基于模糊多目标决策的城市水资源优化配置研究

针对城市用水系统的多水源、多用水户的特点,建立了城市水资源多目标分配模型.为对模型求解,首先计算各目标的模糊隶属度,将模型转化为模糊多目标决策模型,通过逐步缩小决策空间,最终得到模型的满意解.并以大连市为例,得到其2010、2020水平年的多水源多用水户的水资源配置结果.最后,分析了模糊多目标决策模型中各目标权重不同时对结果的影响.结果显示,该优化模型及模糊决策是合理可行的.     

基于多目标规划的杨凌示范区水资源优化配置

介绍了水资源优化配置理论,在分析杨凌示范区供用水现状基础上,全面考虑该区社会、经济与环境协调发展的实际情况,建立以经济、社会、环境综合效益最大为目标的多目标优化模型;采用目标逼近法,并结合大系统总体优化对所建立的模型进行求解,得到了杨凌示范区不同规划水平年(2010、2020)、不同设计保证率(50%、75%)条件下的水资源优化配置结果;通过对该优化配置结果的分析与讨论,提出了相应的保障措施及对策.     

An Improved Solving Approach for Interval-Parameter Programming and Application to an Optimal Allocation of Irrigation Water Problem

In this study, an improved single-step method (SSM) is developed based on two-step method (TSM) to solve the interval-parameter linear programming (ILP) model of which the right-hand sides are highly uncertain. Two numerical examples are presented to ascertain appropriate value of λ in SSM. The risk preference degree of λ could be 0.8 for maximum objective function type. To demonstrate the applicability of the developed method, an agricultural water management problem has been provided in the case study section. The results show that SSM is more effective than TSM for complete solutions. There is only partial solution obtained from the first submodel of TSM, because the right-hand side of the wheat output constraint is highly uncertain. Finally, local farmers’ net benefit reaches to [8.949, 12.442]?×?10⁸ RMB (the unit of Chinese currency). The priority order of crops that are needed to be irrigated by surface water is maize > wheat > cotton.     

Optimization of Nebhana Reservoir Water Allocation by Stochastic Dynamic Programming

This study is devoted to the identification of an optimal rule that would permit to improve the water resources management of dam in arid condition. The Nebhana dam is considered in this study as a representative of a set dams situated in such condition. The water storage is used for irrigation purpose. The identification of an optimal rule is based on two opposite objectives: the satisfaction of the irrigation water demand and the safeguard of a minimal water storage in the dam. By considering different weights for these objectives, the stochastic dynamic programming technique was lead to various optimal rules for the water resources management of the Nebhana dam. This technique takes into account the variability of the volume of water inflow to the dam on the basis of their occurrence probability; the water losses by means of forecasting models and the water resources goals using weight coefficients. The identified optimal rule would permit to estimate the necessary water release volume for irrigation by considering the water storage and the decision period.     

天津市水资源多目标优化配置研究

在综合考虑经济、社会、生态、水环境等因素的基础上,建立天津市区域水资源多目标优化模型,利用遗传算法结合理想点法对多目标模型进行求解,在最终对各用水部门给予政策倾斜的前提下,给出不同水资源优化配置方案,以协助决策者制定切实可行的用水方案,实现水资源的可持续发展。     

基于混合算子遗传算法的水资源优化配置

构建了以经济效益、社会效益、生态效益为多目标的水资源配置模型,针对模型中存在的多目标多约束优化问题,对基本遗传算法进行改造,设计了一个混合算子遗传算法,并用算例进行验证,最后将水资源优化配置模型和算法应用于东江流域。实例计算结果表明,基于混合算子遗传算法的多目标水资源优化配置模型配置结果合理可行,可作为研究流域水资源配置的决策依据。遗传算法作为新型智能算法,可应用于水资源配置领域。     

馆陶县水资源优化配置研究

目前,水资源日益紧缺,供需矛盾尖锐.如何合理配置本区域内的有限水资源,以实现社会、经济及环境的协调发展成为摆在水资源管理者面前的一个首要问题.以2005年为现状水平年、2015年为规划水平年,对馆陶县规划水平年P=50%和P=75%2种保证率情况下的水资源量通过建模进行优化配置,并用Matlab软件进行求解,得到水资源优化配置结果,从而为水资源管理者提供参考.     

保定市南水北调中线供水区水资源优化配置

通过对供水区水资源优化配置和联合调度,针对南水北调中线一期工程实施后供水区内多种水源联合运用的局面,提出了优先利用引江水,合理配置地表水,充分回用中水,逐步改善生态用水,控制开采地下水,强化全民节约用水的调配思路和措施建议,并对南水北调工程实施后的水资源联合调度提供指导.     

