Participatory Optimization Scenario for Water Resources Management: A Case from Jordan

Participatory optimization scenario process was developed for water resources management of the Zarqa River Basin in Jordan. The basin was selected to represent a case study of semi-arid area in the Mediterranean because of its entire range of prototypical water management problems. The nature of the institutional framework, the severity of the water related problems and concentration of population in the basin have required the need for stakeholders’ involvement in the optimization process. The paper demonstrates a Water Resources Model (WRM) consisting of integrated cascade of modules, embedded in a framework of a participatory approach in water resources optimization. The system includes baseline scenario, identification of constrains and instruments, the optimization scenario and analysis of results. In a participatory approach, stakeholders identified the optimization criteria (constraints) and the management interventions (instruments). Constraints were set to securing high supply/demand ratio of 0.98 and improving reliability of supply to 75 %, while specific eight instruments were suggested and manipulated by the model to achieve the above criteria. The results of the WRM optimization scenario showed that the specified constraints were met so that the supply/demand ratio increased from 0.90 to 0.996 and the reliability of supply improved from 58 % to 84 %. The benefit/cost ratio, water shortfall, and the economic efficiency had responded effectively. The model proved its efficiency in using the full featured basin characteristics towards baseline and optimization scenarios with the support of stakeholders in simulating the basin behavior over time using the model parameters.     

Urban Water Management Using Fuzzy-Probabilistic Multi-Objective Programming with Dynamic Efficiency

This paper introduces a new multi-objective optimization model for integrated urban water management. The model, based on compromise programming, is applied for the case of Tabriz city in Iran. The water demand of this city is rapidly growing and because of the limited resources, water supply is now more vulnerable to any mismanagement. Therefore the model attempts to optimize the water supply plan of city concerning three main objectives of maximizing the water supply, minimizing the cost and minimizing the environmental hazards. Due to the vagueness in defining the first objective, it is modeled by using the fuzzy set theory. Further, the uncertainty in satisfying some constraints is tackled by using the chance constraint approach. The decision variables are the extent of water withdrawal from the city aquifer, three different water transfer schemes and also the extent of demand management by leaks detection and pipes rehabilitation. Then the fuzzy-probabilistic multi-objective model is solved by considering the new idea of dynamic efficiency in the utility of decision maker and the results provide the optimum water supply in the planning horizon. The model results in robust solutions in which the demand management option dominates the new water transfer. Implementing the results of this model supports the environmental conservation and sustainable development.     

Multi-Reservoir System Optimization using Chlorophyll-<Emphasis Type="Italic">a</Emphasis> Trophic Indexes

The problem of managing water scarcity by resorting to complex interconnected multi-source water systems needs to utilize management optimization techniques analyzing aspects of water quantity and quality in a common strategy. In the southern regions of Mediterranean Europe, the greater part of water resources for supply systems are derived from artificial reservoirs and water systems can become quite complex since they interconnect several sources and demand centers, as indeed occurs in the Region of Sardinia (Italy). A simplified approach to the requirement to insert water quality aspects in the mathematical optimization model can be achieved by examining the trophic conditions of reservoirs. Trophic State Indexes (TSI) based on Carlson’s (1977) make it possible to insert quality constraints in the water management optimization model also considering complex multi-reservoir and multi-user systems. Model formalization and implementation by the optimization toolkit WARGI (Water Resource system optimization aided by Graphical Interface) (Sechi and Zuddas 2000; Manca et al. 2004; Salis et al. 2005) is illustrated in this paper. The usefulness of a mixed quantity–quality optimization approach has been confirmed by WARGI application to a real multi-reservoir water resources system in southern Sardinia. The optimization model remains computationally efficient dealing with this complex multi-reservoir system and the obtained results can be seen as a reference target in a subsequent simulation phase.     

Basin Scale Water Resources Systems Modeling Under Cascading Uncertainties

Global change in climate and consequent large impacts on regional hydrologic systems have, in recent years, motivated significant research efforts in water resources modeling under climate change. In an integrated future hydrologic scenario, it is likely that water availability and demands will change significantly due to modifications in hydro-climatic variables such as rainfall, reservoir inflows, temperature, net radiation, wind speed and humidity. An integrated regional water resources management model should capture the likely impacts of climate change on water demands and water availability along with uncertainties associated with climate change impacts and with management goals and objectives under non-stationary conditions. Uncertainties in an integrated regional water resources management model, accumulating from various stages of decision making include climate model and scenario uncertainty in the hydro-climatic impact assessment, uncertainty due to conflicting interests of the water users and uncertainty due to inherent variability of the reservoir inflows. This paper presents an integrated regional water resources management modeling approach considering uncertainties at various stages of decision making by an integration of a hydro-climatic variable projection model, a water demand quantification model, a water quantity management model and a water quality control model. Modeling tools of canonical correlation analysis, stochastic dynamic programming and fuzzy optimization are used in an integrated framework, in the approach presented here. The proposed modeling approach is demonstrated with the case study of the Bhadra Reservoir system in Karnataka, India.     

