Optimization Model Of Water-food-energy System In Xiangyang Section Of The Middle Reaches Of Hanjiang River

As strategic basic resources,water,food and energy are the three core elements on which human beings depend,and neglect of any one of them will affect the steady development of society.In the Water-food-energy(WFE)relationship,the production,distribution and dispatching of water requires energy consumption,the production and use of food cannot be separated from the consumption of water and energy,and the extraction,processing and transformation of energy also requires water and food,making the three WFE interdependent and closely linked.As a traditional production base for grain,cotton,oil and fishery,the Hanjiang River basin is also a water source and impact area for the South-North Water Transfer Project,and has the important task of “sending a reservoir of clear water northwards” and maintaining ecological security.However,the Hanjiang River basin is facing the problem of limited water supply,for example,in the northern Hubei region,which accounts for 3.6% of the province’s water resources and9.75% of the arable land,grain production accounts for 12.43% of the province,and the shortage of water resources has exacerbated the conflict between WFE in the region.To this end,in 2018 the National Development and Reform Commission issued the Development Plan for the Hanjiang River Ecological and Economic Belt,which clearly sets out the requirements of “effectively protecting and utilising water resources”,“developing efficient ecological agriculture” and “accelerating the development and utilisation of clean energy”.Therefore,it is important to study the relationship of WFE systems and develop a synergistic management strategy for WFE to promote the positive interaction and coordinated development of regional WFE.In this study,the ARIMA method is used to predict the annual precipitation of the Xiangyang section of the Hanjiang River and obtain the probability distribution values at different flow levels.A two-stage credible stochastic programming method(GTCS)with Green Z-score criterion is developed,which can deal with probabilistic uncertainties,optimise risks arising from system satisfaction,parameter imprecision,etc.,reflect different risk attitudes of decision makers and improve the reliability of decisions.The GTCS is applied to the Xiangyang section of the Han River to construct a water-grainenergy system optimisation model(WFEM),with system benefit optimisation as the research objective and available water resources,water supply and multi-reservoir balance as constraints,to obtain water allocation,food production,hydropower generation and system benefit scenarios for different planning periods,different flow levels and different confidence levels,providing decision makers with scientific and rational decision Support The specific conclusions are as follows:(1)Municipal,industrial,and agricultural users experience varying amounts of water shortages.Agricultural users have the most severe water shortages,followed by industrial users and municipal users the least.Overflows occurred mainly at flow scenarios of h =4 and h = 5.Stochastic events(e.g.,water shortage or overflow)are corrected for by recourse behaviour in two-stage stochastic planning,which allows for optimal water allocation scenarios.Based on the Green Z-score criterion,the solution results under the Hurwicz and Laplace criteria are chosen as the optimal water allocation scheme for various flow levels.(2)Food production reduction decreases gradually with increasing water flow level.The decision maker could choose the result under optimistic neutrality(e.g.,Hurwicz and Laplace decision criterion)as the optimal grain yield scenario for different flow levels in the study area.(3)Electricity generation shortages decrease progressively with increasing flow levels and,simultaneously,generation shortages could lead to generation losses.Decision makers could choose the optimal generation outcome in a robust neutral state(e.g.,Laplace and Maximin’s criterion)as the optimal generation solution,thus regulating the balance between the expected demand target for generation and supply capacity in the study area and reducing generation losses.(4)The optimism coefficient had a positive effect on system benefits,while the robustness coefficient and plausibility level had a negative effect on system benefits.Decision makers could adjust for changes in system benefits based on the Green Z-score criterion and plausibility levels,considering the system benefit results under a neutral attitude(α = 0.8,λ = 0.5,β = 50)as a compromise and optimal solution for future waterfood-energy planning.