 5496.14 5867.42 6365.78
Suface Area of Lake Nasser Againist Water Level calculated from different griding methods 7000.00 6500.00
2
Surface Area "km "
6000.00 inverse Distance kriging local polynomial Minimum Distance Nearest Neighbor Triangulation
5500.00 5000.00 4500.00 4000.00 3500.00 3000.00 155
160
165
170
175
180
185
Water Level "m"
Figure (3 – 17): The surface area of lake Nasser calculated from different griding methods
86
Triangulation W.L. 180 W.L. 160
Kriging
Inverse Distance Cross Section ( Adindan ) Local Polynomial
Minimum Distance
Nearest Neighbor
Natural Neighbor
Figure ( 3 – 18 ) : Comparison between the cross sections made from contour maps created by different griding methods and the field survey data for the same section
87
Suface Area of Lake Nasser Againist Water Level calculated from Local Polynomial Method
Surface Area "Km2"
7000 6500
y = 22.296e0.0311x R2 = 0.9985
local polynomial
6000
Expon. (local polynomial)
5500 5000 4500 4000 3500 3000 155
160
165
170
175
180
185
Water Level "m"
Figure (3 – 19): The relation between the surface area of Lake Nasser and the water levels upstream HAD
From figures (3-17) and (3-18), it can be concluded that the most suitable griding method for lake Nasser is ( Local Polynomial ).
Figure (3-19) shows the relation between the surface area and water level and the trend line. This relation can be represented by the following exponential equation:
A = 22.296 e 0.0311 ( WL ) R2 = 0.9985
Equ.(3.4)
Where A
: surface area of Lake Nasser (km2)
WL
: average annual water level of lake Nasser (m)
88
This equation I valid only in the water level range from 158m to 182m and not applicable for the others.
The surface area of Lake Nasser for different water levels computed by this study are compared to the corresponding values of remote sensing techniques as well as to that resulted from (1)Abou El Ata in 1970. Table (3 – 11) and Figure (3 – 20) show the results of this comparison. The difference between the two equations is lies between ( -3 % to 10 % )
Table (3 – 11): The results of the two equations of calculating the surface area of Lake Nasser from Remote Sensing Equation and Abu El-Ata equation Water Level (m)
158 160 162 164 166 168 170 172 174 176 178 180 182
Water Surface Area in km2 Abou El Ata
Remote Sensing
Equation
Equation ( Equ. 3.1 )
2735 2950 3102 3454 3726 4016 4308 4652 4996 5358 5738 6118 6540
3036 3231 3438 3658 3893 4143 4409 4692 4993 5314 5655 6017 6404
89
Comparison between the results of Remote Sensing Equation and Abo El Ata Equation 7000 6500
2
Surface Area "km "
6000 5500 5000
Abo El Ata Remote Sensing
4500 4000 3500 3000 2500 2000 155
160
165
170
175
180
185
Water Level "m"
Figure (3 – 20): The comparison between the results of surface area equations
90
CHAPTER ( IV ) COMPUTATION OF EVAPORATION LOSSES This chapter highlights the most common methods and procedures used to estimate the evaporation losses. Some of these procedures depend on theoretical analyses others depends on formulae based on atmospheric elements. However, the application of each method is based on the lake surface area and the availability of data. Some of these methods will be presented hereafter and are applied to compute the amount of water lost by evaporation from Lake Nasser.
4.1. Methods of Computations:
In this study, four methods will be used to estimate evaporation rate.
4.1.1. Method (I) Evaporation Pan:
After (52)Varshney R.S. ( 1977 ), evaporation has been measured by a diverse assortment of instruments and methods. Some of the smaller instruments that have been used are the Piche evaporimeter, the evaporation scale of H Wild and porous clay bulbs of various designs, called atmometers.
All these
instruments measure evaporation from very small amounts of water, micro-scopic when compared to volumes considered in engineering hydrology. 91
This method is available in Egypt. but there is one gauge in Aswan metrological station. The coefficient of this gauge is between ( 0.55 – 0.80 ). It means that there is an error in reading with about ( ± 25 % ). Figure ( 4 – 1 ) shows two types of Class A Pan gauges.
Figure ( 4 – 1 ) : Two different types of Class A Pan
92
4.1.2. Method (II) Bulk Aerodynamic 4.1.2. Method (II) Bulk Aerodynamic: After (25)Makary A.Z.( 2000 ), the aerodynamic evaporation estimation approach, was applied through the evaporation studies at lake Hefner (51)U. S. Geological Survey, (1952), and supported by investigations at lake Mead (16)Harbeck, G.E., (1958), lake Eucumbene and other lakes in Australia (54)Webb, (1960), and (21)Hoy et. al., (1977):
E = N U ( es – ed )
Equ.(4.1)
Where: E
: evaporation ( mm/day )
N
: constant equals 0.1296
U
: wind velocity at height 2m above water ( m/sec ).
es
: saturated vapor pressure at water temperature ( Hectopascal )
ed
: vapor pressure of air 2m above water ( Hectopascal ).
For conversion for other latitudes and nontemprate regions, the value of the coefficient should be modified inversely with the average
absolute
temperature
(Web,
1965).
Taking
into
consideration the values of average air temperature at lake Nasser it was found that the appropriate coefficient equals to 0.126 (32)(Omar, M.H., 1981).
93
4.1.3 Method (III) Modified Bulk Aerodynamic
This method represents the bulk Aerodynamic method with some modifications added by the Russian. These modifications can be expressed as follows:
E = 0.13 ( 1 + 0.7 U2 ) ( ea – ed )
Equ.(4.2)
Where: E
: evaporation rate ( mm/day )
U2
: wind velocity 2m above water ( m/sec ).
ea
: saturated vapor pressure at air temperature ( Hectopascal )
ed
: vapor pressure in air 2m above water ( Hectopascal ).
The main difference between this method and the previous one is that this method always gives a value for evaporation even at the case of air velocity equals to Zero.
4.1.4 Method (IV) Penman Method :
(33)Penman (1948) presented a theory and a formula for the estimation of evaporation from weather data, which allows to compute the evaporation from a free water surface using readily available standard meteorological data only. 94
Rn E a E 1
Equ.(4.3)
Where : E
: evaporation rate (mm/day)
Rn
: solar balance for water surface
Rn
: Rns – Rnlg
Rns
: short wave radiation. = RG ( 1 – α )
RG
: short wave radiation actually received at the earth from sun and sky.
α
: reflection coefficient = 0.04 to 0.09
Rnlg
: long wave radiation.
n Rn lg Tk4 0.56 0.092 ed 0.1 0.9 Equ.(4.4) N
Where: σ
: Stephan – Boltzman constant
Tk
: absolute air temperature ( Kelven )
ed
: actual air vapor pressure 2m above water
n
: actual Number of hours of sunshine ( hours/day )
N
: possible Number of hours of sunshine ( hours/day )
Δ
: de / dT Rate of change of vapor pressure against air temperature
γ
: Constant = 0.67 95
Ea
: heat available for evaporation from open water
Ea = 0.35 ( 0.5 + 0.01 U2 ) ( ea – ed )
Equ.(4.5)
Where U2
: wind velocity 2m above water ( mile/day ).
ea
: saturated vapor pressure at air temperature ( Hectopascal )
ed
= Vapor pressure in air 2m above water ( Hectopascal ).
This method is considered to be the best method in estimating the evaporation losses because it take into consideration the energy budget method and the bulk aerodynamic method. The result of this method is in good accordance with the evaporation gauge method. Since 1948 some constants of this formula were modified to be suitable for different weather conditions.
Most of these modifications were made for the long wave radiation ( Rnlg ) and also for the wind velocity in the term ( Ea ).