Pressure Management Model for Urban Water Distribution Networks

A technique for leakage reduction is pressure management, which considers the direct relationship between leakage and pressure. To control the hydraulic pressure in a water distribution system, water levels in the storage tanks should be maintained as much as the variations in the water demand allows. The problem is bounded by minimum and maximum allowable pressure at the demand nodes. In this study, a Genetic Algorithm (GA) based optimization model is used to develop the optimal hourly water level variations in a storage tank in different seasons in order to minimize the leakage level. Resiliency and failure indices of the system have been considered as constraints in the optimization model to achieve the minimum required performance. In the proposed model, the results of a water distribution simulation model are used to train an Artificial Neural Network (ANN) model. Outputs of the ANN model as a hydraulic pressure function is then linked to a GA based optimization model to simulate hydraulic pressure and leakage at each node of the water distribution network based on the water level in the storage tank, water consumption and elevation of each node. The proposed model is applied for pressure management of a major pressure zone with an integrated storage facility in the northwest part of Tehran Metropolitan area. The results show that network leakage can be reduced more than 30% during a year when tank water level is optimized by the proposed model.     

Optimal allocation of surface water in regional water management

Surface water is a scarce reource that is applied by various users for a variety of activities. The regulation of surface water use is an element of regional water management at various management levels. At each management level, the allocation of surface water supply capacity is a policy instrument. An optimization model has been formulated to support the evaluation of potential allocations at a particular management level. The model describes the allocation problem as a network, in which arcs represent waterways and nodes represent inlets and locations where there is a demand for surface water supply. The use of surface water for a specific activity at a specific node is referred to as an application, for example, for sprinkling, for use as cooling water, for dissolving effluent, and for conservation of environmental areas. The optimization model generates the optimal allocation of surface water and of surface water supply capacity. The operation of the model was demonstrated by a case study, where it was applied to maximize the expected revenues in agriculture (measured as value added).     

Management Strategy of Groundwater Resources and Recovery of Over-Extraction Drawdown Funnel in Huaibei City, China

Groundwater overexploitation is threatening our ecosystems and even the life of future generations. Once happens, elimination of the bad influence will be a long-term process. It should be a feasible approach to take the environmental recovery as a whole by the way of the groundwater management. A case study of water resources management in Huaibei city, within semiarid region of north Anhui province, China, was illustrated, especially on the issues of groundwater over-extraction drawdown funnel recovery. Taking into account the water demand for satisfying the urban development in the next 15 years, three target years of water resources planning were postulated as the present (2005), the short-term (2010) and the long-term (2020), respectively. Four hydrological years: wet year, mean year, dry year and extremely dry year, were also defined by the rainfall data for many years. A groundwater management model which could deal with twelve possible scenarios (3 target years of water resources planning ×4 hydrological years) was established based on simulation and optimization. The groundwater management model could optimize the strategies of water resources development, integrate various kinds of water sources, e.g. groundwater, surface water and additive water sources, and meet the water demand for the urban development within an area of Huaibei city. Importantly, in accordance with the groundwater management model solutions, the issues of groundwater over-extraction drawdown funnel, which has formed within the Huaibei downtown area for many years and lead to some environmental and social problems, would be solved over the whole planning period.     

Well Field Management Using Multi-Objective Optimization

Efficient management of groundwater resources is important because groundwater availability is limited and, locally, groundwater quality has been impaired because of contamination. Here we present a multi-objective optimization framework for improving the management of a water works that operates with infiltration basins, injection wells and abstraction wells. The two management objectives are to minimize the amount of water needed for infiltration and to minimize the risk of getting contaminated water into the drinking water wells. The management is subject to a daily demand fulfilment constraint. Two different optimization methods are tested. Constant scheduling where decision variables are held constant during the time of optimization, and sequential scheduling where the optimization is performed stepwise for daily time steps. The latter is developed to work in a real-time situation. Case study optimization results are presented for the Hardhof water works in Zurich, Switzerland. It is found that both methods perform better than the historical management. The constant scheduling performs best in fairly stable conditions, whereas the sequential optimization performs best in extreme situations with heavy rainfall or large changes in water demand.     

