Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 25, 2009
Publication Date: November 3, 2009
Citation: Cho, J., Bosch, D.D., Lowrance, R.R., Strickland, T.C., Vellidis, G. 2009. Effect of Spatial Distribution of Rainfall on Temporal and Spatial Uncertainty of SWAT Output. Transactions of the American Society of Agricultural and Biological Engineers. 52(5):1545-1555. Interpretive Summary: Computer based hydrologic and water quality models have become a common tool for examining field and watershed scale processes. The models have proved to be useful tools for examining alternative management scenarios and their impact on the environment. However, the simplicity of model application and their widespread use has led to misuse, often resulting in incorrect interpretation of model results. One of the critical components of the process is the accurate representation of rainfall and its inherent spatial variability. This study examines several methods for incorporating spatially variable rainfall data into the Soil and Water Assessment Tool (SWAT), including the method currently used by the ArcView interface to the model (AVSWAT-X). Our findings indicate as the number of rain gauges used in the simulation decreases, the uncertainty in the hydrologic and water quality model output increases exponentially. In addition, methods which proportionally distribute the rainfall data across the watershed provide superior results to the current methods incorporated into the model. Proposed methods and results will be helpful for preparing multiple rain gauge input for SWAT and to better understand the possible effects of incorporating spatially variable rainfall into the model.
Technical Abstract: Accurate rainfall data are critical for accurate representation of temporal and spatial uncertainties of simulated watershed-scale hydrology and water quality from models. The objective of this study was 1) to assess the impacts of different methods for incorporating spatially variable rainfall input into the Soil and Water Assessment Tool (SWAT) on hydrology and water quality simulations and 2) to examine the seasonal and spatial uncertainties of the model output with respect to rain gauge density. The study uses three different methods to incorporate spatially variable rainfall into the SWAT model and three levels of subwatershed delineation within the simulated watershed. The impacts of ten different gauge-density scenarios on hydrology and water quality were subsequently evaluated by using the highest gauge-density scenario as a baseline for comparison. The centroid-method, currently used in AVSWAT-X interface, increased variations in measured annual rainfall and corresponding simulated streamflow as subwatershed delineation level changed from high-density to low-density. The Thiessen averaging method for each subwatershed (Thiessen-method) and the inverse-distance-weighted averaging method for the entire watershed (average-method) gave the same rainfall estimates for high, medium, and low resolution subwatershed delineation and the impacts of delineation on streamflow were less with these two methods. During 1987, with highest spatial variation in rainfall on LRK, at least 11% of the variation in predicted streamflow was due to variation in rainfall for the different watershed delineations. As a result, the Thiessen-method or the centroid-method with sufficient subwatersheds is recommended for SWAT simulation of a watershed with high spatial variability of rainfall. As the number of rain gauges used for the simulation was decreased, the uncertainty in the hydrologic and water quality model output increased exponentially. Total phosphorus was the most sensitive to the changes in rain gauge density with an average coefficient of variation (CV) of 0.30 from three watersheds, followed by sediment, total nitrogen, and streamflow. Seasonal variations in simulated streamflow and water quality were higher during summer and fall seasons compared to spring and winter seasons. These seasonal and temporal variations according to gauge-density scenarios can be attributed to the rainfall patterns within the watershed. Proposed methods and results will be helpful to prepare multiple rain gauge input for SWAT and to understand the possible effects of spatial and temporal scale on uncertainties of SWAT output from other watersheds.