| description abstract | A large area basin-scale (LABs) hydrologic model is developed for regional, continental, and global hydrologic studies. The heterogeneity in the soil-moisture distribution within a basin is parameterized through the statistical moments of the probability distribution function of the topographic (wetness) index. The statistical moments are derived using GTOPO30 (30 arc sec; 1-km resolution) digital elevation model data for North America. River basins and drainage network extracted using this dataset are overlaid on computed topographic indices for the continent and statistics are extracted for each basin. A total of 5020 basins with an average size of 3255 square kilometers, obtained from the United States Geological Survey HYDRO1K data, is used over the continent. The model predicts runoff generation due to both saturation and infiltration excess mechanisms along with the baseflow and snowmelt. Simulation studies are performed for 1987 and 1988 using the International Satellite Land Surface Climatology Project data. Improvement in the terrestrial water balance and streamflow is observed due to improvements in the surface runoff and baseflow components achieved by incorporating the topographic influences. It is found that subsurface redistribution of soil moisture, and anisotropy in hydraulic conductivities in the vertical and horizontal directions play an important role in determining the streamflow and its seasonal variability. These enhancements also impact the surface energy balance. It is shown that the dynamics of several hydrologic parameters such as basin mean water table depth and saturated fraction play an important role in determining the total streamflow response and show realistic seasonal and interannual variations. Observed streamflow of the Mississippi River and its subbasins (Ohio, Arkansas, Missouri, and Upper Mississippi) are used for validation. It is observed that model baseflow has a significant contribution to the streamflow and is important in realistically capturing the seasonal and annual cycles. | |
