Water-Body Monitoring and Erosion–Deposition Analysis of East Dongting Lake Based on Long Time-Series Remote Sensing Data
Over the past century, interconnected lakes along the middle and lower Yangtze River have undergone significant siltation, shrinkage, and even disappearance, exacerbating hydrological extremes, such as floods, droughts, and abrupt dry–wet transitions. To investigate the evolution of the r...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11071998/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849420341278932992 |
|---|---|
| author | Lihua Wang Jian Xu Sunan Shi Guozhong Li Shiming Yao Hualong Luan Xiao Xiao Zican He |
| author_facet | Lihua Wang Jian Xu Sunan Shi Guozhong Li Shiming Yao Hualong Luan Xiao Xiao Zican He |
| author_sort | Lihua Wang |
| collection | DOAJ |
| description | Over the past century, interconnected lakes along the middle and lower Yangtze River have undergone significant siltation, shrinkage, and even disappearance, exacerbating hydrological extremes, such as floods, droughts, and abrupt dry–wet transitions. To investigate the evolution of the river–lake relationship in East Dongting Lake under these new conditions, this study utilized the Google Earth Engine platform to extract the water-body extent of East Dongting Lake from 1987 to 2023. We quantified spatiotemporal variations through three analytical dimensions: interannual dynamics, monthly fluctuations, and water-body type. In addition, a correlation analysis between water-body area and water level was conducted using water-level data from Chenglingji and Lujiao. Key findings include: First, a declining trend in the maximum annual water surface area (−0.16 km²/yr), contrasted with an increasing trend in the minimum areas (+1.14 km²/yr); second, pronounced intra-annual variability, with peaks in July (936.70 km²) and minima in January (231.56 km²); and third, a strong correlation was observed between the water surface area of East Dongting Lake and the water levels recorded at Chenglingji and Lujiao hydrological stations. Among the four regression models evaluated, the cubic polynomial model exhibited the highest fitting performance (<italic>R</italic><sup>2</sup>>0.9). Notably, under similar water-level conditions (particularly at middle and low levels), the water area of East Dongting Lake exhibited a decreasing trend. A slight reduction in the permanent water bodies in the central and southwestern regions was observed, alongside an increase in the proportion of seasonal water bodies. These trends suggest that some areas of East Dongting Lake may be undergoing a siltation process. |
| format | Article |
| id | doaj-art-eb3b857e5bf84ecea989508ba7303f85 |
| institution | Kabale University |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-eb3b857e5bf84ecea989508ba7303f852025-08-20T03:31:46ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-0118175801759110.1109/JSTARS.2025.358599011071998Water-Body Monitoring and Erosion–Deposition Analysis of East Dongting Lake Based on Long Time-Series Remote Sensing DataLihua Wang0https://orcid.org/0009-0009-9407-082XJian Xu1https://orcid.org/0000-0003-0579-8472Sunan Shi2Guozhong Li3Shiming Yao4Hualong Luan5Xiao Xiao6Zican He7Spatial Information Technology Application Department, Changjiang River Scientific Research Institute, Changjiang Water Resources Committee, Wuhan, ChinaSpatial Information Technology Application Department, Changjiang River Scientific Research Institute, Changjiang Water Resources Committee, Wuhan, ChinaSpatial Information Technology Application Department, Changjiang River Scientific Research Institute, Changjiang Water Resources Committee, Wuhan, ChinaSpatial Information Technology Application Department, Changjiang River Scientific Research Institute, Changjiang Water Resources Committee, Wuhan, ChinaRiver Research Department, Changjiang River Scientific Research Institute, Changjiang Water Resources Committee, Wuhan, ChinaRiver Research Department, Changjiang River Scientific Research Institute, Changjiang Water Resources Committee, Wuhan, ChinaSpatial Information Technology Application Department, Changjiang River Scientific Research Institute, Changjiang Water Resources Committee, Wuhan, ChinaRiver Research Department, Changjiang River Scientific Research Institute, Changjiang Water Resources