Evaluation and prediction of carrying capacity of soil and water resources in Lanzhou City based on the CA–Markov model

ABSTRACT To promote sustainable development, evaluating the carrying capacity of soil and water resources has become indispensable. This study establishes an evaluation system using the driving force–pressure–state–impact–response framework and employs the entropy weight cloud model to comprehensively assess the water and soil resource capacity of Lanzhou. Additionally, the CA–Markov model and the gray prediction model were deployed to forecast Lanzhou's future water and soil resource capacity. The evaluation from 2010 to 2022 indicates consistent classification at overloaded or severely overloaded levels, highlighting systemic inefficiency in water and soil resource utilization, which poses a significant obstacle to sustainability. Notably, urbanization rate, water productivity coefficient, and per capita water resources were identified as key factors influencing these results. Based on the forecast for the next 5 years (2023–2027), the water and soil resource capacity of Lanzhou is expected to further decline, posing challenges to sustainable development. This study provides technical support and decision-making guidance for the formulation of Lanzhou's water and soil resource management strategies and sustainable development planning, playing a key role in promoting efficient resource utilization and protecting regional water and soil resources.

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Publication Details

Journal
Water Science & Technology Water Supply
Published
2024-12-18
DOI
https://doi.org/10.2166/ws.2024.262
Citations
2
Primary Topic
Water Resources and Sustainability
Type
article
Field-Weighted Citation Impact
0.40

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article

Evaluation and prediction of carrying capacity of soil and water resources in Lanzhou City based on the CA–Markov model

Tianhong Zhou, Hualan Wang, Junying Chu, Kai Ma et al.
2 citations
Water Science & Technology Water Supply
Water Resources and Sustainability
0.40
article

Evaluation and prediction of carrying capacity of soil and water resources in Lanzhou City based on the CA–Markov model

Tianhong Zhou, Hualan Wang, Junying Chu, Kai Ma, Junfeng Gao, Feihu An
article en
2 citations

Abstract

ABSTRACT To promote sustainable development, evaluating the carrying capacity of soil and water resources has become indispensable. This study establishes an evaluation system using the driving force–pressure–state–impact–response framework and employs the entropy weight cloud model to comprehensively assess the water and soil resource capacity of Lanzhou. Additionally, the CA–Markov model and the gray prediction model were deployed to forecast Lanzhou's future water and soil resource capacity. The evaluation from 2010 to 2022 indicates consistent classification at overloaded or severely overloaded levels, highlighting systemic inefficiency in water and soil resource utilization, which poses a significant obstacle to sustainability. Notably, urbanization rate, water productivity coefficient, and per capita water resources were identified as key factors influencing these results. Based on the forecast for the next 5 years (2023–2027), the water and soil resource capacity of Lanzhou is expected to further decline, posing challenges to sustainable development. This study provides technical support and decision-making guidance for the formulation of Lanzhou's water and soil resource management strategies and sustainable development planning, playing a key role in promoting efficient resource utilization and protecting regional water and soil resources.

Water Science & Technology Water SupplyVol. 25(1)
Lanzhou Jiaotong University (CN), China Institute of Water Resources and Hydropower Research (CN)
Chinese Academy of Engineering
Openalex Percentile: Top 37%
Water Resources and Sustainability
0.40
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Evaluation and prediction of carrying capacity of soil and water resources in Lanzhou City based on the CA–Markov model — Tianhong Zhou, Hualan Wang, et al. · Water Science & Technology Water Supply (2024) | TGRS Research Map | TGRS