Towards a better understanding of flood generation and surface water inundation mechanisms using NASA remote sensing data products
Abstract
Floods annually cause several weather-related fatalities and financial losses. According to NOAA and FEMA, there were 43 deaths and 18 billion dollars paid out in flood insurance policies during 2005. The goal of this work is to improve flood prediction and flood risk assessment by creating a general model of predictability of extreme runoff generation using various NASA products. Using satellite-based flood inundation observations, we can relate surface water formation processes to changes in other hydrological variables, such as precipitation, storage and soil moisture, and understand how runoff generation response to these forcings is modulated by local topography and land cover. Since it is known that a flood event would cause an abnormal increase in surface water, we examine these underlying physical relationships in comparison with the Dartmouth Flood Observatory archive of historic flood events globally. Using ground water storage observations (GRACE), precipitation (TRMM or GPCP), land use (MODIS), elevation (SRTM) and surface inundation levels (SWAMPS), an assessment of geological and climate conditions can be performed for any location around the world. This project utilizes multiple linear regression analysis evaluating the relationship between surface water inundation, total water storage anomalies and precipitation values, grouped by average slope or land use, to determine their statistical relationships and influences on inundation data. This research demonstrates the potential benefits of using global data products for early flood prediction and will improve our understanding of runoff generation processes.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.H52G..08L
- Keywords:
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- 1655 Water cycles;
- GLOBAL CHANGE;
- 1816 Estimation and forecasting;
- HYDROLOGY;
- 1847 Modeling;
- HYDROLOGY;
- 1855 Remote sensing;
- HYDROLOGY