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Ecological vulnerability assessment based on multi-sources data and SD model in Yinma River Basin, China

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  • Zhang, Feng
  • Liu, Xingpeng
  • Zhang, Jiquan
  • Wu, Rina
  • Ma, Qiyun
  • Chen, Yanan

Abstract

Ecological vulnerability assessment is a key approach to adaptation to and mitigation of environmental degradation. To assess the ecological vulnerability of Yinma River Basin in cold mountain region of China, the ecological vulnerability index (EVI) model was established based on the integrated system dynamic (SD) model and driving force-pressure-state-impact-response-management (DPSIRM) framework. Using multi-sources data including meteorological, remote sensing, basic geographical, sample and socio-economic data, the values of EVI were calculated. The assessment results indicated that the overall ecosystem vulnerability conditions in the study area experienced a degenerating trend. The extremely, heavily and moderately vulnerable zones were mainly distributed in the north-central and southwest parts of the basin. The slightly and lightly vulnerable areas were distributed in the southeast part of the basin. For the distribution of ecological vulnerability grades, in administrative regions, the high rate of slightly vulnerable level and light vulnerable level appeared in Shuangyang district and Panshi city while the largest area rate of moderately, heavily and extremely vulnerable level were distributed in Dehui city, Nongan county, Jiutai district and Yitong county. The study demonstrated that the SD model could efficiently reflect the dynamic mechanism of the basin ecological vulnerability and the results gained closely reflected the reality of the study area.

Suggested Citation

  • Zhang, Feng & Liu, Xingpeng & Zhang, Jiquan & Wu, Rina & Ma, Qiyun & Chen, Yanan, 2017. "Ecological vulnerability assessment based on multi-sources data and SD model in Yinma River Basin, China," Ecological Modelling, Elsevier, vol. 349(C), pages 41-50.
    • Handle: RePEc:eee:ecomod:v:349:y:2017:i:c:p:41-50
    DOI: 10.1016/j.ecolmodel.2017.01.016
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    3. Qin Liu & Tiange Shi, 2019. "Spatiotemporal Differentiation and the Factors of Ecological Vulnerability in the Toutun River Basin Based on Remote Sensing Data," Sustainability, MDPI, vol. 11(15), pages 1-19, August.
    4. Tan, Kun & Zhao, Xiaoqing & Pu, Junwei & Li, Sinan & Li, Yuhao & Miao, Peipei & Wang, Qian, 2021. "Zoning regulation and development model for water and land resources in the Karst Mountainous Region of Southwest China," Land Use Policy, Elsevier, vol. 109(C).
    5. Wang, Qiang & Zhan, Lina, 2019. "Assessing the sustainability of the shale gas industry by combining DPSIRM model and RAGA-PP techniques: An empirical analysis of Sichuan and Chongqing, China," Energy, Elsevier, vol. 176(C), pages 353-364.
    6. Han Zhang & Qingshan Feng & Bingchuan Yan & Xianbin Zheng & Yue Yang & Jian Chen & Hong Zhang & Xiaoben Liu, 2023. "State of the Art of Oil and Gas Pipeline Vulnerability Assessments," Energies, MDPI, vol. 16(8), pages 1-17, April.
    7. Chunsheng Wu & Gaohuan Liu & Chong Huang & Qingsheng Liu & Xudong Guan, 2018. "Ecological Vulnerability Assessment Based on Fuzzy Analytical Method and Analytic Hierarchy Process in Yellow River Delta," IJERPH, MDPI, vol. 15(5), pages 1-14, April.
    8. Yaohan Cheng & Chengxiu Li & Shuting He & Ling Li & Liangyun Dong & Xiuli Wang, 2023. "Coordinated Development Path of Cultivated Land Utilization in Henan Section of the Yellow River Basin," Land, MDPI, vol. 12(7), pages 1-24, July.
    9. Su, Jia & Huang, Guangqiu, 2018. "Simulation and analysis of ecosystem vulnerability with cascading spread caused by dust migration based on object function GeoPetri net," Ecological Modelling, Elsevier, vol. 379(C), pages 54-72.
    10. Mingxin Wen & Ting Zhang & Long Li & Longqian Chen & Sai Hu & Jia Wang & Weiqiang Liu & Yu Zhang & Lina Yuan, 2021. "Assessment of Land Ecological Security and Analysis of Influencing Factors in Chaohu Lake Basin, China from 1998–2018," Sustainability, MDPI, vol. 13(1), pages 1-28, January.
    11. Dong Li & Chongyang Huan & Jun Yang & Hanlong Gu, 2022. "Temporal and Spatial Distribution Changes, Driving Force Analysis and Simulation Prediction of Ecological Vulnerability in Liaoning Province, China," Land, MDPI, vol. 11(7), pages 1-25, July.

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