MULTI-LAYER MESH APPROXIMATION OF INTEGRATED HYDROLOGICAL MODELING FOR WATERSHEDS: THE CASE OF THE YASU RIVER BASIN

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1 MULTI-LAYER MESH APPROXIMATION OF INTEGRATED HYDROLOGICAL MODELING FOR WATERSHEDS: THE CASE OF THE YASU RIVER BASIN Toshiharu KOJIRI and Amin NAWAHDA 1 ABSTRACT A method for applying the multi-layer mesh typed runoff model approach using Hydro-BEAM (Hydrological Basin Environmental Assessment Model) into the regional watersheds is presented. The Yasu River basin in Japan is investigated as a case study illustrating the method. The spatiotemporal characteristics for both water quantity and quality are calculated using the kinematic wave model for saturated overland flow, and Richard s equation is used for the unsaturated subsurface flow. These models are combined for the case of the Yasu River basin in order to simulate runoff, interception, soil moisture, evapotranspiration, and recharge to groundwater. The formulation of the interception loss cause by roofs in city catchments is derived and used for estimating the effective rainfall amounts. The formulation of the reservoir is evaluated using the basin division approach (upstream and downstream of the reservoir). Human utilization of land is evaluated using the dynamics of land use approach. Historical hydrological data is used in the combination of the mentioned approaches, in order to achieve the integrated basin management. AKEYWORDS: Basin division; Kinematic wave; Land use; Unstaurated flow; Reservoir; Distributed runoff model 1. INTRODUCTION The Yasu River is located in Shiga prefecture, Japan, and is one of the main water sources for Lake Biwa, which supplies more than 14 million people in Kyoto, Kobe, and Osaka regions. Averaged annual precipitation for the regions ranges from mm for the lower and upper catchments, respectively. The area of the whole basin is 445 km 2, the area of the reservoirs catchments is 68 km 2 (see Figure 1.) and the length of the river channel is 95 km. The total population is approximately 22,. Small river flows and draw-down of the groundwater table in the lower catchments and conservation of the water quality are the main concerns in the Yasu River basin. 1 Water Resources Research Center, Disaster Prevention Institute, Kyoto University Gokasho, Uji, Kyoto, , Japan I-58

2 Integrated hydrological modeling of various basin scenarios using Hydro-BEAM allows for objective-orientated decision making to achieve efficient basin management. The impact of each decision can be therefore formulated mathematically as an objective function [1]. Several studies have been done for developing a hydrological model for the Yasu River basin. Kato has presented the use of the tank model for simulating the runoff and the operation of reservoirs for the upper catchments [8]. Kimaru developed a groundwater model for the lower catchments of the basin and investigated the impacts of land use changes [9]. A groundwater observation wells in the lower catchments of the basin have been constructed by Kyoto University, the collected data shows a drawdown of the groundwater levels. GIS based modeling was used for simulating the emission of pollutants from agricultural areas which spread along the river sides [12].the mentioned studies were limited to sub-catchments of the whole basin, meanwhile the basin response to the hydrological cycle has to cover the whole basin. The aim of this study is to develop a hydrological model that can be able to integrate the physical and nonphysical behaviors of the watershed. The integration process illustrates an increase of the nonlinearity, which is caused by the dynamic behavior of water flow, and the spatiotemporal variations of the differential coefficients relating to the physical quantities. These causes are affecting the validity of the linear hydrological model [6]. 1 1 km Figure 1. The Yasu River Basin/Japan 2. METHODOLOGIES The hydrological cycle involves complicated interactions between the atmosphere, surface water, and groundwater. A large-scale model was developed by Jennifer [4] for areas with a shallow groundwater table, and it was found that 5-2% of the groundwater is evaporated from the basin each year. The three-layer model has mathematical and physical constraints due to different residence times of water within each layer. One approach is to include the interactions between each model using a statically-linked coding of input data with Hydro-BEAM, by using averages of the output of the other models [1]. Another approach is to use a dynamically-linked coding with Hydro-BEAM. For the case study of the Yasu River basin, the first approach is I-59