For the term ( Ea ) It was considered to be:
Ea = 0.35 ( 0.5 + 0.01 U2 ) ( ea – ed )
New it is reformed as : 96
Equ.(4.6)
Ea = 0.26 ( 0.5 + 0.7 U2 ) ( ea – ed )
Equ.(4.7)
Taking into consideration that the velocity unit is ( m/sec )
For the term Rnlg It was considered to be:
Rn lg 0.56 0.0912 ed
Equ.(4.8)
New it is reformed to be:
Rn lg 0.56 0.079 ed
Equ.(4.9)
In (9) El. Bakry, M.M., (1983) estimated the net solar radiation in lake Nasser and it was found that Soinbak 1963 equation is the suitable equation to estimate the long wave radiation as follows :
Where the value of Rnlg was taken as
n Rn lg Tk4 0.56 0.092 ed 0.1 0.9 N
Equ.(4.4)
but now it is considered to be as:
n Rn lg 352.8 0.195Tk4 0.1 0.9 / 59 N
: permeability coefficient of water surface = 0.97 97
Equ.(4.10)
Then the final Penman equation becomes
Rn E a E 1
Equ.(4.3)
n 352.8 0.195Tk4 0.1 0.9 N Rn 1 RG 59
Equ.(4.11)
Ea 0.260.5 0.7U 2 ea ed
Equ.(4.7)
Table (4 – 1) contains the calculations of evaporation for the two stations Aswan and Abo Simble according to the four mentioned methods and the available data.
98
Table (4 – 1): The calculated evaporation rate ( mm/day ) for Aswan and Abo Simble stations using the four methods
Method Jan. Feb. March April May June July Aug. Sep. Oct. Nov. Dec. Annual Average
I There is no Pan gauge in this station
II 5.19 5.45 9.11 12.5 16.25 18.83 15.07 16.73 17.01 15.42 9.23 6.48 12.27
III 5.04 5.58 9.02 12.68 16.22 18.79 16.04 17.12 16.84 14.69 8.79 6.14 12.24
IV 5.38 6.23 8.74 10.57 11.86 12.83 11.66 11.81 11.26 10 7.3 5.79 9.45
Abo Simbel Station – ( Station Code = 62419 ) , ( Station position : Lat. 22 º 22’ – Long. 31 º 36’ – Altitude = 187.00m ) Method Jan. Feb. March April May June July Aug. Sep. Oct. Nov. Dec. Annual Average
I 5.2 6.6 8.65 10.5 12.35 13.65 13 12.45 11.65 10.1 7.2 5.65
II 5.25 6.76 10.34 13.75 16.35 19.77 18.02 16.76 15.32 12.16 7.39 5.57
III 5.27 6.83 10.26 13.88 16.71 20.09 18.65 17.49 15.75 12.52 7.56 5.59
IV 5.43 6.92 9.15 10.97 11.86 13.16 12.65 11.94 10.7 9.02 6.56 5.31
9.75
12.29
12.55
9.47
Aswan Station – ( Station Code = 62414 ) , ( Station position : Lat. 23 º 58’ – Long. 32 º 47’ – Altitude = 192.70m ) 99
Calculated Evaporation Acording to the different methods at ( Abo Simble Station )
Evaporation ( mm / day )
25 Method ( II )
20
Method ( III ) Method ( IV )
15 10 5
ec . D
ov . N
ct . O
Se p.
Au g.
Ju ly
Ju ne
ay M
Ap ril
Fe b. M ar ch
Ja n.
0
Months
Figure (4 – 2): The calculated evaporation at Abo simble station using the different methods Calculated Evaporation Acording to the different methods at ( Aswan Station )
Evaporation ( mm/day )
25
Method ( I ) Method ( II )
20
Method ( III ) Method ( IV )
15 10 5
Ju ly Au g. Se p. O ct . N ov . D ec .
Ju ne
il M ay
Ap r
ch
b.
M ar
Fe
Ja n.
0 Months
Figure (4 – 3): The calculated evaporation according to the different methods at Aswan station 100
Figure (4 – 2) and (4 – 3) show the result of evaporation calculations using the four methods at Abo Simble and Aswan stations. It is clear that the four methods give very close results in the months experiencing low temperature ( November, December , January and February ), but for the rest of the year the results of methods ( I and IV ) are very close to each other and the results of methods ( II and III ) show good agreement together but are higher than the other two methods ( I and IV ).
4.2. New Collected Data to Estimate the Evaporation Losses
To enhance the estimation of evaporation and reach more accurate results about the amount of water lost by evaporation, a recent data were collected with the help of the High Aswan Dam Authority and under their supervision and responsibility for the six metrological stations in lake Nasser. This data is the average monthly rate of evaporation from the different stations as follows, tables from (4 – 2) to (4 – 6) illustrate these data.
101
Table (4 – 2): Average monthly evaporation rate calculated from the floating station at Abo Simble ( mm/day ) Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Average
Jan. ------------3.36 4.52 4.47 --------5.00 5.67 4.60
Feb. ----3.87 ------4.56 2.97 4.37 --------5.46 5.91 4.52
March --3.03 6.14 ------3.99 4.20 3.96 --------6.25 6.38 4.85
April --4.25 --------6.23 4.16 4.96 --------8.06 6.06 5.62
May --3.19 --------6.68 5.33 6.07 7.00 4.57 7.32 --9.30 7.07 6.28
June --5.60 --10.26 ----6.91 6.61 6.86 5.88 5.04 7.16 --11.04 --7.30
Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Average
July ----10.13 ------7.66 6.69 5.69 6.10 4.12 7.48 --9.40 --7.16
Aug. ----8.88 ------7.23 5.96 5.81 7.06 --7.64 --10.96 --7.65
Sep. ----9.74 ------6.97 6.75 5.00 6.00 --7.86 --10.67 --7.57 102
Oct. 6.20 --10.23 --6.25 --5.45 4.98 --7.73 --7.27 --10.06 --7.27
Nov. 6.29 --6.36 --2.96 6.91 7.25 5.96 ----4.48 ----7.47 --5.96
Dec. 5.07 5.31 4.81 ----6.28 5.41 4.84 ----5.78 --6.48 5.72 --5.52
Table ( 4 – 3 ) : Average monthly evaporation rate calculated from the floating station at North Allaqi Khore ( mm/day ) Year 1995 1996 1997 1998 1999 2000 Average
Jan. --6.01 ------3.87 4.94
Feb. 5.10 ------4.90 4.26 4.75
March --5.70 ----3.65 3.82 4.39
April 5.42 6.75 ----5.14 3.95 5.32
May 5.89 6.03 ----5.86 3.84 5.41
June 9.99 6.93 ----6.85 --7.92
Year 1995 1996 1997 1998 1999 2000 Average
July --7.40 ----6.23 --6.82
Aug. --6.28 ----7.46 --6.87
Sep. 10.48 5.01 ----6.74 --7.41
Oct. --4.44 --5.72 6.67 --5.61
Nov. --3.43 --5.30 6.24 --4.99
Dec. 7.34 3.11 ----4.99 --5.15
103
Table (4 – 4): Average monthly evaporation rate calculated from the ( Old ) floating station at Aswan ( mm/day ) Year 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 Average
Jan. --5.10 4.33 6.46 5.35 5.84 5.67 6.25 4.20 4.73 6.06 5.23 --5.17 5.61 6.24 5.52 5.45
Feb. --3.83 2.85 6.42 5.24 5.95 5.83 5.44 4.79 4.66 6.14 6.12 5.54 5.21 4.78 5.02 4.60 5.15
March --2.07 2.04 7.69 5.54 6.25 5.57 5.85 5.31 4.56 5.94 5.92 6.33 4.57 5.61 4.78 5.56 5.22
April --3.50 3.46 7.17 6.33 7.37 6.82 5.65 4.74 5.33 6.66 6.35 6.11 7.04 5.49 4.66 5.54 5.76
May --3.25 3.43 7.51 7.95 8.35 7.38 7.10 6.53 7.36 8.09 8.02 7.90 6.88 7.53 6.41 5.99 6.86
June 4.78 3.60 5.43 7.36 7.36 8.81 8.39 8.03 7.23 7.89 9.04 10.11 7.90 9.33 9.30 8.85 8.86 7.50
