Unraveling the Importance of the Yangtze River and Local Catchment on Water Level Variations of Poyang Lake (China) After the Three Gorges Dam Operation: Insights From Random Forest Modeling
Investigating the contributions of the factors influencing lake water level and their related changes with regard to hydraulic facilities is vital for understanding the driving mechanism of water level variations under the manifold pressures from anthropogenic activities and climate change. In this...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-07-01
|
| Series: | Frontiers in Earth Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2022.927462/full |
| _version_ | 1811323212121767936 |
|---|---|
| author | Bing Li Bing Li Bing Li Guishan Yang Guishan Yang Guishan Yang Rongrong Wan Rongrong Wan Rongrong Wan Yanan Wang Yanan Wang Yanan Wang Chen Xu Dianchang Wang Chuang Mi |
| author_facet | Bing Li Bing Li Bing Li Guishan Yang Guishan Yang Guishan Yang Rongrong Wan Rongrong Wan Rongrong Wan Yanan Wang Yanan Wang Yanan Wang Chen Xu Dianchang Wang Chuang Mi |
| author_sort | Bing Li |
| collection | DOAJ |
| description | Investigating the contributions of the factors influencing lake water level and their related changes with regard to hydraulic facilities is vital for understanding the driving mechanism of water level variations under the manifold pressures from anthropogenic activities and climate change. In this study, a random forest (RF) model was used to investigate the changes of the relationship between water level and discharge of the Yangtze River and local tributaries in Poyang Lake, China, based on daily hydrological data from 1980 to 2018. The results indicated that RF exhibited robust capability for water level prediction in Poyang Lake, with average R2 of 0.95, 0.88, 0.92, and 0.94 for the dry, rising, wet, and recession seasons, respectively. Predictor importance analysis showed that the discharge of the Yangtze River had greater influence on the water level than the discharge of local tributaries except for the dry season in Poyang Lake, where the influence on the water level was evident with discharge less than 5,000 m3/s. The influence of the Yangtze River also showed a clear attenuation pattern as the distance from the outlet of the lake increased, where the water level was constantly regulated by the Yangtze River. In addition, the partial dependence plots also indicated that the Yangtze River discharge changes after the TGD operation have resulted in remarkable water level decreases in the wet and recession seasons, especially for the recession period. Meanwhile, a slight increase in water level was predicted under identical discharge of local catchment in the dry season, which was only concentrated in the outlet of the lake. This study indicated the RF model as a robust technique for water level predictions and attribution analysis under multiple temporal and spatial scales. Moreover, this study confirmed the uneven influences of the Yangtze River and local tributaries on water level across different seasons, gauging stations, and phases. |
| first_indexed | 2024-04-13T13:50:02Z |
| format | Article |
| id | doaj.art-69177ae23ced45f2acb8a0258b919096 |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-04-13T13:50:02Z |
| publishDate | 2022-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj.art-69177ae23ced45f2acb8a0258b9190962022-12-22T02:44:21ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632022-07-011010.3389/feart.2022.927462927462Unraveling the Importance of the Yangtze River and Local Catchment on Water Level Variations of Poyang Lake (China) After the Three Gorges Dam Operation: Insights From Random Forest ModelingBing Li0Bing Li1Bing Li2Guishan Yang3Guishan Yang4Guishan Yang5Rongrong Wan6Rongrong Wan7Rongrong Wan8Yanan Wang9Yanan Wang10Yanan Wang11Chen Xu12Dianchang Wang13Chuang Mi14Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, ChinaCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, ChinaCollege of Nanjing, University of Chinese Academy of Sciences, Nanjing, ChinaKey Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, ChinaCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, ChinaCollege of Nanjing, University of Chinese Academy of Sciences, Nanjing, ChinaKey Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, ChinaCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, ChinaCollege of Nanjing, University of Chinese Academy of Sciences, Nanjing, ChinaKey Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, ChinaCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, ChinaCollege of Nanjing, University of Chinese Academy of Sciences, Nanjing, ChinaSuzhou University of Science and Technology, Suzhou, ChinaChina Three Gorges Corporation, Wuhan, ChinaChina Three Gorges Corporation, Wuhan, ChinaInvestigating the contributions of the factors influencing lake water level and their related changes with regard to hydraulic facilities is vital for understanding the driving