Waste Load Allocation in Rivers using Fallback Bargaining

In this paper, bargaining process between different stakeholders involved in a waste load allocation problem is simulated using the Fallback Bargaining (FB) concept. The paper considers two main parties in a waste load allocation problem. On the one hand, there are wastewater dischargers intending to minimize their treatment costs and on the other hand, there is an environmental protection agency which monitors the river water quality at a checkpoint downstream of the location of dischargers. In this paper, different alternatives which are combinations of dischargers’ treatment scenarios are defined. A water quality simulation model is utilized to estimate the concentration of the water quality indicator along the river based on a selected alternative. If the concentration of water quality indicator in the selected checkpoint violates the water quality standards, a penalty function is used to calculate the amount of penalty assigned to dischargers. The allocated cost to each discharger is computed considering his treatment scenario as well as the penalty allocated to him. Two kinds of Fallback bargaining procedure termed as Unanimity Fallback Bargaining (UFB) and Fallback bargaining with Impasse (FBI), which both aim at minimizing the maximum dissatisfaction of bargainers in a negotiation problem, are utilized for finding a Compromise Set (CS) of alternatives. In this paper, the best alternative (alternatives) among CS members is (are) selected using a social choice theory namely Condorcet winner. The results of these two approaches are compared and the final alternative is selected which shows the initial Tradable Discharge Permits (TDPs) allocated to dischargers. Finally, in order to decrease the total allocated cost to dischargers, initial allocated TDPs are exchanged between them using the Extended Trading Ratio System (ETRS) developed by Mesbah et al. (Environ Model Software 24:238–246, 2009). The applicability and efficiency of the proposed methodology is investigated by applying it to a case study of the Zarjub River in the northern part of Iran.     

A Nonlinear Interval Model for Water and Waste Load Allocation in River Basins

In this paper, a new methodology is proposed for simultaneous allocation of water and waste load in river basins. A nonlinear interval number optimization model is used to incorporate the uncertainties of model inputs and parameters. In this methodology, the bounds of the uncertain inputs are only required, not necessarily knowing their probability density or fuzzy membership functions. In the proposed model, the existing uncertainties in water demands and monthly available water are considered in the optimization model. Also the economic and environmental impacts of water allocation to the agricultural water users are taken into account. To have an equitable water and waste load allocation, benefits are reallocated to water users using some solution concepts of the cooperative game theory. Results of applying the methodology to the Dez river system in south-western part of Iran show its effectiveness and applicability for water and waste load allocation in an uncertain environment.     

Equitable Waste Load Allocation in Rivers Using Fuzzy Bi-matrix Games

This paper presents a new game theoretic methodology for equitable waste load allocation in rivers utilizing fuzzy bi-matrix games, Non-dominated Sorting Genetic Algorithms II (NSGA-II), cooperative game theory, Bayesian Networks (BNs) and Probabilistic Support Vector Machines (PSVMs). In this methodology, at first, a trade-off curve between objectives, which are average treatment level of dischargers and fuzzy risk of low water quality, is obtained using NSGA-II. Then, the best non-dominated solution is selected using a non-zero-sum bi-matrix game with fuzzy goals. In the next step, to have an equitable waste load allocation, some possible coalitions among dischargers are formed and treatment costs are reallocated to discharges and side payments are calculated. To develop probabilistic rules for real-time waste load allocation, the proposed model is applied considering several scenarios of pollution loads and the results are used for training and testing BNs and PSVMs. The applicability and efficiency of the methodology are examined in a real-world case study of the Zarjub River in the northern part of Iran. The results show that the average relative errors of the proposed rules in estimating the treatment levels of dischargers are less than 5?%.     

Non-Uniform Flow Effect on Optimal Waste Load Allocation in Rivers

In this study, the effects of non-uniform flow due to: (i) inflow from tributaries and (ii) the presence of a downstream control structure (such as a weir or a barrage), on the optimal waste load allocation decision and the resulting cost-equity trade-off relationships, have been investigated. These effects are illustrated with in the framework of a typical cost-equity multi-objective optimization model for optimal waste load allocation in rivers. This framework consists of an embedded river water quality simulator with gradually varied flow and transport (BOD-DO) modules and a cost-equity multi-objective optimization model. A multi-objective evolutionary algorithm known as Non-dominated Sorting Genetic Algorithm-II is used for solving the optimization problem. The optimal fraction removal levels, the treatment cost and the system inequity measure are under predicted in certain reaches of the river, if the uniform flow assumption is made, while actually non-uniform flow conditions exist. This effect is quite pronounced when the flow non-uniformity results from a downstream control structure such as a weir.     

