A GIS-supported method for detecting the hydrological ... - CiteSeerX

Landscape Ecology vol. 5 no. 2 pp 107-124 (1991) SPB Academic Publishing bv, The Hague

A GIS-supported method for detecting the hydrological mosaic and the role of man as a hydrological factor Lotta Anderson and Ake Sivertun Department of Water and Environmental Studies, Linkoping University S-581 83, Linkoping, Sweden Keywords: GIs, soil-wetness, hydrological response, water-partitioning, human activities

Abstract

A Geographical Information System (GIs)-supported method was developed for predicting the spatial distribution of soil wetness as an indicator to determine the probability of an area to act as a groundwater recharge or discharge area. The method was based on overlays of maps with the distribution of hydrological responsedetermining factors. An application was made for the Svarti river basin (south-central Sweden). Changes in the soil-wetness mosaic due to human activities were also analyzed. Since the 1870s drainage and forestry had, according to the analysis, decreased by 5 % the parts of the basin that act as discharge areas during wet spells. In the agriculturally dominated sub-basins, the alterations were larger. Forty percent of the open land had been artificially drained. The main shift of soil wetness index classes was caused by an alteration of areas that earlier fluctuated between groundwater discharge and recharge into typical recharge areas. For the plains, the shift from discharge areas to recharge areas was also significant. A conceptual water partitioning model was used to assess the spatial distribution of water flows (evaporation and recharge), as a response to climatic inputs, for areas with different physiographic and vegetative characteristics. The present water flow pattern was compared with the response mosaic of the 1870s. The increased maximum daily recharge peaks during autumn constitute the only significant change in the hydrological response for the studied area as a whole. The consequences that the desiccation of the landscape have on chemical and biological processes were discussed.

Introduction

Every landscape consists of a mosaic of factors that determine the spatial distribution of hydrological response in the form of groundwater recharge, runoff generation, evaporation and storage of rain and snowmelt in the soil. The regional variability of average precipitation and snowmelt rates are also related to the landscape mosaic. In general, precipitation rates increase and air temperatures decrease with increased altitude. Landscape factors related

to soil type and topography are relatively stable over time. Human influences in the form of altered canopy cover changes the mesoscale mosaic. Land management may also have hydrological effects, especially when it intervenes directly in the runoff generation process; artificial drainage is a noticeable example. In Sweden, there are at present signs of accelerating forestation on farm land that no longer is profitable for agricultural production. For the forest dominated areas, there are indications of

108 that the runoff/precipitation ratio has decreased over the last decades (Jutman et al. 1989). This might be a sign of hydrological response to changed canopy cover. LundegrCn (1983) found a trend towards increased investments in artificial farmland drainage. However, the last years have shown that this probably was just a temporary increase. On the other hand, the acreage of artificially drained forests is increasing. The effects of artificial drainage are not limited to river discharge. The transformation of discharge areas into recharge areas makes vegetation more directly dependent on rainfall fluctuations, i.e. more susceptible to drought. In this connection, it is worth pointing out that agricultural irrigation had increased in the area during the last decades (MAnsson 1988). The main increase occurred during the 1970s, which included the only period between 1883 and 1987 for which severe water stress conditions were detected during four consecutive years (Anderson 1989). Transit times are of overriding importance for the chemical composition of water that reaches rivers. These will be longer if the water passes through a soil matrix that is drier than it would have been without artificial drainage, but they can also be shorter if drier soil conditions increase the possibility of macropore flow. Another example of the effects of desiccation of the landscape, caused by artificial drainage and afforestation, is decreased rates of denitrification and thus changes in nitrogen flow. On a larger scale, there are also feedbacks between soil moisture conditions, vegetation properties and the precipitation over land (Rowntree and Sangster 1986). Due to the build-up of radiatively active greenhouse gases in the atmosphere, climate, as well as land use, might change over time. Without the help of a system that can integrate information about spatially heterogeneous factors, it is very difficult to determine the distribution of landscape elements with similar hydrological response. A Geographical Information System (CIS), provides a means to detect the spatial distribution of landscape elements with different conjunctions of factors relevant to the studied phenomena. In recent years there has been a rapid

development of computerized map overlays for ecohydrological applications. Determination of “runoff-production zones” and identification of changes in the quality of water from agricultural land (Hopkins and Clausen 1985), and the estimation of bacterial densities and suspended solids in runoff (Gilliland and Baxter-Potter 1987) are examples. In this study, a CIS has been used to detect the spatial distribution of soil wetness zones in an area in south-central Sweden. Human-induced changes of the hydrological-response pattern were also assessed.

Theoretical background The concept of hydrological response zones The generally accepted theory of runoff generation is based on the contributing area concept, where areas either act as groundwater recharge or discharge areas of water during rainfall or snowmelt events. The extension of contributing discharge areas is dynamic and increases during wet spells as the water table rises. According to a theory developed by Eagleson (1982), water-limited natural vegetation systems are in stable equilibrium with their climatic and pedologic environments with a canopy cover and selection of species that act to minimize the water-demand stress. Thus, topographical and soil characteristics, vegetation and the wetness status of the soil are factors that are strongly interdependent (Fig. 1). Temperature and precipitation patterns, which are strongly dependant on elevation, have a mesoclimatic control on the vegetation. The hydrological response to soil type and location on the slope sometimes can be inseparable (Hawley et al. 1983). There is often a link between soil permeability and the type of vegetation. According to Eyre (1968), forests develop on sandy porous soils where deep root systems maintain access to the rapidly percolating water and sometimes also to the groundwater. Low permeability limits the penetration of water into deeper layers of the soil but tends to retain the solutes. Clayey soils, therefore, primarily support the shallow rooted vegetation.

