www.ijcrt.org © 2018 IJCRT | Volume 6, Issue 2 May 2018 | ISSN: 2320-2882 IJCRT1135347 International Journal of Creative Research Thoughts (IJCRT) www.ijcrt.org 311 Assessment of GIS and Remote Sensing-Based Flood Vulnerability of Shilabati River Basin Using AHP Method Ujjwal Bhandari 1 and Mousumi Roy 2 * Syamaprasad College, 92, Shyama Prasad Mukherjee Rd, Jatin Das Park, Patuapara, Bhowanipore, Kolkata, West Bengal 700025, India 1 Vivekananda College for Women, Diamond Harbour Rd, Jadu Colony, Barisha, Kolkata, West Bengal 700008, India 2 Abstract: Floods in the Shilabati River basin (3,019 km 2 ) are due to both climatological reasons and a combination of other factors related to the catchment. The existing flood risk forecasting system by the Indian Meteorological Department is devoid of a sound flood forecasting system though the downstream catchment is frequently affected by flood every alternative year. Therefore, in this study an attempt has been made to develop a workable forecasting system, considering remotely sensed data for analysis. Both the multi-criteria-based weightage method and the based approach are considered for finding the flood risk zones of the basin. Most of the agricultural watersheds in India are ungauged, having no records of the rainfall-runoff processes. This has led to the development of techniques for estimating surface runoff from ungauged basins. From the several methods for runoff estimation of ungauged watersheds, the curve number method (SCS-CN) is used here as a distributed model whose method along with its derivatives has been widely applied to ungauged watershed systems and has proved to be a rapid and accurate estimator of surface runoff. This method was originally developed by the US Department of Agriculture, Soil Conservation Service and documented in detail in the National Engineering Handbook, Hydrology (NEH-SCS). Landsat satellite images were used to obtain land cover information through the ERDAS Imagine 9.2 platform. The thematic layers like soil map, elevation map, rainfall map, and land cover map were created in the TNT mips platform. Curve numbers are assigned for different land cover and soil types. In the present study, the runoff varies from 3.91 mm to 64.83 mm of the study area. From the above-said method, we create an index-based vulnerability analysis that predicts the risk zones of the study area. Finally, five categories of flood risk were established (very low risk to very high flood risk zones; 0.009 to 0.088). However, it can give the flood risk probability in the basin very precise and cost-effective. Keywords: Flood vulnerability, Shilabati river basin, Geospatial technique, AHP, Flood risk index 1.1 Introduction Overflow of tidal or inland water by rapid accumulation of runoff in normally dry regions as partially or completely is a general temporary condition of Flooding (Jeb and Aggarwal, 2008). Floods are considered one of the most vulnerable natural hazards and are generally turned into disasters (Alcantara Ayala, 2002). Precipitation mainly occurs in the monsoon months (Viz. June to September). Floods cannot be controlled