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  • Title: Remote sensing estimation of the flood storage capacity of basin-scale lakes and reservoirs at high spatial and temporal resolutions.
    Author: Chen T, Song C, Zhan P, Yao J, Li Y, Zhu J.
    Journal: Sci Total Environ; 2022 Feb 10; 807(Pt 1):150772. PubMed ID: 34619207.
    Abstract:
    The flood storage of lakes and reservoirs plays an important role in flood regulation and control in floodplains. However, the flood storage capacity of lakes and reservoirs is ineffectively quantified at the basin scale due to the limited access to in-situ data and poor quality of optical satellite images in flooding seasons. To address this, taking a typical floodplain basin (the Poyang Lake basin) in the Yangtze as a study case, radar satellite data combined with measured bathymetry and digital elevation model data were utilized to reconstruct the time series of the water inundation area and water storage change of all lakes and reservoirs larger than 1 km2 during the once-in-a-generation flood event that occurred in 2020 (termed as the 2020 flood event hereafter). Results show that the flood storage capacity of Poyang Lake can reach the maximum at 12.18 Gt, and that for other lakes and reservoirs within the basin is approximately 2.95 Gt. It indicates a total flood-storage capacity of 15.13 Gt for the basin-scale lakes and reservoirs, approximately accounting for 45.02% of the terrestrial water storage change of the basin. The storage capacity of Poyang Lake was approximately four times larger than the entirety of other lakes and reservoirs in the basin despite that its maximum water inundation area is in the proportion of 2.58 times other water bodies. This finding indicates that the Poyang Lake provided the dominant contribution to flood storage among all the lakes and reservoirs in the basin. This study introduced a remote sensing approach to quantify the flood storage capacity of basin-scale lakes and reservoirs at high spatial and temporal resolutions during the flood event, which could fill the insufficiently-quantified knowledge about dynamics of lakes and reservoirs in areas lacking full-covered in-situ data records. This study also helps to offer a quantitative basis to improve flood forecasting and control for the public authority, stakeholders, and decision-makers.
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