Assessing the impacts of cascade reservoirs on Pearl River environmental status using machine learning and satellite-derived chlorophyll-a concentrations

Rivers play a crucial role in in global matter cycling and energy flow, contributing significantly to biogeochemical cycles and the development of human civilization. Reservoirs, as prevalent artificial water bodies, modify river flow and impact energy and environmental dynamics. These reservoirs can directly affect riverine ecosystems by retaining algal materials, thereby altering Chl-a concentrations in downstream water bodies. Nevertheless, the mechanisms by which reservoirs influence Chl-a concentrations in rivers remain poorly understood. This study utilized Landsat 8/9 images and in-situ measurements from the Pearl River to develop a machine learning model and generate a Chl-a concentration dataset spanning 2013-2022. We also examined the mechanisms through which reservoirs and the natural environmental factors affect Chl-a concentrations by regulating the Pearl River. The findings indicate that anthropogenic factors, primarily the construction of reservoirs and dams, play a significant role in shaping the spatial distribution of riverine Chl-a concentrations along the Pearl River. As the river traverses reservoirs in the upper and middle reaches, Chl-a concentrations in both the mainstem and tributary sections exhibit a distinct decrease. The highest Chl-a concentrations were observed in the headwaters of the Xijiang River, followed by a decline in the midstream, and a subsequent increase downstream. It also revealed that, river Chl-a levels are consistently lower before entering a reservoir, higher within it, and further decreased after exiting. Reservoirs, by intercepting and storing upstream sediment and nutrients, allow only a small amounts to pass through dams into downstream sections, thereby influencing riverine Chl-a concentrations. Furthermore, Chl-a concentrations in the Pearl River peak during summer and reach their lowest levels in winter, with water temperature being the dominant driver of seasonal and interannual Chl-a variations (r = 0.88, p < 0.01). Other environmental factors such as pH, dissolved oxygen (DO), total phosphorus (TP), total nitrogen (TN), and Chl-a concentrations were found to be positively correlated. Our findings indicate that cascade reservoirs have a more significant impact on river environmental status. To effectively address river water quality degradation and maximize the benefits of reservoirs, coordinated water diversion and protective measures between the reservoirs are required.

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Publication Details

Journal
Journal of Environmental Management
Published
2025-04-18
DOI
https://doi.org/10.1016/j.jenvman.2025.125406
Citations
3
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
2.45
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article

Assessing the impacts of cascade reservoirs on Pearl River environmental status using machine learning and satellite-derived chlorophyll-a concentrations

Lishan Ran, Qianqian Yang, Zhongyang LI, Xiankun Yang et al.
3 citations
Journal of Environmental Management
Water Quality Monitoring Technologies
2.45
article

Assessing the impacts of cascade reservoirs on Pearl River environmental status using machine learning and satellite-derived chlorophyll-a concentrations

Lishan Ran, Qianqian Yang, Zhongyang LI, Xiankun Yang, Bowen Cao, Shuai Chen
article en
3 citations

Abstract

Rivers play a crucial role in in global matter cycling and energy flow, contributing significantly to biogeochemical cycles and the development of human civilization. Reservoirs, as prevalent artificial water bodies, modify river flow and impact energy and environmental dynamics. These reservoirs can directly affect riverine ecosystems by retaining algal materials, thereby altering Chl-a concentrations in downstream water bodies. Nevertheless, the mechanisms by which reservoirs influence Chl-a concentrations in rivers remain poorly understood. This study utilized Landsat 8/9 images and in-situ measurements from the Pearl River to develop a machine learning model and generate a Chl-a concentration dataset spanning 2013-2022. We also examined the mechanisms through which reservoirs and the natural environmental factors affect Chl-a concentrations by regulating the Pearl River. The findings indicate that anthropogenic factors, primarily the construction of reservoirs and dams, play a significant role in shaping the spatial distribution of riverine Chl-a concentrations along the Pearl River. As the river traverses reservoirs in the upper and middle reaches, Chl-a concentrations in both the mainstem and tributary sections exhibit a distinct decrease. The highest Chl-a concentrations were observed in the headwaters of the Xijiang River, followed by a decline in the midstream, and a subsequent increase downstream. It also revealed that, river Chl-a levels are consistently lower before entering a reservoir, higher within it, and further decreased after exiting. Reservoirs, by intercepting and storing upstream sediment and nutrients, allow only a small amounts to pass through dams into downstream sections, thereby influencing riverine Chl-a concentrations. Furthermore, Chl-a concentrations in the Pearl River peak during summer and reach their lowest levels in winter, with water temperature being the dominant driver of seasonal and interannual Chl-a variations (r = 0.88, p < 0.01). Other environmental factors such as pH, dissolved oxygen (DO), total phosphorus (TP), total nitrogen (TN), and Chl-a concentrations were found to be positively correlated. Our findings indicate that cascade reservoirs have a more significant impact on river environmental status. To effectively address river water quality degradation and maximize the benefits of reservoirs, coordinated water diversion and protective measures between the reservoirs are required.

Journal of Environmental ManagementVol. 382
University of Padua (IT), Guangzhou University (CN), Guangzhou Institute of Geography (CN), University of Hong Kong (HK)
Openalex Percentile: Top 12%
Water Quality Monitoring Technologies
2.45
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