The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review
文献类型：期刊论文
| 作者 | Jiang, DJ ; Wang, K
|
| 刊名 | WATER
 |
| 出版日期 | 2019-08 |
| 卷号 | 11期号:8页码:1615 |
| 关键词 | satellite-based remote sensing streamflow simulation hydrological model data assimilation |
| DOI | 10.3390/w11081615 |
| 产权排序 | [Jiang, Dejuan] Chinese Acad Sci, Yantai Inst Coastal Zone Res, Key Lab Coastal Environm Processes & Ecol Remedia, Yantai 264003, Shandong, Peoples R China ; [Wang, Kun] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China |
| 文献子类 | Review |
| 英文摘要 | A hydrological model is a useful tool to study the effects of human activities and climate change on hydrology. Accordingly, the performance of hydrological modeling is vitally significant for hydrologic predictions. In watersheds with intense human activities, there are difficulties and uncertainties in model calibration and simulation. Alternative approaches, such as machine learning techniques and coupled models, can be used for streamflow predictions. However, these models also suffer from their respective limitations, especially when data are unavailable. Satellite-based remote sensing may provide a valuable contribution for hydrological predictions due to its wide coverage and increasing tempo-spatial resolutions. In this review, we provide an overview of the role of satellite-based remote sensing in streamflow simulation. First, difficulties in hydrological modeling over highly regulated basins are further discussed. Next, the performance of satellite-based remote sensing (e.g., remotely sensed data for precipitation, evapotranspiration, soil moisture, snow properties, terrestrial water storage change, land surface temperature, river width, etc.) in improving simulated streamflow is summarized. Then, the application of data assimilation for merging satellite-based remote sensing with a hydrological model is explored. Finally, a framework, using remotely sensed observations to improve streamflow predictions in highly regulated basins, is proposed for future studies. This review can be helpful to understand the effect of applying satellite-based remote sensing on hydrological modeling. |
| WOS关键词 | DISTRIBUTED HYDROLOGICAL MODEL ; ENSEMBLE KALMAN FILTER ; SENSED SOIL-MOISTURE ; MULTISATELLITE PRECIPITATION ANALYSIS ; SNOW WATER EQUIVALENT ; EVAPOTRANSPIRATION DATA ASSIMILATION ; STATE-PARAMETER ESTIMATION ; LAND-SURFACE TEMPERATURE ; RIVER-BASIN ; SWAT MODEL |
| WOS研究方向 | Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:000484561500089 |
| 资助机构 | Key R&D Program of China [2017YFD0300402] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [41701495, 40901028] |
| 源URL | [http://ir.yic.ac.cn/handle/133337/24889]  |
| 专题 | 烟台海岸带研究所_近岸生态与环境实验室 烟台海岸带研究所_中科院海岸带环境过程与生态修复重点实验室 |
| 作者单位 | 1.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China 2.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Key Lab Coastal Environm Processes & Ecol Remedia, Yantai 264003, Shandong, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Jiang, DJ,Wang, K. The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review[J]. WATER,2019,11(8):1615. |
| APA | Jiang, DJ,&Wang, K.(2019).The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review.WATER,11(8),1615. |
| MLA | Jiang, DJ,et al."The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review".WATER 11.8(2019):1615. |
入库方式： OAI收割
来源：烟台海岸带研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。