3 used. The watershed is classified into recharge meshes and discharge meshes. Precipitation infiltrates in recharge meshes and the excess forms the runoff in discharge meshes, which flows laterally to a seasonal stream during rain events through the subsurface layer which has a relatively high hydraulic conductivities [5]. The stream volume is highly affected by the spatiotemporal characteristics of the land use, and the human utilization of land. Runoff The meshes of the basin are classified into river and slop types; each mesh is modeled using N layers, with the surface layer using the kinematic wave model for unsteady one-dimensional flow, as illustrated by the following equations: A q + = rtx (, ) (1) t x m q= f( x, A) = α A (2) Where A is the area of the flow cross section, q is the discharge of the river or the overland runoff, r is the lateral flow, α and m in equation (2) are computed by using Manning equation, or sin( θ ) 2/3 q= AR (3) n Where θ is the average slope of the stream bed or the slope meshes, n is the roughness coefficient, and R is the hydraulic radius. Richard s equation for unsaturated flow in one dimension is used in order to simulate the moisture profile of the soil and to estimate the spatiotemporal recharge to groundwater. For calculating the potential pressure-saturation equation the Van-Genuchten style equation is used. Evapotranspiration ET Evapotranspiration is description of both evaporation and transpiration by the plants; the temporal behaviors of weather conditions and groundwater level are affecting the rate of ET. There are many methods to estimate ET according to the amount of available metrological data and. The heat and mass balance methods are used to evaluate the evapotranspiration for each mesh in the watershed according to Bulk Method. Interception A fraction of rainfall is not contributing with the runoff formation, caused by interception. The interception can be caused by the roof of houses in city meshes, also by the vegetation cover which has a certain storage capacity. A fraction of the intercepted water evaporates; another fraction falls to the ground in larger drops or flow I-6

4 over the body of the interceptor to reach the ground surface. The interception process is highly affected by the rainfall intensity and the conditions of the interceptor. The interception by vegetation is estimated using Horton equation (1919), or I = C+ VEt (11) Where I is the interception loss, C is the interception storage depth, V is the ratio of vegetation surface area to its projected area on the ground, E is the evaporation rate, and t is the storm duration. Interception by the city meshes is described as follows; Ir = Cr + VrEt (12) Where I r is the interception loss by roofs in city mesh, C r is the interception capacity of houses, V r is the area ratio of roofs and the total area of the city mesh. In the Japanese over urbanized areas in Japan the rain is intercepted and delayed by the roofs of the residential buildings, then drained to the streets drainage or evaporates. Basin division The basin is naturally divided into upper and a lower catchments, the upper catchments is subjected to dry and wet precipitations that differs in the time and the magnitude of the effective amount, also from a geological point view the startigraphy of the lower part, which is mainly fluvial, differs from the upper catchments, therefore the hydrological parameterization illustrates some problems for the calibration of the hydrological model. The infliction point between the upper and the lower catchments can be considered as an optimal site for constructing a reservoir which can be utilized for the disaster prevention, and a source of energy. The runoff is simulated using the kinematic wave approximation, the analytical solution for the conservation of mass and momentum equations show that the speed of the kinematic wave is a function of the runoff depth for the river and the slop meshes, therefore the wave propagation from the upper catchments down to the lower catchments will subjected to the will known shock wave [2], therefore the cascading of the wave catchments using the basin division approach in hydrological modeling is used in order to avoid the drawbacks of the shock waves. Reservoirs can be classified into two types; natural and controlled reservoirs, the controlled reservoirs are operated in order to achieve certain objective functions, this can be considered as a strong down stream control for the developed kinematic wave in the upper catchments and the kinematic wave approximation is no longer valid [13]. I-61

