报告题目：Satellite Remote Sensing of Large Lakes and Reservoirs 

　　报 告 人：Huilin Gao 

　　主 持 人：兰措研究员 

　　地    点：915会议室 

　　时    间：2014年8月19日（周二）14:00−15:30 

　　简    介：Huilin Gao is an assistant professor at Texas A&M University (TAMU). She received her B.S. and M.S. degrees in atmospheric sciences from Peking University, China. In 2005, she received her Ph.D degree in water resources engineering from Princeton University. Dr.Gao’s research interests are hydrologic monitoring and predictions, climate change, land-atmosphere interactions, water resources management, water quality modeling, and satellite remote sensing in hydrology.  

　 Abstract: The majority of surface freshwater is stored in large lakes and reservoirs. However, consistent observations of lakes and reservoirs are limited mostly to developed countries, and even there the records are often difficult to access. This unbalanced spatial distribution of observational data makes it challenging to assess the effects of alterations to the hydrologic cycle by climate change and human activities, and these effects are not well represented in current earth system models. Satellite remote sensing offers a unique opportunity for monitoring large lakes and reservoirs from space. In this presentation, the satellite remote sensing approaches for estimating lake/reservoir elevations, areas, and storage variations are reviewed. Specifically, two reservoir remote sensing algorithms and their associated datasets (one at global and one at regional scale) are introduced in detail. At the global scale, a total of 34 reservoirs were selected for which good quality surface elevation data could be obtained from satellite radar altimeters (for the period from 1992 to 2010). For each of these reservoirs, an unsupervised classification approach was applied using the Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day 250 m vegetation product to estimate the surface water areas over the MODIS period of record (2000 to 2010). The elevation-area relationships for the reservoirs were derived by combining the MODIS-based area estimates with satellite altimeter-based estimates of reservoir water elevations. At a regional scale, storage time series were estimated from 2000 to 2012 for a total of 21 South Asian reservoirs. These reservoirs represent 28% of the integrated reservoir capacity in South Asia. The monitoring approach is built upon surface area values obtained from MODIS (using an improved algorithm) and surface elevation measurements obtained from the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land Elevation Satellite (ICESat). Future directions and opportunities for more comprehensive data products are discussed. Furthermore, applications of the remotely sensed lakes/reservoir datasets in multiple disciplinary areas are summarized.

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