Application of SWAT Model in Runoff Simulation of DMIP 2 Watersheds K. Venkata Reddy Asst Prof, Department of Civil Engineering/NIT Warangal, Warangal 506004, Email:
[email protected] Deva Pratap Prof, Department of Civil Engineering/NIT Warangal, Warangal 506004, Email:
[email protected] T. Reshma Research Scholar, Department of Civil Engineering/NIT Warangal, Warangal 506004, Email:
[email protected] V. Revanth Under Graduate student, Department of Civil Engineering/NIT Warangal, Warangal 506004, Email:
[email protected]
Abstract Developments in computer technology have revolutionized the study of hydrologic systems and water resources management. Several computer-based hydrologic/water quality models have been developed for applications in hydrologic modeling and water resources studies. Distributed parameter models, necessary for basin-scale studies, have large input data requirements. Geographic Information Systems (GIS) and modelGIS interfaces aid the efficient creation of input data files required by such models. One such model available for the water resources professionals is the Soil and Water Assessment Tool (SWAT), a distributed parameter model developed by the United States Department of Agriculture. The objective of the study presented in this paper is to evaluate the surface runoff generation for a well monitored experimental watersheds using ArcSWAT model. The model has been applied to the Distributed Model Intercomparison Project Phase 2 (DMIP2) watersheds. Rainfall data, Land Use (LU)/Land Cover (LC), soil data and Digital Elevation Model (DEM) data of the watersheds has been downloaded from the website of the Hydrology Laboratory (HL) of NOAA's National Weather Service (NWS), USA. The down loaded database has been modified in the GIS environment. The simulation of the runoff in watersheds has been carried out and is compared with observed runoff. The hydrologic behavior of watersheds has been studied based on the simulation results.
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The present study emphasized the applicability of ArcSWAT models in the watersheds with geospatial database and to understand the hydrologic behavior of the watersheds. Keywords: ArcSWAT, GIS, runoff simulation, DMIP 2 Watersheds
Introduction SWAT is the acronym for Soil and Water Assessment Tool, a river basin or watershed scale model developed by Dr. Jeff Arnold for the USDA agricultural research services (ARS). SWAT was developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watershed with varying soils, land use and management conditions over long periods of time. SWAT is a continuous time model, that is, a long-term yield model having the capability of scenario generation, so as to equip the policy makers with a wider range of options, which makes it the ideal tool to be used for such a study (Singh and Gosain, 2011). The Hydrology Laboratory (HL) of NOAA's National Weather Service (NWS) initiated the second phase of the Distributed Model Intercomparison Project (DMIP 2). The main aim of DMIP 2 is to invite the academic community and other researchers to guide the NOAA/ NWS's distributed modeling research by participating in a comparison of distributed models applied to test data sets in two vastly different geographic regions. The complete geospatial and hydrological
database
of
DMIP
2
watersheds
is
kept
in
the
website
(http://www.nws.noaa.gov/oh/hrl/dmip/2/) and made it available for public users. Luzio and Arnold (2005) described the background, formulation and results of an hourly input output calibration approach proposed for the SWAT watershed model. They applied the methodology for 24 representative storm events occurred during the period between 1994 and 2000 in the Blue River basin, USA. Kalin and Mohammed (2006) described the potential use of Next Generation Weather Radar (NEXRAD) technology as an alternative source of precipitation data to the conventional surface rain gauges. They calibrated and validated the SWAT model for monthly stream flow, base flow and surface runoff. Hydrographs generated from both gauge and NEXRAD driven model simulations compared well with observed flow hydrographs. Pranay et al., (2012) presented the critical hydrologic processes and corresponding SWAT parameters that affect the volume and timing of monthly flow generation in mountainous watersheds and also 584
suggest a common SWAT parameter set for snow dominated and mountainous watershed and the results justify the applicability of the ArcSWAT model in snow dominated and mountainous watersheds. This paper presents the application of ArcSWAT model in simulation of hourly runoff in the DMIP-2 watersheds.
