SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Importance of Detailed Soil Information for Hydrological Modelling in an Urbanized Environment 
Authors:van Tol, J.J., G.M. van Zijl and S. Julich 
Year:2020 
Journal:Hydrology 
Volume (Issue):
Pages: 
Article ID:34 
DOI:10.3390/hydrology7020034 
URL (non-DOI journals): 
Model:SWAT+ 
Broad Application Category:hydrologic only 
Primary Application Category:soil data resolution effects 
Secondary Application Category:baseflow and/or other hydrologic component analysis 
Watershed Description:630 km^2 Jukskei River, which drains a portion of Gauteng Province between the Cities of Johannesburg and Pretoria in northeast South Africa. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:Soil information is critical in watershed-scale hydrological modelling, however, it is still debated which level of complexity the soil data should contain. In the present study, we have compared the effect of two levels of soil data on the hydrologic simulation of a mesoscale, urbanised watershed (630 km²) in central South Africa. The first level of soil data, Land Type (LT) data, is currently the best, readily available soil information that covers the whole of South Africa. In the LT database, the entire study area is covered by only two soil types. The second level of soil data (DSM) was created by means of Digital Soil Mapping based on hydropedological principles. It resulted in six different soil types with different hydrological behavior (e.g. interflow, recharge, responsive). The two levels of soil data were each included in the hydrological model SWAT+. To compare the effects of different complexity of soil information on the simulated water balance, the outputs of the uncalibrated models were compared to the three nested gauging stations of the watershed. For the LT scenario the simulation efficiency calculated with the Kling-Gupta-Efficiency (KGE) for the three nested gauging stations (640 km², 550 km², 54 km²) of 0, 0.33 and -0.23 were achieved respectively. Under the DSM scenario KGE increased to 0.28, 0.44 and 0.43 indicating an immediate improvement of the simulation by integrating soil data with detailed information on hydrological behavior. In the LT scenario, actual evapotranspiration was clearly underestimated compared to MODIS-derived aET, while surface runoff was overestimated. The DSM scenario resulted in higher simulated aET compared to LT and lower surface runoff. The higher simulation efficiency of DSM in the smaller headwater catchments can be attributed to the inclusion of the interflow soil type which covers the governing runoff generation process better than the LT scenario. Our results indicate that simulations benefit from more detailed soil information, especially in smaller areas where fewer runoff generation processes dominate. 
Language:English 
Keywords:hydrological processes; hydropedology; predictions in ungauged basins; SWAT+ model