Remote sensing and GIS based rainfall-runoff modelling using SCS-CN method: A case study of river Kelo in Raigarh district, Chhattisgarh

Abstract

Runoff is one of the most important hydrological variables used in most of the land and water resources applications. The determination of surface runoff at micro level is essential to address soil and water conservation practices in a watershed. Understanding the basic relationships between rainfall, runoff and soil loss are studied for effective management and utilization of water resources and soil conservation service. Curve Number (CN) method is mainly used for estimating infiltration characteristics of the watershed, based on the land use property and soil property. In the present study an attempt is made to estimate the surface runoff for Kelo River in Raigarh district, Chhattisgarh using SCS-CN method. Hydrological soil group (HSG), land use / land cover Map, Soil and multi spectral remote sensing data are used for the analysis. Runoff is computed for different areas barren land, agriculture, forest and hard surface. Based on these derived information soil classification falls under group A and group C. Performance evaluation of the SCS-CN method have been carried out by calculating mean absolute deviation (MAD), root mean square error (RMSE), coefficient of correlation (CC) and coefficient of efficiency (CE). During testing of SCS-CN method, the values of MAD, RMSE, CC and CE were found to be 2.18 mm, 4.03 mm, 92.7 % and 83.04 % respectively. These details are useful in identifying runoff potential in Kelo river in Raigarh district and developing appropriate soil and water conservation structures.