基于多目标规划模型的新疆鄯善县水资源优化配置研究

鄯善县作为资源性缺水地区,近年来随着经济的高速增长、矿产开发、人口的增加以及工业化和城市化快速推进,水资源所承受的压力进一步加大。水资源的短缺严重制约了该地区经济社会发展和居民生活质量的提高。如何合理有效地进行水资源优化配置,合理地配置工农业和生活用水,显得十分必和迫切。应用多目标规划模型分析鄯善县自然条件和当前社会经济发展趋势,基于社会经济可持续发展和水资源可持续利用的观点,对鄯善县的资源利用结构进行了优化研究,建立了水资源优化配置模型系统。     

A Fair Approach for Multi-Objective Water Resources Allocation

Due to the effect of climate change, rapid population growth and widespread water pollution, fresh water becomes an increasingly scarce natural resource. Optimal allocation of water resources is one of the most effective resolutions to deal with rising water demand and insufficient freshwater resources. This study proposes a fair approach for water resources allocation by employing the Sperner’s lemma to solve the conflicts of different objectives and those of competing regions. A multi-objective optimal allocation model is firstly formulated to generate the Pareto frontier surface, which maximizes the economic interest while minimizing the amount of organic pollutants. Subsequently, the approach searches for acceptable allocation schemes over the Pareto frontier surfaces through the total water quantity and envy-free constraints. The proposed model is applied to the middle and lower reaches of Hanjiang river basin in China. Results indicate that water allocation between multi-region can achieve Nash equilibrium by using the water conflict resolution method to select fair water allocation schemes, in which each region obtains its preferred water quantity. The proposed approach is proved effective for water resources management in the case study and demonstrates the potential for effective application in other basins.

     

Developing an Interactive Spatial Multi-Attribute Decision Support System for Assessing Water Resources Allocation Scenarios

Water Resources Management - In water resource management, assessing water resource allocation scenarios (WRASs) is an important multi-attribute decision making (MADM) problem. It involves...     

水资源优化配置方案综合评价的模糊熵模型研究及应用

摘要：基于水资源优化配置方案具有多目标性和模糊不相容性的特点，在模糊理论分析的基础上，结合欧氏贴近度的概念，建立了基于欧氏贴近度的水资源优化配置方案综合评价的模糊优选模型。模型中基于信息熵建立了专家自身权重模型来修正层次分析法得到的指标主观权重，得到的指标融合权重减少了权重确定的主观性。以天津市水资源优化配置方案综合评价为例介绍了该模型的具体运用，结果表明，该模型用于水资源优化配置方案评价是合理、可行的，为水资源优化配置方案综合评价提供了一种新的决策方法。 关键词：模糊理论；欧氏贴近度；信息熵；水资源配置；综合评价     

广州市水资源优化配置探讨

建立一个以广州市水资源合理利用为目标，考虑主要水库和河道防洪、供水、航运、压成等约束的广州市水资源优化配置多目标分析模型，采用大系统“分解协调”原理，运用逐步宽容约束法及递阶分析法，在特枯水年来水情况下，针对全市各单元区2020年水平年需水状况，通过13个中型水库与河道、区间径流联合调度，进行自流域至供水行业的多层次优化的水资源配置，得出各个用水户的配水结果及缺水状况，提出在区域上分7片配水解决广州市水资源供需问题的方案。     

基于优化配置的北京市水资源影子价格研究

通过用水效益分摊法分别率定了北京市农业、工业和生活用水的净效益参数,结合北京市供需水分析,构建了简化的北京市水资源优化配置线性规划模型,经模型求解得到北京市水资源影子价格。结果表明:2011年北京市水资源影子价格为12.87元/m~3。该成果反映了北京市当年水资源供需状况和价格水平下的水资源价值,可为当地进行水权交易提供参考,为制定科学合理的水价标准和完善水价体系提供技术支撑。     

Optimal Inter-Basin Water Allocation Using Crisp and Fuzzy Shapley Games

In recent years, uneven distribution of available water resources as well as increasing water demands and overexploiting the water resources have brought severe need for transferring water from basins having sufficient water to basins facing water shortages. Therefore, optimal allocation of shared water resources in water transfer projects, considering the utilities of different stakeholders, physical limitations of the system and socioeconomic criteria is an important task. In this paper, a new methodology based on crisp and fuzzy Shapley games is developed for optimal allocation of inter-basin water resources. In the proposed methodology, initial water allocations are obtained using an optimization model considering an equity criterion. In the second step, the stakeholders form crisp coalitions to increase the total net benefit of the system as well as their own benefits and a crisp Shapley Value game is used to reallocate the benefits produced in the crisp coalitions. Lastly, to provide maximum total net benefit, fuzzy coalitions are constituted and the participation rates of water users to fuzzy coalitions are optimized. Then, the total net benefit is reallocated to water users in a rational and equitable way using Fuzzy Shapley Value game. The effectiveness of this method is examined by applying it to a large scale case study of water transfer from the Karoon river basin in southern Iran to the Rafsanjan plain in central Iran.     

