Improved SCS-CN Model Incorporating Storm Duration and Rainfall-based Initial Abstraction for Runoff Estimation

Abstract

The need of incorporating storm intensity or duration in Soil Conservation Service Curve Number (SCS-CN) methodology for improved direct surface runoff estimation for a watershed has been highlighted by many engineers and hydrologists since long and despite this fact, it is still poorly explored. Therefore, this study aims to present storm duration-based improved SCS-CN models for estimating more accurate direct surface runoff from rainfall events. The accuracy and consistency of improved models are tested on a large rainfall-runoff dataset (18,660 rainfall events) derived from 39 watersheds in the USDA-ARS. Furthermore, the quantitative model’s performance is also evaluated employing six widely accepted statistical measures viz. root mean square error (RMSE), mean absolute error (MAE), normalized root mean square error (NRMSE), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), observations standard deviation ratio (RSR), and several grading criteria. These models are compared with the original SCS-CN model (M1) and its simple form (M2) with traditionally fixed initial abstraction ratio (λ) as 0.2. The resulting lowest values of RMSE, NRMSE, MAE, NSE, PBIAS and highest values of RSR and ranking grading system (RGS) for the proposed models (M3-M5) reveal that their performance is better than M1 and M2 models. The proposed M5 model incorporating both storm duration and varying initial abstraction (Ia) as a certain percentage of rainfall, performed the best followed by M3 incorporating only storm duration. According to RGS, M5 also ranked first with the highest marks (195) followed by M3 (140). Due to high accuracy in predicted runoff, M5 can be recommended for both small and large watersheds as it overcomes the following issues: fixed λ (=0.2), assumption of constant rainfall intensity (time-independent), fixation of Ia at 2% of rainfall and applicability to only small watersheds, restricting the application of original SCS-CN and its modified versions.

Impact of Changes in Short-Term Rainfall on Design Floods: Case Study of the Hnilec River Basin, Slovakia

“…According to Adornado and Yoshida (2010), Moretti and Montanari (2008), Soulis and Valiantzas (2012), and Mishra and Singh (2004), this method has become an inseparable part of many simulation models. Furthermore, the SCS-CN method can be applied to various landscape structures, soils, and climate conditions (Warner et al 2010;Vojtek and Vojteková 2016;Singh et al, 2015;Tedela et al, 2012;Mishra et al, 2012;Verma et al, 2021). These researchers have also indicated that the SCS-CN method can be effectively used for small and large river basins with heterogeneous land uses.…”