A multi-method integrated simulation system for water resources allocation

Water resources allocation is an important technical tool to alleviate the conflict between water supply and demand, improve the water resources utilization efficiency, and achieve the control target of total water resources utilization. However, the current water resources allocation theory is immature, and there are few objective and quantitative allocation methods, which leads to the relatively backward allocation practice. Moreover, the amounts of allocable water resources change dynamically, which makes the static and single traditional allocation scheme difficult to adapt to changes. To address the above issues, this research comprehensively integrated multiple types of allocation models to build a multi-method integrated simulation system for water resources allocation. The results show that the system supports visually generated schemes and dynamically simulates water resources allocation. The application of the simulation system enhances the reliability of results. And the dynamic adaptability of allocation results supports allocation decisions.

Optimal Land And Water Allocation Model For The Maximization of Net Agricultural Return In Drought Prone Regions

In this study, the land and water resources allocation model was developed to determine optimal cropping patterns and water resources allocations at different rainfall probability exceedance levels (PEs) to ensure maximum agricultural return in the Hormat-Golina valley irrigation command area, Ethiopia. To account the uncertainty of rainfall variability, the monthly dependable rainfall was estimated at three levels of reliability (20, 50 and 80% PEs) which are representing wet, normal and dry seasons based on regional experience. The irrigation water demand which was used as an input to the optimization model was estimated at each level of reliability by using CROPWAT model. The net annual returns of optimal cropping patterns were estimated as 181, 179 and 175 million Ethiopia Birr at 20 %, 50 % and 80 % PEs, respectively. The result of the optimal cropping pattern indicates that, the net annual return of the command area was increased to 45.75%, 45.84% and 47.01% than the Government targeted at 20%, 50% and 80% PEs, respectively. The findings reveal that the optimal land and water resources allocation model is very useful to the planners and decision makers to maximize the agricultural return particularly in areas where land and water resources are limited.

Optimal Allocation of Water Resources and Eco-Compensation Mechanism Model Based on the Interval-Fuzzy Two-Stage Stochastic Programming Method for Tingjiang River

In this work, based on the upper line of water resources utilization and the bottom line of water environmental quality of “Three Lines, Single Project”, a fuzzy optimization method was introduced into the Tingjiang River water resources optimal allocation and eco-compensation mechanism model, which is based on the interval two-stage (ITS) stochastic programming method. In addition, a Tingjiang River water resources allocation and eco-compensation mechanism model based on the interval fuzzy two-stage (IFTS) optimization method was also constructed. The objective functions of both models were to maximize the economic benefits of the Tingjiang River. The available water resources in the basin, the water environmental quality requirements, and regional development requirements were used as constraints, and under the five hydrological scenarios of extreme dryness, dryness, normal flow, abundance, and extreme abundance, the water resources allocation plan of various sectors (industry, municipal, agriculture, and ecology) in the Tingjiang River was optimized, and an eco-compensation mechanism was developed. In this work, the uncertainty of the maximum available water resources in each region and the whole basin was considered. If the maximum available water resources were too high, it would lead to a large waste of water resources, whereas if the maximum available water resources were too low, regional economic development would be limited. Therefore, the above two parameters were set as fuzzy parameters in the optimization model construction in this work. The simulation results from the IFTS model showed that the amount of water available in the river basin directly affects the water usage by various departments, thereby affecting the economic benefits of the river basin and the amount of eco-compensation paid by the downstream areas. The average economic benefit of the Tingjiang River after the optimization of the IFTS model simulation was [3868.51, 5748.99] × 108 CNY, which is an increase of [1.67%, 51.9%] compared to the economic benefit of the basin announced by the government in 2018. Compared to the ITS model, the economic benefit interval of the five hydrological scenarios of extreme dryness, dryness, normal flow, abundance, and extreme abundance was reduced by 28.54%, 44.9%, 31.49%, 40.37%, and 36.43%, respectively, which can improve the economic benefits of the basin and provide more accurate decision-making schemes. In addition, the IFTS simulation showed that the eco-compensation quota paid by downstream Guangdong Province to upstream Fujian Province is [28,116.4, 30,738.6] × 104 CNY, which is a reduction of [8461.404, 110,836] × 104 CNY compared to the 2018 compensation scheme of the government. Compared to the ITS model, the range of eco-compensation values was observed to increase by 9.94%, 54.81%, 15.85%, 50.31%, and 82.90%, respectively, under the five hydrological scenarios, which reduces the burden of ecological expenditure downstream and provides a broader decision-making space for decision-makers and thus enables improved decision-making efficiency. At the same time, after the optimization of the IFTS model, the additional water consumption of the second stage of the Tingjiang River during the extremely dry year decreased by 62.11% compared to the results of the ITS model. The additional water consumption of the industrial sector decreased by 68.39%, the municipal sector decreased by 59.27%, and in the first phase of water resources allocation for 14 districts and counties in the Tingjiang River, industrial and municipal sectors are the main two sectors. After introducing the fuzzy method into the IFTS model, the difference in the water consumption by these two sectors in the basin under different hydrological scenarios can be alleviated, and the waste of water resources caused by too low water allocation or excessive water allocation can be avoided. The national and local (the downstream region) eco-compensation quotas can be indirectly reduced, and the risk of water resources allocation and eco-compensation decision-making in the basin can be effectively reduced.

