Scale problems and aggregation in hydrological regionalization

Transcription

1 FRIEND: Flow Regimes from International Experimental and Network Data (Proceedings of the Braunschweig Conference, October 1993). IAHS Publ. no. 221, Scale problems and aggregation in hydrological regionalization INTRODUCTION G. E. ARNOLD & J. A. P. H. VERMULST Ministry of Transport, Public Works and Water Management, Institute for Inland Water Management and Waste Water Treatment, PO Box 17, 8200 AA Lelystad, The Netherlands Abstract Integrated water management needs new techniques, methods and tools to support the decision making process and the implementation of policy. In developing and applying a new hydrological model for the unsaturated zone, scale problems occur. The scale on which decisions have to be made differs strongly from the scale of the natural variability on which processes take place, especially for water quality problems. The modelling scale, which is determined by both the discretization of space and time, has been chosen in such a way that the natural variability of the processes can be simulated adequately. For the spatial information, which has been detailed extensively, use has been made of a Geographical Information System. In order to keep computation times and memory demands of data bases within acceptable limits, aggregation is necessary. The errors caused by aggregation could be considerably restricted by aggregation according to the purpose of the computations, i.e. taking into account the relevance of hydrological units for the results of the model. One of the tasks of the Institute for Inland Water Management and Waste Water Treatment (RIZA) is to promote a socially desirable water management of the inland waters. Considering the many, mostly conflicting interests, an integrated approach to water management will be necessary in executing this task. Integrated water management means taking into account both the relations between the water quantity and water quality aspects of the surface water and groundwater, and the relations between water management and the other fields of policy (environmental issues and rural and urban planning). For its activities on policy analysis and evaluation, RIZA has developed an extensive set of simulation models, the so-called PAWN models. Originally, the models were developed in order to optimize the water distribution on a national level, especially in times of water shortage. During the eighties, environmental problems such as dehydration of ecosystems and problems due to excessive application of manure became more and more important. In order to cope with the environmental problems mentioned above, existing models have been adapted and new models have been developed. An important problem during the redesign of the models is that the scale of policy, i.e. the scale on which decisions have to be made does not correspond with the scale of the natural variability of the processes which take place. There are two ways of classifying scales (Leynse, 1993). The first is a division according to the type of action. Besides the above mentioned scales of policy and variability of processes, the scale of

2 484 G. E. Arnold & J. A. P. H. Vermulst modelling and the scale of monitoring can be distinguished. On the other hand, scales can be divided according to physical dimensions. A distinction into a mondial, fluvial, regional and local scale is generally used. For each of these scales, a further distinction can be made into supra- or sub-scales (Table 1). In Table 2, both ways of classifying scales have been combined. For the three most important problems with which RIZA's instruments have to cope, water distribution, dehydration of ecosystems and manure problems, an indication is given of the physical scale on which various actions and features (respectively monitoring, variability of processes, modelling and policy) take place. As RIZA is responsible for the water management policy on a national level, this implies that for both water distribution and environmental problems, policy decisions have to be made on the (sub)fluvial scale (Arnold et al, 1993). The scale of natural variability of processes related to water quantity, as well as the monitoring scale of these processes, is generally regional. The modelling scale of the PAWN models is based on the regional scale of natural variability on the one hand, and the sub-fluvial scale of policy decisions on the other hand. The Netherlands are divided into 80 so-called PAWN districts. For each of these PAWN districts, the discharges or water demands can be computed by distinguishing a number of hydrological units. The results of the computa- Table 1 Terminology of scale levels. "Mondial" "Fluvial" "Regional" "Local" supra 10 9 km 2 sub supra sub supra sub supra sub 10 8 km km km km km km km 2 10 km 2 10 km 2 10 ha lha Table 2 Combination of scales for water distribution, dehydration and manure problems. Monitoring Variability in processes Mondial Fluvial Regional W W Local Q, D Q,D Modelling W, Q,D Policy W, Q, D W: calculations on water distribution; Q: water quality calculations; D: calculations on dehydration.

