An Integrated GIS-AHP based Drought vulnerability Assessment for Kurnool district, Andhra Pradesh, India

Abstract

Among nature's most insidious hazards is drought. The consequences vary from region to region, and it is sometimes called a 'creeping phenomenon'. Our societies are increasingly being affected by droughts that have developed slowly and steadily over several years. Farming is negatively affected by droughts, which can result in devastating losses. The severity and frequency of droughts can vary widely depending on several factors, including climatic conditions, temperature, and economic conditions, such as population density and irrigated land conditions. Therefore, in comparison to conventional methods, remote sensing-based studies provide the most comprehensive monitoring and mapping of droughts. The study illustrates how Geographic Information Systems (GIS) can aid drought vulnerability assessments through the use of analytical hierarchy analysis and geographical information systems. This study uses GIS for spatial analysis of drought in Kurnool district, Andhra Pradesh, India. Thirteen parameters such as Slope, Elevation, Aspect, Soil texture, Geology/Lithology, Land use & Land cover (LULC), Drainage density, Distance from the water bodies, Ground water fluctuation, Normalized difference vegetation index (NDVI), Rainfall, Land Surface Temperature (LST) and Topographic wetness index (TWI)were chosen and considered for the study. In order to produce drought maps of both spatial and temporal extent, these indices were integrated. Using pair-wise comparison matrices, AHP calculates weights for each criterion. Drought Vulnerability Assessment (DVA) map is generated by analyzing the thematic maps of all the parameters. According to the combined multi-criteria decision making and GIS results, the drought vulnerability index is 42.5. Using the output DVA map, ample information will be available on drought severity in the region and agricultural vulnerability. Accordingly, this study proposes combining AHP with GIS to map drought regions.

Landscape-Scale Long-Term Drought Prevalence Mapping for Small Municipalities Adaptation, the Czech Republic Case Study

“…The national monitoring programmes do not provide sufficient detail for use at the municipality scale and, therefore, Geographic Information System (GIS) techniques and a multidisciplinary approach are required to better recognise the characteristics, occurrence, and effects of drought at the regional and local scale for sustainable production and land-use planning [32]. Besides climatic factors, landscape factors with high spatial variability must be involved.…”

“…Ref. [32] used the Analytical Hierarchical Process (AHP) method integrated in GIS with 13 factors-slope, elevation, aspect, soil texture, geology/lithology, LULC aggregated categories, drainage density, distance from water bodies, ground water fluctuation, normalised difference vegetation index (NDVI), see [17,35,36], rainfall, land surface temperature (LST), see [37][38][39], and topographic wetness index (TWI), see [39,40], to assess vulnerability to drought in the city of Kurnool, India. The study area covered approximately 8500 sq.km.…”