Assessment and enhancement pathways of the water-energy-food-economy-ecosystem nexus in China's yellow river basin

Chenjun Zhang, Yaqiu Wei, Xiangyang Zhao and Jinren Hu

Energy, 2025, vol. 316, issue C

Abstract: Expanding the traditional Water-Energy-Food (WEF) Nexus to a Water-Energy-Food-Economy-Ecosystem (WEFEE) Nexus can facilitate a more scientific and comprehensive evaluation of a region's sustainable development level. This paper employed a slacks-based measure super-efficiency (Super-SBM) Network Data Envelopment Analysis (DEA) model to measure the efficiency of the WEFEE system and agricultural water saving in the Yellow River Basin (YRB) from 2005 to 2022. Subsequently, multiple scenarios were set up, and a Grey Elman Neural Network Model based on Genetic Algorithm (GM-GA-Elman) was designed to predict the efficiency. The study showed that: (1) The introduction of economy and ecosystem into the WEF system to form the WEFEE system resulted in a significant increase in efficiency; (2) The efficiency of the WEFEE system in the YRB had been at a relatively high level from 2005 to 2022, while the agricultural water-saving efficiency generally low; (3) The GM-GA-Elman model demonstrated a commendable capability in forecasting the efficiency metrics and tendencies of the WEFEE system within the YRB; (4) Scenario 4 was identified as the optimal scenario of the WEFEE system. Scenario 7 represented an optimal situation for agricultural water saving. Conflicts existed between the optimization of subsystem efficiencies and the overall efficiency of the WEFEE Nexus.

Keywords: Water-energy-food-economy-ecosystem nexus; Super-SBM; Network DEA; Grey model; Genetic algorithm; Elman neural network model (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:316:y:2025:i:c:s0360544225001343

DOI: 10.1016/j.energy.2025.134492

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