基于卫星雷达测高技术的湖库动态监测理论、方法和研究进展

Water level is an important variable that indicates the variations in the vertical dimension of inland water bodies. However, in-situ monitoring of water level of lakes and reservoirs is expensive. Thus, the coverage of gauging network is relatively low. The satellite altimetry technology, originally used for ocean research, has been widely applied for inland water research on a local to regional and global scale. As the success of several altimetry missions, the situation of data scarcity has been mitigated, especially in the recent decade.The literature review shows that the mainstream of altimetry research for lakes and reservoirs focuses on one specific or few lakes/reservoirs aiming at a detailed investigation. Regarding the altimetry data sets, most studies use high-level products (i.e. water level data instead of raw signals) from one certain database, such as Hydroweb, DAHITI, etc., but very few exploit the low-level products. The major research foci include temporal variations of water level, and the attribution of water level changes in the context of climate changes. Besides, some publications research the water storage changes and thus assess the water resources and management issues, while some others focus on catchment hydrologic modeling with water levels of lakes/reservoirs as constraints.In this short review article, we first briefly introduced the theory of inland altimetry, followed by the descriptions of major freely open-access products of different levels. Then, we summarized the common data processing procedures including data screening, waveform retracking, outlier removal, time series construction, etc. We intend to guide the newcomers to prepare data for their own studies of interest when dealing with low-level products if necessary. Moreover, we reviewed the latest progresses of inland water altimetry, especially for lakes and reservoirs research. The progresses are reported in three main directions, i.e., water level monitoring and analysis, dynamics of water storage, and catchment hydrologic modeling. The latter two directions involve more data sets other than altimetry-derived water levels and still need more research for further advancement.We concluded this study with recommendations on future research topics, such as new data processing techniques (e.g. Fully-Focused SAR and Wide swath InSAR processing, Machine Learning, etc.) to extract water levels that are more accurate. We also provide introductions of several proposed or planed future altimetry missions (e.g. SWOT, Sentinel-3 Next Generation Topography, Sentinel-6-Next Generation, etc.) that will provide many opportunities for lake and reservoir research beyond just lake/reservoir monitoring. Moreover, we highlight the value of multi-mission (or constellations) data sets for high spatio-temporal resolution mapping of inland water bodies. Meanwhile, it is also very important to develop freely open-access high-level databases for end users, such as hydrological modelers.