A system dynamic model to quantify the impacts of water resources allocation on water-energy-food-society (WEFS) nexus

Sustainable management of water-energy-food (WEF) nexus remains an urgent challenge, as interactions between WEF and community sensitivity and reservoir operation in water system are often neglected. This paper aims to provide a new approach for modeling WEF nexus by incorporating community sensitivity and reservoirs operation into the system. The co-evolution behaviors of the nexus across water, energy, food and society (WEFS) were simulated by the system dynamic model. The reservoirs operation was simulated to determine water supply for energy and food systems by the Interactive River-Aquifer Simulation water resources allocations model. Shortage rates for water, energy and food resulted from the simulations were used to qualify their impacts on WEFS nexus through environmental awareness (EA) in society system. Community sensitivity indicated by EA can adjust the co-evolution behaviors of WEFS nexus through feedback loops. The proposed approach was applied to the mid-lower reaches of Hanjiang river basin in China as a case study. Results show that EA accumulation is mainly from shortages of water and energy, and the available water and energy are the vital resources to sustain WEFS nexus. Feedback driven by EA effectively keeps the system from collapsing and contributes to the concordant development of WEFS nexus. Water resources allocation can remarkably ensure water supply through reservoirs operation, decreasing water shortage rate from 16.60 % to 7.53 %. The resource constraining the WEFS nexus is transferred from water to energy. This paper therefore contributes to the understanding of interactions across WEFS system and helps the efficiency improving of resources management.

Optimal Multi-Sectoral Water Resources Allocation Based on Economic Evaluation Considering the Environmental Flow Requirements: A Case Study of Yellow River Basin

Competitions and disputes between various human water sectors and environmental flow of the river are exacerbated due to the rapid growth of the economy in Yellow River basin as well as the limited supply of available water resources in recent decades. It is necessary to implement rational and effective management and allocation to alleviate the pressure of water shortage. In order to promote economic development and maintain the ecological balance of the river, both the water allocation to the river environmental system and different human needs should be of concern when making the allocation polices. This study developed a water allocation model based on Nash–Harsanyi bargaining game theory for optimal water resources allocation among agricultural, industrial, domestic, public, and urban ecological water (watering for urban green space) sectors while ensuring the environmental flow requirements of lower reaches. A comprehensive economic evaluation framework is built to assess the economic benefits of different water uses that were taken as the basis of water allocation model. The annual environmental base flow is 7.50 billion m3 in the lower reaches of Yellow River. Moreover, the optimal annual allocations for agricultural, industrial, domestic, public, and urban ecological water use sectors are estimated as 33.7, 6.42, 3.96, 1.75 and 2.68 billion m3, respectively.

Modeling the Dispute Settlement of Reservoir In View of the Water Quality Issues: A Novel Hybrid Group Game Theory-Fuzzy Logic Approach

To choose the best policy of the water resources allocation, considering both the quantitative and qualitative factors based on the possible uncertainties, there has always been a significant problem in the dry lands from perspectives of the decision makers. In this paper, using Game Theory concept, a novel hybrid approach of the Game Theory based fuzzy logic is proposed to reconcile conflicts among stakeholders of dam reservoirs who have their own different strategies and utilities to choose the best policy in order to gain the highest profit regarding the situations they deal with. In the proposed method, after the fuzzification of decision makers’ strategies, a matrix called a “priority matrix” is formed in which a combination of their strategies and priorities is presented as the matrix elements. Based on the concept of Nash equilibrium, an optimized scenario is elected from among the bargaining scenarios constructed via the integrated strategies. This method has the privilege of providing a game space in which a large variety of strategies and priorities of many decision makers can be modeled in a fuzzy space of variables to reach a point of agreement. In this study, the 15-Khordad Dam of Iran is selected as a case study area which faces problems such as salinity, low quality water, and conflicts among stakeholders. The results of the study indicated that the proposed method could be led to an optimized strategy for the water resources allocation.

Comparison of Transboundary Water Resources Allocation Models Based on Game Theory and Multi-Objective Optimization

Transboundary water resources allocation is an effective measure to resolve water-related conflicts. Aiming at the problem of water conflicts, we constructed water resources allocation models based on game theory and multi-objective optimization, and revealed the differences between the two models. We compare the Pareto front solved by the AR-MOEA method and the NSGA-II method, and analyzed the difference between the Nash–Harsanyi Leader–Follower game model and the multi-objective optimization model. The Huaihe River basin was selected as a case study. The results show that: (1) The AR-MOEA method is better than the NSGA-II method in terms of the diversity metric (Δ); (2) the solution of the asymmetric Nash–Harsanyi Leader–Follower game model is a non-dominated solution, and the asymmetric game model can obtain the same water resources allocation scheme of the multi-objective optimal allocation model under a specific preference structure; (3) after the multi-objective optimization model obtains the Pareto front, it still needs to construct the preference information of the Pareto front for a second time to make the optimal solution of a multi-objective decision, while the game model can directly obtain the water resources allocation scheme at one time by participating in the negotiation. The results expand the solution method of water resources allocation models and provide support for rational water resources allocation.