长江流域洞庭湖区出入湖磷通量模拟及水质预测：机器学习与传统水文模型耦合方法

刘杰; 陈前; 许妍; 查悉妮; 张美一; 辛小康; 唐文忠; 张洪

doi:10.3799/dqkx.2024.061

Volume 49 Issue 11

Nov. 2024

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Article Navigation > Earth Science > 2024 > 49(11): 3995-4007

Liu Jie, Chen Qian, Xu Yan, Zha Xini, Zhang Meiyi, Xin Xiaokang, Tang Wenzhong, Zhang Hong, 2024. Simulation of Phosphorus Inflow and Outflow Fluxes and Water Quality Prediction in Dongting Lake Area of the Yangtze River Basin: A Coupled Approach of Machine Learning and Traditional Hydrological Modeling. Earth Science, 49(11): 3995-4007. doi: 10.3799/dqkx.2024.061

Citation:

Liu Jie, Chen Qian, Xu Yan, Zha Xini, Zhang Meiyi, Xin Xiaokang, Tang Wenzhong, Zhang Hong, 2024. Simulation of Phosphorus Inflow and Outflow Fluxes and Water Quality Prediction in Dongting Lake Area of the Yangtze River Basin: A Coupled Approach of Machine Learning and Traditional Hydrological Modeling. Earth Science, 49(11): 3995-4007. doi: 10.3799/dqkx.2024.061

Citation:

Liu Jie, Chen Qian, Xu Yan, Zha Xini, Zhang Meiyi, Xin Xiaokang, Tang Wenzhong, Zhang Hong, 2024. Simulation of Phosphorus Inflow and Outflow Fluxes and Water Quality Prediction in Dongting Lake Area of the Yangtze River Basin: A Coupled Approach of Machine Learning and Traditional Hydrological Modeling. Earth Science, 49(11): 3995-4007. doi: 10.3799/dqkx.2024.061

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Simulation of Phosphorus Inflow and Outflow Fluxes and Water Quality Prediction in Dongting Lake Area of the Yangtze River Basin: A Coupled Approach of Machine Learning and Traditional Hydrological Modeling

doi: 10.3799/dqkx.2024.061

Liu Jie^{1, 2
,
,},
Chen Qian^{2, 3},
Xu Yan^{2
,
,},
Zha Xini⁴,
Zhang Meiyi^{1, 5},
Xin Xiaokang⁴,
Tang Wenzhong^{1, 5
,
,},
Zhang Hong^{1, 5}

1.
State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
2.
School of Civil Engineering, Southeast University, Nanjing 210018, China
3.
Shanghai Municipal Engineering Design Institute (Group) Co., Ltd., Shanghai 200092, China
4.
Changjiang Water Resources Protection Institute, Wuhan 430051, China
5.
University of Chinese Academy of Sciences, Beijing 100049, China

Received Date: 2024-06-03
Publish Date: 2024-11-25

Abstract

Abstract

Fluctuations in phosphorus fluxes to and from the lake have a direct impact on the stability of river ecosystems. In the Dongting Lake area, where water quality fluctuates, the SWAT model was used to simulate the phosphorus inflow and outflow fluxes and to analyze the retention rate in each area. A coupled model was constructed based on hydrophysical processes, being trained by the results of the SWAT model and using the model to make scenario predictions of recent water quality in the lake area. The results showed that the inflow and outflow phosphorus fluxes in Dongting Lake showed obvious seasonal variations, with inorganic phosphorus being the main phosphorus format. From 2012 to 2021, the average TP inflow flux in Dongting Lake was 2.94×10⁴ t/a, the average TP outflow flux was 3.34×10⁴ t/a, and the average TP outflow concentration was 0.13 mg/L. Among the sub-basins, the Sankou area as the area with the largest contribution of phosphorus flux into the lake and the highest TP output concentration, should be emphasized to manage the phosphorus pollution in this area. The low TP retention rate in the Dongting Lake area may turn it into an important source of TP in the lower reaches of the Yangtze River. Coupled modeling is relatively precise for simulating the output process of river phosphorus fluxes, with all NSE values > 0.8, and all RMSE values are low at the RPE value at 10% level, which realizes the simulation modeling of the LSTM network instead of the large-scale distributed physical model.Based on the above model, the recent TP output concentration of Dongting Lake area was predicted according to the "Dongting Lake Water Environment Comprehensive Management Plan", and the scenario of controlling the TP concentration inflow into the lake in each area at 0.1 mg/L can realize the water environment planning objectives of the lake area.
- phosphorus inflow and ouflow fluxes,
- coupled model,
- machine learning,
- phosphorus retention,
- water quality prediction,
- Dongting Lake area,
- hydrogeology,
- environmental geology

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References(48)

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