109 R e c h a r g e areas

Discharge areas

Top of hypsograph high slopes

Bottom of hypsograph flat .- -

---I.-Erosion, fine par-

-1-

I

+---t

ticles washed out Shallow, permeable well drained soils

-- -3

Post glacial sedimentation Deep soils with low permeability nutrient rich

Low water content i n

topsoil, water transported dawnhills

topsoil, shallow water

table receives water f r o m Uphill w e a s

Favourable for forests Favourable for grassland

-

Groundwater level

Water flow path

Fig. 1. Generalized water flow paths in a landscape profile (lower part) and characteristic interrelations between slope, soil, and vegetation, indicated by vertical arrows (upper part).

For stable systems, interrelations between various landscape factors and soil wetness make it possible to detect the distribution of a single unknown factor, provided that others are known. Human intervention, in the form of canopy cover changes and artificial drainage, can disturb the natural soil-topography-vegetation-wetness system. These instabilities will usually be kept as long as they are economically profitable. Provided that no irreversible changes have occurred, the system will then again evolve towards the undisturbed.

Human influences on the mesoscale hydrological mosaic In areas with a humid climate, deforestation will increase soil moisture content, the extension of discharge areas, and runoff volumes (e.g. Andersson 1988; Brandt et al. 1988; Lundin 1979; RosCn 1984). This is due to reduction of transpiring surfaces and of interception losses. In addition, if all deep roots are removed, transpiration will be reduced in times of limited water availability in the top soil. Changed canopy cover does not intervene only

with runoff generation because the vegetation regulates the degree of soil saturation. It may also influence the possibility of macropore flow since channels can be developed by decayed roots (Beven, 1982). The hydrological response to artificial drainage depends on the nature of the soil, the location within the river basin, the antecedent soil moisture conditions, and on the type of artificial drainage. Annual runoff generally increases because of reduced evaporation. However, if a significant increase in biomass production occurs as an effect of artificial drainage, evaporation might be increased, and consequently, runoff will decrease (Heikurainen and Paivanen 1970). From clayey soils, artificial drainage will reduce peak flows when the soil is saturated because of less surface runoff. However, after prolonged dry periods, when cracks have developed, water is quickly transported into the drains, resulting in higher peak flows than before the artificial drainage (Robinson and Beven 1983). From sandy soils, with less frequent topsoil saturation, artificial drainage can speed up flow during times of soil saturation. However, due to lowering of the groundwater table, artificial drainage increases the soil moisture storage buffer, with the effect that runoff is decreased after periods with soil moisture deficits. For organic soils, the effect on soil moisture content is usually only found in a restricted zone around the tile drains (Hudson and Roberts 1982). This limited increase of the storage capacity may not be sufficient to counter the effects of faster flows through the artificial drainage network, and so lead to increasing peak discharge (Newson and Robinson 1983). The type of artificial drainage technique is of critical importance for the hydrological response. Open drains increase flow rates considerably in comparison with natural peatlands, and even more so compared to peatlands with under-drains (Moore and Larson 1979). The type of drain is of critical importance for runoff generation also from other soil types. Seuna and Kauppi (1981), for example, showed that surface runoff and spring maximum flow decreased and annual runoff increased when open ditches were substituted by under-drains in a

110 small cultivated area with mainly clayey and silty soils. The hydrological response at river basin level of an artificial scheme and of changes in the canopy cover might be opposite to the local effects. Artificial drainage of sandy soils in the upper parts of a basin can locally speed up the runoff generation. Water generated from the uplands may be transported away from the river basin before the lowland maximum runoff generation is created. The total peak from the basin will therefore be reduced (Newson and Robinson 1983). Another example is that the location of clear-cuttings has been shown to affect peakflows due to nonsynchronous snowmelt and other time delays in the basin (Brandt et al. 1988).

terized by intensively cultivated plains with few lakes, and the bedrock consists of limestone and shale covered by clayey soils. There are no large urban areas within the study area. The area belongs to the driest parts of Sweden, with an annual average (1931- 1961) precipitation of 630 mm and actual evaporation of 450 mm (Falkenmark 1976). The average annual temperatures are 0.5-1°C lower, and the annual precipitation about 50 mm higher in the hilly parts in the extreme south, compared to the plains in the north. However, the climatic pattern is not static. Climatic stations that on average had the lowest summer precipitation have been shown to be among the wettest for single years (Anderson 1989).

