Suitability of watershed models to predict distributed hydrologic response in the Awramba Watershed in Lake Tana Basin
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Moges, M. A.; Schmitter, Petra; Tilahun, S. A.; Langan, Simon; Dagnew, D. C.; Akale, A. T.; Steenhuis, T. S. 2016. Suitability of watershed models to predict distributed hydrologic response in the Awramba Watershed in Lake Tana Basin. Land Degradation and Development, 43p. (Online first) doi: 10.1002/ldr.2608
Permanent link to cite or share this item: http://hdl.handle.net/10568/78547
Planning effective landscape interventions is an important tool to fight against land degradation and requires knowledge on spatial distribution of runoff. The objective of this paper was to test models that predict temporal and spatial distribution of runoff. The selected models were PED-WM, HBV-IHMS and SWAT. We choose 7 km2 Awramba watershed in the Lake Tana basin with detailed hydrological information for testing these models. Discharge at the outlet, rainfall and distributed information on infiltration rates, water table and extent of the saturated area were collected from 2013 to 2015. The maximum saturated area was 6.5% of the watershed. Infiltration rates exceeded rainfall intensities 91% of the time. Hence saturation excess runoff was the main runoff mechanism. Models were calibrated for the rainy seasons 2013, 2014 and validated for 2015. For daily flow validation, the PED-WM model (Nash Sutcliff efficiency, NSE = 0.61) outperformed HBV-IHMS (NSE = 0.51) and SWAT (NSE = 0.48). Performance on monthly time step was similar. Difference in model behavior depended on runoff mechanism. In PED-WM saturation excess is the main direct runoff process and could predict the maximum extent of the saturated area closely at 6.9%. HBV-IHMS model runoff simulation depended on soil moisture status and evapotranspiration, and hence was able to simulate saturation excess flow but not the extent of the saturated area. In SWAT where infiltration excess is the main runoff mechanism could only predict the monthly discharges well. This study shows that prevailing runoff mechanisms and distribution of runoff source areas should be used for proper model selection.
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