PLOT-DERIVED PARAMETERS FOR BASIN COMPUTATIONS

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1 Hydrological Sciences-Bulletin-des Sciences Hydrologiques, XXI, 1 3/1976 PLOT-DERIVED PARAMETERS FOR BASIN COMPUTATIONS GEORGE H. COMER and HEGGIE N. HOLT AN Hydrograph Laboratory, Plant Physiology Institute, Northeastern Region, ARS, USD A, Beltsville, Maryland 20705, USA Abstract. Data fiom small plots within a basin were used with a digital basin model to estimate parameters for computing runoff from the entire basin. The parameters inferred from soils and crop data were optimized using the digital model to compute runoff from the plots. The optimized values of soil and crop parameters were then used to compute the runoff from the total basin. The results demonstrate the value of plot data and the importance of a deterministic model which uses parameters derived from readily available soil and crop data. Paramètres derives de parcelles à des fins de calculs pour les bassins versants Résumé. On a utilisé des données de petites parcelles dans un bassin avec un modèle digital-hydrographique pour évaluer des paramètresjiour le calcul d'écoulement du bassin entier. Les paramètres qu'on a déduit des données des sols et des récoltes ont été optimisé par l'utilisation du modèle digital pour calculer l'écoulement des parcelles. Puis on a utilisé les valeurs optimisées des paramètres du sol et des récoltes pour calculer l'écoulement du bassin entier. Les résultats démontrent la valeur des données des parcelles et l'importance d'un modèle déterministique utilisant des paramètres dérivés des données facilement disponibles des récoltes et des sols. INTRODUCTION The use of basin models has increased dramatically during the past decade. These models have been developed by various agencies and groups to serve many purposes, e.g. planning, research, and environmental considerations. The ideal basin model would be one that can be used for all purposes; this model would of necessity be very complex. The Hydrograph Laboratory of the US Department of Agriculture has developed and is testing such a mathematical model (Holtan and Lopez, 1971 ; Holtan et al, 1975). This model treats a basin as a distributed system and attempts, by dividing it into zones, to operate on homogeneous hydrological response units of the basin. This model is essentially a complex accounting model which keeps a record of the additions and withdrawals of water by all the acting processes. Because of this unique feature, USDAHL-74 has not only been used to compute runoff from basins, but also to compute soil moisture status in a soil profile (England, 1975a), and évapotranspiration and percolation from lysimeters (England, 1975b; England and Coates, 1971), and to provide the rates and amounts of water movement for computing agricultural chemical transports (Frère et al, 1975). A model of this complexity requires many input parameters derived from available soil data, cropping patterns, topography, and specific climatic information. The parameters have a physical meaning and are measured directly or their values are inferred from measurements. Parameter adjustments are made by a direct search optimization technique (Comer and Henson, 1976) to achieve optimum fits with observed data. In the current study, hydrological records from small plots (1.83 m by 3.66 m) located to represent the diversity of a basin of approximately 20 ha, are used to optimize the parameters on soils and crops. These parameters were then applied to the hydrological zones of the encompassing basin to compute runoff. The model is next used to obtain the optimum 53

2 values for inferred basin parameters. This provides a bridge between small plots and basins and indicates that the model is capable of reproducing the runoff from small plots and from the entire basin using the plot parameters to represent zones of the parent basin. MODEL AND DATA REQUIREMENTS The 'USDAHL-74 Revised Model of Watershed Hydrology' is a mathematical treatment of the land phase elements of the hydrological cycle. A continuous accounting of water storage is maintained by the computational scheme. The basin is divided into zones based on soil characteristics, topography, elevation sequence, and land capability. If there is a diversity of crops on each zone, each crop is also recognized individually. The individual treatment of crops and zones makes this model a dispersed system that is very flexible and useful. The data requirements for this model include the climatological data, basin descriptors, and soil parameters. The climatological data include: (1) Precipitation: precipitation data are entered as the amount of precipitation since the last entry. Ideally, these data would be entered when the slope of the accumulation versus time curve changes, i.e. breakpoints. Precipitation must be designated as solid (snow) when it is not liquid. (2) Air temperature: temperatures are entered as weekly averages. (3) Evaporation data: evaporation data are entered as average daily evaporation from a Class A evaporation pan for each week of the year. Basin data required are: (1) Land use data: data regarding the land use, tillage practices, harvest dates, etc. for each crop. The data should be sufficient to assign percentages of each crop to each zone into which the basin has been divided. (2) Soil data: data on the final constant infiltration rate, the total porosity, field capacity, and wilting point are required. The topsoil depth and the total soil depth must also be known. (3) Crop data: the limit is nine crops for which estimates of the vegetative density, depression storage, ratio of potential évapotranspiration to pan evaporation, rooting depth and the upper and lower cardinal temperatures must be made. These three parameters are used with topographical data to divide the basin into zones of similar hydrological response. For each zone the parameters required are: number of hectares average slope of the zone, average slope length for each zone, the percentage of each crop in that zone, and the percentage of the zone that cascades to the next zone or the disposition of the water if it does not cascade. Analyses of regional or nearby streams or the study stream itself can be used to estimate groundwater recharge and the recession coefficients for subsurface groundwater flow (Holtan and Lopez, 1971; Holtan et ai, 1975). DISCUSSION AND RESULTS The basin used in this study, Watershed W-II, is located near Edwardsville, Illinois, USA (Fig. 1). Based on soil, land capability, and elevation sequence, the basin was divided into four zones. Within Zones 1, 2, and 3, small 1.83 m by 3.66 m plots were considered representative of the zones where they were located. Plot 69 represented only a small portion of the soil in Zone 3, but does represent 21 per cent of the crops on Zone 1 (grass and weeds) 54