The Geographical Information System Methods and data

A GIs-supported method was used to detect the present mesoscale distribution of zones with different soil wetness response to meteorological events. The analysis was bases on overlays of maps with the distribution of individual landscape factors that are typical either for groundwater recharge, intermediate (temporary fluctuations between recharge and discharge) or discharge areas. It was hypothesized that changes of the canopy cover and artificial drainage by humans, have changed the hydrological landscape mosaic, thereby inducing changes in hydrological response. The GIS and a conceptual water partitioning model, based on the soil moisture balance (Anderson 1988), were used to detect changes since the 1870s in the hydrological response mosaic. The study was made for the Svarti River basin, in south-central Sweden (Fig. 2 ) . The study area, which is the portion of the basin downstream of Lake Sommen, extends over 1430 km’. Within the area, different regions can be distinguished according to land-use and geographical characteristics. The regions in the south are hilly and covered with forests and numerous small lakes; coniferous forests on a bedrock of granite capped with till dominates these areas. The north and a transitional zone along the Svarti river are charac-

The low-cost EBBA I1 system (from the Swedish Space Corporation) and the software package EASI/PACE (from Perceptron, Canada) were combined to perform image processing and do logical operations between the involved factor maps (Sivertun 1989). A Cipher tape station was used to read satellite images and other data from tapes. Map digitizing was performed using a Calcomp 9100 digitizer. The CAD program, AutoCad, in combination with and IBM/AT, facilitated the digitizing. An IBM/AT was also used as an interface between the various hardware components of the GIS (Sivertun et al. 1986). Programs were written to facilitate the transfer of data between the system components. Since the GIS used is a raster based system, programs that transformed the vector-based output from the AutoCad were used. A pixel size of 125 x 125 m was used in this study. The used factor maps and databases were not available at the same level of detail and aggregation. The implications, for the actual study, of integrating data sets with different resolution are addressed in the “Discussion” section. Water divides, rivers and lakes were identified using the hydrological data base HYPOS, developed at the Swedish Meteorological and Hydrological Institute (SMHI). Bodies of water smaller than

111

Fig. 2. The Svarti river basin north of lake Sommen (Sweden), divided into subbasins.

1 km’ were detected from a Landsat 5 TM image. Elevation data in a 500 x 500 m grid net, with a height resolution of 0.1 m, were obtained from the Swedish Land Survey (LMV). Soil type information was based on Swedish Geological Survey (SGU) maps (1 :50.000), including information on particle size distribution at a depth of 0.3-0.5 m below the soil surface. These maps covered most of the studied area. For the extreme southern part, however, a map of quaternary deposits of Sweden (1 :1.OOO.OOO), plus maps of the distribution of peat land (1:100.000), had to be used. The main part of the soil maps were manually digitized. Some, very heterogenous areas, were digitized by scanning, made by SGU and the LMV. From these data bases, four single-factor maps, which contained information on landscape factors

that could be considered constant over the studied time interval, were constructed. One map included distances to lakes and rivers. An elevation map was constructed by calculating the average elevations for 500 x 500 m grids. The slope between the 500 x 500 m grids were calculated as tangens for the difference in the average elevation between the grids, divided by the distance between the centers of the grids (500 m). The slope index map was obtained from the calculated maximum slope between a grid and its eight neighbors. The relative heigh map was derived from hypsographs, constructed by the GIS for each sub-basin. Relative height for a pixel was defined as the percentage of the sub-basin in which the pixel is situated that is situated at lower elevations. The digitized soil map included five classes. The

112 classification of mineral soils was done according to the main particle size fraction at a depth of 0.3-0.5 m below soil surface: sandy and gravelly (> 0.2 mm), silty (0.002-0.2 mm), and clayey (< 0.002 mm). In addition, organic soils and areas with soil depths below 0.3-0.5 m were included as separate classes. Two single-factor maps for landscape factors that underwent considerable changes over the studied time interval were also constructed. One map covered the spatial extension of dewatering projects and under-drainage with state subsides under authorization of the County Agricultural Board (Lantbruksnamnden) 1879-1985. Artificial drainage activities were very intensive during the first part of this period (Fig. 3). During the latter part, they mainly consisted of improvements of old drainage works (Sivertun and Castensson, in manuscript). Admittedly, the artificial drainage map has some limitations: Drainage works made without state subsidies, and artificial forest drainage are not included. The age of different works is not consistent. Most of the old works have, however, been improved over time. Canopy cover has also undergone changes over time. For the early 1870s the distribution of forest and open land was manually digitized from maps of rural hundreds (former used division of a county, called harad in Swedish), produced in the scale of 1:50.000. The present canopy cover was determined from a satellite image interpretation, based on the three near infra red bands in a Landsat 5 TM image from September 1985. This selection of wave lengths and time of the year has been shown to be the most favorable for remote sensing interpretation of forest land in southern Sweden (Ekstrand 1985). A map of canopy cover changes was evaluated by superimposing the two canopy cover maps. The first step in the analysis was to make an overlay of topographical and soil type related maps. A weighing scheme was used to classify these maps according to their properties being typical for groundwater discharge or for recharge areas (Table 1). The classification rules where based on the present knowledge of the importance of various landscape factors for the distribution of soil moisture deficits and groundwater levels.

Fig. 3. Accumulated number of drainage works reported to the Local Land Survey in Ostergotland until 1950.

