1
|
Cho MS, Park J. Spatiotemporal lake area changes influenced by climate change over 40 years in the Korean Peninsula. Sci Rep 2024; 14:1144. [PMID: 38212426 PMCID: PMC10784581 DOI: 10.1038/s41598-023-51084-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 12/30/2023] [Indexed: 01/13/2024] Open
Abstract
Water resources in lakes of the Korean Peninsula play a significant role in society and ecosystems in both South and North Korea. This study characterized spatiotemporal changes in the lake area during the dry season (March-May) in the Korean Peninsula over the last 40 years. The satellite images (Landsat 5-9) were used to derive annual areas of 975 lakes during the dry season from 1984 to 2023. Our analysis indicated that the MNDWI is the optimal remote sensing-based index for delineating lake areas in the Korean Peninsula, with an overall accuracy of 92.3%. Based on the selected index, the total lake areas of the dry seasons have increased from 1070.7 km2 in 1984 to 1659.3 km2 in 2023, mainly due to newly constructed dam reservoirs. While the detailed changes in lake area vary, we found divergent results based on their sizes. The large lakes (> 10 km2) showed their area increased by 0.0473 km2 (0.1%) every year and have more influences from climate change. On the contrary, the small lakes (≤ 10 km2) have area decreases by 0.0006-0.006 km2 (0.15-0.5%) every year and have less influence from climate change. This study shows that the spatiotemporal lake area changes are determined by either climate change or human activity.
Collapse
Affiliation(s)
- Myung Sik Cho
- Center for Global Change and Earth Observations, Michigan State University, Lansing, MI, USA
| | - Jinwoo Park
- Department of Geography and Geographic Information Science, University of North Dakota, Grand Forks, ND, USA.
| |
Collapse
|
2
|
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.
Collapse
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
| |
Collapse
|
3
|
Tiwari AD, Pokhrel Y, Kramer D, Akhter T, Tang Q, Liu J, Qi J, Loc HH, Lakshmi V. A synthesis of hydroclimatic, ecological, and socioeconomic data for transdisciplinary research in the Mekong. Sci Data 2023; 10:283. [PMID: 37188677 DOI: 10.1038/s41597-023-02193-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 04/27/2023] [Indexed: 05/17/2023] Open
Abstract
The Mekong River basin (MRB) is a transboundary basin that supports livelihoods of over 70 million inhabitants and diverse terrestrial-aquatic ecosystems. This critical lifeline for people and ecosystems is under transformation due to climatic stressors and human activities (e.g., land use change and dam construction). Thus, there is an urgent need to better understand the changing hydrological and ecological systems in the MRB and develop improved adaptation strategies. This, however, is hampered partly by lack of sufficient, reliable, and accessible observational data across the basin. Here, we fill this long-standing gap for MRB by synthesizing climate, hydrological, ecological, and socioeconomic data from various disparate sources. The data- including groundwater records digitized from the literature-provide crucial insights into surface water systems, groundwater dynamics, land use patterns, and socioeconomic changes. The analyses presented also shed light on uncertainties associated with various datasets and the most appropriate choices. These datasets are expected to advance socio-hydrological research and inform science-based management decisions and policymaking for sustainable food-energy-water, livelihood, and ecological systems in the MRB.
Collapse
Affiliation(s)
- Amar Deep Tiwari
- Department of Civil and Environmental Engineering, Michigan State University, East Lansing, Michigan, USA
| | - Yadu Pokhrel
- Department of Civil and Environmental Engineering, Michigan State University, East Lansing, Michigan, USA.
| | - Daniel Kramer
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, USA
| | - Tanjila Akhter
- Department of Civil and Environmental Engineering, Michigan State University, East Lansing, Michigan, USA
| | - Qiuhong Tang
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Junguo Liu
- School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, China
| | - Jiaguo Qi
- Center for Global Change and Earth Observations, Michigan State University, East Lansing, Michigan, USA
| | - Ho Huu Loc
- Water Engineering and Management, Asian Institute of Technology, Khlong Nueng, Pathum Thani, Thailand
| | - Venkataraman Lakshmi
- Engineering Systems and Environment, University of Virginia, Charlottesville, Virginia, USA
| |
Collapse
|