Year 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 Average
July 5.69 5.72 5.58 8.74 8.74 9.91 9.69 9.55 8.68 9.15 10.07 9.83 9.80 9.68 10.05 8.96 6.19 8.26
Aug. 6.46 5.32 7.50 10.72 10.72 10.43 9.46 9.54 8.70 9.59 10.01 10.42 11.71 9.91 9.95 8.98 9.16 8.95
Sep. 6.38 7.23 1.41 11.36 11.02 10.40 10.49 9.42 9.32 9.35 10.50 10.95 11.75 10.61 12.14 10.31 7.18 9.03
Oct. 5.34 5.19 9.39 10.20 8.73 8.47 8.94 8.10 7.24 8.87 8.76 10.71 10.81 10.89 10.38 9.42 6.92 8.41
Nov. 6.22 4.32 8.45 7.15 7.65 7.37 7.32 7.59 6.51 6.72 6.76 5.74 8.75 8.12 8.34 6.95 6.11 6.70
Dec. 5.23 4.13 6.59 7.06 6.08 6.49 6.52 5.26 5.43 6.26 5.97 10.71 6.79 6.88 6.53 5.76 5.23 5.98
104
Table (4 – 5): Average monthly evaporation rate calculated from the ( New ) floating station at Aswan ( mm/day ) Year 1995 1996 1997 1998 1999 2000 Average
Jan. 3.00 5.38 4.86 4.29 5.79 5.13 4.74
Feb. 4.29 --5.71 4.57 6.24 5.66 5.29
March 5.68 4.93 4.93 5.78 5.34 6.47 5.52
April 6.50 7.17 6.43 7.11 6.56 6.20 6.66
May 9.70 8.12 6.90 8.02 7.13 8.00 7.98
June --9.02 8.50 9.76 8.16 9.66 9.02
Year 1995 1996 1997 1998 1999 2000 Average
July --9.63 --10.10 8.67 11.89 10.07
Aug. --11.26 --11.11 10.39 --10.92
Sep. --10.56 --10.53 10.08 --10.39
Oct. --9.65 9.49 9.63 10.13 --9.73
Nov. --5.40 5.44 6.64 7.30 --6.20
Dec. 7.17 5.30 5.18 7.12 5.63 --6.08
Table (4 – 6): Average monthly evaporation rate calculated from the floating station at Wadi El Arab ( mm/day ) Year 1999 2000 Average
Jan. --5.33 5.33
Feb. --5.28 5.28
March --5.78 5.78
April --6.00 6.00
May --8.06 8.06
June -------
Year 1999 2000 Average
July -------
Aug. -------
Sep. -------
Oct. -------
Nov. -------
Dec. 4.40 --4.40
105
4.3. Calculating Water Volume Lost by Evaporation
Using the available data the monthly evaporation rate for each station are calculated. Table (4 – 7) shows the evaporation rate. Some modifications must be made for table (4 – 7) to have an average monthly for each station. This modifications are for station Aswan ( Old ) and Aswan ( New ), the average will be calculate for these two stations. For station ( Wadi El Arab ) there are few readings and it can not be taken into consideration. The average monthly of this station will thus be obtained from the average of the two adjacent stations ( Allaqi Khore and Abo Simble ).
Table (4 – 7) will consequently be modified to table (4 – 8).
106
Table (4 – 7): The average monthly evaporation rate for each station ( mm / day ) Aswan Aswan Allaqi Wadi El Abo Station ( Old ) ( New ) Khore Arab Simble km From 2 2 75 170 230 HAD Jan. 5.45 4.74 4.94 5.33 4.6 Feb. 5.15 5.29 4.75 5.28 4.52 March 5.22 5.52 4.39 5.78 4.85 April 5.76 6.66 5.32 6 5.62 May 6.86 7.98 5.41 8.06 6.28 June 7.5 9.02 7.92 --7.3 July 8.26 10.07 6.82 --7.16 Aug. 8.95 10.92 6.87 --7.65 Sep. 9.03 10.39 7.41 --7.57 Oct. 8.41 9.73 5.61 --7.27 Nov. 6.7 6.2 4.99 --5.96 Dec. 5.98 6.08 5.15 4.4 5.52
Table (4 – 8): Modified average monthly evaporation rate for each station ( mm / day ) Allaqi Wadi El Abo Station Aswan Khore Arab Simble km from 2 75 170 230 HAD Jan. 5.1 4.94 4.77 4.6 Feb. 5.22 4.75 4.64 4.52 March 5.37 4.39 4.62 4.85 April 6.21 5.32 5.47 5.62 May 7.42 5.41 5.85 6.28 June 8.26 7.92 7.61 7.3 July 9.17 6.82 6.99 7.16 Aug. 9.94 6.87 7.26 7.65 Sep. 9.71 7.41 7.49 7.57 Oct. 9.07 5.61 6.44 7.27 Nov. 6.45 4.99 5.48 5.96 Dec. 6.03 5.15 5.34 5.52 107
The volume of water lost by evaporation will be calculated by using the three following methods:
4.3.1. First - Yearly Average of Evaporation Rate
In this method the yearly average of the evaporation rate will be calculated from the monthly average of each station and the average of the twelve months is then computed. At the end, one value of the average daily rate of evaporation will be obtained. Table (4 – 9) shows the calculation of the yearly average. Table (4 – 9): Calculation of the yearly average of the evaporation rate ( mm / day ) Station Jan. Feb. March April May June July Aug. Sep. Oct. Nov. Dec. Average
Aswan 5.1 5.22 5.37 6.21 7.42 8.26 9.17 9.94 9.71 9.07 6.45 6.03 7.33
Allaqi Khore 4.94 4.75 4.39 5.32 5.41 7.92 6.82 6.87 7.41 5.61 4.99 5.15 5.8
Wadi El Arab 4.77 4.64 4.62 5.47 5.85 7.61 6.99 7.26 7.49 6.44 5.48 5.34 6
108
Abo Simble 4.6 4.52 4.85 5.62 6.28 7.3 7.16 7.65 7.57 7.27 5.96 5.52 6.19
Yearly Average evaporation rate ( mm / day ) 6.33
From table (4 – 9) it can be concluded that the yearly average of the daily evaporation rate is:
E = 6.33 mm/day
By using the data of Lake Nasser area calculated in chapter (III), the equation ( Equ. 3.4 ) can be used to calculate the volume of water lost by evaporation.
The annual volume of water lost by evaporation can be calculated from the following equation:
V = E x A x 365 / 1000000
Equ.(4.12)
Where
V
: annual volume of water ( milliard m3 / year )
E
: evaporation rate ( mm / day )
A
: surface area of lake Nasser (km2) calculated from (Equ. 3.4)
4.3.2. Second - Monthly Average of the Evaporation Rate
In this method, the monthly average will be used in the calculation in stead of the using the yearly average of evaporation rate.
109
From table (4 – 8) the monthly average can be calculated from the average of each station as shown in table (4 – 10). Table (4 – 10): The average monthly evaporation rate (mm / day) Allaqi Wadi El Abo Station Aswan Khore Arab Simble Average Jan. 5.1 4.94 4.77 4.6 4.85 Feb. 5.22 4.75 4.64 4.52 4.78 March 5.37 4.39 4.62 4.85 4.81 April 6.21 5.32 5.47 5.62 5.66 May 7.42 5.41 5.85 6.28 6.24 June 8.26 7.92 7.61 7.3 7.77 July 9.17 6.82 6.99 7.16 7.53 Aug. 9.94 6.87 7.26 7.65 7.93 Sep. 9.71 7.41 7.49 7.57 8.05 Oct. 9.07 5.61 6.44 7.27 7.1 Nov. 6.45 4.99 5.48 5.96 5.72 Dec. 6.03 5.15 5.34 5.52 5.51 By using the calculated area of lake Nasser which is indicated in chapter (3), the volume of the water lost by evaporation can be calculated for each water level. By using the average monthly evaporation rate, the annual volume of water lost by evaporation can be calculated as follows: 1
V A Em n / 1000000
Equ.(4.13)
12
where V
: annual volume of water ( milliard m3 / year )
Em
: average monthly Evaporation rate ( mm / day )
n
: No. of days for each month.
