Leveraging open-source geospatial tools for drought risk analysis: Zambia case study

This report presents a comprehensive approach to drought risk assessment in Zambia using open-source geospatial tools and freely available satellite and climate datasets. Drought—one of the most damaging slow-onset hazards—affects agriculture, water resources, and livelihoods across Zambia, making rigorous, data-driven analysis essential for early warning and climate-resilient planning. Building on global drought classification frameworks and modern risk assessment methods, the study integrates hazard, exposure, and vulnerability components to generate national and sub-national drought risk profiles. Using QGIS as the core GIS tool, the study demonstrates how meteorological (SPI, SPEI), agricultural (NDVI, VHI), and hydrological indicators can be combined with exposure datasets such as crop area and population distribution. Vulnerability indicators related to sensitivity and adaptive capacity further refine the analysis. Together, these layers produce detailed drought hazard maps, vulnerability indices, and a final drought risk matrix identifying high-risk districts across Zambia. The case study illustrates the value of open-source data and tools supported by Python scripting, cloud-based data, and Earth Observation tools. The findings underscore the importance of integrated drought monitoring, targeted interventions, and anticipatory action. By adopting these methods, Zambia can strengthen climate resilience, enhance early warning systems, and support evidence-based drought risk management.