Measuring Flood Resilience using Remote Sensors

Abstract

What are the effects of floods on reporting likelihood and observable outcomes? I examine this question in the context of a Randomized Control Trial (Shukla and Baylis, 2019) aimed at adopting a specific new technology for small-scale farmers in Bihar, India. I study two effects; first, to which extent adaptation to a regular rainfall pattern (the South Asian Monsoon) makes farmers under-report the impact of floods/heavy rainfall. To do so, I use inundation maps from satellite-measured floodwater to compare observed and reported floods. Second, given that I can determine which household lives near flooded areas, I measure their impact on food security outcomes. On the one hand, there is significant evidence in favor of under-reporting bias, but I also find little evidence of impacts on food security outcomes.