A
: surface area of Lake Nasser (km2) calculated from equation A = 22.296 e 0.0311 ( WL )
(WL) : average monthly water level.
110
Equ.(3.4)
4.3.3. Third - Monthly average evaporation rate for each station
In this method, the monthly average evaporation rate of each station individually will be used. Each station will indicate to the effectiveness of the area of the lake according to the available number of stations. The area of the lake can be divided into four areas according to the locations and position of each station. Figure (4 – 4) shows the four divided parts and the location of the station in each part.
Figure (4 – 4): The division of the lake into four parts according to the location of each station 111
By the help of the satellite images, contour lines are developed for the four divided areas of the lake. A special software was used to achieve this requirements. These contour lines are utilized to calculate the surface area corresponding to any desired water level as shown in figures (4 – 5) to (4 – 12) and the values of areas are shown in tables (4 – 11) to (4 – 14).
112
Figure (4 – 5): Part ( I ) of lake Nasser served by Aswan Station Table (4 – 11): Surface area of part ( I ) of lake Nasser for each water level
Water Level (m)
Surface Area ( km 2 )
158.40 160.00 162.00 164.00 166.00 168.00 170.00 172.00 174.00 176.00 178.00 180.00 181.22
254.9146 287.0241 314.8304 334.0151 349.4963 363.2433 377.0078 391.5792 407.8157 425.4659 447.2648 489.789 521.8131
113
Surface area of Part I of lake nasser for different water levels 550 Part I ( Calculated )
Surface Area "km 2"
500
y = 4.1438e
0.0265x
2
Expon. (Part I ( Calculated ))
R = 0.9699
450 400 350 300 250 200 155
160
165
170
175
180
185
Water Level "m"
Figure (4 – 6): The surface area of Part I of Lake Nasser for different water levels
Ap1 = 4.1438 e 0.0265 ( WL )
Equ.(4.14)
Where Ap1
: surface area of Part I of Lake Nasser (km2)
WL
: average monthly water level of Lake Nasser (m)
V p1 Ap1 Em n / 1000000 1
Equ.(4.15)
12
Where Vp1
: annual volume of water from part I(Milliard m3 / year)
Em
: average monthly evaporation rate for Aswan Station (mm / day)
Ap1
: aurface area of part I of lake Nasser (km2)
n
: No. of days for each month.
114
Figure (4 – 7): Part ( II ) of lake Nasser served by Allaqi station Table (4 – 12): Surface area of lake Nasser for each water level ( part II) Water Level (m) Surface Area ( km 2 ) 158.40 1206.146 160.00 1302.43 162.00 1408.954 164.00 1493.204 166.00 1571.021 168.00 1647.885 170.00 1724.549 172.00 1813.436 174.00 1899.923 176.00 1993.763 178.00 2104.787 180.00 2243.814 181.22 2498.306 115
Surface area of Part II of lake nasser for different water levels 2600
Surface Area "km 2"
2400 2200
y = 14.659e0.0281x R2 = 0.9865
Part II ( Calculated ) Expon. (Part II ( Calculated ))
2000 1800 1600 1400 1200 1000 155
160
165
170
175
180
185
Water Level "m"
Figure (4 – 8): The surface area of (Part II) of Lake Nasser for different water levels
Ap2 = 14.659 e 0.0281 ( WL )
Equ.(4.16)
Where Ap2
: surface area of Part II of lake Nasser (Km2)
WL
: average monthly water level of lake Nasser (m)
V p 2 Ap 2 E m n / 1000000 1
Equ.(4.17)
12
Where Vp2
: annual volume of water from part II (Milliard m3/ year)
Em
: average monthly evaporation rate for Allaqi Station (mm/ day)
Ap2
: surface area of part II of lake Nasser (Km2)
n
: No. of days for each month.
116
Figure (4 – 9): Part ( III ) of lake Nasser served by Wadi El Arab station Table (4 – 13): Surface area of lake Nasser for each water level (part III)
Water Level (m)
Surface Area ( km 2 )
158.40 160.00 162.00 164.00 166.00 168.00 170.00 172.00 174.00 176.00 178.00 180.00 181.22
552.728 565.6348 577.6928 617.1549 658.2391 693.8013 725.6183 781.9388 831.1638 883.4488 951.5003 1016.326 1072.334
117
Surface area of Part III of lake nasser for different water levels 1200 y = 4.8708e0.0296x R2 = 0.9915
Part III
1100
Surface Area "km 2"
Expon. (Part III) 1000 900 800 700 600 500 400 155
160
165
170
175
180
185
Water Level "m"
Figure (4 – 10): The surface area of (Part III) of Lake Nasser for different water levels
Ap3 = 4.8708 e 0.0296 ( WL )
Equ.(4.18)
Where Ap3
: surface area of Part III of lake Nasser (Km2)
WL
: average monthly water level of lake Nasser (m)
V p 3 Ap 3 E m n / 1000000 1
Equ.(4.19)
12
Where Vp3
: annual volume of water from part III (Milliard m3 / year)
Em
: average monthly evaporation rate for Wadi El Arab Station (mm / day)
Ap3
: surface area of part III of lake Nasser (Km2)
n
: No. of days for each month.
118
Figure (4 – 11): Part (IV) of lake Nasser served by Abo Simble station Table (4 – 14): Surface area of lake Nasser for different water level (part IV)
Water Level (m)
Surface Area ( km 2 )
158.40 160.00 162.00 164.00 166.00 168.00 170.00 172.00 174.00 176.00 178.00 180.00 181.22
1082.799 1089.799 1159.247 1215.917 1326.432 1433.458 1576.782 1702.425 1798.574 1934.416 2100.613 2196.008 2273.328
119
Surface area of Part IV of lake nasser for different water levels 2400
Surface Area "km 2"
2200
y = 3.9948e0.0351x R2 = 0.9939
Part IV Expon. (Part IV)
2000 1800 1600 1400 1200 1000 155
160
165
170
175
180
185
Water Level "m"
Figure (4 – 12): The surface area of (Part IV) of Lake Nasser for different water levels
Ap4 = 3.9948 e 0.0351 ( WL )
Equ.(4.20)
Where Ap4
: surface area of Part IV of lake Nasser (km2)
WL
: average monthly water level of lake Nasser (m)
V p 4 Ap 4 E m n / 1000000 1
Equ.(4.21)
12
Where Vp4
: annual volume of water from part IV (milliard m3/ year)
Em
: average monthly evaporation rate for Abo Simble station (mm/ day)
Ap4
: surface area of part IV of lake Nasser (km2)
n
: No. of days for each month. 120
The annual volume of water lost by evaporation for the entire area of the lake will be obtained from the summation of the four calculation representing the four parts as follows:
V = Vp1 + Vp2 + Vp3 + Vp4
Equ.(4.22)
To make a comparison of the three methods of calculations a data from Nile Research Institute for the daily water levels upstream HAD for the years (1987 – 1995 - 2000) will be analyzed with the average monthly evaporation daily rate to reach the volume of water lost annually.
Tables (3 - 6), (3 – 7) and (3 – 8), from the previous chapter, show the daily water level and the average monthly water level for the years 1987,1995 and 2000 upstream High Aswan Dam respectively.
Calculating the water volume lost by evaporation by the three methods mentioned before for the year 2000.
First Method:
WL ( Average ) = 178.89 m V = 13.43 milliard m3
121
179.98 179.29 178.65 178.01 177.02
176.06 176.58 179.15 180.32 180.6 180.36
Average Evaporati on Rate
4.78 4.81 5.66 6.24 7.77
7.53 7.93 8.05 7.10 5.72 5.51
July Aug. Sep. Oct. Nov. Dec.
180.6
Feb. March April May Jun
Average WL
4.85
Month
Jan.
Second Method:
V = 13.37 milliard m3
Third Method: Vp1 = 1.26 Milliard m3 Vp2 = 4.70 Milliard m3 Vp3 = 2.11 Milliard m3 Vp4 = 4.79 Milliard m3 V total = 12.86 milliard m3
122
Calculating the water volume lost by evaporation by the three methods mentioned before for the year 1995.