When analysis of spatial variability of soil moisture dynamics is made on a mesoscale, topography is usually the most critical factor (Beven and Kirkby 1979; Hawley et al. 1983). The relative height distribution is related to the amount of flow accumulated from upslope, and slope gradients help to determine the rate of flow towards lower parts. A concentration of large areas into the upper part of the hypsograph is therefore an indicator of large recharge areas, whereas large areas in the lower parts is an indicator of extensive discharge areas. Admittedly, the relative height was the wetnessindicator for which it was most difficult to find a rational basis where to put the class limits. Different limits were tested. The ones that finally were chosen seemed to give the best compatibility to the soil type and slope maps, in terms of the spatial distribution of the different wetness-classes. As discussed below, it was shown that the distribution between the three relative height distributions classes varied significantly between the forest-dominated and the agricultural dominated basins, which demonstrates that this is a significant classification factor. Since the calculated slopes are calculated for points, representing the centers of 500 x 500 m grids, the calculated slope indexes were low (Table 1). A slope of 1O corresponds to a height difference of 8.75 m, between the average elevations of two 500 x 500 m grids, whereas a slope of 2" corresponds to a height difference of 17.45 m. These two values (1 O and 2") were chosen as the limits between the three classes for slope as a wetness indicator. This was partly due to the fact that, owning to system limitations common in raster image processing, all values were coded as integers. Our own familiarity with the area, combined with studies of

113 Tuble 1. Classification soil-wetness indicators (bold figures) for different time-stable landscape factors. The landscape factors are divided according to if they are typical for discharge, intermediate or recharge areas. Indicates

Discharge Intermediate Recharge

Slope between 500 m grids

Distance from water (m)

Soil type

(XO)

Relative hight in sub basin (Yo lower situated)

0-1 2 2 = 4 >2 = 8

0- 20 I) 2 21- 60 4 61 - 100 * 8

0-125 I) 2 125-250 = 4 >250 8

Organic or clayey 0 Silty 2 Sandy, gravelly, or soil depth 0.3 - 0.5 m 4

-

topographic maps, confirms that the choice of these slope angle limits gives a division of the study area within three topographic zones that is consistent with reality. The geographical position of rivers and lakes is also determined by topography and it is evident that the probability of soil saturation is affected by the distance to open water. The 125 m basis of the three classes is due to the size of a pixel. Storage capacity and permeability are the main soil factor components of importance for the soil moisture regime. The only soil depth information available was the extraction of areas with soil depths less than 0.3-0.5 m. Such areas were classified as indicating conditions typical for recharge areas, since runoff usually is infiltrated further downslope. Permeability was reflected in terms of dominating particle size. Soils with high permeability were classified as typical for recharge areas. Organic soils were considered as typical for discharge areas, since their genesis demands saturated soil conditions. As previously mentioned, soil type is related to topography. Due to the strong interrelationship between soil type and topography, which limits the additional information given by the soil type, the soil relared wetness indicators were given lower values than the other indicators (Table 1). For areas that had become artificially drained, a soil-wetness indicator, that transformed these areas towards drier soil-wetness classes, was superimposed over the original overlay. A sensitivity analysis was conducted to determine how the choice of class limits for this indicator would effect the distribution of discharge- and recharge areas. When a indicator value of 6 was chosen, the total value of the

-

-

-

soil wetness index was changed towards more well drained conditions by one or two classes, depending on the earlier value. Lower values gave an insignificant influence on the soil-wetness distribution. The chosen value might underestimate the effects of drainage for some areas, but since we were not able t o divide the values between different types of drainage, and knowledge about the effects of drainage performed in areas with different combinations of landscape factors is weak, the same indicator was used for all artificially drained areas. The values for forest land were chosen so that deforestation changed the index by one class towards discharge areas and afforestation changed the index by one class towards recharge areas (Table 2). It seemed realistic to assume that the influence of land use changes on soil wetness are smaller than those from artificial drainage. The chosen values gave small, but significant changes of the distribution between discharge- and recharge areas. In the final map overlay, landscape factors that changed over time were combined with those that were considered constant between the two studied points of time. The landscape was divided into six soil wetness classes (Table 3), of which the two wettest can in most cases be interpreted as discharge areas. The two driest classes have characteristics typical for recharge areas. The dry areas are characterized by, on the average, the highest soil moisture deficits and the deepest ground water levels, due to the conjunction of wetness determining landscape factors. The class limits were chosen so that a realistic distribution between recharge- and discharge simultaneously could be achieved both for the forest dominated, hilly sub-basins, where a massive

114 Table 2 . Soil-wetness indicators to be superimposed over the time-stable overlay to indicate the influence of human interventions in the hydrological response mosaic. Change towards

Land use

Drainage

Discharge Recharge

Open land * 0 Forest =1 4

No =) 0 Yes * 6

Table3. Classification of soil-wetness indicators into six wetness classes. Wetness class

Wetness indicator value

Discharge 1 Discharge 2 Intermediate 1 Intermediate 2 Recharge 1 Recharge 2

6- 8 10- 12 14- 16 18-20 22 - 24 26 - 40

areal concentration towards discharge areas would be expected, and for the agricultural dominated plains, where a large proportion of land that sometimes acts as recharge areas is likely to occur. This might seem like an ad hoc strategy, but until extensive field experiments have been undertaken, this is how far we can come.

The water partitioning model A conceptual water partitioning model, based on the soil moisture balance (Andersson 1988) was used to detect differences in the hydrological response on climatic input for sub-basins with different distributions of soil-types, canopy cover and land management. The model was driven by information on daily precipitation amount and mean daily air temperature (averages from five stations in the area) from one year with large snowmelt during spring (1977) and from one year with heavy autumn rainstorms (1978). In addition, long-time averages (193 1- 1960) of monthly mean potential evaporation (Wallen 1966), calculated with the Penman equation (Penman 1948), were used after being par-