5 Dynamics of land use The dynamic behavior of the basin caused by physical or nonphysical processes, has a great influences on the representative quantitative and qualitative parameterization of the hydrological model. The seasonal parameterization is introduced in this study in order to enhance the simulation of the actual processes. This is can be considered as an indirect connection with laboratory and mathematically based models. The dynamics of the land use is related to the residence time of water in the basin [3], and to the human utilization of land. Kajisa has also shown the major effect of the paddy fields in Japan on the peak runoff of catchments and simulates the temporal storage capacity of the paddy fields [7]. Reservoir operation The reservoir is operated according to an operational outline that considers the designed functions. The probabilistic nature of the reservoir operation hardens the process of integrating with the physical hydrological models. An approach is presented in this study that considers the seasonality of the reservoir operation. The reservoir can be operated to supply water for irrigation, generation of electricity, drinking water, base flow of the river, and disasters prevention that might caused by floods. To achieve the mentioned objectives the number of operation seasons, and the extremes of the seasonal water demands and safety operation, are utilized for the hydrological model. Two methods were examined for routing the reservoir; at first to simulate the reservoir using the linear storage model. At second to use the basin division approach. Integrated Hydrological Modeling the integration between the mentioned hydrological process is achieved by considering the spatiotemporal conditions of the water cycle within each mesh, as shown in Figure 2. The rainfall will be subjected to losses due to interception and evapotranspiration, the remaining amount is considered to be the effective rainfall amount, there will be no developed surface runoff unless the saturation condition of the soil type is reaches at point (a), the saturation condition at this point depends on the groundwater level, evaporation, water uptake by plants, infiltration, or irrigation, and other existing sinks or sources. Surface Runoff Rainfall Event (a) Sub-Surface Layer Soil Moister Groundwater Level Figure 2. I-62

6 3. CASE STUDY: THE YASU RIVER BASIN In order to calculate the spatiotemporal distributions of the simulation results, the basin is divided into one kilometer by one kilometer square meshes (see Figure 3.). Land uses are classified into five types as follows: 1) mountains, forests; 2) paddy fields; 3) farms; 4) urban areas; 5) water bodies. There are two reservoirs are located in the upper catchments of the Yasu River basin. The Yasu reservoir is used to supply water for irrigation when shortages occur in the downstream area, and to control floods, and it has a capacity of (7.8 1) x 1 6 m 3. The Aoto reservoir is used to supply domestic water (.8 m 3 /sec) and to satisfy industrial water demand (.533 m 3 /sec). The monitored operation of Aoto dam at point (1) depends on the flow at point (2) at Yokoda Bridge, and at point (3) at Minagutchi (Figure 3.). The monitored flow is 1.68 m 3 /sec in the Yasu main stream. The basin division approach is used in order to model the operation of the two reservoirs. 2 Water intake Rain gage 3 1 Figure 3. Distribution of rain gages and water intakes The land use dynamic approach is used in order to simulate the seasonal behavior of the basin vegetation. The groundwater table in the Yasu River basin is highly affected by heavy rainfall in summertime, and is also affected by the seasonally increasing demands of water for agricultural production. There has been a clear draw-down of the water table over the past 3 years [9]. There are many causes for this trend, such as growing demands, urbanization, dynamics of land uses, and climate change. Hydro-BEAM is capable of considering most of these causes in simulating distributed rainfall-runoff. However the development of a groundwater model for the whole basin illustrates a certain difficulties. The available groundwater level observing wells are located close to the river main channel, also the number of wells which has a time series data is small. The complete equipotential map and the hydrological cross section of the whole basin are not available. The water is supplied from the reservoirs and other stations in the lower catchments. The water is used for domestic purposes, and agricultural and industrial productions. I-63

7 Simulation Requirements The catchments area is divided into meshes as shown in figure 4 and for each mesh the following distributed data are used: 1- Spatial data: Figure 4. 1 geological formation 2 soil map 3 elevation 4 land uses 5 slope 6 flow direction 7 existing sewers 2- Temporal data: 1 metrological data 2 land utilization 3 groundwater level 4 operation of existing sinks 5 water consumption 6 discharge of pollutants 3- Setting parameters: 1 total number of cells 2 small time step 3 simulation period 4- State parameters: 1 surface: roughness coefficients 2 soil parameters channel or sewer: roughness coefficients 4 parameters for Bulk evapotranspiration Elevation (m) Figure Elevation Mesh Number Figure 6. Paddy 2% City 13% Agric. 11% City 1% Agric. 4% Water 9% Paddy 8% Water 2% Mountain 65% Mountain 76% Figures 4, 5, and 6 show a sample of the distributed input data, the model allow for temporal seasonal updating of all input data for the land use dynamics approach. Figure 7. illustrates the rational method for calculating the representative infiltration and roughness coefficients for each mesh. Soil Map Land Use Map Soil 1 Soil 2 * j j i A i Utilization Paddy City Agriculture ** nl nl j j n = n i = A Figure 7. i I-64