First Method: WL ( Average ) = 175.22 m V = 11.98 milliard m3
176.86
176.52 176.02 175.38 174.78 173.8 172.66 173.03 175.37 176.19 176.1 175.93
Average Evaporati on Rate
4.78 4.81 5.66 6.24 7.77 7.53 7.93 8.05 7.10 5.72 5.51
Feb. March April May Jun July Aug. Sep. Oct. Nov. Dec.
Average WL
4.85
Month
Jan.
Second Method :
V = 11.93 milliard m3
Third Method: Vp1= 1.14 Milliard m3 Vp2= 4.24 Milliard m3 Vp3= 1.89 Milliard m3 Vp4= 4.21 Milliard m3 V total = 11.38 Milliard m3
123
Calculating the water volume lost by evaporation by the three methods mentioned before for the year 1987.
First Method: WL ( Average ) = 158.14 m V = 7.04 milliard m3
179.98 179.29 178.65 178.01 177.02
176.06 176.58 179.15 180.32 180.6 180.36
Average Evaporati on Rate
4.78 4.81 5.66 6.24 7.77
7.53 7.93 8.05 7.10 5.72 5.51
July Aug. Sep. Oct. Nov. Dec.
180.6
Feb. March April May Jun
Average WL
4.85
Month
Jan.
Second Method:
V = 6.99 milliard m3
Third Method: Vp1= 0.72 Milliard m3 Vp2= 2.62 Milliard m3 Vp3= 1.14 Milliard m3 Vp4= 2.30 Milliard m3
V total = 6.78 milliard m3 124
Table (4 – 15): Comparison between the three methods of calculating the evaporation losses Year
Average
First
Second
Third
WL(m)
milliard m3
milliard m3
milliard m3
2000
178.89
13.43
13.37
12.86
1995
175.22
11.98
11.93
11.38
1987
158.14
7.04
6.99
6.78
Comparison Between the Three Methods of Calculating the Evaporation Losses 14
Losses (milliard m3)
13 12 11
First Method Second Method
10
Third Method
9 8 7 6 2000
1995
1987
Year
Figure (4 – 13) : Comparison between the three methods of calculating evaporation losses for different years
125
It can be concluded from the previous computations, table (4 – 15) and figure (4 – 13) that the three years give resemble trend. This proves that the procedure of computing the average rate of evaporation resulted from the metrological information at each station is considered the most effective parameter in computing the evaporation losses. This result is very clear in the third method which indicate dividing the surface area of the lake to many parts and each part related to the nearest metrological station. This procedure raises the point that the area of effectiveness for each station should be studied and defined. That means that the defined area of effectiveness should experience similar metrological information. However, this type of study may hoist the issue that many other metrological stations should be implemented in the lake area.
126
CHAPTER (V)
SUGGESTIONS FOR DECREASING EVAPORATION LOSSES IN LAKE NASSER The main objective of this study is to estimate accurately the amount of water lost by evaporation from Lake Nasser and to suggest to decrease these losses as possible. This chapter discuss proposals, that were introduced before by some researchers in the Ministry of Water Resources and Irrigation, to decrease these losses and apply the remote sensing technique to improve the visibility of these proposals.
5.1. Methods to Decrease Evaporation Losses from Lake Nasser:
Many alternatives were introduced to decrease the evaporation losses. Some of these alternatives are related to the dam operating rules, others apply the usage of specific crops to minimize evaporation. On the other hand, the closure of the secondary channel might also be a solution.
5.1.1. Decreasing the Evaporation Losses by Changing the Upstream Levels of the HAD
The idea of decreasing the evaporation losses by changing the upstream levels of the HAD was made by Prof. Dr. Mohamed 127
Mahmoud Gaser the head of Hydraulic Research Institute. By using the remote sensing equation the amount of water saved by this method will be defined. The average annual water budget is about 84 milliard m3 and the maximum annual water budget (about 150 milliard m3) was recorded in year 1886 – 1887 at Aswan. On the other hand, the minimum annual water budget (about 42 Milliard m3) was recorded in year 1913 – 1914 at Aswan. Figure (5 – 1) shows the annual water budget at Aswan from year 1870 to 1995. 160
140
Income milliard m3
120
100
80
60
40
1870-1871
1895-1896
1920-1921 1945-1946 Water Years
1970-1971
1995-1996
Figure (5 – 1): Incoming annual water budget
The HAD is built to protect Egypt from flood, it was partially commissioned in 1964. The general rules that managed the water level upstream HAD can be summarized as follows: 128
The water level upstream HAD can not exceed 182 m for the safety purposes of the HAD.
The water level upstream HAD must be 175 m in the beginning of the water year ( 1st August ).
The water level upstream HAD can not be less than 147 m to ensure the operation of the electric turbines.
These rules have been applied since the dam commission. According to these rules, the historical storage observations upstream the dam can be concluded as follows:
In the period 1968 to 1978 the water enter the reservoir for the first time. As a result, the losses due to the seepage were very large and the maximum water level upstream HAD did not exceed (174 m).
The period 1978 to 1988 represents low flood period. As a result, the storage capacity of lake Nasser was minimum. The recorded capacity for that period was about 130 milliard m3. About 70 milliard m3 were withdrawn to complete the yearly requirements and compensate the low flood income.
The period 1988 to 1998, is considered high flood period. The lake was full for the first time since dam commission.
The period 1998 – 1999 and 1999 – 2000 high floods were received and at the same time the lake was full. This resulted extra releases downstream the dam. These extra releases cause many problems to the downstream encroachments around the 129
river banks and in the flood plain areas. As a way of management, many thoughts were asserted to think about minor changes in the dam operational rules specially the water level in the upstream direction at the beginning of each water year. It was meant by that to maximize the benefit of the HAD and to minimize the losses of water due to evaporation.
This should be considered to permit less or more water levels upstream HAD at the beginning of the water year. The decrease or increase of the water levels will be achieved according to the yearly coming flood and the lake storage situation. The decrease of the water level upstream the dam will decrease the water surface area of the lake which is a direct function of evaporation losses.
On the other hand the increase of the water level
upstream will permit more storage in the lake and at the same time no extra releases have to be done.
At the downstream as this study focuses on the evaporation reduction, the only management to be discussed here is the reduction of the water level upstream the HAD. Figure (5 – 2) is a thematic diagram that shows the current situation of water level management.
130
3
WL ( 182.00 ) [ Emergancy water level ]{ 130 milliard m } WL ( 175.00 ) [ 1st August ] { 121.3 milliard m3} Life Storage 3
WL ( 147.00 ) [ Electric Turbine ] {31.6 milliard m} Dead Storage
Figure (5 – 2): The current situation of water level management
The proposed reduction of the water levels will be through different stages as follows: -
lower the water level at the beginning of the water year (1st August ) from 175m to 173m or 170m.
-
The level of the dead storage capacity must be decreased also from 147m to 144m to keep the life storage capacity without changing,. Taking into consideration that the amount of sediment will be decreased by the construction of ( Roseras Dam ) and ( Khashm El Kerba Dam ) in Sudan . Figure (5 – 3) is a thematic diagram that shows how to lower the water level upstream HAD.