Committee, Wuhan, ChinaOver the past century, interconnected lakes along the middle and lower Yangtze River have undergone significant siltation, shrinkage, and even disappearance, exacerbating hydrological extremes, such as floods, droughts, and abrupt dry–wet transitions. To investigate the evolution of the river–lake relationship in East Dongting Lake under these new conditions, this study utilized the Google Earth Engine platform to extract the water-body extent of East Dongting Lake from 1987 to 2023. We quantified spatiotemporal variations through three analytical dimensions: interannual dynamics, monthly fluctuations, and water-body type. In addition, a correlation analysis between water-body area and water level was conducted using water-level data from Chenglingji and Lujiao. Key findings include: First, a declining trend in the maximum annual water surface area (−0.16 km²/yr), contrasted with an increasing trend in the minimum areas (+1.14 km²/yr); second, pronounced intra-annual variability, with peaks in July (936.70 km²) and minima in January (231.56 km²); and third, a strong correlation was observed between the water surface area of East Dongting Lake and the water levels recorded at Chenglingji and Lujiao hydrological stations. Among the four regression models evaluated, the cubic polynomial model exhibited the highest fitting performance (<italic>R</italic><sup>2</sup>>0.9). Notably, under similar water-level conditions (particularly at middle and low levels), the water area of East Dongting Lake exhibited a decreasing trend. A slight reduction in the permanent water bodies in the central and southwestern regions was observed, alongside an increase in the proportion of seasonal water bodies. These trends suggest that some areas of East Dongting Lake may be undergoing a siltation process.https://ieeexplore.ieee.org/document/11071998/East Dongting lakeGoogle Earth Engine (GEE)lake evolutionlong-term serieswater-body extraction |
| spellingShingle | Lihua Wang Jian Xu Sunan Shi Guozhong Li Shiming Yao Hualong Luan Xiao Xiao Zican He Water-Body Monitoring and Erosion–Deposition Analysis of East Dongting Lake Based on Long Time-Series Remote Sensing Data IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing East Dongting lake Google Earth Engine (GEE) lake evolution long-term series water-body extraction |
| title | Water-Body Monitoring and Erosion–Deposition Analysis of East Dongting Lake Based on Long Time-Series Remote Sensing Data |
| title_full | Water-Body Monitoring and Erosion–Deposition Analysis of East Dongting Lake Based on Long Time-Series Remote Sensing Data |
| title_fullStr | Water-Body Monitoring and Erosion–Deposition Analysis of East Dongting Lake Based on Long Time-Series Remote Sensing Data |
| title_full_unstemmed | Water-Body Monitoring and Erosion–Deposition Analysis of East Dongting Lake Based on Long Time-Series Remote Sensing Data |
| title_short | Water-Body Monitoring and Erosion–Deposition Analysis of East Dongting Lake Based on Long Time-Series Remote Sensing Data |
| title_sort | water body monitoring and erosion x2013 deposition analysis of east dongting lake based on long time series remote sensing data |
| topic | East Dongting lake Google Earth Engine (GEE) lake evolution long-term series water-body extraction |
| url | https://ieeexplore.ieee.org/document/11071998/ |
| work_keys_str_mv | AT lihuawang waterbodymonitoringanderosionx2013depositionanalysisofeastdongtinglakebasedonlongtimeseriesremotesensingdata AT jianxu waterbodymonitoringanderosionx2013depositionanalysisofeastdongtinglakebasedonlongtimeseriesremotesensingdata AT sunanshi waterbodymonitoringanderosionx2013depositionanalysisofeastdongtinglakebasedonlongtimeseriesremotesensingdata AT guozhongli waterbodymonitoringanderosionx2013depositionanalysisofeastdongtinglakebasedonlongtimeseriesremotesensingdata AT shimingyao waterbodymonitoringanderosionx2013depositionanalysisofeastdongtinglakebasedonlongtimeseriesremotesensingdata AT hualongluan waterbodymonitoringanderosionx2013depositionanalysisofeastdongtinglakebasedonlongtimeseriesremotesensingdata AT xiaoxiao waterbodymonitoringanderosionx2013depositionanalysisofeastdongtinglakebasedonlongtimeseriesremotesensingdata AT zicanhe waterbodymonitoringanderosionx2013depositionanalysisofeastdongtinglakebasedonlongtimeseriesremotesensingdata |