Mapping Flooding and Inundation Dynamics Using Spaceborne GNSS-R Observations

Even the youngest child knows that fresh water is crucial for life, and it’s easy to see and appreciate our reservoirs, lakes, and rivers for the numerous services they provide, not only for drinking water but also for transportation and the health of our ecosystems. But inland surface water is both a friend and a foe. Too much of it can be devastating for communities—floods are one of the costliest natural disasters, and they often disproportionally impact the most vulnerable members of those communities. Too little of it, though, can be just as destructive. Years-long droughts empty reservoirs, increase wildfire risk, and can lead to conflict over remaining water resources. Quantifying the amount and extent of inland surface water is thus important for knowing where we lie in this delicate balance between abundance and scarcity.

A variety of approaches to map flood and inundation dynamics already exist, be they stream gage data, hydrologic models, or remote sensing observations from satellites. All of them have advantages and challenges, and none alone provide a complete picture of the extent of surface water at any one particular moment. This presentation will describe a new approach to mapping flooding and inundation dynamics, which can provide complementary information to that which already exists via other sensors, models, or networks. This approach uses spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) observations to infer surface water extent. Currently, the vast majority of spaceborne GNSS-R data come from the Cyclone GNSS (CYGNSS) constellation, a NASA mission comprised of eight small satellites orbiting the tropics.  Here, we will present flood inundation maps derived from CYGNSS data for the full period of record (2017 – present), which are gridded to three km and have a temporal revisit rate of three days. We will discuss the retrieval algorithm, its validation, limitations of our approach, and plans to disseminate the data to the public. Finally, we will comment on the potential of GNSS-R data beyond CYGNSS to provide hydrologic information to the broader research community and other end users.