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Li B, Wan R, Yang G. Centennial dynamics of floodplain wetland in the largest freshwater lake in China: Implications on floodplain lake restoration. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 353:120192. [PMID: 38286070 DOI: 10.1016/j.jenvman.2024.120192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 12/04/2023] [Accepted: 01/20/2024] [Indexed: 01/31/2024]
Abstract
Long-term mapping of floodplain wetland dynamics is fundamental for wetland protection and restoration, but it is restricted to decadal scales using satellite observations owing to scarcity of spatial data over long-term scales. The present study concentrates on the centennial dynamics of floodplain wetland in Poyang Lake, the largest freshwater lake in China. Historical topographic maps and Landsat imagery were combined to reconstruct the centennial floodplain wetland map series. A robust random forest algorithm for the land cover classification was used to investigate the conversion of the floodplain wetland to other land cover types and quantify the magnitude of the influence of hydrological disconnection over the past century. Results show that the Poyang Lake floodplain wetland experienced a net loss of 35.7 %, from 5024.3 km2 in the 1920s-1940s to 3232.1 km2 in the 2020s, with the floodplain wetland loss occurring mostly from the 1950s to the 1970s. In addition, agricultural encroachment was identified as the predominant driver of floodplain wetland loss, with a total area of 931.0 km2 of the floodplain wetland converted into cropland. Furthermore, approximately 600 km2 of sub-lakes (larger than 1 km2) became isolated from the floodplain and thus unaffected by seasonal flood pulses, which highlights the need to account for the impact of hydrological disconnection on floodplain wetland dynamics. This study indicated the combination of historical maps and satellite observations as an effective tool to track long-term wetland changes. The resultant dataset provides an extended baseline and could shed some light on floodplain wetland conservation and restoration.
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Affiliation(s)
- Bing Li
- Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, PR China; University of Chinese Academy of Sciences, Beijing, 100049, PR China; College of Nanjing, University of Chinese Academy of Sciences, Nanjing, 211135, PR China; Poyang Lake Wetland Research Station, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, PR China
| | - Rongrong Wan
- Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, PR China; University of Chinese Academy of Sciences, Beijing, 100049, PR China; College of Nanjing, University of Chinese Academy of Sciences, Nanjing, 211135, PR China; Poyang Lake Wetland Research Station, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, PR China.
| | - Guishan Yang
- Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, PR China; University of Chinese Academy of Sciences, Beijing, 100049, PR China; College of Nanjing, University of Chinese Academy of Sciences, Nanjing, 211135, PR China.
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Dou X, Guo H, Zhang L, Liang D, Zhu Q, Liu X, Zhou H, Lv Z, Liu Y, Gou Y, Wang Z. Dynamic landscapes and the influence of human activities in the Yellow River Delta wetland region. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 899:166239. [PMID: 37572926 DOI: 10.1016/j.scitotenv.2023.166239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 08/09/2023] [Accepted: 08/09/2023] [Indexed: 08/14/2023]
Abstract
The Yellow River Delta (YRD) wetland is one of the largest and youngest wetland ecosystems in the world. It plays an important role in regulating climate and maintaining ecological balance in the region. This study analyzes the spatiotemporal changes in land use, wetland migration, and landscape pattern from 2013 to 2022 using Landsat-8 and Sentinel-1 data in YRD. Then wetland landscape changes and the impact of human activities are determined by analyzing correlation between landscape and socio-economic indicators including nighttime light centroid, total light intensity, cultivated land area and centroid, building area and centroid, economic and population. The results show that the total wetland area increased 1426 km2 during this decade. However, the wetland landscape pattern tended to be fragmented from 2013 to 2022, with wetlands of different types interlacing and connectivity decreasing, and distribution becoming more concentrated. Different types of human activities had influences on different aspects of wetland landscape, with the expansion of cultivated land mainly compressing the core area of wetlands from the edge, the expansion of buildings mainly disrupting wetland connectivity, and socio-economic indicators such as total light intensity and the centroid mainly causing wetland fragmentation. The results show the changes of the YRD wetland and provide an explanation of how human activities effect the change of its landscape, which provides available data to achieve sustainable development goals 6.6 and may give an access to measure the change of wetland using human-activity data, which could help to adject behaviors to protect wetlands.
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Affiliation(s)
- Xinyu Dou
- School of Earth and Space Sciences, Peking University, Beijing 100871, China; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
| | - Huadong Guo
- School of Earth and Space Sciences, Peking University, Beijing 100871, China; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China.
| | - Lu Zhang
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China.
| | - Dong Liang
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China
| | - Qi Zhu
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China
| | - Xuting Liu
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China
| | - Heng Zhou
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China
| | - Zhuoran Lv
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China
| | - Yiming Liu
- School of Earth and Space Sciences, Peking University, Beijing 100871, China; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
| | - Yiting Gou
- International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China
| | - Zhoulong Wang
- Signal & Communication Research Institute, China Academy of Railway Sciences Group Co., Ltd, Beijing 100081, China
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