Study area and Methodology The ArcSWAT model has been applied to the Blue river basin, USA. It is one of the experimental watersheds of DMIP-2. It has an area of 1233 sq km. The methodology adopted for simulation of flow in the Blue River is shown in Figure 1. Relevant geospatial and hydrological data of the study area has been downloaded from the website of the Hydrology Laboratory (HL) of NOAA's National Weather Service (NWS), USA in ASCII format. The ASCII data is converted to raster data and projected to UTM 14N. Then the geospatial data is clipped to the blue river basin. Selection of DMIP2 watersheds
Downloading the required hydrological data from the website
Preparation of Database as per the requirement of ArcSWAT model
Simulation of Sub-daily runoff using ArcSWAT Figure 1: Flow chart showing the methodology followed in the present study
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SWAT Model Application The input for ArcSWAT model consists of Digital Elevation Model (DEM), rainfall, soil characteristics, topography, vegetation and other relevant physical parameters of the watershed. ArcSWAT model is applied for the hourly runoff simulations of the watershed. The model has been used for the sub-daily runoff simulation. The extracted rainfall data of the study area which is in .asc format is converted to raster data using ArcTool box. Then all rainfall files are reprojected to UTM. Automatic delineation of watershed boundary and other sub-watersheds within the watershed has been carried out using DEM of the watershed in the SWAT model. The watershed boundary with sub-basins is shown in Figure 2. The slope map, soil map and Land Use/Land Cover map which are modified as per the standard classifications available in the SWAT model are shown in Figure 3, Figure 4 and Figure 5 respectively. The soil classes of Blue river watershed are as follows: sand (4.17%), Sandy Loam (24.87%), Silt Loam (0.21%), Loam (52.43%), Silt Clay (4.1%) and Clay (14.10%). LU/LC classes of the watershed are as follows: Evergreen Needle leaf Forest (4.2%), Deciduous Broadleaf Forest (13.41%), Mixed Forest (0.96%), Woody Savannah (77.37%), Grasslands (1.97%), Croplands (0.86%), Urban and BuiltUp (0.99%) and Cropland/Natural Vegetation Mosaic (0.21%). In SWAT, a watershed can be divided into multiple sub-watersheds, which are then further subdivided into unique soil/land use categories called Hydrologic Response Units (HRUs). In ArcSWAT model, Simulation of flow has to be carried out in the five steps (1) Project set up (2) watershed Delineation (3) HRU definition (4) Weather Generator data (5) Run SWAT.
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Figure 2: Automatic delineation sub-basins of Blue river basin in ArcSWAT
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Figure 3. Modified slope map of Blue river basin
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Figure 4. Modified soil map of Blue river basin
Figure 5. Modified Land use/Land cover map of Blue river basin
Results and Discussions August, 2002 rainfall has been used as input for simulation of runoff. The simulated runoff hydrograph is shown in Figure 6. Simulation results are shown in Table 1. From the hydrograph, it is seen that the volume of runoff and time to peak has been simulated within the variation 70%. However, the model was not able to capture the peak runoff. There are more than sixty parameters in SWAT model and it is difficult to have exact information on all these parameters. Some physical parameters such as Channel width and Channel depth vary along the channel reaches. These are the some of the reasons for improper simulation of peak runoff. It is observed that, the values of runoff on recession limb of hydrographs are higher than observed one. The channel roughness and infiltration parameters are may be the reasons for this behavior. The calibration and sensitivity analysis of model may improve the simulations.
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RAINFALL INTENSITY
SIMULATED
OBSERVED
Figure 6. Simulation and observed runoff hydrographs for the Blue river basin for the month of August, 2002
Table 1. Simulation results for Blue River Basin Rainfall month
Volume of runoff (mm)
Peak runoff (m3/sec)
Time to peak (sec)
observed
simulated
observed
simulated
observed
simulated
August, 2002
2596.716
2172.707
217.04
41.6
358
358
Conclusions This study describes the application of ArcSWAT model for simulation of sub-daily runoff on DMIP 2 watershed. The model has been applied for the August, 2002 rainfall data. From the simulation it is observed that, model is able to simulate the volume of runoff and time to peak runoff, but large variations are observed in peak runoff. This may be because that sensitivity analysis over the model parameters may improve the simulation results. Presently only one rainfall event is simulated to understand the applicability of ArcSWAT model for hourly flow simulation in DMIP-2 watersheds. The simulation of runoff for other rainfall events and study of hydrologic regime of watershed is under progress. The present study emphasized the applicability of ArcSWAT models in the watersheds with complete geospatial dataset and to understand the hydrologic behavior of the watersheds.
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References Luzio, M. Di. and J. G. Arnold. (2004). Formulation of a hybrid calibration approach for a physically based distributed model with NEXRAD data input. Journal of Hydrology. 298,136154. Kalin, L. and M. M. Hantush. (2006). Hydrologic Modeling of an Eastern Pennsylvania Watershed with NEXRAD and Rain Gauge Data. Journal of Hydrologic Engineering. Vol. 11(6),555569. Pranay, S., M. Ahmadi, and M. Arabi. (2012). GIS Application of SWAT- Hydrologic modeling in major river basins of Colorado. AWRA 2012 spring specialty conference new orleans, louisiana, march 26 28. Singh, A. and A. K. Gosain. (2011). Scenario generation using geographical information system (GIS) based hydrological modelling for a multijurisdictional Indian River basin. Journal of Oceanography and Marine Science. 2(6), 140147.
Acknowledgements Our sincere thanks to officials of Distributed Hydrologic Model Intercomparison Project - Phase 2 (DMIP 2) for maintaining the geospatial and hydrological data of DMIP 2 watersheds in the public domain through website (http://www.nws.noaa.gov/oh/hrl/dmip/2/).
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