8 RESULTS In the Yasu River Basin there are more than eight groundwater observation wells, the groundwater level data for each mesh is evaluated according to the available equipotential maps of the basin, Figure 8. shows a sample of the used data. The water for human, industrial, and agricultural consumptions is distributed from the Aoto Dam, as shown in Figure 9. The simulated runoff at the Yasu Dam is shown in Figure 1 (1996/8), the small time step is (2 minutes). Unfortunately the observed measurements are unreliable and seem unsatisfactory. Therefore the change of the storage of the dam is used to estimate the daily average inflow from the upper catchments, the observed daily average runoff is (.7 t/s), and the simulated value is (.74 t/s). m Time (hr) Figure 8. Observed groundwater levels Water intake (m 3 /s) Minakuchi IshibeLeft IshibeRight Time (day) Figure 9. Water intake amount from Q (t/s) Runoff-Yasu Dam (96) Time (2min) (m/sec) Figure 1. I-65

9 The Hydro-BEAM is applied to hourly data from the upper and lower catchments using a historical data of ten years. Undefined parameters were adjusted by trial and error in order to minimize the residual error between the calculated and the observed data, as shown in Figure 11. The observed data is not shown here because further statistical analyses have to be done to check the reliability of the existing data. 6 Precipitation (mm/hr) Snow depth (mm), Temperature ( C) Evapotranspiration (mm/hr) Simulated runoff (m 3 /sec) Time (hr) Figure 11. Precipitation, snow storage, temperature, evapotranspiration, and runoff in the Yasu River basin outlet (1996). I-66

10 Figures 13 shows sample of the simulations for a rainfall event, evapotranspiration, and an assumed constant water uptake by plant, Figure 14. shows the corresponding temporal change of the soil water profile using one dimensional Richard s equation mm/hr Rainfall, Evapotranspiration, & Uptake by plants Figure 13. Time(hr) Temporal Soil-Water Profile The model can show the possible impacts caused by the change of the watershed characteristics such as the change of land uses, Figure 15. illustrates the predicted change if the government will use 3% of the agricultural areas for urbanization. Water content hr 12 hr hr Figure 14. Time Depth (min)(cm) Figure 15. Q (t/s) Runoff -Aoto Dam (96) Rainfall Existing Future Time (2min) (m/sec) CONCLUSIONS The results from this study show that the Hydro-BEAM can be used effectively not only for the basin hydrological management, but also for the future planning; the model encounters many physical parameters which have a strong relation with human utilization of water and land. The model can provide an efficient tool for estimating the groundwater recharge; also it can provide an efficient tool for predicting the water related disasters. I-67

11 REFERENCES 1- Bear J Modeling Groundwater Flow and Pollution. D.Reidel, Holland. pp Beldring S. 2. Kinematic wave approximations to hillslope hydrological processes in tills. Hydrological Process 14: Beven K On subsurface storm flow: an analysis or response times. Hydrological Science Journal 4: Jennifer P. 22. Putting aquifers into atmospheric simulation models: an example from the Mill Creek Watershed, northeastern Kansas, Advances in Water Resources 25: Johansson P-O Diurnal groundwater level fluctuations in sandy till-a model analysis. Journal of Hydrology 87: Ishihara T Fundamental researches on the unit hydrograph method and its application. Japan Society of Civil Engineers 6: 3-3, pp Kajisa T. 21. Effect of paddy field on peak runoff: an unsteady 2D model study. International Commission on Irrigation and Drainage, 1 st Asian Regional Conference, Seoul. 8- Kato T. 22, Research on the water cycle for the upper basin of the Yasu River. Proceedings of the Yasu river basin project. Kyoto University. 9- Kimaro T. 22. Groundwater modeling coupled with SVAT model and its application to the Yasu River Basin. Annual DPRI, Kyoto University 45B: Kojiri T. 2.GIS-BASED environment model for water quantity and quality with river basin simulation, Kyoto University /WRRC/DPRI. 11- Kovacs G Methods to characterize groundwater-atmosphere interactions. International Association of Hydrology Scientists: Wallingford; pp Namkung, H. 22. An estimation of pollutant loading using GIS including the irrigation model, Tottori University. Proceedings of the Yasu river basin project. Kyoto University. 13- Shin H Modeling Of Rivers. Wiley New York; pp 9-(2-31). I-68