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Research on phosphorus load prediction of Baiyangdian Basin based on coupling model
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Yu-ang GAO1, Shuang-jiang LI1, Zi-shuai ZHENG1, Hao-jia WANG1, Xiao-ning LI1, Zi-qiong LI1, Zhao-nan DU1, Jian-sheng CUI1, Lu-lu ZHANG1, 2, *
China Environmental Science | 2025, 45(12) : 6793 - 6804
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China Environmental Science | 2025, 45(12): 6793-6804
• Environmental Ecology •
Research on phosphorus load prediction of Baiyangdian Basin based on coupling model
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Yu-ang GAO1, Shuang-jiang LI1, Zi-shuai ZHENG1, Hao-jia WANG1, Xiao-ning LI1, Zi-qiong LI1, Zhao-nan DU1, Jian-sheng CUI1, Lu-lu ZHANG1, 2, *
Affiliations
  • 1.College of Environment Science and Engineering, Hebei University of Science the Technology, Shijiazhuang 050000, China
  • 2.Hebei Provincial Key Laboratory of Pollution Prevention Biotechnology, Shijiazhuang 050000, China
Published: 2025-12-20
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This study established an integrated SWAT-LSTM-MLP model to investigate phosphorus flux dynamics in the Baiyangdian Basin, China. The SWAT simulations revealed three key findings: (1) the average annual phosphorus input of the basin was 717.3t/a(57.6kg/km2·a) during 2019~2023, and the organic phosphorus (78.8%) was the main form, which showd an increasing trend in 2023; (2) the phosphorus flux showed significantly seasonal variation, the flood seasons (June-September) accounted for 85.57% of annual phosphorus loading (49.28kg/km2), which was significantly positive correlations (P<0.01) with precipitation, runoff, and sediment load; (3) for the spatial distribution, the phosphorous load of Fu-Cao-Pu River (79.3kg/km2, 32.09%) and Baigou Diversion Canal (66.6kg/km2, 26.96%) was higher than other region. Furthermore, in order to avoid the deficiency of the SWAT mobile in nonlinear varaitions, the LSTM-MLP hybrid model was applied to improve the accuracy of phosphorous load prediction. The model results showed that:(1) the LSTM-MLP hybrid model significantly improved prediction accuracy (NSE>0.9, RMSE<4kg/km2) compared to conventional LSTM (NSE>0.8, RMSE<7kg/km2), particularly in capturing peak values; (2) simulate analysis under different sediment reduction scenario demonstrated that the Baigou Diversion Canal under 60% sediment reduction scenario can reduce 35.29% of phosphorus load, which was the most effective regions among all subregions.

SWAT model  /  machine learning  /  phosphorus flux  /  sediment reduction  /  Baiyangdian Basin
高宇昂, 李双江, 郑子帅, 王浩加, 李晓宁, 李子琼, 杜兆楠, 崔建升, 张璐璐. 基于耦合模型的白洋淀流域磷负荷削减模拟. 中国环境科学, 2025 , 45 (12) : 6793 -6804 .
Yu-ang GAO, Shuang-jiang LI, Zi-shuai ZHENG, Hao-jia WANG, Xiao-ning LI, Zi-qiong LI, Zhao-nan DU, Jian-sheng CUI, Lu-lu ZHANG. Research on phosphorus load prediction of Baiyangdian Basin based on coupling model[J]. China Environmental Science, 2025 , 45 (12) : 6793 -6804 .
Year 2025 volume 45 Issue 12
45
12
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  • Receive Date:2025-05-25
  • Online Date:2026-10-08
  • Published:2025-12-20
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  • Received:2025-05-25
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Affiliations
    1.College of Environment Science and Engineering, Hebei University of Science the Technology, Shijiazhuang 050000, China
    2.Hebei Provincial Key Laboratory of Pollution Prevention Biotechnology, Shijiazhuang 050000, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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