3 Fig. 1 Watershed W-II near Edwardsville, Illinois, USA, showing zone boundaries and plot locations. so it was used to optimize the crop parameters for grass and weeds. Plot 68 represented the soils of both Zones 1 and 4. The data from each of the four plots were used to optimize 11 parameters. The optimization criterion was the minimization of the sum of the square of the deviations between computed and observed daily runoff. The 11 parameters are described briefly; for a complete description, see USDAHL-74 Revised Model of Watershed Hydrology. GR maximum rate of groundwater recharge [mm/h] ; f c final constant rate of infiltration after prolonged wetting [mm/h] ; FCAP1 field capacity in the topsoil layer (per cent by volume); FCAP2 field capacity in the subsoil layer (per cent by volume); A a vegetative parameter which theoretically is the percentage of porosity that is surface connected [mm/h/mm 1-4 ]; VD volume of depression storage that must be filled before overland flow begins [mm]; ETEP the ratio of evaporation potential to the pan evaporation, unique for each crop; Root depth the depth to which roots grow and effectively extract moisture [cm] ; T u the upper cardinal temperature at which a crop will grow without damage to the crop [ C] ; Ti the lower cardinal temperature at which a crop will grow without damage to the crop [ C] ; THAW the temperature at which snowmelt begins [ C]. 55

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5 Each parameter optimized is one which is either inferred from data or subject to errors in measurement which make the value less deterministic than some other parameters in the model. The parameter GR was optimized for each plot; however, this value as determined from a small plot cannot be used to represent a large basin because of the different flow re gimes which operate in a large basin. The initial estimates and the optimized parameters for each plot are given in Table 1. In each case, the standard error of estimate for daily discharge was reduced by at least 10 per cent by optimization. Figure 2 shows the computed versus observed runoff using the optimized parameters. The standard error of estimate for all plots combined is 4.6 mm which is 35 per cent of the standard deviation of the observed discharge. Fig. 2 Graph of observed versus computed daily runoff for four plots in Watershed W-II, Edwardsville, Illinois. The optimized parameters from the four plots were used to compute the flow from the entire basin and provided a significant improvement over using the initial parameters. Further improvement in the adherence of the computed versus observed data was obtained by optimizing the following zone parameters in the computations: slope, slope length, per cent of each zone that cascades to the next zone, and groundwater recharge. Table 2 presents the pertinent statistics which demonstrate the model performance with the four parameter sets. Figure 3 is a plot of observed versus computed daily discharge for Watershed W-II. The computations of discharge were made using optimized soil and crop parameters from the small plots and basin parameters which were optimized to give the minimum sum of the squares of the deviations between observed and computed daily discharge. This study demonstrates a method or model for using available data on soils, crops, and other agricultural practices, and which makes calculations on the areas within a basin in an elevation sequence consistent with flow paths in the basin. The model places in perspective the value of plot data in basin modelling. 57

6 OBSERVEO DAILY RUNOFF, mm Fig. 3 - Graph of observed versus computed daily runoff for Watershed W-II, Edwardsville, Illinois. TABLE 2 Initial and optimum parameter values for Edwardsville, Illinois, Watershed W-II Parameter GR Slope length [m] Zone 1 Zone 2 Zone 3 Zone 4 Slope [%] Zone 1 Zone 2 Zone 3 Zone 4 % Cascading to next zone Zone 1 Zone 2 Zone 3 S e [mm] Initial Optimized

7 SUMMARY AND CONCLUSIONS The results of this study demonstrate the use of USDAHL-74 Revised Model of Watershed Hydrology in matching several hydrological phenomena simultaneously. Basin runoff and the runoff from the four small plots were computed with good accuracy using the same input parameters for soils and crops. This study also demonstrates the value of plot data in basin modelling; these data could have been used without any basin data to derive the parameters for computing the runoff. These results suggest that the current model is a good representation of the hydrological cycle of a basin. It also demonstrates the feasibility of dividing the basin into homogeneous units for computations, based on the soils and topography. By critically studying the structure of this model and carefully examining the disparities between observed data and computed values, we should improve the model. REFERENCES Comer, G.H. and Henson, W.H. (1976) An optimization technique adapted to USDAHL-74 Revised Model of Watershed Hydrology. Wat. Resour. Bull. England, C.B. (1975a) Soil moisture accounting component of the USDAHL-74 Revised Model of Watershed Hydrology. Wat. Resour. Bull. 11 (3), England, C.B. (1975b) Root depth as a sensitive parameter in a deterministic hydrologie model. Wat. Resour. Bull. 11 (5), England, C.B. and Coates, M.J. (1971) Component testing within a comprehensive watershed model Wat. Resour. Bull. 7 (3), Frère, M.H., Onstad, C.A. and Holtan, H.N. (1975) Agricultural chemical transport model USDA ARS-H-3. Holtan, H.N. and Lopez, N.C. (1971) USDAHL-70 Model of Watershed Hydrology. USDA Tech. Bull. no Holtan, H.N. et al. (1975) USDAHL-74 Revised Model of Watershed Hydrology. USDA Tech. Bull. no

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