131
WL ( 182.00 ) [ Emergancy water level ] { 130 Milliard m3 } WL ( 170.00 - 173.00 ) [ 1st August ] { 97.6 - 111.1 Milliard m3 } Life Storage WL ( 144.00 )
{ 25.3 Milliard m3 }
Dead Storage
Figure (5 – 3): The suggestion of lowering the water level upstream HAD
5.1.1.1 The advantages of changing the upstream levels of the HAD:
From lowering the water level upstream HAD the following will occur:
a - Evaporation will be reduced By using the equation Equ.(4.12) given in chapter 4 to calculate the annual evaporation losses, the evaporation was calculated for a medium flood year (2000) and the losses were: Vtotal = 12.97 milliard m3
By decreasing the water level upstream HAD for the same year (2000) by 2 m during January, February, March, April, May, June and December and 3 m for the high water level months July, August, September, October and November, the evaporation losses can be calculated by the same equation: 132
Vtotal = 12.00 milliard m3
It can be concluded that the reduction of the water level upstream HAD will decrease the evaporation losses by about 1 Milliard m3 / year , it is about 8% of the total losses.
b - The amount of water transmitted to lake Nasser by seepage will increase:
The gain losses due to infeltration from lake nasser are due to the recharge to and discharge from the Nubian Sandstone. They consist of a through flow to the regional ground water system and local bank storage that absorbs water when the reservoir level rises and the return of water when the level drops (39)Sadek Nahla ( 2002 ). An empirical equation by (60)WMP (1981) is used to estimate seepage losses and bank storage gain and losses, the equations describe seepage and bank storage changes:
S = 0.038 ( H – 110 )
Equ.(5.1)
dB = 0.60 dA ( H – 126 ) for rising stage
Equ.(5.2)
dB = -5.77 dA dH
Equ.(5.3)
for falling stage
where S
: monthly through flow to ground water ( 109 m3 )
H
: Water level upstream HAD (m)
dB
: change in bank storage ( 109 m3 ) 133
dA
: change in lake Area ( 109 m2 )
dH
: change in water level upstream HAD ( m )
By lowering the water level upstream HAD from 175 m to 173 m, the amount of water which comes to Lake Nasser by side seepage will increase from 280 Million m3 to 330 Million m3 and this amount reaches 480 Million m3 at level 170 m.
It can be concluded that this proposal will save annual amount of water about 1.5 milliard m3.
5.1.1.2. The disadvantages of changing the upstream Water Level at HAD:
The following are the disadvantages of lowering the water level upstream HAD:
In case of lowering the water level upstream HAD from 175 m to 173 m then to 170 m the life storage capacity will decrease from 90 milliard m3 to 80 milliard m3 at level 173 m and 66 milliard m3 at level 170 m.
In case of lowering the dead storage capacity level from 147 m to 144 m the electric turbines will not function because the designed water level of the operation is 147m.
134
It can be thus concluded that decreasing the evaporation losses by lowering the water levels (to change the dam operational rules) can give reasonable
results by using different scenarios and combinations
between increase and decrease the water level upstream HAD along the water year to reach the optimum solution.
5.1.2. Decreasing the Evaporation Losses by Cultivating Special Crops on the Lake Surface:
Rice is a crop that consumes a lot of water. Therefore it is suggested to use part of the lake area in cultivating rice. This will be very useful in decreasing the amount of water lost by evaporation
5.1.2.1. Environmental Requirements for Rice Cultivation
Rice is one of the crops that grow in water, other crops can not live in water because of oxygen absence. In case of rice, it can transfer oxygen to the roots, which are covered completely by water and the leaves.
Rice cultivation is widely spread all over the world because it can be cultivated between Latitude 40° N and 40° S. It can be cultivated either in humid or dry regions. The critical conditions for rice cultivation are the availability of large amount of water. Some kinds of rice need fresh water and another can grow at lower water qualities. The most suitable temperature for rice 135
growth is 20 °C at the early stage of the crop germination (90 – 150 days). The maximum temperature that can be accepted by the crop is between 37° C – 40 ° C in case of the water absence. This can happen only for a short period. 5.1.2.2. The Suitable Type of Soil for Cultivating Rice
The most suitable type of soil for cultivating rice is the heavy and dense soil which can keep water inside as long as possible. That means that the soil should contain over 70% of clay and silt in its content. The chemical condition of the soil is not important and can be replaced by artificial chemicals. The rice gives good results in a soil of pH value between 5.5 – 6 and gives a poor results if the soil has a pH value between 7 and 8 .
5.1.2.3. The Proposed Cultivation Plan
According to the previous conditions it is important to choose the suitable place and time to cultivate rice in the area of lake Nasser. There are 5 metrological stations measuring temperature along the lake Nasser. They are located at Aswan airport, 7 km North HAD, just downstream HAD, 1 km upstream HAD, North Abo Simble and at Abo Simble airport, respectively.
Tables ( 5 – 1 ) (a, b, c, d, and e) show the recorded air temperatures at the 5 stations.
136
Table (5 – 1): The average air temperatures recorded at the 5 metrological stations a – Aswan Airport Maximum Minimum Jan. Feb. March April May June July August Sep. Oct. Nov. Dec.
23.5 26.2 30.5 35.3 38.7 41.8 41.1 41 39.5 36.4 29.8 25
8.1 9.6 13 17.9 21.4 24.3 24.8 24.8 22.6 19.6 14.6 9.7
Daily Average
Night Average
Day Average
15.5 17.8 22 26.9 30.5 33.4 33.5 33.3 31.1 27.9 21.8 17
13 15.1 19.1 24 27.7 30.5 30.8 30.6 18.3 25.1 19.3 14.5
18 20.5 24.9 29.8 33.3 36.3 36.2 36 33.9 30.7 24.3 19.5
Night Average 15.1 19.7 27 29.6 31.6 31.6 31.5 29.4 24.6 19.5 14.5 14.5
Day Average 18.9 23.9 31.6 34.8 36.4 36.6 36.1 33.8 29.2 23.7 18.7 18.5
b – Downstream HAD Maximum Minimum Jan. Feb. March April May June July August Sep. Oct. Nov. Dec.
21.2 22.2 28.7 35.9 38.7 40.9 40.5 39.7 39 34.5 29.4 24.5
9.6 9.9 14.6 20.3 24.2 25.8 26.4 26.1 24.7 21.4 16.3 12.4
137
Daily Average 17 21.8 29.3 32.2 34 34.1 33.8 31.6 26.9 21.6 16.6 16.5
c –Upstream HAD Maximum Minimum Jan. Feb. March April May June July August Sep. Oct. Nov. Dec.
21.8 22.2 27.4 33.2 37 38.5 39 39.1 38.9 32.3 27.4 23.8
12.1 12.2 16.1 20.1 24 25.5 27.2 28 26.7 21.9 17.6 14.1
Daily Average 16.8 16.9 21.9 26.6 29.9 31.2 33.3 33.5 32.4 26.8 22.3 18.6
Night Average 15.2 15.3 20 24.5 27.8 29.1 31.4 31.6 30.4 25.1 20.7 17
Day Average 18.4 18.5 23.8 28.7 32 33.3 35.2 35.3 34.4 28.5 23.9 20.2
Night Average 14.9 15.4 19.9 24.5 27.5 28.8 31.3 31.8 30.2 24.6 20.5 17.2
Day Average 18.1 18.8 23.5 28.5 31.7 33.4 35.1 35.2 34 27.8 23.7 20.2
d – Abo Simble Maximum Minimum Jan. Feb. March April May June July August Sep. Oct. Nov. Dec.
21.4 22.2 28.2 33.2 36.7 39.2 39.6 39.4 38.5 31.5 27 23.4
11.7 12 17 21.1 23.9 24.9 27.9 29 26.9 21.5 17.4 14.3
138
Daily Average 16.5 17.1 21.7 26.5 29.6 31.1 33.2 33.5 32.1 26.2 22.1 18.7
e – Abo Simble Airport
Jan. Feb. March April May June July August Sep. Oct. Nov. Dec.
Maximum Minimum Daily Average 23 8.1 15.4 25.4 9.2 17.4 30.1 13.6 21.9 35.9 18.8 27.5 39.3 22.7 31.3 41.1 24.1 33 41.1 24.6 33.3 40.5 24.5 32.9 39.3 23.8 31.6 36.3 21.1 28.7 29.6 14.7 22.1 24.9 10.1 17.4
Night Average 13 14.7 19.2 24.7 28.6 30.2 30.6 30.3 29.1 26.2 19.7 15
Day Average 17.8 20.1 24.6 30.3 34 35.8 36 35.3 34.1 31.2 24.5 19.8
The stages of rice cultivation will be proposed as follows :
First stage: 30 days
Second stage: Soil preparation 20 days.
Third stage: First germination stage 20 days.
Forth stage: Second germination stage 30 days.
Fifth stage: Mid season stage 40 days.
Sixth stage: Final stage 30 days.