mechanism of water level variations under the manifold pressures from anthropogenic activities and climate change. In this study, a random forest (RF) model was used to investigate the changes of the relationship between water level and discharge of the Yangtze River and local tributaries in Poyang Lake, China, based on daily hydrological data from 1980 to 2018. The results indicated that RF exhibited robust capability for water level prediction in Poyang Lake, with average R2 of 0.95, 0.88, 0.92, and 0.94 for the dry, rising, wet, and recession seasons, respectively. Predictor importance analysis showed that the discharge of the Yangtze River had greater influence on the water level than the discharge of local tributaries except for the dry season in Poyang Lake, where the influence on the water level was evident with discharge less than 5,000 m3/s. The influence of the Yangtze River also showed a clear attenuation pattern as the distance from the outlet of the lake increased, where the water level was constantly regulated by the Yangtze River. In addition, the partial dependence plots also indicated that the Yangtze River discharge changes after the TGD operation have resulted in remarkable water level decreases in the wet and recession seasons, especially for the recession period. Meanwhile, a slight increase in water level was predicted under identical discharge of local catchment in the dry season, which was only concentrated in the outlet of the lake. This study indicated the RF model as a robust technique for water level predictions and attribution analysis under multiple temporal and spatial scales. Moreover, this study confirmed the uneven influences of the Yangtze River and local tributaries on water level across different seasons, gauging stations, and phases.https://www.frontiersin.org/articles/10.3389/feart.2022.927462/fullwater level fluctuationsrandom forestpartial dependencePoyang LakeTGD operation |
| spellingShingle | Bing Li Bing Li Bing Li Guishan Yang Guishan Yang Guishan Yang Rongrong Wan Rongrong Wan Rongrong Wan Yanan Wang Yanan Wang Yanan Wang Chen Xu Dianchang Wang Chuang Mi Unraveling the Importance of the Yangtze River and Local Catchment on Water Level Variations of Poyang Lake (China) After the Three Gorges Dam Operation: Insights From Random Forest Modeling Frontiers in Earth Science water level fluctuations random forest partial dependence Poyang Lake TGD operation |
| title | Unraveling the Importance of the Yangtze River and Local Catchment on Water Level Variations of Poyang Lake (China) After the Three Gorges Dam Operation: Insights From Random Forest Modeling |
| title_full | Unraveling the Importance of the Yangtze River and Local Catchment on Water Level Variations of Poyang Lake (China) After the Three Gorges Dam Operation: Insights From Random Forest Modeling |
| title_fullStr | Unraveling the Importance of the Yangtze River and Local Catchment on Water Level Variations of Poyang Lake (China) After the Three Gorges Dam Operation: Insights From Random Forest Modeling |
| title_full_unstemmed | Unraveling the Importance of the Yangtze River and Local Catchment on Water Level Variations of Poyang Lake (China) After the Three Gorges Dam Operation: Insights From Random Forest Modeling |
| title_short | Unraveling the Importance of the Yangtze River and Local Catchment on Water Level Variations of Poyang Lake (China) After the Three Gorges Dam Operation: Insights From Random Forest Modeling |
| title_sort | unraveling the importance of the yangtze river and local catchment on water level variations of poyang lake china after the three gorges dam operation insights from random forest modeling |
| topic | water level fluctuations random forest partial dependence Poyang Lake TGD operation |
| url | https://www.frontiersin.org/articles/10.3389/feart.2022.927462/full |
| work_keys_str_mv | AT bingli unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT bingli unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT bingli unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT guishanyang unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT guishanyang unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT guishanyang unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT rongrongwan unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT rongrongwan unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT rongrongwan unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT yananwang unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT yananwang unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT yananwang unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT chenxu unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT dianchangwang unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling AT chuangmi unravelingtheimportanceoftheyangtzeriverandlocalcatchmentonwaterlevelvariationsofpoyanglakechinaafterthethreegorgesdamoperationinsightsfromrandomforestmodeling |