American Journal of Science Engineering and Technology · 2019 · 14 citations · 0 references
Natural ResourcesEarth SciencesHydrologyCatchment HydrologyHydrologic ModelingWatershed HydrologyCatchment AnalysisHydrological ModelingRainfall-runoff AnalysisRainfall-runoff ModelingRainfall-runoff ProcessesRainfall-runoff RelationshipsCatchment-scale Hydrologic ModelingHydrological Model CalibrationHydrological Model ValidationInput Data AnalysisPrecipitation-runoff ModelingRunoff ModelingSurface Runoff ModelingUncertainty Assessment
This study was conducted to identify the best hydrological models in simulating the discharge in a comparative approach /SWAT and HBV light/ at Geba cathment and identifying of models which represent realistic simulation at sub basin scale. The various modelling procedure (i.e input data, sensitivity analysis, calibration, validation and uncertainty assessment) were employed to test the models performance. The results shows that K2, MAXBAS, BETA are more sensitive than other model parameters in HBV light model and CN2, GWQMN and SOL_AWC are more sensitive parameters in case of SWAT. The calibration results of HBV light and SWAT as evaluated by E<sub>NS</sub>, R<sup>2</sup> and PBIAS are 0.70, 0.71 and 0.73, 0.81, -11% respectively. Moreover, an E<sub>NS</sub>, R<sup>2</sup> and PBIAS of 0.71, 0.72 and 0.72, 0.72, 4.1% were obtained during validation Period for HBV light and SWAT models respectively. From the uncertainity plot for HBV light most of the simulated flow are inside the 95PPU with high predictive uncertainity band in Monte Carlo Simulation as comparsion with the SWAT CUP uncertainity analysis by SUFI 2 and from the uncertainity plot in SWAT model most of the simulated hydrograph is outside the upper and lower band and less predictive uncertainiy. These mentioned results depicted that both models are well reasonably simulated the discharge of Geba catchment and from uncertainity and identifiability of parameter applying HBV light model could be effective in simulation of runoff for sustainable water resources management in the watershed run off.