Runoff Depth Estimation using SCS-CN Method in Jhargram Community Development Block - A Remote Sensing and Geographic Information System Approach

Santanu Pani, Abhisek Chakrabarty, (doi: 10.23953/cloud.ijarsg.296)


Jhargram Community Development blocks which is situated on a watershed divider of Kansabati river basin and Dulung river basin. At a glance the area is suffering for water resource in some of the major parts. Surface runoff is one of the most important indicators of surface water availability, ground water recharge, soil practice etc. In this regard, estimation of runoff is highly needed for water resource planning, management and environment impact analysis. And Geographical Information System (GIS) and Remote Sensing (RS) techniques are used to calculate the runoff depth, it is one of the most time consuming way in recent days. The US Department of Agriculture (USDA), Soil Conservation Service Curve Number (SCS-CN) method which is the most widely used method is very effective in this study. In fact, the model is a quantitative description of land use-land cover and soil complex characteristics of a watershed and their impact on surface water flow. ERDAS Imagine 2014 and ArcGIS 10.1 are the platform which generate the input maps like sub watershed & micro watershed delineation, drainage map, soil map & hydrological soil map, classification of land use/ land cover, elevation & slope map, Rainfall map, area calculation for each class. The rainfall map is prepared from the rainfall data of different stations. After sequentially used the equations of SCS-Curve Number method the different years from 2010 to 2014, the final prioritization map has been generated which shows the value of runoff depth from high to low. Similarly, there has been shown the runoff-rainfall relationship over the last five years. Wherever the runoff depth is high, the infiltration rate is low due to soil and slope. With seeing the results of this case study, this can be used for further management of water resources as well as water scarcity of this area.


GIS; Remote sensing; Runoff; SCS-CN

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