## Abstract Watershed areal rainfall estimation, which is one of the most important and fundamental aspects in hydrological forecasting and various kinds of catchmentโscale hydrological models, is widely used in the analysis of hydrological regime change, and its precision has a direct influence on
Comparative assessment of two distributed watershed models with application to a small watershed
โ Scribed by Latif Kalin; Mohamed H. Hantush
- Publisher
- John Wiley and Sons
- Year
- 2006
- Tongue
- English
- Weight
- 538 KB
- Volume
- 20
- Category
- Article
- ISSN
- 0885-6087
- DOI
- 10.1002/hyp.6063
No coin nor oath required. For personal study only.
โฆ Synopsis
Distributed watershed models are beneficial tools for the assessment of management practices on runoff and waterinduced erosion. This paper evaluates, by application to an experimental watershed, two promising distributed watershed-scale sediment models in detail: the Kinematic Runoff and Erosion (KINEROS-2) model and the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model. The physics behind each model are to some extent similar, though they have different watershed conceptualizations. KINEROS-2 was calibrated using three rainfall events and validated over four separate rainfall events. Parameters estimated by this calibration process were adapted to GSSHA. With these parameters, GSSHA generated larger and retarded flow hydrographs. A 30% reduction in both plane and channel roughness in GSSHA along with the assumption of Green-Ampt conductivity K G-A D K s , where K s is the saturated conductivity, resulted in almost identical hydrographs. Sediment parameters not common in both models were calibrated independently of KINEROS-2. A comparative discussion of simulation results is presented. Even though GSSHA's flow component slightly overperformed KINEROS-2, the latter outperformed GSSHA in simulations for sediment transport. In spite of the fact that KINEROS-2 is not geared toward continuous-time simulations, simulations performed with both models over a 1 month period generated comparable results.
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