titioned across the days of a month. The simulation model produced daily values of soil moisture deficits, evaporation and runoff generation. The calculations were made for nine combinations of soil types (sandy and silty, clayey, or organic), canopy cover (open or forest) and land management (artificial drainage). Calculations were separately made for lakes and rivers. For these, recharge was put equal to amounts of rainfall and snowmelt, and evaporation was considered equal to the Penman potential for water surfaces (Penman 1948). The GIS was used to make the division into these ten landscape elements by making an overlay of digitized canopy cover, soil types, lakes and rivers, and artificial drainage. Parameter values and subroutines that differed between the landscape elements are shown in Table 4. For the forested and open sandy or silty soils, the simulation model was calibrated and verified against soil moisture data from the Velen representative basin (Andersson 1988). For the open clayey soils, calibration and verification was made against measurements from the Kalltorp experimental field (Andersson 1989). These two field stations are situated in the vicinity of the studied area and have soil characteristics typical for the area. Parameter values for the other landscape elements were determined from a combination of information achieved from these field experiments and from the conclusions, referred to in the literature cited above in the “Theoretical background” section. The parameters in the snow routines were those generally used in the runoff simulation model HBV (Bergstrom 1976). The snow correction compensates for snow interception losses from tree canopies. The rainfall interception simulation model was calibrated against interception measurements from the Velen forest (Bringfelt and Hirsmar 1974). Interception was only calculated for the forested areas. Actual evaporation was assumed to equal the potential rate until a certain soil moisture deficit was reached. For organic soils, however, evaporation was assumed never to be reduced below the potential. As stated in the “Theoretical background” section, when soil moisture contents exceed field capacity, the peak flows from clayey soils are often

115 Table 4 . Parameters values in the simulation model that differed between various landscape elements. S = sandy and silty soils, C = clayey soils, 0 = organic soils, D = artificially drained. Ea = actual evapotranspiration, Ep = potential evapotranspiration, + FC = soil moisture is allowed to exceed field capacity, FC = soil moisture is not allowed to exceed field capacity, macro = unsaturated macropore flow considered, SM = soil moisture. Landscape element

S Open C Open 0 Open S Open D C Open D 0 Open D S Forest C Forest 0 Forest

Maximum SM deficit (mm)

Ea limiting SM deficit (mm)

Drainage routine

(070)

Degree-day factor (mm/day X T )

90 90 90 90 90 90 60 60 90

3.5 3.5 2.8 3.5 3.5 2.8 2.8 2.8 3.5

200 130 40 230 60 80 245 160 40

45 0 Ea = Ep 45 0 55 I0 30 Ea = Ep

+ FC

Snow correction

reduced after artificial drainage has been introduced. This was simulated by allowing a gradual drainage of the water above field capacity, with a velocity that depended on the degree of saturation (5 mm/day at soil saturation). The surface runoff from saturated, not artificially drained, clayey soils was simulated by letting all water above field capacity contribute to runoff within one day. The previously discussed fact that artificial drainage can speed up the runoff from saturated sandy and silty soils was simulated by letting all water above field capacity contribute to runoff within one day. For saturated, not artificially drained, sandy and silty soils, the return to field capacity was simulated to be more gradual (10 mm/day at soil saturation, linearly decreasing between soil saturation and field capacity). For drained clayey soils (Robinson and Beven 1983) and for the forested sandy and silty soils (de Vries and Chow 1978) unsaturated macropore flow during heavy rainstorms was assumed to take place with a rate depending on antecedent soil moisture conditions. It was assumed that the maximum available storage volume for infiltrating water (i.e. the plant available water) increased as a consequence of artificial drainage and afforestation, due to lowering of the groundwater table.

FC FC FC + FC FC +FC, macro FC FC

Results The spatial variability of soil and topographic variables relevant to the spatial distribution of soil wetness is shown in Fig. 4. Human impact on the hydrological response mosaic in the form of artificial drainage works and canopy cover changes since the 1870s is presented in Fig. 5. In Fig. 6, the spatial distribution of areas belonging to the six soil wetness classes, and the spatial distribution of areas that since the 1870s have been affected by human soil wetness-impacting activities are shown. This study was based on the assumption that there exists strong interrelationships between landscape factors and between these factors and the soil wetness (Fig. 1). The similarity between the distribution of soil and topographical related factors (Fig. 6 ) and of the canopy cover (Fig. 5) is an example of such relationships.

The hydrological response mosaic of today A heterogenous mosaic of areas with different soil wetness classes (Figs. 6 and 7) and water flow (Fig. 8 and Table 5) was found. This was due to the heterogenous spatial distribution of individual factors, important for the hydrological response (Figs. 4 and 9). The analyses are separately presented (Figs. 7 , 8, 9, 11, 12 and Table 5) for forest dominated,

120 RELATIVE HEIGHT

SLOPE

CLOSE

SOIL

Averoge

Forest dominated

$ 50 Mixed Open land

Forest

Agricultural dam tnoted

Agricultural

dioinoge

Lakes and water coursei

Svortd centrol basin

Fig. 11. Area of land cover in 1870s (left) and 1980s (right) respectively. The percentage of land reported as being artificially drained is also shown. Fig. 9. Distribution of individual response-determining landscape factors for typical sub-basins in Svarti basin, characterized by various degrees of canopy cover.

