Four-decade dynamics of the water color in 61 large lakes on the Yangtze Plain and the impacts of reclaimed aquaculture zones

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The lakes on the Yangtze Plain, a critical source of freshwater and fisheries for hundreds of millions of people in China, have lost a considerable portion of their surface area due to reclamation since the 1950s. Landsat satellites can provide long-term collections of high-resolution images and thus offer great potential for hindcasting the lake reclamations of aquaculture zones and their long-term impacts on the lacustrine water color. Using Landsat observations from 1984 to 2018 and a Forel-Ule index (FUI) model, we studied the water color dynamics of 61 lakes on the Yangtze Plain. Three distinct change patterns were found among the 61 examined lakes, and 25 of the 61 lakes showed statistically significant changes in the annual hue angle values (P < 0.05). We further collected environmental parameter datasets (runoff, normalized difference vegetation index (NDVI), and wind speed) and a lacustrine reclamation dataset, and measured the concentrations of chlorophyll-a (Chl-a) and dissolved organic carbon (DOC) from two field trips. We investigated their correlations with water color change from different facets. The results showed that the long-term water color in 33 of the 61 lakes exhibited significant correlations with environmental factors. The reclaimed aquaculture zones in this region have caused differences in the water color between the reclaimed area and that in adjacent natural waters. The Chl-a and DOC levels derived from field surveys further confirmed that reclaimed aquaculture zones increased light-absorbing materials in the water and may deteriorate water quality. This study is an important step forward in understanding the water quality changes in lake ecosystems affected by human impacts and natural variability.

TidsskriftScience of the Total Environment
Antal sider14
StatusUdgivet - 2021

Bibliografisk note

Funding Information:
This work was supported by the National Natural Science Foundation of China (NOs: 41971304, 41890852 and 41890851), the Shenzhen Science and Technology Innovation Committee (JCYJ20190809155205559) and the High-level Special Funding of the Southern University of Science and Technology (Grant No. G02296302, G02296402). We thank the US NASA for providing Landsat and NDVI data and the National Tibetan Plateau Data Center for providing wind speed data.

Publisher Copyright:
© 2021

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