From Hazard to Consequence: Impact-Based Drought Monitoring and Prediction

Growth in satellite observations and modeling capabilities has transformed drought monitoring by enabling near real-time situational awareness. Yet many operational efforts still emphasize hazards rather than impacts, and they often miss the compound and cascading risks that frequently accompany drought, including heatwaves, wildfires, floods, and debris flows. In this presentation, we first introduce a real-time drought monitoring and seasonal prediction system that integrates diverse data streams with AI-based algorithms for drought forecasting (https://drought.eng.uci.edu/). We then describe how drought information can be expanded beyond hazard metrics by incorporating impact and vulnerability data to support impact-based assessment of extremes and decision-relevant risk insights (https://water.eng.uci.edu/).  Using several examples, we argue for an impact-centered drought monitoring paradigm that links hydroclimate conditions to physical and societal outcomes, such as crop yield losses, food insecurity, energy production disruptions, and labor impacts. We also highlight key challenges that must be addressed to make this approach operational, including inconsistent and incomplete drought impact records, limited Information about local water management and human interventions (e.g., demand, intra- and inter-basin transfers, pumping, and withdrawals), and persistent gaps between impact models and existing drought monitoring workflows. Finally, we discuss anthropogenic drought as a framing concept and show how impact-based drought analysis can be strengthened by representing drought as a coupled climate–human phenomenon rather than a purely climatic hazard.