Combining machine learning and stakeholder expertise to uncover drought-society interactions
Understanding how drought affects society is key to building more resilient systems. In my research, I explore these interactions between drought and society using
- stakeholder expertise mapped through participatory modelling
- Machine learning on large datasets of biophysical drought indicators and socio-economic impact
Both approaches aim to to uncover patterns, feedbacks, and pathways of vulnerability that are often missed in conventional analyses.
Research Highlights
Several papers have been published on this topic.
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🔄 Understanding Compound and Cascading Impacts of Hydrological Extremes
This perspective outlines pluralistic methods—both quantitative and qualitative—for analyzing the complex, multi-sector impacts of droughts and floods, aiming to support more integrated and adaptive risk management.
đź“„ Earth’s Future, 2023 -
🌾 Exploring Flash Drought Impacts in Germany
This study examines the increasing frequency of flash droughts in Germany, linking biophysical conditions to perceived socio-economic impacts, and highlights the need for faster response systems and consistent monitoring to improve preparedness. đź“„ Environmental Research Letters, 2024 -
🌾 Socio-Economic Impacts of the 2018–2022 Multi-Year Drought in Germany
This study analyzes the socio-economic impacts of the 2018–2022 multi-year drought in Germany, highlighting distinct impact patterns and regional variations compared to single-year events, and underscores the need for tailored strategies to manage prolonged droughts.
đź“„ Natural Hazards and Earth System Sciences, 2024 -
🌍 Emergent Knowledge from Diverse Stakeholder Crowds on Cascading Drought Impacts
This study uses participatory modeling to demonstrate how pooling diverse stakeholder knowledge uncovers emergent insights, such as feedback loops and previously overlooked variables, that enhance understanding of cascading drought impacts.
đź“„ Environmental Development, 2024
