A modeling framework for the dynamic correlation between agricultural sustainability and the water-land nexus under uncertainty

Abstract

Sustainability is the core concept of modern agricultural planning. Existing studies lack quantitative research on the dynamic effects of the optimal use of agricultural water and land resources (AWLR) on agricultural sustainability. This paper constructs a simulation-optimization-assessment-based modeling framework for the dynamic correlation between agricultural sustainability and the water-land nexus under uncertainty. The framework includes uncertainty simulation of the water supply and demand, development of an optimization model for synergistic regulation of AWLR, and construction of a two-layer dynamic response relationship function between integrated water and land resource use and agricultural sustainability. This framework provides the following advantages: (1) the synergistic allocation of AWLR can be optimized to achieve synergistic development of the five dimensions of resources, economy, society, ecology and environment; (2) the dynamic probability distribution of AWLR and the corresponding response to each dimensional objective and agricultural sustainability can be generated; and (3) the response of agricultural sustainability and AWLR use to changing environments can be obtained. The framework was quantified and analyzed via stochastic simulation, multi-objective nonlinear optimization and fuzzy C-means clustering and applied to the Heilongjiang area of the Songhua River Basin in China. The results indicate that when the irrigation water volume is reduced by 10% and the planted area is increased by 5% in the study area, the economic efficiency increases by 10.49%, the social and ecological effects increase by 10%, and the agricultural sustainability increases by 10.07%. The initial surface water and groundwater irrigation amounts should be regulated within the ranges of [600,800] 107 m3 and [400,600] 107 m3, respectively, and the total amount should not exceed 1150,107 m3. The proposed framework can help reveal the intrinsic linkages between agricultural sustainability and AWLR allocation considering different environmental change scenarios, which can provide authorities with AWLR management decisions in response to changing environments.