| Autor: |
Chi-Ming Lee, Chung-Yen Kuo, Chi-Hua Yang, Huan-Chin Kao, Kuo-Hsin Tseng, Wen-Hau Lan |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Journal of Hydrology: Regional Studies, Vol 44, Iss , Pp 101227- (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2214-5818 |
| DOI: |
10.1016/j.ejrh.2022.101227 |
| Popis: |
Study region: Tsengwen Reservoir, Taiwan. Study focus: Water 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 region: Results 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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