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University of Twente (ITC) 2006

Drought Risk Assessment using Remote Sensing and GIS : A case study of Gujarat

Chopra Parul

Titre : Drought Risk Assessment using Remote Sensing and GIS : A case study of Gujarat

Auteur : Chopra Parul

Université de soutenance : University of Twente International Institute for Geo-Information Science and Earth Observation (ITC)

Grade : Master of Science in Geo-information Science and Earth Observation in Hazard & Risk Analysis 2006

Drought is the most complex but least understood of all natural hazards. It is broadly defined as “severe water shortage”. Low rainfall and fall in agricultural production has mainly caused droughts. A droughts impact constitutes losses of life, human suffering and damage to economy and environment. Droughts have been a recurring feature of the Indian climate therefore study of Historical droughts may help in the delineation of major areas facing drought risk and thereby management plans can be formulated by the government authorities to cope with the disastrous effects of this hazard. In recent years, Geographic Information Science (GIS) and Remote Sensing (RS) have played a key role in studying different types of hazards either natural or man-made. This study stresses upon the use of RS and GIS in the field of Drought risk Evaluation. In the present work an effort has been made to derive drought risk areas facing agricultural as well as meteorological drought by use of temporal images from NOAA-AVHRR (8km) based Normalized Difference Vegetation Index (NDVI) (1981- 2000) and meteorological based Standardized Precipitation Index (SPI). Correlation and regression analysis was performed between NDVI, SPI, Rainfall anomaly and Food grain anomaly. SPI values were interpolated to get the spatial pattern of meteorological based drought. Food grain yield trend was plotted and an equivalent NDVI threshold was identified to get the agricultural drought risk. Similarly rainfall anomaly and NDVI were correlated and a threshold defined by IMD for meteorological drought was used to derive meteorological drought risk. The NDVI and rainfall was found to be highly correlated (r=0.6) in water limiting areas. Apart from this, the highest NDVI-rainfall correlation associated with one-month time lag shows rainfall event induced vegetation growth in subsequent periods. The NDVI-rainfall correlation was found to be highly influenced by mean rainfall condition and vegetation types. Highest NDVI-rainfall correlation was obtained for vegetation types in rainfed crops, followed by irrigated crops and subsequently by forest with minimum correlation. It is therefore concluded that temporal variations of NDVI are closely linked with precipitation. Results of correlation and regression analysis between SPI and crop yield showed that SPI could be used as an indicator of regional crop production. Since each of the factors ; NDVI, SPI and detrended food grain yield anomaly had positive linear correlation with each other it was observed that the above factors can be effectively used for monitoring and assessing the food grain production and thereby, appropriate agricultural practices can be adopted to minimize drought effects. Resultant risk map obtained by integrating agriculture and meteorological drought risk map indicates the areas facing a combined hazard. It also represents the frequency of years a particular area faced the hazard. It was evident from the study that central and northeastern parts of Gujarat are more prone to drought either agricultural or meteorological. The research shows motivating results that can be used in taking corrective measures timely to minimize the reduction in agricultural production in drought prone areas. The results obtained provide objective information on prevalence, severity level and persistence of drought conditions, which will be helpful to the resource managers in optimally allocating scarce resources.

Version intégrale (ITC)

Page publiée le 29 décembre 2011, mise à jour le 12 octobre 2018