An integrated model of eutrophication controls in reservoir-affected tributaries of the Three Gorges Reservoir

Reservoir-affected tributaries are highly susceptible to nutrient enrichment and algal proliferation, yet their trophic responses can differ markedly under broadly comparable hydrodynamic influence. Here, we examined why two adjacent 1st-order tributaries of the Three Gorges Reservoir (TGR), the Pengxi and Modao Rivers, have shown contrasting eutrophication responses despite experiencing broadly comparable reservoir influence since 2003. We hypothesized that watershed-scale differences in agricultural non-point-source pollution account for these contrasting responses. To test this hypothesis, we integrated the Soil and Water Assessment Tool (SWAT) with partial least squares structural equation modeling (PLS-SEM) to link land use/land cover, hydrology, and nutrient transport to river nutrient enrichment. The agriculture-dominated Pengxi watershed showed higher nutrient export than the more forested Modao watershed. PLS-SEM further showed agricultural land cover had the strongest positive pathway association in the Pengxi watershed (β = 0.731, p < 0.001), whereas forest land cover showed a strong negative pathway association in the Modao watershed (β = -0.812, p < 0.001), consistent with a hydrological buffering role.. These results indicate that watershed land use/land cover composition, rather than reservoir hydrodynamics alone, helps explain differential trophic responses among reservoir tributaries, and they support targeted land use management to mitigate eutrophication in reservoir-affected river systems.

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Publication Details

Journal
Inland Waters
Published
2026-10-13
DOI
https://doi.org/10.1080/20442041.2026.2748308
Primary Topic
Soil and Water Nutrient Dynamics
Type
article
Field-Weighted Citation Impact
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article

An integrated model of eutrophication controls in reservoir-affected tributaries of the Three Gorges Reservoir

Amechi Sampson Nwankwegu, Muhammad Waqas Yonas, Pingyu Lv, Oluwafemi Adewole Adeyeye et al.
Inland Waters
Soil and Water Nutrient Dynamics
article

An integrated model of eutrophication controls in reservoir-affected tributaries of the Three Gorges Reservoir

Amechi Sampson Nwankwegu, Muhammad Waqas Yonas, Pingyu Lv, Oluwafemi Adewole Adeyeye, Guanglang Yang, Xiaojiao Luo, Zenghui Song, Ahmed Anwar Hassan, Xuexing Yao, Yemei Kong, Lei Zhang, Wei Huang, Connor Newman, Yan Zhang, Bai Guoxin
article en

Abstract

Reservoir-affected tributaries are highly susceptible to nutrient enrichment and algal proliferation, yet their trophic responses can differ markedly under broadly comparable hydrodynamic influence. Here, we examined why two adjacent 1st-order tributaries of the Three Gorges Reservoir (TGR), the Pengxi and Modao Rivers, have shown contrasting eutrophication responses despite experiencing broadly comparable reservoir influence since 2003. We hypothesized that watershed-scale differences in agricultural non-point-source pollution account for these contrasting responses. To test this hypothesis, we integrated the Soil and Water Assessment Tool (SWAT) with partial least squares structural equation modeling (PLS-SEM) to link land use/land cover, hydrology, and nutrient transport to river nutrient enrichment. The agriculture-dominated Pengxi watershed showed higher nutrient export than the more forested Modao watershed. PLS-SEM further showed agricultural land cover had the strongest positive pathway association in the Pengxi watershed (β = 0.731, p < 0.001), whereas forest land cover showed a strong negative pathway association in the Modao watershed (β = -0.812, p < 0.001), consistent with a hydrological buffering role.. These results indicate that watershed land use/land cover composition, rather than reservoir hydrodynamics alone, helps explain differential trophic responses among reservoir tributaries, and they support targeted land use management to mitigate eutrophication in reservoir-affected river systems.

Inland Waters
Suez Canal University (EG), Bureau of Plant Industry (PH), Southwest University (CN), Changjiang Water Resources Commission (CN)
Openalex Percentile: Top 23%
Soil and Water Nutrient Dynamics
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