Surface Runoff Estimation Of Sind River Basin Using SCS-CN Method And GIS Technology
Abstract Rainfall and runoff are significant hydrologic component in the water resources assessment. Rainfall is the primary source of recharge into the ground water. Understanding of rainfall and runoff is necessary for assessment of water availability. The runoff generation procedure is extremely complex. Accurate runoff assessment is carried out for useful management and improvement of water resources. Many methods are available to estimate runoff from rainfall; however, the SCS-CN method still remains the most popular, fruitful and frequently used method. Runoff curve number (CN) is a key factor of the SCS-CN method and it is depends on land use/land cover (LULC), soil type, and antecedent soil moisture (AMC). Different parameters, like land use/land cover, hydrological soil characteristics (HSG), rainfall data (P), Potential Maximum Retention (S), Antecedent Moisture Condition (AMC), Weighted Curve Number (CN), that are the mandatory inputs to SCS model, have been either derived from remote sensing data or from conventional data collection systems. The advance application of Remote Sensing and GIS techniques used to estimate surface runoff based on different parameters. The total area of present study is 26207.02 km2 of Sind River Basin, located in the northern part of Madhya Pradesh, India. The daily rainfall data of 23 weather stations (2005-2014) was collected and used to predict the daily runoff from the Sind river basin using SCS-CN method and GIS technique for the duration of 2005-2014, annual average of daily rainfall are 777.07 mm and annual average of daily runoff calculated for Sind river basin are 133.71 mm. The developed rainfall–runoff model has been used to understand the characteristics of the watershed and its runoff.