Determination and Verification of Antecedent Soil Moisture Using Soil Conservation Service Curve Number Method under Various Land Uses by Employing the Data of Small Indian Experimental Farms

Antecedent soil moisture (ASM) is one of the most important factors affecting the rainfallrunoff modelling process. Its existence and influence in computing runoff using soil conservation service curve number (SCS-CN) method have been a point of discussion for many decades. In this study, a novel procedure has been proposed to calculate the ASM by modifying the SCS-CN method and verify its applicability by comparing the computed ASM with the observed soil moisture. Natural rainfall, runoff, and soil moisture data from eight small experimental farms with different land-use viz. sugarcane, maize, black gram, and fallow land, located at Roorkee, India, have been utilized. The ASM is computed by optimizing two parameters, i.e., absolute maximum potential retention (Sabs) and initial abstraction coefficient (lambda), and the optimization is carried out by minimizing root mean square error (RMSE). Results show that there exists a good correlation between observed and computed ASM for sugarcane, black gram, and maize with maize showing the highest correlation (R-2 > 0.6). Fallow land shows the least correlation (R-2 of 0.32), which may be due to the inadequacy of data. This study will be helpful in calculating ASM for ungauged catchments having different land use and will further broaden the applications of SCS-CN method.