3 Scale problems and aggregation in hydrological regionalization 485 tions for each PAWN district form the input for a national water distribution network (sub-fluvial scale). The natural variability of dehydration of ecosystems and processes resulting from excessive supply of manure is generally on the local or even the sub-local scale level. For manure problems, this is illustrated by the fact that for the Schuitenbeek, a basin area of 8000 ha in Netherlands (Fig. 1), 75% of the total P load originates from only 15 % of the entire area. The temporal variability is also great: approximately 75 % of the yearly P load is transported during only 30 % of the year. In order to simulate the effects of excessive manuring adequately, the original modelling scale of the PAWN models has been detailed. In order to be able to make decisions on a national scale, a translation of the model computations on a local scale to results on a sub-fluvial scale has to be made. This paper deals with the way in which RIZA has tackled this scale problem. METHOD Model concepts Within the policy instruments the model for the unsaturated zone plays an important and central role. The model forms the core of the national water distribution model and serves as the hydrological base for water quality and eco-hydrological models. In order to simulate the changes in seepage or infiltration the model is linked to NAGROM (= the NAtional GROundwater Model for the saturated zone) (De Lange, 1991). Figure 2 shows an overview of the relation between some models of the PAWN instruments. The model for the unsaturated zone is a one dimensional model, in which the hydrological calculations are made for each hydrological unit. A hydrological unit is defined as a unique combination of vegetation, soil type and geohydrological situation. The different water flows can be simulated as a function of meteorological conditions taking into account the interaction with the surface water system. A hydrological unit is schematized into an one dimensional two-layered system, consisting of an effective root zone and a subsoil. The root zone and the subsoil can be subdivided into several soil physical units. Based on the soil map of the Netherlands (scale 1 to ), the soil is schematized into 23 soil units, which are converted to soil physical units by means of soil physical data. In combination with water quality models the soil is schematized into several segments to distinguish surface runoff, interflow and drainage. The processes are simulated in a time step stationary way, with time steps of 10 days. It is also possible to use shorter time steps. Because of this semi-stationary concept, the time step has a minimum value (De Leeuw, 1993). Geohydrologically, the Netherlands can be divided in two area types, the pleistocene area in the southern and eastern part of the Netherlands and the holocene area in the northern and western part. The holocene area in the northern and western part is mainly low lying areas (< 2 m a.m.s.l.). In the low polder areas high water levels which are controlled artificially prevail. The relatively higher sandy parts (> 2 m a.m.s.l.) in the eastern and southern part of the Netherlands have lower water levels and drainage is mostly by gravity. The interaction between the groundwater and surface water is related

4 486 G. E. Arnold & J. A. P. H. Vermulst ^ $> Meadows Maize Forests 5SJSSSS lllllllll Urban area Other land use Fig. 1 The Schuitenbeek area in the Netherlands. to groundwater classes. For each groundwater class a broken linear drainage function has been derived. The seepage fluxes are supplied by NAGROM.

5 Scale problems and aggregation in hydrological regionalization 487 DEMNAT- 2 NITSOL/PHOSOL AGRICULTURE MODEL B3R THE 'UNSATURATED ZONE DM NAGROM Fig. 2 Some models of the PAWN package. Scale level As already stated in the introduction, RIZ A has to prepare and to evaluate policy decisions on a sub-fluvial scale. Table 2 shows that for water quantity studies, the scale of natural variability and the scale of monitoring do not differ too much from the scale of policy. However, dealing with environmental issues like manure problems and dehydration of ecosystems, scale problems occur because the scale of natural variability and also the monitoring scale of these processes differ too much from the sub-fluvial scale of policy (Arnold et al., 1993). On the one hand, the formulae and concepts used to describe the processes should be adapted to the scale on which these processes take place. For example, for the simulation of leaching of nitrate and phosphorus through the soil profile, the drainage fluxes which for water quantitative studies consist of only one velocity component, have to be divided into two or even more velocity components. On the other hand, the modelling scale, which is determined by both the discretization of space and time, should be chosen in such a way that the natural variability of the processes can be adequately simulated. From earlier studies into the behaviour of nutrients in the soil (Kroes, 1990), it became clear that in particular the spatial discretization of the PAWN models showed too little detail. Therefore, in the first instance, the spatial information has been detailed extensively. With a Geographical Information System, several layers of information have been combined, resulting in unique hydrological units with areas corresponding to the local or sub-local scale level. The following layers of information were combined: 1. For the areas with gravitational drainage elements from the NAtional GROundwater Model for the Netherlands (NAGROM) (De Lange, 1991), for the "polder" areas the contours of various polders. Both NAGROM elements and polders correspond with seepage or infiltration fluxes from or to the deeper groundwater. 2. A map with groundwater fluctuation classes. This division into areas with more or less the same pattern of groundwater fluctuation is thought to be characteristic for the interaction between groundwater and surface water, i.e. drainage and infiltration of surface water. 3. Soil physical units. These units represent the physical characteristics of the soil and therefore determine the permeability of the soil and the intensity of capillary rise.

