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Open AccessReview

The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review

by Dejuan Jiang 1,* and Kun Wang 2
Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, Shandong, China
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
Author to whom correspondence should be addressed.
Water 2019, 11(8), 1615;
Received: 1 June 2019 / Revised: 26 July 2019 / Accepted: 1 August 2019 / Published: 4 August 2019
(This article belongs to the Special Issue Satellite Application on Support to Water Monitoring and Management)
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. View Full-Text
Keywords: satellite-based remote sensing; streamflow simulation; hydrological model; data assimilation satellite-based remote sensing; streamflow simulation; hydrological model; data assimilation
MDPI and ACS Style

Jiang, D.; Wang, K. The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review. Water 2019, 11, 1615.

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