Collaborative research: adaptation of populations to heightened flood incidence: satellite data and experimental evaluations of early warning systems

This Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program will fund a $417,787 research project at Yale University to investigate how farmers in low-income settings adapt to increased flood risks due to climate change. The research consists of two projects:

The first project will combine global flood data, NASA satellite imagery, and vegetation indices to assess the impacts of flooding on agricultural practices, crop choices, and public health. The second project will evaluate the effectiveness of a community-based flood early warning system integrated with Google's flood forecasting technology. This research aims to provide critical insights that can inform policies to increase resilience in flood-prone regions and guide U.S. foreign aid decisions. The award period is from August 15, 2024 to July 31, 2026.

Abstract

This award will fund a research project that investigates how farmers in low-income settings adapt to increased risk of flooding, the effects of these flood episodes on health, and how these farmers access and use information on accurate flood forecast. Climate change is increasing flood risks globally, impacting one in four individuals, but not much is known about how agriculture adapts to increased flood risk and this research makes significant contribution to our understanding of how farmers adapt to flood risks. The proposed research consists of two projects. The first project will combine the global flood database, NASA?s modis satellite imagery and enhanced vegetation index to study the impact of flooding on agriculture with a focus on how farmers change their farming practices, crop choices, and the health of affected people. The second project will study how farmers access and use accurate flood forecasts by combining a community-based outreach program with google?s flood forecasting system. The results of this research will provide important inputs into policies to increase resilience in flood-prone regions and provide guidance on U.S. Foreign aid policies. This award will fund research that uses two projects to investigate the effects of flooding on agricultural practices and livelihoods of people in low-income settings. The first project will combine data from the global flood database, NASA?s modis satellite imagery, and the enhanced vegetation index to assess the impacts of flooding on agriculture, focusing on land use dynamics by farmers. The PIS will study the contemporaneous and long-term impact of flooding on agricultural production, crop choice, and whether flooding?s effect on agriculture varies by its timing. The second project expands on an existing project that enhances the reach and impact of flood early warning systems (EWS) in low-income settings. To do this, the PIS will combine google?s advanced flood-forecasting technology with a community-based alert system. The community-based outreach will be randomized for treatment and control communities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are planned for this award.