6 488 G. E. Arnold & J. A. P. H. Vermulst 4. Information on land use. With this information layer the évapotranspiration characteristics can be determined. In order to guarantee the implementation of the above schematization for the entire area of the Netherlands, only nationwide geographical data bases have been used. The first layer, that of the NAGROM elements, can be characterized as regionally scaled. The groundwater fluctuation classes have been derived from the Netherlands soil map scale 1:50 000, whereas the soil physical units have been derived from the Netherlands soil map scale 1: Information on land use comes from the LGN data base (a national land use data bank), a grid-oriented data base consisting of pixels of 25 x 25 m, derived from satellite images. In order to avoid information loss in advance, the original data bases have been applied as far as possible. However, the land use data have been aggregated from 25 x 25 m pixels to 100 x 100 m pixels, because even on a subregional scale, the number of hydrological units became too large. Applying the above method of schematization, the model concepts have been tested extensively for the (sub-regional) basin area of the Schuitenbeek (Vermulst, 1993). For this basin with an area of approximately 8000 ha, 265 hydrological units were derived. Extrapolating to the national level, this implies approximately unique hydrological units, which is far too many. In order to keep computation times and memory demands of data bases within acceptable limits and in order to keep control over the computations, further aggregation steps have to be made. Methods of aggregation For the aggregation of hydrological units, several methods can be applied. The most simple form is scaling up of input data on the basis of the area of the map elements (elimination of small map elements by assigning them to the largest neighbouring map element). An important disadvantage of this method is the fact that the proportions between several classes will change. Hydrological units with a relatively small area or consisting of a large number of map elements, which are often of major importance for the processes, might be assigned to larger map elements of minor importance for the processes. Bakker et al. (1991) developed a method to maintain the original area distribution, namely by assigning different weighting factors to each class. For applications on national (sub-fluvial) scale, this method is not suitable, because the weighting factors cannot be derived in a uniform way and may be different for each region. A more elegant solution is aggregation according to the purpose of the computations. Taking into account the relevance of hydrological units for the results of the model, for certain applications, the errors caused by aggregation could be considerably restricted. The interaction between the phreatic groundwater and the deeper groundwater (seepage or infiltration fluxes), as well as the interaction between the phreatic groundwater and the surface water (drainage fluxes), are more or less the basis for the model applications dealt with in this paper. Not only are both seepage and drainage fluxes of great importance for the calculation of the water balance, but they also determine to a large extent the dehydration effects on vegetation types and the transport of nutrients into groundwater and surface water. Therefore, the schematization of geohydrological units (NAGROM elements or "polders") and the information layer of groundwater fluctuation classes have not been aggregated in the first instance. The restriction of the number of

7 Scale problems and aggregation in hydrological regionalization 489 hydrological units is mainly achieved by aggregation of soil physical units and types of land use. In the first instance, this aggregation takes place by using so-called cluster dendrograms. In these dendrograms, which can be derived by several mathematical techniques, combinations of groundwater fluctuation classes, soil physical units and land use types can be compared on the basis of differences in a "decision parameter". This parameter is thought to be decisive for the processes. An example of a cluster dendrogram is presented in Fig. 3. Choosing a certain tolerance error on the x-axis, the possible combinations of soil physical units and land use types can be derived. Further aggregation can be accomplished on the basis of the area of the units. In agreement with the object of the calculations, certain units with a relatively small area can be maintained. RESULTS AND DISCUSSION The effect of aggregation is illustrated for the study in the Schuitenbeek area (Vermulst, 1992, 1993). Besides the so-called basic schematization, comprising 265 unique units, some five aggregation scenarios were worked out: Scenario 0 (SO): basic scenario, basic schematization (265 unique units). B2 B10 B9 B20 B3 B4 B18 B5 ' B14' B7 B8 ' L1 L14 L2 L4 L12 L3 B12- B13- B16- B19- L13- L12- L7 : 115 ;M Error in decision parameter (mm) J I I I I I I I I I I ^ B : soil physical units L : type of land use Fig. 3 A cluster dendrogram related to manure problems.