Averuse so1L

DISTANCE 10

SLOPE 1%1

Forest dominated 180

160

110

120 110

0

20

4

60

80

100

% o f toto, ore0

0

20

LO %Of

60 toto1

80

1W

OreO

m61-lo0 lntervolr of relative heights I%] 0-20

m21-60

Fig. 10. Hypsographs from the forest dominated sub-basin Strilsnas, and from the agriculture dominated sub-basin Skenaia, situated in the lower parts. The lowest 20%, the intermediate, and the highest 40% of the relative height distributions are shown.

charge classes. A concentration of the area into the upper height interval was typical for the forest dominated sub-basin, as indicated by the hypsograph from Strilsnas (Fig. 10). The forest dominated sub-basins were also characterized by high slope indexes and a large percentage of sandy soils (Fig. 9). Due to a high canopy cover, the yearly Q/P-ratio was low (Table 5 ) . Snow interception losses from the tree canopies made the runoff-generation during spring (March-April) from these sub-basins lower than the average during the snow rich year of 1977 (Fig. 8). After heavy autumn (SeptemberNovember) rainstorms, the maximum daily runoffgeneration was calculated to be high in the forested areas due to unsaturated macropore flow (Fig. 8). The agriculturally dominated Skenai basin, and the plains of the central basin, was characterized by

Fig. 12. Distribution of man-induced changes among different landscape factors in typical sub-basins in Svarta basin, characterized by various degrees of canopy cover.

low slope indexes, and by a relative height distribution concentrated towards the lower height range of the hypsograph (Fig. lo). Clayey soils were more common than in the forest dominated sub-basins. In the Skenai basin, about half of the area was, however, covered by sandy soils (Figs. 4 and 9). Due to a combination of topographic and soil factors, a large fraction of the land was in the intermediate soil wetness class (Fig. 7). The sparse canopy cover made the yearly Q/P-ratio 6% higher from the Skenai basin compared to the average for the whole area (Table 5). During periods with extensive snowmelt, both the total, and the daily maximum runoff-generation was calculated to be significantly higher from the Skenai basin than from other subbasins (Fig. 8). The larger volume was obtained because snow interception losses from non forested areas are insignificant. The larger daily maximum

121

runoff-generation was due to the large amounts of artificially drained sandy soils from which high daily maximums of runoff-generation were simulated to occur during saturated soil conditions. During summer, the runoff-generation was calculated to be somewhat higher and evaporation somewhat lower than the average for the whole area (Fig. 8). In autumn, as an effect of smaller soil moisture deficits, the total runoff-generation was significantly higher from the Skenai basin compared to the others (Fig. 8). The daily maximum runoffgeneration was lower than average, since the calculated amount of unsaturated macropore flow was larger from other basins. The Lilli and Kapelli basins are characterized by large inter-basin differences, with a concentration towards forested recharge areas in the southern parts, and with intermediate and discharge areas in the agriculturally dominated northern parts (Fig. 6).

Changes over time of the hydrological response mosaic According to calculations based on the overlay, the forest coverage decreased by 8% between the 1870s and the 1980s, due to deforestation of 16% and afforestation of 8% of the area (Figs. 5, 11). Deforestation was most extensive in the agriculturally dominated Skenai basin, and concentrated in areas favorable for cultivation. In contrast, the forested acreage increased in the forest-dominated sub-basins. In the uplands, afforestation was most significant on organic soils and in areas close to rivers. In the agricultural plains, however, the forested areas in the vicinity of the rivers decreased (Fig. 12). The overlay illustrated that artificial drainage activities in the uplands was concentrated in areas with organic soils and low slopes, close to the rivers. In the plains, drainage was mainly concentrated in areas with clayey soils in the lower height intervals of the hypsograph (Fig. 12). Consequently, artificial drainage was most intense in such areas where canopy cover changes had occurred. During the studied time interval, agricultural land under drainage had increased from being in-

significant t o about a 20% coverage of the studied area (Figs. 3 and 12). According to the analysis, 40% of the artificial drainage was on clayey soils, and about a third of the clayey soils had been artificially drained. Only 13% of the sandy soils were drained. However, since more than half of the basin is covered by sandy soils (Fig. 4), this corresponds to 40% of the total acreage artificially drained. The analysis indicated that human activities on average had caused a decrease of discharge areas by 5% since the 1870s (Fig. 7). The hydrological response to increased artificial drainage and the effects of decreased canopy cover work in opposite directions. Therefore, the total shift of land between soil wetness classes was smaller than the shift that would have been caused by artificial drainage only. The main shift was from the intermediate towards the groundwater recharge areas. For the plains, the shift from discharge to intermediate or recharge areas was also significant. The maximum daily runoff-generation during spring was estimated to have decreased from the forest-dominated sub-basins since the 1870s. For the other sub-basins the spring maximum was, according to the simulations, increased. For the central and the Skenai basin, increased total volumes were also indicated. The most evident change during summer was the decreased evaporation from the Skenai basin (Fig. 8). During autumn, the indicated increase in the maximum daily runoffgeneration was larger than during spring with significant increases for all sub-basins except by those dominated by forest. For the Skenai basin, an increased average autumn runoff-generation was also indicated. The simulated dependence between soil type and the hydrological response to artificial drainage resulted in a high maximum runoff-generation during autumn from the Kapellai, which had a high amount of drainage on clayey soils. The spring maximum, however, was simulated to be marginally larger from the Skenaa basin, which had a higher proportion of artificial drainage on sandy soils. The only significant change of water flow pattern on average for the whole basin was an increase in maximum daily runoff-generation during autumn.

