INTEGRATION OF SPATIAL INFORMATION TECHNOLOGY AND MULTIPLE DROUGHT INDICES FOR DROUGHT VULNERABILITY MAPPING IN ODISHA, INDIA

摘要

Spatial information technology, i.e. remote sensing (RS), geographical information system (GIS) and global positioning system (GPS) has proved to be an efficient tool in drought vulnerability assessment of any region around the globe. In this study, GIS and remote sensing techniques have been integrated with multiple drought indices to analyze the vulnerability of a region (Tel river basin) to drought in the Kalahandi district of Odisha, India. Numerous drought indices have been computed and maps of various drought indices have been generated through GIS based interpolation. The Standardized Precipitation Index (SPI) has been used to quantify the precipitation deficit. Standardized Water-level Index (SWI) has been used to assess ground water recharge deficit. The Normalized difference vegetation index (NDVI) and Normalized difference water index (NDWI) were analyzed to monitor the vegetation vigor and moisture availability. The years 1966, 1972, 1979, 1987 and 2002 were the most drought-affected years during the investigation period as revealed by the SPI analysis using inverse distance weighted interpolation. The NDVI values of the study area varied from -0.13 to 0.69 and the NDWI values varied from -0.44 to 0.97. NDWI values decreased more in response to drought conditions than NDVI, indicating that NDWI was more sensitive than NDVI to the onset of drought conditions. The time series analysis of SWI maps indicated that hydrological drought in the watershed during both the pre-monsoon and post-monsoon periods varies from no drought conditions to mild drought conditions in all most all the years under observation. The drought vulnerability maps generated through various drought indices like SPI, NDVI, NDWI and SWI indicate that meteorological, hydrological and vegetative droughts in the Tel river basin are not linearly correlated with one another. The study shows that combination of various indices offer better understanding and better monitoring of drought conditions in this region.