Regional water and land resource equilibrium optimization allocation under climate change

Luoyang City, Henan Province, China In recent decades, climate change and accelerated urbanization have driven intensifying competition for water and land resources, rendering conventional allocation methods increasingly inadequate for addressing complex future demands. To address this challenge, we proposes a regional water and land resource equilibrium optimization allocation framework under climate change (RWLEOFCC). The framework can predict regional water resource variations under diverse climate scenarios and land-use patterns. It incorporates Maslow's hierarchy of needs theory to integrate equilibrium principles into demand-side considerations, while comprehensively considering the mutual feedback mechanisms between water and land to achieve joint coordinated allocation. Furthermore, a two-layer nested algorithm based on successive approximation and nonlinear multi-objective programming (SA-NLMOP) is developed to efficiently iteratively solve the framework and obtain the regional optimal land use pattern and optimal water allocation scheme. The optimized allocation scheme demonstrates multidimensional improvements over the current status quo: Satisfaction increased by 1.65–14.47 %, available water resources expanded by 0.141–0.308 × 10⁸ m³ , and the supply-demand ratio improved by 2.94–9.56 %. Although GDP exhibits a slight decline, the rigid demands of water users are largely met, and the overall resource utilization becomes more coordinated and efficient. This study offers new insights and technical support for adapting to climate change, mitigating water scarcity, and promoting the equilibrium allocation of regional water and land resources. • Optimal allocation of regional water and land resources under three SSP scenarios. • A two-layer nested SA-NLMOP algorithm is developed to efficiently solve the RWLEOFCC. • Selecting the regional optimal GCM by Taylor diagram analysis of downscaled data. • Applying equilibrium theory to resource allocation reduces interregional competition.