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Predicting the Evolution Trend of Water and Land Resource Carrying Capacity Based on CA–Markov Model in an Arid Region of Northwest China

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  • Cundong Xu

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
    Key Laboratory for Technology in Rural Water Management of Zhejiang Province, Hangzhou 310018, China
    Henan Provincial Hydraulic Structure Safety Engineering Research Center, Zhengzhou 450046, China)

  • Xiaomeng Hu

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Zijin Liu

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Xin Wang

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Junjiao Tian

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Zhihong Zhao

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

Abstract

The evolution of water and land resource carrying capacity significantly impacts optimal water and land resource allocation and regional sustainable development in arid regions. This study proposes a model that combines cellular automaton (CA) and Markov; this model aids in predicting spatial changes in water and land resource availability. In this study, taking the Jingdian Irrigation District in China’s northwest arid region as an example, we used long-series monitoring data and a Landsat dataset to create a raster-weighted fusion of 18 indicators and quantitatively analyzed the carrying status of water and land resources from 1994 to 2018. The CA–Markov model was used to simulate the carrying status of water and land resources in 2018 and to perform accuracy correction. The validated CA–Markov model was used to predict water and land resource carrying status in 2026 and 2034. The results show (1) from 1994 to 2018, the area of “good carrying” zone increased by 10.42%, the area of “safe carrying” zone increased by 7%, and spatially rose in an arc from the town to the surrounding regions. The area of “critical carrying” zone remains almost unchanged. The area of “slight carrying” zone decreased by 5.18% and the area of “severe carrying” zone decreased by 11.99%. (2) Comparing the actual and predicted carrying state of water and land resources in 2018, it was found that the simulation accuracy of “good carrying”, “safe carrying”, “critical carrying”, “slight carrying”, and “severe carrying” reached 98.71%, 92.07%, 95.34%, 94.05%, and 93.73%, respectively. This indicates that the simulation results have high reliability and applicability. (3) The future medium and long-term carrying status of water and land resources are healthy, but this trend is gradually slowing. The “slight carrying” and “severe carrying” zones show the gradual spatial transition from land desertification to soil salinization.

Suggested Citation

  • Cundong Xu & Xiaomeng Hu & Zijin Liu & Xin Wang & Junjiao Tian & Zhihong Zhao, 2023. "Predicting the Evolution Trend of Water and Land Resource Carrying Capacity Based on CA–Markov Model in an Arid Region of Northwest China," Sustainability, MDPI, vol. 15(2), pages 1-16, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1269-:d:1030263
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    References listed on IDEAS

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    1. Irmi Seidl & Clem A. Tisdell, 2003. "Carrying capacity reconsidered: from Malthus' population theory to cultural carrying capacity," Chapters, in: Ecological and Environmental Economics, chapter 13, pages 192-206, Edward Elgar Publishing.
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    3. Fausto Pedro García Márquez & Benjamin Lev (ed.), 2023. "Sustainability," International Series in Operations Research and Management Science, Springer, number 978-3-031-16620-4, March.
    4. Junfeng Yang & Kun Lei & Soonthiam Khu & Wei Meng, 2015. "Assessment of Water Resources Carrying Capacity for Sustainable Development Based on a System Dynamics Model: A Case Study of Tieling City, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(3), pages 885-899, February.
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