Jiang, DJ
; Wang, K发表期刊WATER
2019-08
卷号11期号:8页码:1615
关键词satellite-based remote sensingstreamflow simulationhydrological modeldata assimilation
研究领域Water Resources
DOI10.3390/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
通讯作者Jiang, Dejuan(djjiang@yic.ac.cn)
作者部门海岸带环境过程实验室
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.
文章类型Review
资助机构Key R&D Program of China [2017YFD0300402]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [41701495, 40901028]
收录类别SCI
语种英语
关键词[WOS]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
研究领域[WOS]Water Resources
WOS记录号WOS:000484561500089
引用统计被引频次：37[WOS][WOS记录][WOS相关记录]
文献类型期刊论文
条目标识符http://ir.yic.ac.cnhttp://ir.yic.ac.cn/handle/133337/24889
专题中科院海岸带环境过程与生态修复重点实验室_海岸带环境过程实验室
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, Yantai Inst Coastal Zone Res, Key Lab Coastal Environm Processes & Ecol Remedia, Yantai 264003, Shandong, Peoples R China;
2.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714Jiang, DJ,Wang, K. The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review[J]. WATER,2019,11(8):1615.
APAJiang, DJ,&Wang, K.(2019).The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review.WATER,11(8),1615.
MLAJiang, DJ,et al."The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review".WATER 11.8(2019):1615.
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