Evaluation of three unit hydrograph models to predict the surface runoff from a Canadian watershed
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- Sarangi, A., Madramootoo, C.A., Enright, P. et al. Water Resour Manage (2007) 21: 1127. doi:10.1007/s11269-006-9072-9
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The predictability of unit hydrograph (UH) models that are based on the concepts of land morphology and isochrones to generate direct runoff hydrograph (DRH) were evaluated in this paper. The intention of this study was to evaluate the models for accurate runoff prediction from ungauged watershed using the ArcGIS® tool. Three models such as exponential distributed geomorphologic instantaneous unit hydrograph (ED-GIUH) model, GIUH based Clark model, and spatially distributed unit hydrograph (SDUH) model, were used to generate the DRHs for the St. Esprit watershed, Quebec, Canada. Predictability of these models was evaluated by comparing the generated DRHs versus the observed DRH at the watershed outlet. The model input data, including natural drainage network and Horton's morphological parameters (e.g. isochrone and instantaneous unit hydrograph), were prepared using a watershed morphological estimation tool (WMET) on ArcGIS® platform. The isochrone feature class was generated in ArcGIS® using the time of concentration concepts for overland and channel flow and the instantaneous unit hydrograph was generated using the Clark's reservoir routing and S-hydrograph methods. An accounting procedure was used to estimate UH and DRHs from rainfall events of the watershed. The variable slope method and phi-index method were used for base flow separation and rainfall excess estimation, respectively. It was revealed that the ED-GIUH models performed better for prediction of DRHs for short duration (≤6 h) storm events more accurately (prediction error as low as 4.6–22.8%) for the study watershed, than the GIUH and SDUH models. Thus, facilitated by using ArcGIS®, the ED-GIUH model could be used as a potential tool to predict DRHs for ungauged watersheds that have similar geomorphology as that of the St. Esprit watershed.