The most important stage is the fifth stage, the average temperature must not exceed 35° C and not less than 15° C. The suitable time for these conditions is from 10 September to 20 October.
139
Then the suggested time schedule for rice cultivation can be as follows:
First stage: From 20 June to 19 July
Second stage: From 1 July to 19 July.
Third stage: From 20 July to 9 August.
Forth stage: From 10 August to 9 September.
Fifth stage: From 10 September to 19 October.
Sixth stage: From 20 October to 19 November.
The crop production at 20 November.
For the suitable place selection, the rice cultivation can be started in the shallow khores, on the eastern side of the lake. The reason for this selection is to grantee the passage of air on the surface of the lake to be cooler.
Tables (5 – 2) to (5 - 5) show the water demand for the rice and the evaporation from the lake surface.
It can thus be concluded that the rice cultivation on part of the top surface of the lake is valuable. However, this proposal should be tested by selecting a small pilot area to apply the proposed plan. Also, a feasibility study to evaluate the cost- benefit analysis should be conducted. The impact of rice cultivation on the water quality of the lake should be investigated.
140
Soil preparation mm/day
1.20 1.18 1.13 1.1 1.1 1.09 1.07 1.06 1.05 1.05 1.05 1.05 1.01 0.92 0.84
1.16 3.74 8.64 10.67 10.45 10.15 9.53 8.93 8.40 7.70 7.0 6.30 5.51 4.50 3.62 106.3
1.8 8.1 8.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 18.0
Difference mm/season
Evapotranspiration mm/day
I II II A A B B B C C C C D D D
Evaporation mm/day
Crop coefficient
3 1 2 3 1 2 3 1 2 3 1 2 3 1 2
Crop demand mm/day
Stage
June July July July Aug. Aug. Aug. Sep. Sep. Sep. Oct. Oct. Oct. Nov. Nov.
1/3 Month
Month
Table(5 – 2):Water demand for rice and evaporation at Aswan
2.96 11.84 16.74 10.67 10.45 10.15 9.53 8.93 8.40 7.70 7.0 6.30 5.51 4.50 3.62 124.3 -
9.04 9.61 10.17 10.1 10.02 9.95 10.68 11.41 12.14 11.66 11.17 10.69 9.97 9.26 8.54 154.41 +
158
1.20 1.18 1.13 1.1 1.1 1.09 1.07 1.06 1.05 1.05 1.05 1.05 1.01 0.92 0.84
141
2.90 11.54 15.86 9.83 9.86 9.83 9.64 9.60 9.56 8.85 8.08 7.45 6.52 5.40 4.38 129.3 -
9.04 9.61 10.17 10.1 10.02 9.95 10.68 11.41 12.14 11.66 11.17 10.69 9.97 9.26 8.54 154.41 +
Difference mm/season
1.8 8.1 8.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 18.0
Evaporation mm/day
1.10 3.44 7.76 9.83 9.86 9.83 9.64 9.60 9.56 8.85 8.08 7.45 6.52 5.40 4.38 111.3
Crop demand mm/day
Soil preparation mm/day
I II II A A B B B C C C C D D D
Crop coefficient
Stage 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2
Evapotranspiration mm/day
June July July July Aug. Aug. Aug. Sep. Sep. Sep. Oct. Oct. Oct. Nov. Nov.
1/3 Month
Month
Table (5 – 3):Water demand for rice and evaporation at Abo Simble
265
5.1.3. Decreasing the Evaporation Losses by the Closure of the Secondary Channels (Khores):
The word (khor) is referred to small secondary channels. These channels may be connected to the main stream or lake in different ways (one side or two sides or more). The main characteristics of khores are the shallow depth of water if compared to the main stream and it is not always full with water. Figure (5 – 4) shows some examples of khores in lake Nasser.
Figure (5 – 4): Some khores in lake Nasser The area of these khores in Lake Nasser represents about one third of the total area of the lake. This indicates the effectiveness of these khores in the evaporation process as they occupy large areas. Therefore, the main idea is to minimize the surface area of the khores by complete or partial 142
closure. In this study, 3 cases of 3 khores will be studied as a pilot area to see the effect of closing these khores. Two methods can be applied to close the khore either by closing the khore completely by constructing a dam at the entrance of the khore, or by closing the khores partially by applying terraces at different levels. The first method is not recommended due to the high cost of dam construction. On the other hand, the second method of terraces construction on the two sides of the khore is better. The proposed levels can be between 170m – 180m with an interval of 2.50 m in the vertical direction and side slope of 1 : 5. The material needed for constructing the terraces can be taken either from the lake bed material or the area around the khore. The proposed terraces can be used for agriculture. Figure (5 – 5) shows a diagram showing the filling method of the khore on steps with a side slope 1 : 5. ( 172.50 ) 5:1
5:1
( 175.00 ) 5 : 1
( 180.00 ) ( 177.50 ) 5 : 1
Sec. X - X
.00 155
.00 160 .00 165
X
X
170.00 172.50
175.00
177.50 180.00
Plan
Figure ( 5 – 5 ) : Diagram showing the method of partially filling the khores by terraces construction
143
5.1.3.1. Khore (Klabsha)
Khore Klabsha is one of the biggest khores in Lake Nasser. It will be selected as a pilot khore for application. It is located about 50 km upstream HAD. By applying the remote sensing technique, the processing of the satellite images and the topographic maps with a scale 1:50000, the analysis was done to calculate the area at different water levels. Figures (5 – 6) and (5 – 7) show the satellite images of the khore in June 1987 with water level of 158.40 m and in November 1998 with water level of 181.2 m, respectively.
144
Figure (5 – 6): Satellite image for (Kalabsha khore) at November (1987) at water level (158.4m)
145
Figure (5 – 7): Satellite image for (Kalabsha khore) at November (1998) at water level of (181.2m)
146
Figure (5 – 8) shows the area of the khore on the topographic maps of scale 1 : 50000.
Figure (5 – 8): (Kalabsha khore) on the topographic maps of scale 1:50000
The different types of data related to khore Kalabsha are integrated in digital format. The data are processed to create the digital elevation model (DTM) for the area of the khore. A contour map for the khore is developed with contour interval of 2.5m as shown in figure (5 – 9). This map will be used to compute the surface area of the khore at different water levels and the results will be shown in table (5–4). 147
Figure (5 – 9): The developed contour map for khore ( Klabsha ) between levels 170 and 180m with interval 2.5 m.
Table (5 – 4): The surface area of khore ( Klabsha ) at different water levels calculated from the generated contours Level (m) 170.0
Surface Area (Km2) 205.35
172.5
224.49
175.0
301.01
177.5
378.79
180.0
513.95
Figure (5 – 10) shows the relation between the water level upstream HAD and the surface area of khore (Kalabsha). Table (5 – 5) contains the details of filling the khore (Kalabsha) and the volume of water saved by the filling of the khore. 148
Surface Area of Khore (Klabsha) at different water levels 600 0.0943x
y = 2E-05e 2 R = 0.9757
Area (km2)
500 400 300 200 100 0 168
170
172
174
176
178
180
182
Water Level (m)
Figure (5 – 10): Surface area of khore (Klabsha) for different levels
Table (5 – 5): Volume of water saved by partial closure of khore (Klabsha) Level
Surface
Added
Evaporation
Evaporation
Saving
(m)
Area
soil
Rate at
losses
Water
(Km2)
Volume
Aswan
(Mm3)
Volume
calculated
(Mm3)
Station
from the
(Mm3)
(mm/day)
equation 180.0
470.70
---
7.32
1257.62
---
177.5
371.84
247.14
7.32
993.49
264.13
175.0
293.75
195.24
7.32
784.84
208.65
172.5
232.05
154.23
7.32
620.00
164.83
170.0
183.32
121.84
7.32
489.79
130.21
149
5.1.3.2. Khore (Allaqi)
Khore Allaqi is located about 110 km upstream of HAD. Figures (5 – 11) and (5 – 12) show the satellite images of the khore in June 1987 at water level of 158.40 m and in November 1998 at water level of 181.2 m, respectively.
