Enhanced flood monitoring and forecasting using remotely sensed earth observations and surface hydrology models.

Floods and droughts are two of the most common recurrent natural disasters that affect billions of people globally with staggering costs in human suffering, economic loss, and risk of growing food insecurity. Increasing global temperatures raises the water-holding capacity of the atmosphere, resulting in enhanced rains and storms. At the same time, it creates more intense dry spells through enhanced evapotranspiration from the land surface. These changes to the hydrological cycle are delivering stronger and frequent droughts and floods across the globe which are not independent events, but rather are intricately linked. Historically droughts have been the focus because of their reliable adverse impacts. In contrast, although floods may have localized adverse impacts, they have been broadly associated with favorable food security outcomes. More recently, however, frequent extreme floods, especially in Africa, have deeply impacted food production and livestock. While monitoring and forecasting droughts has been conducted comprehensively for food insecurity implications, especially by the Famine Early Warning Systems Network (FEWS NET), monitoring and forecasting floods to inform food security outcomes has been conducted at a relatively limited scope. Furthermore, given the apparent trend in increasing adverse impacts associated with flooding, it is important to address this gap. In this article we demonstrate a framework to improve flood monitoring and forecasting by FEWS NET for the food insecure regions of Africa, Central America and Central Asia by leveraging existing flood monitoring and forecasting products developed from remotely sensed Earth observations and hydrological models. The framework integrates satellite derived inundation maps, land surface temperature driven wetness conditions, satellite altimetry, land surface hydrology model estimates and forecast of precipitation, soil moisture and streamflow from multiple sources, to develop ongoing and seasonal prospective of flooding risks. The framework aids in the development of evidence-based and well-informed assumptions for improved food security early warning scenarios related to floods.