An Interval Parameter Model for Cooperative Inter-Basin Water Resources Allocation Considering the Water Quality Issues

In this paper, a new methodology based on interval optimization and game theory is developed for optimal operation of an inter-basin water transfer system considering efficiency, equity and sustainability criteria. A linear version of the agricultural water production function is proposed and used for incorporating deficit irrigation. The interval programming and cooperative game theory are utilized for equitable reallocation of benefits to water users in both water donor and receiving basins. To assess the sustainability of water allocation policies, water quality and environmental flow in the donor basin and groundwater table drawdown in the receiving basin are taken into consideration. The effectiveness of this methodology is examined by applying it to a large scale case study of water transfer from the Karoon river basin in south-west to the Rafsanjan plain in the central part of Iran.     

信息熵在水污染物总量区域公平分配中的应用

在综合已有公平分配准则的基础上，通过综合考虑待分配区域的经济、自然等客观因素，筛选出反映公平准则的相关指标。借鉴信息熵的概念，计算单位指标负荷污染物量信息熵，应用熵值法得到各指标的权重，加权求和得到总的信息熵。构建以加权信息熵最大化为目标的规划模型，设定合理的运算规则和约束条件，制定基于公平性的水污染物总量的区域初始分配方案。将该方法实际应用于天津市各区县的水污染物分配，采用信息熵权衡公平准则指标得到方案一到四，结果表明：东丽区、汉沽区和中心城区是重点削减区域，其次是塘沽区和宁河县。该方法可以定量化地反映多种公平准则，得到公平可行的分配方案。     

山区河流二维推移质数学模型及应用研究——以望谟河整治工程为例

为了充分利用我国西南山区丰富的水能资源,同时减少望谟河因山洪引起的高含沙水流洪涝和泥石流灾害,应用二维水流泥沙数学模型常用的控制方程式,采用有限体积法对方程进行离散,并使用"冻结法"对模型中陆地边界进行处理,建立了具有一定通用性的山区河流的二维推移质数学模型。利用建立的模型对贵州省望谟河新屯段进行了流场和推移质冲淤模拟计算,并进行了望谟河整治工程影响分析。结果表明:对于望谟河水位和河床冲淤变形验算,数值模型计算值与经验公式推算变化趋势一致,数值也较为接近;整治工程实施后望谟河沿程的水位绝大部分发生不同程度的降低,仅局部存在微小的抬高;望谟河整治后,同流量下,水位降低,流速归槽泥沙淤积减小,有利于河道防洪。     

不确定负荷下小干扰稳定的区间分析方法

计及负荷的不确定性,提出了区间负荷下的小干扰稳定区间分析方法。基于增广矩阵的灵敏度求解,推导了振荡模式的阻尼比对负荷有功的灵敏度指标。以负荷灵敏度指标为指导,通过迭代搜索求解了典型负荷水平下关键振荡模式的阻尼比区间极值,进而可以确定区间负荷下的阻尼比区间分布,并据此可推断特征值阻尼比随负荷变化的规律,提供更加全面的稳定性信息。通过 4机系统和新英格兰39节点系统的算例实现,验证了该方法的有效性,与蒙特卡罗模拟法的结果对比,表明了该方法计算结果的正确性和计算速度上的优越性。     

Nonlinear Interval Parameter Programming Combined with Cooperative Games: a Tool for Addressing Uncertainty in Water Allocation Using Water Diplomacy Framework

Water Resources Management - This paper shows the utility of a new interval cooperative game theory as an effective water diplomacy tool to resolve competing and conflicting needs of water users...     

A Multi-objective Linear Programming Model with Interval Parameters for Water Resources Allocation in Dalian City

Water resources management has been of concern for many researchers since the contradiction between increased water demand and decreased water supply has become obvious. In the real world, water resources systems usually have complexities among social, economic, natural resources and environmental aspects, which leads to multi-objective problems with significant uncertainties in system parameters, objectives, and their interactions. In this paper, a multi-objective linear programming model with interval parameters has been developed wherein an interactive compromising algorithm has been introduced. Through interactive compromising conflicts among multi-objectives, a feasible solution vector can be obtained. The developed model is then applied to allocation of multi-source water resources with different water qualities to multiple users with different water quality requirements for the Dalian city for 2010, 2015 and 2020 planning years. The model pursues the maximum synthesis benefits of economy, society and the environment. The results indicate that the proportion of reused water to the total water amount is gradually increasing, and the proportion of agricultural water consumption to the total water consumption is gradually decreasing. The allocation of multi-source water resources to multiple users is improved due to incorporation of uncertain factors into the model that provide useful decision support to water management authorities.     

