Improved SCS-CN–Inspired Model有用 2012.pdfVIP

Improved SCS-CN–Inspired Model P. Suresh Babu1 and S. K. Mishra2 Abstract: The present study enhances the Soil Conservation Service curve number (SCS-CN) predictions by improving the model structure, considering the following issues of concern: implementation of antecedent moisture condition procedure, fixation of initial abstraction ratio (λ) at 0.2, usage of the potential maximum retention parameter, and incorporation of storm intensity or duration in runoff estimation. A five- parameter M3 model is proposed, with storm duration and a new parameter Sabs (potential maximum retention), to overcome most of the above limitations prevailing in the SCS-CN model. For simplicity and practical applications obviating storm-duration data, a four-parameter M4 model is also proposed. The performance of the suggested and the available models has been evaluated using the data of 82 small watersheds in the United States of America. As demonstrated, the M3 model performs the best, whereas the conventional SCS-CN model performs the poorest among all the models studied. DOI: 10.1061/(ASCE)HE.1943-5584.0000435. ? 2012 American Society of Civil Engineers. CE Database subject headings: Rainfall duration; Storms; Runoff; Hydrologic models. Author keywords: AMC; CN method; Rainfall-runoff model; SCS-CN; Storm duration. Introduction The USDA Soil Conservation Service curve number (SCS-CN) ap- proach is an empirical method for estimating rainfall excess. It is an event-based lumped conceptual model. Among the various rainfall- runoff models, the Natural Resource Conservation Service curve number (NRCS-CN) model, formerly called the SCS-CN model, is popular in use due to its simplicity, ease of use, widespread acceptance, and the significant infrastructure and institutional mo- mentum provided by the Natural Resource Conservation Service (NRCS). To date, no alternative has been proposed that possesses so many of these advantages, and therefore it has been and contin- ues to be commonly used