8 490 G. E. Arnold & J. A. P. H. Vermulst Scenario 1 (51): joining of a number of soil physical units and land use types. Maintains distinction between maize and other agricultural lands and between clay, peat and sandy soils. With the exception of maize, all units <4.5 ha eliminated (result: 88 units of account). Scenario 2 (52): as 1. Per water table class 1 unit nature. Maize units < 1 ha and other units < 4.5 ha eliminated (69 units of account). Scenario 3 (53): as 2. Clustering of some NAGROM elements (33 units of account). Scenario 4 (54): As 3. Greater elimination of smaller hydrological units: maize <2 ha and others < 15 ha (23 units of account). Scenario 5 (55): "minimum" scenario. Experts choose three simulation units which peak as regards to surface and two maize units (5 units of account). Note: the 265 units for the Schuitenbeek area convert to approximately units in the whole of the Netherlands! On the basis of these 5 aggregation scenarios the discharges of the Schuitenbeek were calculated for the period 1977 to The results have been summarized in Table 3. In addition, the loads of nitrogen and phosphorus in the Schuitenbeek have been calculated for the period from 1988 to In Table 4, the results of the original schematization and two aggregation scenarios have been compared to measured nitrogen and phosphorus loads. The first aggregation scenario (56), consisting of approximately 30 units, corresponds to Scenario 4 mentioned above, with the difference that the distinction between podzol soil types and "eerd" soil types (the latter having a considerably higher content of organic matter), has been maintained in all cases. The second aggregation scenario (57) was derived entirely on the basis of area (elimination of all units with an area lower than 25 ha) and also consists of approximately 30 units. CONCLUSIONS Aggregation of the input from 265 to 23 units (Scenarios 1 to 4) hardly affects the calculated annual discharges. For all these four scenarios it applies that the error is less than 10%. The annual hydrograph hardly deviates from the calculations with the original schematization. The differences in the hydrograph between the measured discharges and the dis- Table 3 Calculated and measured average discharges in mm year" 1 and the statistical parameters S and D in mm months" 1 of measured and calculated discharges of Parameter Q A D Number of units Measured nvt Calculated SO SI S S S S = standard divergence in the monthly discharges; D = average absolute divergence between the calculated monthly discharge and monthly discharge derived from measurements. 5

9 Scale problems and aggregation in hydrological regionalization 491 Table 4 Calculated and measured yearly loads of nitrogen and phosphorus (tons), the standard divergence in monthly loads (tons) and the relative error (%) in computed monthly loads from 1988 to Parameter Measured Calculated Scenario 50 Scenario 56 Scenario 57 N S N RE N P 5 P RE P Number of units N, P = yearly loads of nitrogen, phosphorus (tons); 5 N P = standard divergence in monthly loads of N, P (tons); RE NP =relative error in monthly loads of N, P (%). charges calculated with the original schematization are a few times greater than the difference in hydrograph as a result of the aggregation of the input data. The aggregation scenarios 3 and 4 appear to be therefore serious options for generating the input on a nationwide scale. The calculation of N loads for the Schuitenbeek area is strongly determined by the hydrological situation and to a lesser extent by difference in type of land use and manuring intensity. Therefore, the results of the scenarios S6 and SI are similar and do not differ very much from the original situation. The P loads into the surface water are strongly determined by the depth phosphorus has intruded into the soil. Therefore, the calculated P loads strongly depend on the assumed manuring intensity and to a lesser degree on the calculated hydrological situation. This is illustrated by the fact that the results of P calculations are affected by aggregation in general and especially by the method of aggregation (scenario S6 versus SI). In order to guarantee the highest possible reliability of all model applications, RIZA has chosen to base the steps of aggregation upon the purpose of the calculations. REFERENCES Arnold, G. E., de Lange, W. J., Parmet, B. W. A. H. & Van de Ven, F. H. M. (1993) Schaalproblemenbij het gebruik van modellen op (sub-)fluvialeschaal; millimeteren op de vierkante kilometer. CHO-TNO Rapporten en nota's no. 31. Schaalproblemen in de Hydrologie. Bakker, H. C. & Allewijn, R. (1991) VergelijkingvanLandsatTM Landgebruiks-classificatiesen RuimtelijkeAggregaties. Meetkundige Dienst, Rapport nr. MD-LKR-R Kroes, J. G., Roest, C. W. J., Rijtema, P. E. & Locht, L. J. (1990) De invloed van enige bemes-tingsscenario's op de afvoer van stikstof en fosfor naar het oppervlaktewater in Nederland. Staring Centrum, Rapport nr. 55. Lange, W. J. de (1991) A groundwater model of the Netherlands. RIZA Report Leeuw, A. M. de (1993) Voorstudie Redesign DEMGEN; Tijdstap, berging oppervlaktewater en berekening vochtprofiel (T 1037). WaterloopkundigLaboratorium, Delft. Leynse, A. (1993) Probleemaanpak/schematisatie. CHO-TNO Rapporten en nota's no. 31. Schaalproblemen in de Hydrologie.

10 492 G. E. Arnold & J. A. P. H. Vermulst Vermulst, J. A. P. H. (1992) Redesign DEMGEN: Toetsing van de hydrologische schematisatie op afvoeren van de Schuitenbeek. RIZA werkdokument X. Vermulst, J. A. P. H. (1993) Toetsing van de waterkwaliteitsmodellennitsol en PHOSOLop stikstof- en fosfaatvrachten in de Schuitenbeek. RIZA nota