Robust Methods for Identifying Optimal Reservoir Operation Strategies Using Deterministic and Stochastic Formulations

Water allocation in a competing environment is a major social and economic challenge especially in water stressed semi-arid regions. In developing countries the end users are represented by the water sectors in most parts and conflict over water is resolved at the agency level. In this paper, two reservoir operation optimization models for water allocation to different users are presented. The objective functions of both models are based on the Nash Bargaining Theory which can incorporate the utility functions of the water users and the stakeholders as well as their relative authorities on the water allocation process. The first model is called GA–KNN (Genetic Algorithm–K Nearest Neighborhood) optimization model. In this model, in order to expedite the convergence process of GA, a KNN scheme for estimating initial solutions is used. Also KNN is utilized to develop the operating rules in each month based on the derived optimization results. The second model is called the Bayesian Stochastic GA (BSGA) optimization model. This model considers the joint probability distribution of inflow and its forecast to the reservoir. In this way, the intrinsic and forecast uncertainties of inflow to the reservoir are incorporated. In order to test the proposed models, they are applied to the Satarkhan reservoir system in the north-western part of Iran. The models have unique features in incorporating uncertainties, facilitating the convergence process of GA, and handling finer state variable discretization and utilizing reliability based utility functions for water user sectors. They are compared with the alternative models. Comparisons show the significant value of the proposed models in reservoir operation and supplying the demands of different water users.     

Optimal Allocation of Land and Water Resources in a Canal Command Area in the Deterministic and Stochastic Regimes

Water logging is a universal problem of irrigated agriculture and it is a serious threat to the sustainability of irrigated agriculture in many arid and semiarid regions. Limbasi branch canal command area of Mahi Right Bank Canal (MRBC) project, Gujarat, India is also found to be affected by water logging conditions. Present study deals with the formulation of the Deterministic Linear Programming (DLP) and Chance Constrained Linear Programming (CCLP) models which maximizes net return from a canal command area while simultaneously mitigating water logging conditions. The developed models are applied to the Limbasi branch canal command area. The objective function is to maximize net annual return and decision variables are the seasonal cropping pattern and seasonal water supply. Analysis shows that under optimal conditions in the DLP model, there was a 40% deviation of crop area from existing cropping pattern and Net Irrigation Requirement (NIR) of crops was satisfied by conjunctive use of 41% of canal water and 59% of groundwater (annually). There was 91.1% increase in ground water exploitation which consecutively moderated rising water table issues. Net annual return was found to increase by 46.6%. In the CCLP model, NIR of crops was considered as a stochastic variable and normal distribution was found as the best fit. The CCLP model was run from 2 to 40% risk levels and cropping pattern under 10% risk level was considered as optimal at which NIR was satisfied by conjunctive use of 53.8% of canal water and 46.2% of ground water (annually). There was 86% increase in ground water exploitation. The outcome of the study can be used to assist the water resources planners and managers in taking appropriate decisions to develop a sustainable management plan of land and water resources for an overall balance of the system.     

基于单元优化配置方法的陕西省关中地区水资源配置研究

水资源问题已经成为制约陕西省关中地区经济社会发展的瓶颈。为此,建立了省内南水北调受水区水资源单元优化配置模型,采用遗传算法求解该模型,并建立了该地区水资源单元优化配置系统。单元优化配置和常规配置的结果对比表明：在保证各供水保证率前提的基础上可以减少总缺水量9 875万m³。这一结论可为陕西省关中地区合理配置水资源及确定引汉济渭工程调水量提供借鉴。     

Interval-parameter Two-stage Stochastic Nonlinear Programming for Water Resources Management under Uncertainty

Over the past decades, controversial and conflict-laden water allocation issues among competing interests have raised increasing concerns. In this research, an interval-parameter two-stage stochastic nonlinear programming (ITNP) method is developed for supporting decisions of water-resources allocation within a multi-reservoir system. The ITNP can handle uncertainties expressed as both probability distributions and discrete intervals. It can also be used for analyzing various policy scenarios that are associated with different levels of economic consequences when the promised allocation targets are violated. Moreover, it can deal with nonlinearities in the objective function such that the economies-of-scale effects in the stochastic program can be quantified. The proposed method is applied to a case study of water-resources allocation within a multi-user, multi-region and multi-reservoir context for demonstrating its applicability. The results indicate that reasonable solutions have been generated, which present as combined interval and distributional information. They provide desired water allocation plans with a maximized economic benefit and a minimized system-disruption risk. The results also demonstrate that a proper policy for water allocation can help not only mitigate the penalty due to insufficient supply but also reduce the waste of water resources.     

基于水量控制为主的区域水资源优化配置

河北省水资源短缺,水资源短缺影响经济发展。水资源优化配置的目的就是进行水资源的供需协调,使之最大限度地满足水资源需求量,保证社会经济可持续发展。河北省严重缺水,再加上水资源时空分布和区域分布不均,水资源利用率较低。水资源优化配置,遵循水资源供需平衡、调配时间和空间分布,实现水资源在区域生产及生活中的合理分配,以追求生态效益和区域社会经济协调发展的水资源配置方案。