Characterizing spatial–temporal drought risk heterogeneities: A hazard, vulnerability and resilience-based modeling

Ali Khoshnazar, Gerald Corzo Perez, Muhammad Sajjad*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

4 Citations (Scopus)


Droughts are among the most socio-economically costly natural phenomenon. While most of the related research has focused on drought as a hazard, it is essential to go beyond such practice and utilize hazard information in integration with vulnerability and resilience. We put forth a multi-dimensional high-resolution assessment of drought risk in Pakistan on a national scale. To this end, we utilize a Drought Risk Index (DRI) based on integrated Drought Hazard (DHI), Drought Vulnerability (DVI), and Drought Resilience (DReI) indices. We further employ geospatial techniques to identify and pinpoint statistically significant clustering in the form of hot and cold spots (higher and lower values concentration, respectively). To the best of our knowledge, this is a preliminary effort to engage the state-of-the-art space–time pattern mining technique for the simultaneous spatial–temporal dynamics investigation of droughts. We observed varying north–south geographical distributions in DHI across the country with higher drought intensities in southern regions. While a sizeable spatial drought risk disparity is evident across Pakistan, the worst DRI results are seen in Balochistan, followed by Sindh. Notably, around one-third of the country is identified as the hot spot with the highest drought risk, which ascertains a grave situation under global warming. Our comprehensive results provide more insights to prepare for drought mitigation, adaptation measures, and systematic impact evaluation in the face of environmental changes.

Original languageEnglish
Article number129321
JournalJournal of Hydrology
Publication statusPublished - Apr 2023

Scopus Subject Areas

  • Water Science and Technology

User-Defined Keywords

  • Droughts
  • Geographic patterns
  • Geospatial modeling
  • Pakistan
  • Risk analysis


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