Alys Thomas |
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Time:
Tuesday, 1 April 2014
1005 - 1025
Monitoring terrestrial hydrology with GRACE satellites |
Senior Ph.D. Candidate
Speaking on behalf of Dr. Jay Famiglietti
University of California Center for Hydrologic Modeling
Department of Earth System Science
University of California, Irvine |
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Abstract |
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Over the last decade, advances in satellite remote sensing are providing new means for identifying, evaluating, and monitoring climatic and hydrologic extremes (e.g., flood and drought). This presentation provides a detailed overview of past and current research from collaborators and investigators at the UC Center for Hydrologic Modeling concerning regional and global hydrologic extremes and their impacts on terrestrial hydrology. Focus will be on the usage of satellite data from NASA’s Gravity Recovery and Climate Experiment (GRACE) mission, which provides monthly data on terrestrial water storage changes (i.e., for all of the snow, surface water, soil moisture and groundwater) in regions of at least 200,000 square kilometers.
Regional flooding and drought are driven by the surplus or deficit of water in a river basin or an aquifer, yet few hydrologic observing networks yield sufficient data for comprehensive monitoring of changes in the total amount of water stored in a region. GRACE observations have helped to fill this gap.
Topics to be discussed include: how GRACE data have been used to characterize regional flood potential and to assess regional water storage deficits (hydrological drought), measuring groundwater resources in northern India and California’s Central Valley, and evaluating freshwater storage trends in the north-central Middle East, all based on satellite gravity observations. Combining GRACE data with independent observations of snow, surface water and soil moisture has proven to be an effective means of characterizing groundwater storage changes. As an integrated measure of all surface and groundwater storage changes, GRACE data implicitly contains a record of seasonal to inter-annual water storage variations that can likely be exploited to lengthen early warning periods for regional flood and drought prediction.
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