Exploring the scale effect of nonpoint source pollution risk on water quality in Lake Basins of Central Yunnan Plateau using the Minimum Cumulative Resistance model

Nonpoint source (NPS) pollution has emerged as the predominant water environment issue confronting plateau lakes in central Yunnan. Quantitative analysis of the impact of NPS pollution on water quality constitutes the key to preventing and controlling water pollution. However, currently, there is a dearth of research on identifying NPS pollution risks and exploring their relationship with water quality based on the Minimum Cumulative Resistance (MCR) model in the plateau lake basins of central Yunnan. Particularly, studies on the spatial heterogeneity of the impact of NPS pollution on water quality from a multi-scale perspective are scarce. Therefore, this study focuses on three typical lake basins in the Central Yunnan Plateau-Fuxian Lake, Xingyun Lake, and Qilu Lake (the Three Lakes). Utilizing the MCR model to identify NPS pollution risks, the study analyzes seven different scales, including sub-basins, riparian buffer zones (100 m, 300 m, 500 m, 700 m, and 1,000 m) and lakeshore zones, to reveal the multi-scale effects of NPS pollution on water quality through correlation analysis. The results indicate that: (1) Over 60% of the areas in the Three Lakes Basin are at high or extremely high risk, mainly concentrated in flat terrain and around inflow rivers; (2) The area of NPS pollution from paddy field source landscape (PFSL) is greater than that from construction land source landscape (CLSL), and the high-risk areas of NPS pollution are also larger for PFSL compared to CLSL; (3) The mean resistance values of PFSL and CLSL show a significant negative correlation with monthly mean values of water quality indexes (NH<sub>3</sub>-N, TP, COD<sub>Cr</sub>), with the 1,000 m riparian buffer zone scale showing the greatest correlation with most water quality indexes, especially NH<sub>3</sub>-N; (4) The correlation between the mean resistance value of CLSL and the monthly mean values of water quality indexes is significantly higher than that of PFSL, indicating a greater impact of CLSL on water quality compared to PFSL. In summary, PFSL and CLSL are the primary sources of NPS pollution in the Three Lakes Basins. The 1,000 m riparian buffer zone scale is the most sensitive to the impact of NPS pollution on water quality. This study provides scientific references for landscape pattern optimization and precise control of NPS pollution risks in the Central Yunnan Plateau lake basins and offers a new research perspective for exploring multi-scale effects of NPS pollution on water quality.

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Publication Details

Journal
PeerJ
Published
2024-10-18
DOI
https://doi.org/10.7717/peerj.18247
Citations
3
Primary Topic
Water Quality and Pollution Assessment
Type
article
Field-Weighted Citation Impact
0.60

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article

Exploring the scale effect of nonpoint source pollution risk on water quality in Lake Basins of Central Yunnan Plateau using the Minimum Cumulative Resistance model

Shuangyun Peng, Bangmei Huang, Fu Li, Rui Zhang et al.
3 citations
PeerJ
Water Quality and Pollution Assessment
0.60
article

Exploring the scale effect of nonpoint source pollution risk on water quality in Lake Basins of Central Yunnan Plateau using the Minimum Cumulative Resistance model

Shuangyun Peng, Bangmei Huang, Fu Li, Rui Zhang, Xiaoliang Ma, Luping Gong
article en
3 citations

Abstract

Nonpoint source (NPS) pollution has emerged as the predominant water environment issue confronting plateau lakes in central Yunnan. Quantitative analysis of the impact of NPS pollution on water quality constitutes the key to preventing and controlling water pollution. However, currently, there is a dearth of research on identifying NPS pollution risks and exploring their relationship with water quality based on the Minimum Cumulative Resistance (MCR) model in the plateau lake basins of central Yunnan. Particularly, studies on the spatial heterogeneity of the impact of NPS pollution on water quality from a multi-scale perspective are scarce. Therefore, this study focuses on three typical lake basins in the Central Yunnan Plateau-Fuxian Lake, Xingyun Lake, and Qilu Lake (the Three Lakes). Utilizing the MCR model to identify NPS pollution risks, the study analyzes seven different scales, including sub-basins, riparian buffer zones (100 m, 300 m, 500 m, 700 m, and 1,000 m) and lakeshore zones, to reveal the multi-scale effects of NPS pollution on water quality through correlation analysis. The results indicate that: (1) Over 60% of the areas in the Three Lakes Basin are at high or extremely high risk, mainly concentrated in flat terrain and around inflow rivers; (2) The area of NPS pollution from paddy field source landscape (PFSL) is greater than that from construction land source landscape (CLSL), and the high-risk areas of NPS pollution are also larger for PFSL compared to CLSL; (3) The mean resistance values of PFSL and CLSL show a significant negative correlation with monthly mean values of water quality indexes (NH<sub>3</sub>-N, TP, COD<sub>Cr</sub>), with the 1,000 m riparian buffer zone scale showing the greatest correlation with most water quality indexes, especially NH<sub>3</sub>-N; (4) The correlation between the mean resistance value of CLSL and the monthly mean values of water quality indexes is significantly higher than that of PFSL, indicating a greater impact of CLSL on water quality compared to PFSL. In summary, PFSL and CLSL are the primary sources of NPS pollution in the Three Lakes Basins. The 1,000 m riparian buffer zone scale is the most sensitive to the impact of NPS pollution on water quality. This study provides scientific references for landscape pattern optimization and precise control of NPS pollution risks in the Central Yunnan Plateau lake basins and offers a new research perspective for exploring multi-scale effects of NPS pollution on water quality.

PeerJVol. 12
Yunnan Normal University (CN), Kunming University (CN), Yunnan University (CN)
National Natural Science Foundation of China
Clean water and sanitation
Openalex Percentile: Top 33%
Water Quality and Pollution Assessment
0.60
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