Development of a Modified SMA Based MSCS-CN Model for Runoff Estimation

Abstract

The Soil Conservation Service Curve Number (SCS-CN) method developed by the USDA-Soil Conservation Service (SCS, 1972) is widely used for the estimation of direct runoff for a given rainfall event from small agricultural watersheds. The initial soil moisture plays an important role in re-structuring of the SCS-CN method and enables us to prevent unreasonable sudden jump in runoff estimation and this has prompted the concept of soil moisture accounting (SMA) procedure to develop improved SCS-CN based models. Applying the concept of SMA procedure and changed parameterization, Michel et al. Water Resour Res 41(2):1-6 (2005) developed an improved SCS-CN model (MSCS-CN), which could be thought of an improvement over the existing SCS-CN method; however, their model still inherits several conceptual limitations and inconsistencies. Therefore, in this study an attempt is made to propose an improved SMA based SCS-CN-inspired model (MMSCS-CN) model incorporating a continuous function for initial soil moisture and test its suitability over the MSCS-CN and SCS-CN model using a large dataset from US watersheds. Using, Nash and Sutcliffe efficiency (NSE) and root mean square error (RMSE) of these models, the overall performance is further evaluated using rank grading system, and it is found that the MMSCS-CN scores highest mark (95; overall rank I) followed by MSCS-CN with 61 (overall rank II), and SCS-CN model with 51 mark (overall rank III) out of the maximum 105. This study shows Water Resour Manage that the proposed MMSCS-CN model has several advantages and performs better than the MSCS-CN and the existing SCS-CN model.

A Calibrated, Watershed-Specific SCS-CN Method: Application to Wangjiaqiao Watershed in the Three Gorges Area, China

“…Some researchers developed new models or modified the existing SCS-CN rainfall-runoff model by adding more parameters to improve surface runoff prediction accuracy [14,16,22,[37][38][39][40][41][42][43][44]. However, those modified rainfall-runoff models could not solve the problem faced by SCS practitioners or any software that has already integrated the conventional SCS-CN model or embedded λ = 0.20 into its software algorithm.…”

“…However, recent studies concluded that λ should not be a fixed value. Furthermore, some researchers also reported that λ value variation away from the proposed 0.20 value and lower than 0.20 was able to achieve better estimation of runoff prediction results in their studies [15][16][17][18][19][20][21][22]. Based on the median values of natural data for 307 watersheds, a group of researchers from the United States of America suggested a rounded value of λ = 0.05 to produce a better estimation of runoff depth [18].…”

Bivariate Return Period for Design Hyetograph and Relationship with T-Year Design Flood Peak

“…The major conflict is that the classic SCS-CN procedure allows for the estimation of cumulative rainfall excess (and thus cumulative losses) with rainstorms, but does not take time dimension into account in its equations. Several attempts have been made in order to overcome the conceptual limitations and inconsistencies of the original approach, for example, making explicit the concept of soil moisture accounting in a such a manner that is more suited for continuous simulations of rainfall-runoff processes [36,37] or proposing a mixed approach like the CN4GA, which aims to include the event scale correct information from the SCS-CN into the Green-Ampt infiltration equation [38]. Nevertheless, the SCS-CN method is currently indicated by the River Basin Authority of Calabria region as a part of the procedure for design flood estimation within the study region and thus was used in the following sections of the paper.…”

Improvement of the integration of Soil Moisture Accounting into the NRCS-CN model

“…The SS a model, which represents the first formulation that incorporates the SMA evaluation, while maintaining the original conceptualization and tractability, there are still some limitations in the model regarding the intrinsic parameters and the initial conditions. Moreover, the Soil Moisture Accounting (SMA) procedure is incorrectly used (Singh et al, 2015).…”

“…Since the release of this model, it has been the leitmotif of several attempts. Due to difficulties in characterizing the initial soil moisture content, most of the previous works have linked the antecedent conditions to API 5 (Durbude et al, 2011;Jain et al, 2012;Sahu et al, 2010;Sahu et al, 2007;Singh et al, 2015;Suresh Babu and Mishra, 2012). However, as previously shown, the use of this variable could lead to poor results.…”