Flash drought detection and the identification of societal impacts through news articles
Postdoc: Gabriela C. Gesualdo
This research aims to advance impact-informed flash drought detection and risk management. Flash droughts intensify rapidly, and their detection remains challenging due to the lack of a universally accepted definition and differences among existing indicators. Beyond their physical characteristics, understanding the societal impacts of flash droughts remains a critical challenge.
We employ natural language processing and Large Language Models to identify flash drought events and extract information on their locations, timing, and reported impacts from historical newspaper articles.