Probably, agriculture sector is the most vulnerable to extreme weather event such as drought. Droughts are expected to become more frequent and severe in different spatial and time scale in future, with increasing demands, limited and uncertain supplies, and effects of climate change and climate variability. Faced with these challenges, decision makers and planners need information to assist for drought preparedness, allocate resources effectively, and reduce impacts. To minimize the potential harm associated with expected frequent and severe droughts, inhabitants and community need an accurate assessment of the vulnerability of the ecosystem in which they live, and associated adaptation opportunities and constraints. In order to cope the effect of drought in proactive manner by taking up vulnerabilities through a risk management approach, an understanding of the connection of droughts with climatic and local factors like water demand and environmental parameters is essential (Mishra et al., 2010).
Various researchers have been analyzed the concept and defination of vulnerability and concluded that vulnerability has three components (i) the susceptibility of society (i.e. converse of adaptive capacity) which depend upon attributes of society (ii) exposure to hazard (eg. water stress) (iii) coping abilities ( Kates, 1985; Chambers, 1989; Blaikie et al., 1994; Bohle et al., 1994; Downing and Bakker, 2000). Vulnerability mapping can be used in all phases of disaster management viz., prevention, mitigation, preparedness, relief and recovery. There is a increased attention and urgency to undertake research on assessment and mapping of vulnerability with paradigm shift in approach to disaster management world over from relief and response centric towards preparedness, prevention and mitigation centric (Fontaine and Steinemann, 2009).Vulnerability assessment is a foremost step to prepare the contingency plans for a hazard.
Vulnerability of a system is a relative and dynamic measure, it changes due to change in behaviour of society, their adoption to technology, practices and policies. It varies at different temporal and spatial scale, even it varies from season to season from extreme crisis to complete safety (Downing and Bakker, 2000; Wilhite, 2000). The very purpose of assessing vulnerability is to identify and prepare appropriate strategy to reduce the impact of potential damage by a hazard. Over the previous years, the need for vulnerability assessment have been highlighted by many researchers over extant approaches (e.g., impact assessment), and its methodology (e.g. Ribot, 1996; Klein et al., 1999; Smit et al., 1999; Klein and Maciver, 1999; Downing et al., 2001; Kasperson, 2001; Smith et al., 2001; Walker et al., 2002; Anderson, 1994; Eastman et al., 1997; Hewitt, 1997; Keenan and Krannich, 1997). However, because of the complexity of the issue of vulnerability, assessments are commonly subjective and vary between regions and hazards.
Drought is most complex and least understood among the all natural hazards and its vulnerability is not directly observable phenomenon. Because of complexity of system, quantifying the vulnerability to drought is challenging task. Many factors affecting vulnerability to drought but their inclusion depend on data availability. Despite limitations, regional scale drought vulnerability assessment could help decision makers and planners to take appropriate mitigation and adaptation steps before the next drought event and minimize the impacts of that event (Wilhemi and Wilhite, 2002).
Different spatial scale vulnerability assessment is now become possible with the recent advances in remote sensing and GIS integrating various spatial data, but there are still vague methodological problems in fabricate and implementing model at larger scale. Droughts, like other natural phenomena, have spatial and temporal dimensions. Various drought studies necessitated the use of GIS environment for integrating data from different sources (De Jager et al., 1997; Ghosh, 1997; Reed, 1993; Matthews et al., 1994). Wilhemi and Wilhite (2002) presented a methodology for GIS based agricultural drought vulnerability in Nebraska using biophysical factors, viz., climate, soils, landuse, and access to irrigation. Similarly, Prathumchai et al. (2001) carried out a study to evaluate criteria for identifying drought risk areas using weighted linear combination of input factors of topography, soil drainage, ground water, irrigation area, annual evaporation, rainfall and rainy days. Slejko et al. (2009) presented GIS based methodology for drought vulnerability assessment for the agriculture for the west part of Slovenia using environmental factors, viz., solar radiation, soil water holding capacity, irrigation areas, agricultural land use and reference evapotranspiration.
In view of above, this study was undertaken to demonstrate a methodology to assess and map environmental vulnerability to agricultural drought in Rajasthan state of India. It aimed at adopting a conceptual framework of vulnerability, generate spatial datasets of key factors contributing to vulnerability using remote sensing and GIS, estimate weights of factors and then generate classified map of agricultural drought vulnerability. A novelty of this study is that it not only assessed seasonal vulnerability but also assessed and compared intra-seasonal vulnerability for early, mid and late kharif seasons. Further to validate the methodology, the agricultural drought vulnerability rating was compared with food grain productivity and human development index (HDI) at district level.
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