H187-12
Landscape Response to Tropical Cyclones and the Effects of Antecedent Soil Moisture Using SMAP

Tuesday, 15 December 2020: 18:03
Virtual
Andrew Roderick Murray, University of North Carolina at Chapel Hill, Geography, Chapel Hill, NC, United States and Diego Riveros-Iregui, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
Abstract:
In the past five years, twenty tropical cyclones have made landfall in the southeastern United States, many with devastating impacts and particularly in areas that are heavily dependent on groundwater. Geophysical landscape features, temporal variability of soil moisture, and land cover are major drivers of groundwater vulnerability to contamination. Extreme precipitation events such as tropical cyclones overwhelm and impose changes to each of these variables in measurable ways. Investigating the relationships and the ways in which to measure these impacts will enable future forecasting of vulnerability and better inform disaster response efforts, directly and positively affecting human health. Soil moisture typically requires data to be physically collected in the field. However, recent advances in satellite remote sensing have yielded global high-resolution soil moisture maps every 1-3 days. Along with publicly available data, this soil moisture data can be used to help understand hydrological relationships in groundwater resources following extreme precipitation events such as tropical cyclones. We investigate the effects of landscape coupled with both antecedent and post-storm soil moisture conditions using SMAP for twenty tropical cyclones which have made landfall in the southeastern United States over the past five years (since the launch of SMAP) and present findings for links to landscape features. SMAP presents a unique opportunity now that we have over five years of data collection and a significant number of major tropical storms that have made landfall in overlapping geographies with varying seasonality and antecedent conditions. The implications of this research tie into important work being done in both flood and groundwater modelling to estimate areas highly vulnerable to groundwater contamination following extreme weather events.