Journal of Soil and Water Conservation
  • Year: 2021
  • Volume: 20
  • Issue: 2

Evaluation of parameters of SCS-CN-based models for prediction of runoff from watersheds of Jharkhand, India

1Ex-M.Tech. student, Department of Soil & Water Engineering, College of Agricultural Engineering, Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur-848125, Bihar

2Assistant Professor-cum-Scientist, Department of Soil & Water Engineering, College of Agricultural Engineering, Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur-848125, Bihar

*Corresponding author Email id: rksahu77@gmail.com

Online published on 26 August, 2021.

Abstract

Soil Conservation Service Curve number (SCS-CN) method is one of the popular methods to estimate the volume of direct surface runoff for a given rainfall. Recently, an improved version of SCS-CN model called as Sahu-Mishra-Eldho (SME) model was reported incorporating hydrologically sounder procedure for accounting antecedent moisture in the Mishra-Singh (MS) model, a modified version of the SCS-CN model. The present study estimates and evaluates the model parameters of the SME model, the MS model and the original SCS-CN model for the rainfall-runoff datasets of the selected four watersheds of Jharkhand (India). The model parameters were estimated by using the non-linear Marquardt algorithm of constrained least squares. The results indicated that for MS model and SME model, the optimum value of in all the four watersheds is zero. The optimum values of S for MS model for Adda-1, Chitankhari, Indra and Karimati watersheds are found to be 266.78, 256.61, 194.47 and 233.72 mm, respectively while the optimum values of S0 for SME model are found to be 194.39, 329.60, 214.51 and 259.90 mm, respectively. Further, the optimum values of in SME model are found to be 0.35, 1.15, 0.80 and 0.87, respectively. The value of greater than 1 in Chitakhari watershed indicates that there is a seepage inflow to this watershed from the nearby watershed.

Keywords

Curve Number, Direct runoff, Initial abstraction, Retention capacity, Model parameter