Agricultural Multi-Water Source Allocation Model Based on Interval Two-Stage Stochastic Robust Programming under Uncertainty

Numerous uncertainties and complexities exist in the agricultural irrigation water allocation system, that must be considered in the optimization of water resources allocation. In this paper, an agricultural multi-water source allocation model, consisting of stochastic robust programming and two-stage random programming and introducing interval numbers and random variables to represent the uncertainties, was proposed for the optimization of irrigation water allocation in Jiamusi City of Heilongjiang Province, China. The model could optimize the water allocaton to different crops of groundwater and surface water. Then, the optimal target value and the optimal water allocation of different water sources distributed to different crops could be obtained. The model optimized the economic benefits and stability of the agricultural irrigation water allocation system via the introduction of a the penalty cost variable measurement to the objective function. The results revealed that the total water shortage changed from [18.6, 32.3]?×?10⁸ m³ to [15.7, 26.2]?×?10⁸ m³ at a risk level ω from zero to five, indicating that the water shortage decreased and the reliability improved in the agricultural irrigation water allocation system. Additionally, the net economic benefits of irrigation changed from [287.21, 357.86]?×?10⁸ yuan to [253.23, 301.32]?×?10⁸ yuan, indicating that the economic benefit difference was reduced. Therefore, the model can be used by decision makers to develop appropriate water distribution schemes based on the rational consideration of the economic benefit, stability and risk of the agricultural irrigation water allocation system.     

An Economic Model for Water Allocation in North Eastern Spain

The aim of this paper is to construct and apply a model for the allocation of water between two competing users, namely irrigation and hydropower. The model is applied in a case study of a specific water system located in North Eastern Spain. Starting with an irrigation-hydropower joint income function, we develop a constrained maximization process that takes into account the environmental, institutional and actual priority of the water rights. The resulting solution can be useful as a guide for potential bargains between users. Furthermore, we evaluate the results for different supply (precipitation) and water allotments (increase in irrigated land). The results show that there are sufficient incentives so as to reach agreements that lead to improvements in a Pareto sense without side payments.     

An Ultimatum Game Theory Based Approach for Basin Scale Water Allocation Conflict Resolution

Increasing water consumption via competitive demands has resulted in serious water conflicts and the subsequent environmental crisis in the Gavkhouni Watershed with the Gavkhouni swamp in the most downstream located in the central part of Iran. In this research, a two-player ultimatum game theory approach is adopted to not only address the water conflicts with the purpose of environmental reclamation of the drying swamp, but also to ensure economic satisfaction for the upstream landowners and farmers. The Ministry of Energy (MoE) and its subsidiary regional water authority represent the responsible organizations for providing water while the Ministry of Agriculture (MoA) is the primary body in charge of water consumption in the watershed. MoE and MoA are considered as two players in the game, whereas MoE has more power than MoA in terms of allocating water. Five strategies are studied namely: 1 and 2) decreasing water allocation to irrigated agriculture as much as the annual shortage of the Gavkhouni swamp with and without compensation to MoA (D-L), 3 and 4) decreasing water allocation to irrigated agriculture twice as much the annual shortage of the swamp with and without compensation for MoA (D-2 L) and 5) giving up Gavkhouni swamp’s reclamation plan (D). Moreover, three scenarios regarding the relations between environmental and agricultural utilities are designated. According to the results, D-2 L with paying compensation to MoA is chosen as the best alternative in scenario 1 when the environmental utility was assumed to be greater than the agricultural utility. Ultimatum Game Theory has no final solution for scenarios 2 and 3 where the environmental utility is considered to be equal and smaller than agricultural utility. The swamp’s annual environmental water shortage as 324 million cubic meters is supplied by application of both strategies D-L and D-2 L. Ultimatum Games are efficient in assessment of water conflicts to resolve them through careful and planned negotiations.     

