Drought vulnerability range assessment: A dynamic and impact-driven method for multiple vulnerable systems

Abstract

Current approaches to identify vulnerability to drought often lack ground-truthing and transparent methodology; they are also often biased by expert subjectivity. Furthermore, most drought vulnerability assessments are seldom system-specific but of general social relevance. Consequently, resultant vulnerability maps are typically a general snapshot of case-specific decisions, lacking teeth in their statistical soundness and system-specific relevance. Thus, this study presents an impact-based method for a transparent selection of effective vulnerability factors for six vulnerable systems (social, economic, agricultural, ecological, water resources, and energy-industry) The study is based on a backward multivariate linear regression (MLR) model, which links vulnerability factors to historical drought impacts for the case of Iran. The drought vulnerability index (DVI) and the comprehensive drought vulnerability index (CDVI) are calculated by aggregating the vulnerability of the six systems. Four different weighting methods are then applied to combine driving vulnerability factors to assess the vulnerability of each system for three timesteps (2005, 2010, and 2015). The vulnerability values are presented as ranges by combining the results of four weighting methods. Furthermore, identified driving vulnerability factors are classified by their manageability. A range of 154 vulnerability factors were tested as possible drivers, from which 44 were identified as effective factors. Overall, the results especially highlight that the social and economic systems are vulnerable to drought. From a systemic perspective, socioeconomic factors, such as infrastructure development, health conditions, and industrialization, might play a crucial role in reducing vulnerability. Thus, they should be prioritized in vulnerability reduction programs.