Comparative evaluation of models to estimate direct runoff volume from an agricultural watershed

Abstract

Generally, runoff records are the most important input data in water resource management; however, their availability is very limited especially in developing country as compared to rainfall records, especially under medium and small-scale catchments. In our study, we estimated runoff from ungauged agricultural watershed with the curve number method and empirical mathematical models were compared with SCS-CN. Empirical mathematical models (Inglis and De Souza Formula (IDS), Turc relationship (TR), Indian Irrigation Department (DII) model, Coutagine relationship (CR), Khosla method (KH), Justin Equation (JE), Lacey relationship (LR), and Indian Council of Agricultural Research (ICAR)) model were used to estimate annual runoff (in cm). It was found that IDS model has capability to simulate annual runoff as very close to Soil Conservation Service Curve Number (SCS-CN) model and has lowest Root Mean Square Error (RMSE) value as 7.75, and ranking of this model (based on K factor (value of 0.001) analysis) was topmost (or 1st) in comparison to other eight models. This study suggests that empirical mathematical model has potential for annual runoff estimation from ungauged watershed.