From resource matching to economic sustainability: A multi-stage analysis of water-land-economy interactions in the lower Yellow River Basin.

Abstract

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.