Water Resources Allocation in Transboundary River Basins Based on a Game Model Considering Inflow Forecasting Errors

Dynamic transboundary water resources allocation based on inflow prediction results is an important task for water resources management in river basins. This paper takes the watershed management agency as the leader and the associated area as the follower, and proposes a two-level asymmetric Nash-Harsanyi Leader-Follower game model considering inflow forecasting errors. In the proposed model, the Monte Carlo method is used to analyze the uncertainty of various stakeholder allocation results and the response regularity to the total water resource uncertainty. The quantitative relationship between the allocation results of stakeholders and the mean and standard deviation of total water resource uncertainty is subsequently established. The Huaihe River basin in China is selected as a case study. The results show the following: (1) the water allocated to the watershed management agency and three provinces has a normal distribution when the inflow forecasting error obeys the normal distribution; (2) the sum of the mean of the water allocated to stakeholders equals the mean of the forecast water resource and the sum of the standard deviations of the water allocated to stakeholders equals the standard deviation of the forecast water resource; (3) the mean and standard deviation of the allocation results have a good linear relationship with the mean and standard deviation of forecast water resource; (4) the distribution parameters of the stakeholder allocation results can be directly derived from the distribution parameters of the forecast information, thus aiding the stakeholders in making decisions and improving the practical value of the method.

     

Machine Learning Utilization for Bed Load Transport in Gravel-Bed Rivers

Three data-driven techniques, namely artificial neural networks, adaptive-network-based fuzzy inference system, and symbolic regression based on genetic programming, are employed for the prediction of bed load transport rates in gravel-bed steep mountainous streams and rivers in Idaho (U.S.A.), and the potential of several input variables is investigated. The input combinations that were tested are based, mainly, on unit stream power, stream power, and shear stress, and exhibited similarly good performance, with respect to the machine learning technique used, accentuating the importance of the regression model. The derived models are robust, generalize very well in unseen data, and generated results superior to those of some of the widely used bed load formulae, without the need to set a threshold for the initiation of motion, and consequently avoid predicting erroneous zero transport rates.     

基于水权初始配置的区域利益博弈与优化模型

明晰水权初始配置是协调流域内各区域之间水资源综合效益的重要途径。针对流域水权初始配置过程,首先,结合流域内各区域的社会经济发展目标,构建水权初始配置指标体系,采用理想解法,获得水权初始配置初步方案,确定各区域的水权配置量初始值;其次,结合流域内各区域的利益诉求,基于动态博弈理论,分析各区域之间的动态博弈机理,构建动态博弈模型和利益补偿函数,实现水权增加利益主体对水权减少利益主体的利益补偿;然后,确定各区域的水权配置量优化值和流域内各区域水资源综合效益的优化值,并获得水权初始配置优化方案;最后,通过案例分析验证了利益博弈与优化模型在水权初始配置过程中具有较好的适用性。研究表明,水权初始配置本质上是对流域内各区域之间进行利益博弈的过程,通过水权增加利益主体对水权减少利益主体进行利益补偿,可进一步优化各区域的利益和流域水资源综合效益。     

基于WAMS的静态负荷模型参数辩识

广域测量系统(WAMS)应用同步相量测量技术,可对广域分布电力系统的电气量进行实时测量,为大型电力系统的安全分析和稳定控制提供了新的契机。电力系统稳定分析软件中常采用静态负荷模型进行分析,研究表明,负荷模型参数对分析的结果影响很大。文章就广域测量系统在ZIP负荷模型参数辨识方面的应用进行了探讨,比较详细地阐述了辨识原理的内容及其在线应用的具体实现方法。在IEEE-30节点系统上的仿真结果表明验证了该辨识方法的可行性与有效性。     

山西省主要河流纳污调查与分析

本文采用2001年山西省入河排污调查资料。介绍了全省入河排污口的分布、废污水排放量、主要污染物排放量及支流口污染输送量。对主要河流的纳污总量进行了统计分析，并对入河排污的特征进行了简要评价。     

Multi-Objective Parameter Calibration and Multi-Attribute Decision-Making: An Application to Conceptual Hydrological Model Calibration

For calibrating the conceptual hydrological models (CHM), the traditional calibration method with a single objective cannot properly measure all the behaviors of the hydrological system. To obtain a successful parameters calibration, in this paper, we propose a multi-objective cultural self-adaptive electromagnetism-like mechanism (MOCSEM) algorithm, which is first implemented in solving the parameters calibration problem of CHM. In this algorithm, a self-adaptive parameter is applied in local search operation for adjusting the values of parameters dynamically. Meanwhile, cultural algorithm (CA) is adopted to keep a good diversity and uniformity of Pareto-optimal solutions (POS). MOCSEM is tested, firstly, by several benchmark test problems. After achieving satisfactory performance on the test problems, a case study is implemented for parameter calibration of a CHM by comparing the properties of POS obtained by the MOCSEM and other methods. Finally, when the optimization problem quickly becomes a decision-making problem because of the multiple objectives in CHM, fuzzy technique for order preference by similarity to an ideal solution method has been used to rank the POS and select the optimal scheme. The results show that the MOCSEM algorithm can provide high-accuracy parameters of CHM on various decision-making scenarios.