Abstract

Study regionTsengwen Reservoir, Taiwan. Study focusWater level (WL) and water volume (WV) are important indicators for analyzing surface water resources. Satellite remote sensing enables continuous monitoring of inland water bodies in human-inaccessible areas. We integrate Landsat imagery and satellite altimetry to derive long-term (2003–2020) WL and WV variations of Tsengwen Reservoir. First, water area (WA) was extracted from Landsat imagery by Modified Normalized Difference Water Index method and a second-order regression model is proposed to recover the entire WA from cloud-covered images to enhance the data usage. Then, WAs and WLs provided from satellite altimetry are utilized to build a linear regression model which is used to transfer WA into WL. Finally, WV was computed based on the WA and WL. New hydrological insights for the regionResults showed that the usage rate of Landsat-8 imagery utilized for conversion from WA to WL can be increased from 23% to 43%. Moreover, the root-mean-square error of the difference of WLs between the estimates and a local gauge is 2.95–5.56 m, with correlation coefficients (CC) of 0.93–0.99. In addition, the derived WV variations and ground truth showed a good agreement with CC in 0.88–0.97. The results indicated that the integration of multi-source remote sensing technologies can effectively provide long-term hydrological parameters to assist administrative agencies with an appropriate plan for water resources management.

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