Integrated remote sensing and GIS based spatial modelling through analytical hierarchy process (AHP) for water logging hazard, vulnerability and risk assessment in Keleghai river basin, India
摘要
Water-logging disaster is a most important environmental as well as socio-economic problem which directly associated with the utilization of soil and land resources in agricultural command areas. Water resource management and conservation is a crucial approach for agricultural development in a basin area. To identify the maximum extent of waterlogged area in a basin during the pre-monsoon, monsoon and post monsoon season necessitated a multidisciplinary approach that integrates the spatial and non spatial attributes on Geographical Information System (GIS) that can be used by the decision makers for implement strategy of the problematic area in term of waterlogged and flood prone region. The main objective of the present investigation is to identify and mapping of the waterlogged disaster areas and it associated risk using an Analytical Hieratical Process and GIS model through ArcGIS model maker in the Keleghai river basin, India. For this purpose, the post monsoon multi-temporal (1976, 1979, 1987, 1990, 1996, 2000, 2005 and 2009) Landsat™ satellite imagery, topographical maps, ASTER Digital Elevation Model, ground water table and population data have been used to identify the severity level of waterlogged areas and the associated vulnerability level in the basin. We applied digital remote sensing techniques like normalised differences water index, normalised differences vegetation index and normalised differences moisture index to identify the water content pixel from the multi-temporal Landsat™ data. On the other hand, we have considered topographic variation, distance from river and post monsoon groundwater depth as a proxy for waterlogged hazard zoning. In the present study, we applied spatial modelling through Analytic Hierarchy Process (AHP) and GIS to demarcate the hazard and risk level in terms of severe, high, moderate and low. The basic model approach is the conversion of all the thematic layer attributes into a normalised weighted raster as per the water holding capacity through AHP and Multi Criteria Decision Support System. Thereafter, we used combined operation through ArcGIS raster modelling to mapping the severity level of waterlogged hazard area. The assessment of socio-economic impact, we have calculated risk by considering different vulnerability exposures viz. population distribution, settlement density and landuse/landcover. The study demonstrates the integrated remote sensing and GIS based spatial modelling to detect the waterlogged hazard and it associated risk level that occurred due to excessive accumulation of rain and floodwaters. The result depicts the waterlogged hazard zones viz. severe, high, moderate and low and its associated risk levels in the study area which can be helpful for better planning and management of both the drainage system and agriculture activities.