122

The proportion of water flow in the form of runoff had increased from all basins except the forestdominated ones (Fig. 8). The decreased proportion of evaporation was due to the decreased proportion of forested land. It must, however, be realized that areas indicated as forest on the map of hundreds during the 1870s probably had a somewhat different hydrological response compared to areas defined as forests from a satellite image (Fig. 5 ) . It is, for instance, possible that forest evaporation was smaller during 1870 due to a less dense canopy cover and extensive grazing (Kardell 1984).

Discussion The analysis was based on overlays of maps with the distribution of individual landscape factors that are typical either for groundwater recharge, intermediate or discharge areas. The resolution of the data sets varied from the TM data of the present canopy cover, which had a finer (30 x 30 m) resolution than the used pixel size, to the 1:50.000 scale elevation, soil and old vegetation maps, and for a small part in the south, a 1:1.OOO.OOO scale map of Quaternary deposits. For the 1:50.000 scale maps, the uncertainty of the borders between areas that are classified differently were in the order of 50 m. It must also be considered that the manual digitalization of the borders of various classes are made with a lower resolution than could have been obtained if scanning had been used. This is particularly obvious for the soil maps. Due to these weaknesses, the overlay of single-factor maps may result in some questionable classifications, such as the occurrence of artificial drainage in pixels that geologically are classified as bare rocks or very shallow soil (Fig. 12). Misclassifications are a combination of the scale of the original data bases and of the GIs, errors in the used data bases, plus simplifications and mistakes made during the manual digitalization. Since we do not know how often these errors occur, it is difficult to make objective assessments of the frequency of questionable classifications. The improved spatial resolution obtained from scanning is easily detected in Fig. 3. It is, however, doubtful if a finer resolution of these maps would

have had any major effect on the final analysis of the distribution of the soil wetness classes, made with a 125 x 125 m resolution. The coarse resolution of the topographic data is probably a more serious limitation. Firstly, the calculated slopes represent the slope between 500 x 500 cells, and will be unrealistically low. Secondly, a finer resolution is needed, especially in areas with a heterogeneous topography, to find the actual distribution between groundwater discharge- and recharge areas. The aim of this study was to detect the spatial variability of the hydrological response to climatic inputs in the form of soil wetness and water flows (evaporation and groundwater recharge), caused by landscape element variability, and not by spatial climatic variability. Therefore, the same set of meteorological data was used for all sub-basins. When recharge was calculated with local meteorological data from each sub-basin it was shown that the regional meteorological variability was of overriding importance for the spatial distribution of runoff generation. Runoff volume from the forested upland sub-basins became larger than from the agriculturally dominated lowlands when local precipitation data were used (Andersson, in preparation). It is evident that the climatic inputs are linked to the physiographic diversity, with elevation as the main factor. The diversity in water flows from different sub-basins, even for a small (1430 km2) and comparatively climatically homogenous region as the Svarti Basin, is thus often more dependent on the indirect effects of physiographic variability, in the form of mesoscale climatic variability, than it is directly effected by the variability of canopy cover, topography and soil characteristics. According to the analysis, changes of the areal distribution of different soil wetness classes since the 1870s were small for the study area (Fig. 7). Basin scale hydrological response to human alterations of landscape factors are often difficult to detect from records of runoff. This is due to the overriding importance of the natural climatological fluctuations, and the fact that the effects of interventions in the mosaic in different parts of the basin might counteract each other (Fig. 7). It is evident,

123 however, that the effects on runoff generation caused by artificial drainage and canopy cover changes can be large locally (Fig. 5). The classification rules were not based on absolute and objective criteria since the present knowledge quantitative relationships between hydrological variables and landscape factors is weak. The present knowledge of hydrological processes is mainly based on studies of small-scale processes (carried out in laboratories or on plots). Extensive field measurements of runoff, soil moisture- and groundwater dynamics, combined with remote sensing techniques, are needed to make it possible to further develop and verify hypotheses of how the soil wetness distribution and the various landscape factors are interrelated for different landscape elements. The GIS technique provides a good opportunity to integrate experiences from such studies. The results can be used to test and further develop distributed hydrological models, which considers the spatial distribution of soil wetness, groundwater levels, evaporation, and runoff generation. For such model applications, it is more appropriate to use an elevation data base with a better resolution than the 500 x 500 m base used in this study. A 50 x 50 m topographic data base will cover the whole of Sweden by 1989-90. A project which, in addition to maps of the distribution of physiologic characteristics, will use information of soil moisture and groundwater levels, collected from field measurements, and from an airborn SAR system (for which vegetation is transparent, and which has the capability to “see” below the soil surface), to test and further develop distributed hydrological models, has recently been initiated in cooperation between our Department at Linkoping University and the Swedish Defence Research Establishment.

Acknowledgements

Financial support from the Swedish National Science Research Council is gratefully acknowledged. The authors are indebted to Gunnar Petersson for making the GIS possible to use, Charina Bockerud for manual digitizing, and to Lisbeth

