Improving government decision making in response to floods using soil moisture observations from Soil Moisture Active Passive (SMAP) data

Friday, 19 December 2014
Vanessa M Escobar, NASA Goddard Space Flight Center, Greenbelt, MD, United States, Guy Schumann, University of California Los Angeles, Los Angeles, CA, United States and Lynn Joseph Torak, U.S. Geological Survey Georgia Water Science Center, Georgia Water Science Center, Norcross, GA, United States
NASA’s Soil Moisture Active Passive (SMAP) Mission, due to launch January 2015, will provide global observations of the Earth’s surface soil moisture, providing high accuracy, resolution and continuous global coverage. This paper seeks to show how SMAP data can be used in flood applications to improve flood warning/planning operations for the Upper Mississippi River basin. The Mississippi River ranks as the fourth longest and tenth largest river in the world and is noted as one of the most altered rivers in the United States. The Mississippi River has a very long track record of flood events, with the 2011 event being a unique event due to large volumes of snow melt and heavy spring rain in the Upper Mississippi basin. Understanding and modeling these processes and combining them with relevant satellite observations such as soil moisture conditions could help alleviate some of the risk to flooding by identifying when infiltration to soils is cut off causing excessive runoff.

The objective of the analysis is to improve our understanding of how satellite-derived soil moisture will impact basin scaled/multi state decision processes linked to emergency planning and preparedness, such as FEMA FloodSMART. Using the snow hydrology model SNOW-17 (NWS) coupled to a large-scale two-dimensional floodplain inundation model LISFLOOD-FP, the study evaluates how different soil moisture states can be captured by satellites to enable a multi-state decision process focused on flood risk and planning. The study develops a scenario that applies historical soil moisture data from past events to monitor basin soil moisture conditions and yields a percent value of the saturation status. Scenario analysis is particularly important for decision makers such as emergency responders and insurers as their operations depend on their ability to gauge and appropriately assess risk. This analysis will enables insurers to develop mitigation strategies and contingency plans for such events.