Experimental Evaluation of a Flood Forecasting Tool
Between 2011-20, floods caused over 45,000 deaths with most occurring in lower-income countries (Guha-Sapir, 2020). Early warning systems (EWS) for floods can lower human and economic losses and improve post-flood recovery. But, underdeveloped dissemination infrastructure in lower-income countries typically limits their reach and adoption by the most vulnerable: poor less-educated citizens in more remote areas. Cost-effective infrastructure investments are also hindered by a lack of rigorous evidence on how best to relay flood alerts at scale. In collaboration with Google and Yuganter, we propose the first randomized evaluation of a flood EWS in India; it will pair cutting-edge forecasting and Android-based alerting system with grassroots volunteers armed with Android phones and trained in community outreach activities. We anticipate research insights on how to disseminate time-sensitive forecasts that encourage high-cost, higher-return avoidance behavior in response to environmental stressors induced by climate change. Findings will also inform EWS design as Google and Yuganter scale up their flood forecasting and alerting system to reach more than 500 million people in South and Southeast Asia in the next five years.