Estimation of Runoff Using USDA SCS-Curve Number and Autoregressive Time Series Model Parameters for Kachhinda Watershed, Morena District, Madhya Pradesh, India

Abstract

Hydrological modeling is an influential method for examining hydrologic systems, serving as a valuable tool in investigating these systems for both present studies involving two hydrologic runoff models viz. Soil Conservation Service Two methods, namely the Soil Conservation Service-Curve Number (SCS-CN) method and the Autoregressive Time Series model, were utilized in the Kachhinda watershed to estimate surface runoff, CN, and AMC conditions. The study area covers 600 hectares and is sited in Morena district of M.P. in Chambal division. The SCS-CN technique was employed to determine the curve number and estimate surface runoff by using the potential maximum retention. The CN of the watershed was calculated and compared to observed and estimated surface runoff, which were found to be in close agreement with each other. Additionally, an Autoregressive Time Series model was developed to establish the correlation between observed and estimated runoff, resulting in a correlation coefficient of 0.974. Different orders of AR time series models (0, 1, and 2) were tested to predict annual stream flow, and the model goodness of fit was evaluated using the Box-Pierce Portmanteau test and the Akaike Informations Principle. The Akaike Information Criterions value for the Autoregressive (1) model for runoff was found to be 0.919158, which is within the range of the values obtained for Autoregressive (0) (0.207433) and Autoregressive (2) (5.9767) models.