The Soil Conservation Service Curve Number (SCS-CN) is a well-established loss-rate model to estimate runoff. It combines watershed parameters and climatic factors in one entity curve number (CN). The CN exhibits an i...The Soil Conservation Service Curve Number (SCS-CN) is a well-established loss-rate model to estimate runoff. It combines watershed parameters and climatic factors in one entity curve number (CN). The CN exhibits an inherent seasonality beyond its spatial variability, which cannot be accounted for by the conventional methods. In the present study, an attempt has been made to determine the CN for different months of monsoon season with an objective to evaluate the impact of monthly CN on runoff estimation for Ozat catchment (Gujarat State, India). The standard CN and month wise CN were determined by three procedures, viz, the median, geometric mean and standard asymptotic fit using gauged rainfall and runoff. This study shows that the predictive capability of CN determination methods can be improved by using monthly CN. Refined Willmott’s index (dr) and mean absolute error (MAE) were used to assess and validate the performance of each method. The asymptotic fit CN method with monthly CN resulting dr from 0.46 to 0.49 and MAE from 1.13 mm to 1.18 mm was judged to be more consistent with the existing commonly used CN methods in terms of runoff estimation for the study area.展开更多
文摘The Soil Conservation Service Curve Number (SCS-CN) is a well-established loss-rate model to estimate runoff. It combines watershed parameters and climatic factors in one entity curve number (CN). The CN exhibits an inherent seasonality beyond its spatial variability, which cannot be accounted for by the conventional methods. In the present study, an attempt has been made to determine the CN for different months of monsoon season with an objective to evaluate the impact of monthly CN on runoff estimation for Ozat catchment (Gujarat State, India). The standard CN and month wise CN were determined by three procedures, viz, the median, geometric mean and standard asymptotic fit using gauged rainfall and runoff. This study shows that the predictive capability of CN determination methods can be improved by using monthly CN. Refined Willmott’s index (dr) and mean absolute error (MAE) were used to assess and validate the performance of each method. The asymptotic fit CN method with monthly CN resulting dr from 0.46 to 0.49 and MAE from 1.13 mm to 1.18 mm was judged to be more consistent with the existing commonly used CN methods in terms of runoff estimation for the study area.
