Simulation and explanatory analysis of dissolved oxygen dynamics in Lake Ulansuhai, China
Study region: The largest lake in China's Yellow River Basin, Ulansuhai. Study focus: After implementing the optimal noise reduction strategies based on wavelet transform for the high-frequency monitoring data, hybrid models coupling random forests, support vector machines, and artificial neura...
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Elsevier
2025-02-01
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| Series: | Journal of Hydrology: Regional Studies |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581824004580 |
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| author | Fan Zhang Xiaohong Shi Shengnan Zhao Ruonan Hao Biao Sun Guohua Li Shihuan Wang Hao Zhang |
| author_facet | Fan Zhang Xiaohong Shi Shengnan Zhao Ruonan Hao Biao Sun Guohua Li Shihuan Wang Hao Zhang |
| author_sort | Fan Zhang |
| collection | DOAJ |
| description | Study region: The largest lake in China's Yellow River Basin, Ulansuhai. Study focus: After implementing the optimal noise reduction strategies based on wavelet transform for the high-frequency monitoring data, hybrid models coupling random forests, support vector machines, and artificial neural networks were employed to simulate the dissolved oxygen in the lake during both the open-water and ice-covered periods. The optimal hybrid model for each period was selected through extensive analysis, and the shapley additive explanations method was utilized to quantify the contribution of feature variables to the results. New hydrological insight for the region: The results revealed MAE, RMSE, and NSE values of 0.76, 1.01, and 0.92 for WT-RF, and 0.42, 0.55, and 0.84 for WT-SVM. They represent the optimal hybrid models for the open-water and ice-covered periods, respectively. The SHAP analysis showed that water temperature, blue-green algae, pH, turbidity, electrical conductivity, and chlorophyll.a exhibited significant importance in the WT-RF model, in that order. BGA and Chl.a synergistically promoted the increase in DO levels during the open-water period. For the WT-SVM model, Chl.a, BGA, Tur, and Temp exhibited significant contributions to the simulation results in that order. However, only BGA was able to enhance DO levels during the ice-covered period. As seasons change, shifts in key water environment factors affecting DO reveal the complexity of lake ecosystems in a cold and arid region. |
| format | Article |
| id | doaj-art-9a0aaf7e833c4edca821ce022fd25bc0 |
| institution | Kabale University |
| issn | 2214-5818 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Hydrology: Regional Studies |
| spelling | doaj-art-9a0aaf7e833c4edca821ce022fd25bc02025-01-22T05:42:04ZengElsevierJournal of Hydrology: Regional Studies2214-58182025-02-0157102109Simulation and explanatory analysis of dissolved oxygen dynamics in Lake Ulansuhai, ChinaFan Zhang0Xiaohong Shi1Shengnan Zhao2Ruonan Hao3Biao Sun4Guohua Li5Shihuan Wang6Hao Zhang7Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, ChinaWater Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China; State Gauge and Research Station of Wetland Ecosystem, Ulansuhai Lake, Inner Mongolia, Bayan Nur 014404, China; Inner Mongolia Water Resource Protection and Utilization Key Laboratory, Hohhot 010018, China; Corresponding author at: Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China.Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China; Inner Mongolia Water Resource Protection and Utilization Key Laboratory, Hohhot 010018, ChinaInner Mongolia Water Resources Development Center, Hohhot 010011, ChinaWater Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China; Inner Mongolia Water Resource Protection and Utilization Key Laboratory, Hohhot 010018, ChinaInstitute of Pastoral Hydraulic Research, Ministry of Water Resource, Hohhot 010020, ChinaWater Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, ChinaWater Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, ChinaStudy region: The largest lake in China's Yellow River Basin, Ulansuhai. Study focus: After implementing the optimal noise reduction strategies based on wavelet transform for the high-frequency monitoring data, hybrid models coupling random forests, support vector machines, and artificial neural networks were employed to simulate the dissolved oxygen in the lake during both the open-water and ice-covered periods. The optimal hybrid model for each period was selected through extensive analysis, and the shapley additive explanations method was utilized to quantify the contribution of feature variables to the results. New hydrological insight for the region: The results revealed MAE, RMSE, and NSE values of 0.76, 1.01, and 0.92 for WT-RF, and 0.42, 0.55, and 0.84 for WT-SVM. They represent the optimal hybrid models for the open-water and ice-covered periods, respectively. The SHAP analysis showed that water temperature, blue-green algae, pH, turbidity, electrical conductivity, and chlorophyll.a exhibited significant importance in the WT-RF model, in that order. BGA and Chl.a synergistically promoted the increase in DO levels during the open-water period. For the WT-SVM model, Chl.a, BGA, Tur, and Temp exhibited significant contributions to the simulation results in that order. However, only BGA was able to enhance DO levels during the ice-covered period. As seasons change, shifts in key water environment factors affecting DO reveal the complexity of lake ecosystems in a cold and arid region.http://www.sciencedirect.com/science/article/pii/S2214581824004580Dissolved oxygenSeasonal changesWavelet transformMachine learningHybrid modelUlansuhai Lake |
| spellingShingle | Fan Zhang Xiaohong Shi Shengnan Zhao Ruonan Hao Biao Sun Guohua Li Shihuan Wang Hao Zhang Simulation and explanatory analysis of dissolved oxygen dynamics in Lake Ulansuhai, China Journal of Hydrology: Regional Studies Dissolved oxygen Seasonal changes Wavelet transform Machine learning Hybrid model Ulansuhai Lake |
| title | Simulation and explanatory analysis of dissolved oxygen dynamics in Lake Ulansuhai, China |
| title_full | Simulation and explanatory analysis of dissolved oxygen dynamics in Lake Ulansuhai, China |
| title_fullStr | Simulation and explanatory analysis of dissolved oxygen dynamics in Lake Ulansuhai, China |
| title_full_unstemmed | Simulation and explanatory analysis of dissolved oxygen dynamics in Lake Ulansuhai, China |
| title_short | Simulation and explanatory analysis of dissolved oxygen dynamics in Lake Ulansuhai, China |
| title_sort | simulation and explanatory analysis of dissolved oxygen dynamics in lake ulansuhai china |
| topic | Dissolved oxygen Seasonal changes Wavelet transform Machine learning Hybrid model Ulansuhai Lake |
| url | http://www.sciencedirect.com/science/article/pii/S2214581824004580 |
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