Diao Yixuan, Xia Jun, Dong Qianjin, Zuo Qiting, Xie Mengyun
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, China.
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, China.
J Environ Manage. 2025 Apr;380:125078. doi: 10.1016/j.jenvman.2025.125078. Epub 2025 Mar 24.
Global climate change and resource depletion increase the risks of water and land resource scarcity, yet our understanding of how to optimize the matching of these resources and their economic implications remains limited. This study proposes a novel framework based on matching degree analysis to evaluate the matching status of water-land resources and its impact on economic development. Applying a multi-dimensional matching approach to the lower Yellow River floodplain, we explore the spatial and temporal dynamics of water-land matching across different economic development type, along with the impact on the economy. By integrating the Cellular Automata Markov (CA-Markov) model with CMIP6 climate scenarios, we analyze future land-use changes and resource dynamics under various climate conditions. The findings reveal significant regional heterogeneity in the role of water and land resources in economic development. Production-intensive areas exhibit stable resource support, while agriculture-dependent areas show more variability, overall, the degree of water-land matching positively influences economic performance in most regions (66%). As urbanization progresses, gross domestic product (GDP) and urbanization rates emerge as dominant factors shaping resource-economic dynamics. Future projections indicate that water and land resources will stably support economic production in both industrial and agricultural regions. However, regions such as Taiqian and Dong'e, which focus on modern agriculture and ecological protection, are expected to experience more significant fluctuations in resource availability and economic outcomes. This study provides a holistic framework for optimizing resource management and informs policies to enhance regional resilience amid climate change and resource constraints.
全球气候变化和资源枯竭增加了水资源和土地资源稀缺的风险，然而我们对如何优化这些资源的匹配及其经济影响的理解仍然有限。本研究提出了一个基于匹配度分析的新颖框架，以评估水土资源的匹配状况及其对经济发展的影响。应用多维匹配方法对黄河下游洪泛区进行研究，我们探讨了不同经济发展类型下水土匹配的时空动态，以及对经济的影响。通过将元胞自动机-马尔可夫（CA-Markov）模型与CMIP6气候情景相结合，我们分析了各种气候条件下未来的土地利用变化和资源动态。研究结果揭示了水土资源在经济发展中的作用存在显著的区域异质性。生产密集型地区表现出稳定的资源支持，而农业依赖型地区则表现出更大的变异性。总体而言，在大多数地区（66%），水土匹配程度对经济绩效有积极影响。随着城市化进程的推进，国内生产总值（GDP）和城市化率成为塑造资源-经济动态的主导因素。未来预测表明，水土资源将稳定支持工业和农业地区的经济生产。然而，台前和东阿等专注于现代农业和生态保护的地区，预计资源可用性和经济成果将出现更显著的波动。本研究为优化资源管理提供了一个整体框架，并为在气候变化和资源约束下增强区域复原力的政策提供了参考。
