Abstract

While droughts pose notable socio-economic impacts on societies, most of the related research has focused on droughts as a hazard. It is imperative to think beyond the in-practice approaches to provide more integrated tools and solutions for effective drought risk management. In connection with this, the present study introduces an integrated drought risk assessment framework to evaluate multi-dimensional high-resolution drought risk.  A Drought Risk Index (DRI) is computed at the tehsil level in Pakistan — a sub-administrative division under the district government where localized planning and decision-making take place. The DRI is based on Drought Hazard (DHI), Drought Vulnerability (DVI), and Drought Resilience (DReI) indices, which are systematically computed using a diverse range of data (i.e., the standardized precipitation evapotranspiration, soil, land-use land-cover, night-time light, population, and socio-economic variables among others). Furthermore, spatial modelling techniques (i.e., spatial autocorrelation and the Local Indicators of Spatial Association) are applied to locate and highlight statistically significant risk regions. In addition, this preliminary effort engages the state-of-the-art space-time pattern mining technique for the simultaneous spatial-temporal dynamics investigation of droughts. Pakistan exhibits a large geographical heterogeneity in terms of drought risk. Comparatively, the regions from Balochistan province are at the highest risk followed by Sindh. Notably, approximately one-third of Pakistan is identified as the hot spot with the highest drought risk (95% confidence). To an agrarian nation with ~220 million people and among the top 10 most vulnerable countries to climate change impacts, this situation ascertains grave threats under global warming. The comprehensive results from this study are expected to provide important and useful insights to prepare for drought mitigation, adaptation, and systematic impact evaluation in the face of environmental changes.

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