Figure (5 – 11): Satellite image for (Allaqi khore) at November (1987) at water level of(158.4m)
150
Figure (5 – 12): Satellite image for (Allaqi khore) at November (1998) at water level of (181.2m)
Figure (5 – 13) shows the area of the khore in the topographic map of scale 1 : 50000.
151
Figure (5 – 13): (Allaqi khore) on the topographic map of scale 1 : 50000
The collected data related to Allaqi Khore are integrated and processed in digital format to create the digital elevation model ( DTM ) for the khore. A contour map is developed for the khore with an interval of 2.5 m as shown in figure (5 – 14). The surface area of the khore can now be calculated from the contour lines and the results are shown in table (5 – 6).
152
Figure (5 – 14): The developed contour map for khore ( Allaqi ) between water levels 170 and 180m with an interval 2.5 m.
Table (5 – 6): The surface area of khore ( Allaqi ) at different water levels calculated from the generated contour Level (m) 170.0
Surface Area (Km2) 280.14
172.5
292.17
175.0
304.19
177.5
319.01
180.0
333.83
Figure (5 – 15) shows the relation between the water level upstream HAD and the surface area of khore (Allaqi). Table (5 – 7) indicates the 153
details of filling the khore (Allaqi) and the volume of water saved by the filling of the khore. Surface Area of Khore ( Allaqi ) at different water levels 340
0.0175x
y = 14.171e 2 R = 0.999
Area 'km2'
330 320 310 300 290 280 270 168
170
172
174
176
178
180
182
Water Level ( m )
Figure (5 – 15):Surface area of khore (Allaqi) at different water levels Table (5 – 7): Volume of water saved by partial closure of khore (Allaqi) Level
Surface
Added
Evaporation
Evaporation
Saving
(m)
Area
soil
Rate at
losses
Water
(Km2)
Volume
Aswan
( Mm3)
Volume
calculated
(Mm3)
Station
from the
(Mm3)
(mm/day)
equation 180.0
330.70
---
5.8
700.08
---
177.5
316.54
35.39
5.8
670.11
29.97
175.0
302.99
33.88
5.8
641.43
28.69
172.5
290.02
32.42
5.8
613.97
27.46
170.0
277.60
31.04
5.8
587.69
26.28
154
5.1.3.3. Khore (Sara)
Khore Sara is located about 110 km upstream HAD. Figures (5 – 16) and (5 – 17) show the satellite images of the khore in June 1987 at water level of 158.40 m and in November 1998 with water level of 181.2 m, respectively.
Figure (5 – 16): Satellite image for (Sara khore) at November (1987) at water level of (158.4m) 155
Figure (5 – 17): Satellite image for (Sara khore) at November (1998) at water level of (181.2m)
Figure (5 – 18) shows the area of the khore in the topographic map of scale 1 : 50000.
156
Figure (5 – 18): (Sara khore) on the topographic map of scale
1 : 50000
By gathering the khore data together in digital format, digital elevation model (DTM) is produced to create a contour map for the khore with an interval of 2.5 m as shown in figure (5 – 19). The surface area of the khore can also be calculated from the contour lines and the results is shown in table (5 – 8).
157
Figure (5 – 19): The contour map for khore ( Sara ) between levels 170 and 180m with contour interval of 2.5 m.
Table (5 – 8): The surface area of khore ( Sara ) at different water levels calculated from the generated contour Level (m) 170.0
Surface Area (Km2) 13.35
172.5
15.95
175.0
22.45
177.5
30.83
180.0
43.10
158
Figure (5 – 20) shows the relation between the water level upstream HAD and the surface area of khore (Sara). Table (5 – 9) illustrates the details of filling for the khore (Sara) and the volume of water saved by the filling of the khore. Surface Area of khore ( Sara ) at different water levels
Area 'km2'
50.00 40.00
0.1201x
y = 2E-08e 2 R = 0.9902
30.00 20.00 10.00 0.00 168
170
172
174
176
178
180
182
Water Level ( m )
Figure (5 – 20): Surface area of khore (Sara) for different water levels Table(5 – 9):Volume of water saved by partial closure of khore(Sara) Level
Surface
Added
Evaporation
Evaporation
Saving
(m)
Area
soil
Rate at Aswan
losses
Water
(Km2)
Volume
Station
( Mm3)
Volume
calculated
(Mm3)
(mm/day)
(Mm3)
from the equation 180.0
48.93
---
6.19
110.56
---
177.5
36.24
31.73
6.19
81.88
28.68
175.0
26.84
23.50
6.19
60.65
21.24
172.5
19.88
17.40
6.19
44.92
15.73
170.0
14.72
12.89
6.19
33.27
11.65
159
The study of partial closure for the three khores indicated the following:
the partial closure of khore Kalabsha, Allaqi and Sara by constructing terraces between levels 170 m and 180 m need a filling volume 718 Million m3, 132 Million m3 and 85 Million m3, respectively. The amount of water saved from evaporation losses every year are 768 Million m3, 112 Million m3 and 76 Million m3, respectively. The area gained from the filling are 68000 Feddan, 12597 Feddan and 8260 Feddan, respectively.
160
Chapter ( VI ) CONCLUSIONS AND RECOMMENDATIONS The main objective of this study is to find a precise way to calculate the evaporation losses and propose different methods to decrease these losses. To achieve these goals:
Different methods of estimating the evaporation rate was investigated to find the most suitable method to apply in lake Nasser. Also the required metrological data were collected from various sources to cover all the needs to calculate the evaporation rate for Lake Nasser. A new technique was applied to calculate the surface area of Lake Nasser, which is the Remote Sensing Technique. Two sets of satellite images covering the area of Lake Nasser, from the LANDSAT 5 satellite with 7 bands, were processed to calculate the surface area at different water levels. Other sources of data like maps and field survey data were used to complete the required data. Also new method of calculating the volume of water lost by evaporation by dividing the area of lake Nasser into 4 parts according to the metrological stations and their distribution along the lake.
Some suggestions to decrease the evaporation losses were discussed such as modifying the upstream water level of the HAD management, cultivating rice in some areas of lake Nasser and closing some khores of the lake.
161
6.1. Conclusions:
1 - From the calculations of evaporation losses it was found that:
a-
the number of the metrological stations and their distribution along the lake are not sufficient for calculating a precise value to the evaporation rate. There are only 4 stations and not all of them measure the required parameter to calculate the evaporation rate.
b-
the use of Remote Sensing technique in calculating the surface area of Lake Nasser is very useful and suitable for Lake Nasser because it is very huge and the traditional ways of calculating the surface area can't give good results.
c-
the calculation of the surface area can be more precise if we use 5 or 6 sets of satellite images in different water levels.
2 – In order to reduce the evaporation losses:
a-
the upstream water level of HAD should be modified. This can be applied by implementing different scenarios taking into consideration all the operating conditions of the HAD. These scenarios can be made by a computer model.
b-
the rice cultivation on part of the top surface of the lake is valuable. However, this proposal should be tested by selecting a small pilot area to apply the proposed plan. Also, a feasibility study to evaluate the cost- benefit analysis should be conducted. The impact of rice cultivation on the water quality of the lake should be secured. 162
c–
the evaporation losses can be decreased by closing some khores in the. A comprehensive feasibility study must be done on all the khores in Lake Nasser (About 40 Khores). This study is not only for the cost estimation of closing the khore but also to study the climate of the area , the geology of the bed and the surrounding areas, the environmental impact of these areas and also the water quality of the khores.
6.2. Recommendations:
The following are the recommendations for future studies:
1- By using additional sets of satellite images covering the area of Lake Nasser, the calculations of surface area of the lake can be more precise. 2- A comprehensive study can be done to modify the management of the upstream water level of the HAD by using a computer model to make different scenarios to achieve the optimum management method. 3- In case of applying the idea of cultivating some crops such as rice in some areas of Lake Nasser, some field experiments must be done to test this method. 4- A comprehensive study must be done on the khores in Lake Nasser to choose the suitable khores that can be closed and to choose also the way of closing these khores.
163
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