Samuelsson for drawing the figures. Thanks to Professors Reinhold Castensson, Malin Falkenmark and Ulrik Lohm for comments on the manuscript. References Andersson, L. 1988. Hydrological analysis of basin behaviour from soil moisture data. Nordic Hydrol. 19: 1-18. Andersson, L. 1989. Soil moisture deficits in south-central Sweden. I. Seasonal and regional distributions. Nordic Hydrol. 20: 109-122. Bergstrom, S. 1976. Development and application of a conceptual runoff model for Scandinavian Catchments. Bull. Ser. A No. 52, Dep. of Water Resour. Eng., Lund Inst. of Tech., Sweden. Beven, K. and Germann, P. 1982. Macropores and water flows in soils. Water Resour. Res. 18: 1311-1325. Beven, K.J. and Kirkby, M.J. 1979. A physically-based variable contributing area model of basin hydrology. Hydrol. Sci. Bull. 24: 43-69. Brandt, M., Bergstrom, S. and Gardelin, M. 1988. Modelling the effects of clearcutting on runoff - examples from Central Sweden. Ambio 17: 307-313. Bringfelt, B. and Hirsmar, P.O. 1974. A forest evapotranspiration model using synoptic data, SMHI, Rep. RMD, No. 36, Norrkoping, Sweden. Eagleson, P.S. 1982. Ecological optimality in water-limited systems. I. Theory and hypothesis. Wat. Resour. Res. 18: 325-340. Ekstrand, S. 1985. TM data for forest interpretation. Rep. FUF2/17. 4. Swedish Space Corporation, Solna, Sweden. Eyre, S.R. 1968. Vegetation and soils. A world picture. 2nd Ed., Edward Arnold, London. Falkenmark, M. 1976. Vattnets omsattning i olika delar av virt land. Hygien och Miljo 1: 2-10 (in Swedish). Gilliland, M.V. and Baxter-Potter, W. 1987. A geographical information system to predict non-point source pollution potential. Water Res. Bull. 23: 281-291. Hawley, M.E., Jackson, T.J. and McCuen, R. 1983. Surface soil moisture variation on small agricultural watersheds. J. Hydrol. 62: 179-200. Heikurainen, L. and Paivanen, J . 1970. The effect of thinning, clear cutting and fertilization on the hydrology of peatland drained for forestry. Acta Forestalia Fennica 104: 1-23. Hopkins, R.B., Jr. and Clausen, J.C. 1985. Land use monitoring and assessment for nonpoint source pollution control. In Perspectives on Nonpoint Source Pollution. pp. 25-29. EPA 440/5-85-001. Hudson, J.A. and Roberts, G. 1982. The effect of a tile drain on the soil moisture content of peat. J. Agric. Eng. Res. 27: 495-500. Jutman, T., Bergstrom, S. and Eriksson, B. 1989. Long term variations of the water balance in Sweden - a preliminary

124 study. The Publications of the Academy of Finland 9/89. Conference on Climate and Water 1: 103-110. Helsinki, Finland. Kardell, L. 1984. Ostgotaskogen, bonden och naturen (The forest of Ostergotland, the farmer and the environment). In Skogens Ostergotland, Linkoping, Sweden. pp. 1-17 (in Swedish). Lundin, L. 1979. Kalhuggningens inverkan p i markvattenhalt och grundvattennivier (Effects of clear cutting on soil moisture contents and groundwater levels). Rep. 36, Skogsekologi och skoglig marklara, SLU, Uppsala (in Swedish). Lundegren, J . 1983. Draneringsoptimism i 1980-talets Sverige (Drainage optimism in Sweden of the 1980s). Traktorjournalen 7/8: 6-7 (in Swedish). Moore, I.D. and Larson, C.L. 1979. Effects of drainage projects on surface runoff from small depressional watersheds in the north central region. Water Resources Research Center. Bull. 99. Univ. of Minnesota, USA. Minsson, E. 1988. 50 i r med ostgotskt jordbruk (50 yrs of agriculture in Ostergotland). AB Ostgota Correspondenten, Linkoping, Sweden. Newson, M.D. and Robinson, M. 1983. Effects of agricultural drainage on upland streamflow: Case studies in mid-Wales. J. Envir. Mgmt. 17: 333-348. Penman, H.L. 1948. Natural evaporation from open water, bare soil and grass. Proc. R. SOC.,London, Ser. A. 193: 120-146. Robinson, M. and Beven, K.J. 1983. The effect of mole drainage on the hydrological response of a swelling clay soil. J. Hydrol. 64: 205-223.

RosCn, K. 1984. Effect of clear-felling on runoff in two small watersheds in Central Sweden. For Ecol. Mgmt. 9: 267-281. Rowntree, P.R. and Sangster, A.B. 1986. Remote sensing needs identified in climate model experiments with hydrological and albedo changes in the Sahel. In ISLSCP - Proceedings, held in Rome, 2-6 December 1985. pp. 175-187. Seuna, P. and Kauppi, L. 1981. Influence of sub-drainage on water quantity and quality in a cultivated area in Finland. Publications of the Water Research Institute No. 43. National Board of Waters, Finland. Sivertun, A., Castensson, R. and Petersson, G. 1986. CIS - a tool for TEMA research. In Svensk Geografisk Arsbok. pp. 69-82 (in Swedish, summary in English). Sivertun, A. 1989. A geographical information system method to aid in area analysis. In Report from Workshop on Integration of Remote Sensing and PC-based Information Systems in the Management of European Marginal Land, Commission of the European Communities Joint Research Centre, SPI.89.40 ISPRA, Italy. Sivertun, A. and Castensson, R. Introduction of Farmland Drainage Technology in Sweden. Geografiska Annaler Ser. B Human Geography (submitted). de Vries, J . and Chow, T.L. 1978. Hydrological behaviour of a forested mountain soil in coastal British Columbia. Water Resour. Res. 14: 935-942. Wallen, C.C. 1966. Global solar radiation and potential evapotranspiration in Sweden. Tellus 18: 786-800.