WROOM模型及其在渭河流域水量调度中的应用

通用水资源优化调配模型WROOM作为将优化与模拟技术相结合的水资源系统模型,能很好地进行水资源调度问题求解。现根据渭河流域水量调度实际需求,对WROOM模型进行了改进,建立了渭河流域水量调度年调度模型及月调度模型,实现了渭河流域水量调度方案自动化编制,提高了水量调度管理工作的科学化水平。     

Application of Integrated Hydrologic and River Basin Management Modeling for the Optimal Development of a Multi-Purpose Reservoir Project

Multi-purpose reservoir development have been always a big challenge for the management of water resources. This paper describes an integrated approach for investigating catchment hydrology in the development of a hydropower and a canal irrigation system based on model analyses. The investigation aims to adequately determine an optimal domestic and irrigation water resources allocation scheme based on an assessment of the reservoir water balance and capacity for hydropower. The soil and water assessment tool (SWAT) which characterizes basin hydrology and the water management and planning model MODSIM which provides a decision support system for water allocation optimization, were used in this study. The integrated approach was applied to Prek Te River basin in Cambodia. The water demand aspect was examined based on domestic water use, irrigation water, environmental flow, and water losses. An operational rule curve was developed for hydropower operation with respect to a power potential of 13 MW. Hydrologic modeling revealed 90 % dependable water of about 2.7 m³/s during the dry season and 214.3 m³/s during the wet season, indicative of a wet-season dependent reservoir for storage. Results from the 26-years simulation period also showed that diversions for domestic water and irrigation water supply were 92.3 % dependable for a 13 MW capacity hydropower development. The integrated approach was shown to be a valuable decision support tool for water resources management with the determination of an optimum policy for multi-purpose reservoir operation based on available basin water supply.     

Optimal Water Resources Management: Case of Lower Litani River, Lebanon

The pressures of human population and patterns of development frequently jeopardize the integrity of river systems worldwide. An integrated approach to water resources management is essential, particularly in developing countries. This study presents the results of the water resources optimization conducted for the Lower Litani River Basin in Lebanon. The overall aim of the project is to develop, test, and critically evaluate an innovative approach to water resources management in the Mediterranean region. The method explores the ways in which multiple environmental, economic, and social benefits can be achieved through integrated management of water resources. The Water Resources Model was utilized to assess the efficiency of the baseline model scenario and for the optimization process of the different scenarios of the Litani Lower Basin. Strengths, weaknesses, opportunities and threats analysis was applied in order to derive the objectives and constraints. Results revealed that the potential retained scenarios aim at decreasing water consumption and demand, losses, and return flow. These scenarios mainly include the shift to drip irrigation, awareness campaigns, and losses control in domestic supply pipes. Other retained scenarios having a higher shortfall rely on the use of the Channel concrete lining to decrease losses and return flow, in addition to the awareness campaigns in both domestic and irrigation sectors, and less consumptive/more efficient irrigation methods such as sprinkler and drip irrigation at variable application percentages. Hence, most of the interventions or measures proposed are generally not costly and can be implemented.     

Estimating water deficit and its uncertainties in water-scarce area using integrated modeling approach

Accurate assessment of water deficit and related uncertainties in water-scarce areas is strategically important in various fields of water resources management. This study developed a hybrid approach integrating conceptual water balance model and econometric regression to estimate water shortage and its related uncertainties in water-scarce areas. This hybrid approach was used to assess the agricultural water deficit of Beijing, an extremely water-scarce area in China. A predictive model of agricultural water demand was developed using the stepwise multiple regression method, and was validated by comparing the predicted values with observed data. Scenario analysis was employed to investigate the uncertainties of agricultural water shortage and agricultural water demand. This modeling approach can assist water administration in creating sustainable water allocation strategies in water-scarce areas.     

Mitigating Socio-Economic-Environmental Impacts During Drought Periods by Optimizing the Conjunctive Management of Water Resources

Multi-period optimization of conjunctive water management can utilize reservoirs and aquifer carry-over to alleviate drought impacts. Stakeholders’ socio-economic and environmental indices can be used to minimize the socio-economic and environmental costs associated with water shortages in drought periods. The knowledge gap here is the evaluation and inclusion of the socio-economic and environmental value of conjunctive water management in terms of its drought mitigation capability. In this paper, an integrated water quantity-quality optimization model that considers socio-economic and environmental indices is developed. The model considers and integrates reservoir and aquifer carry-over, river-aquifer interaction and water quality with stakeholders’ socio-economic indices of production, net income and labor force employment to evaluate the socio-economic and environmental value of conjunctive water management. Total dissolved solid (TDS) is used as the water quality index for environmental assessments. The model is formulated as a multi-period nonlinear optimization model, with analysis determining the optimal decisions for reservoir release and withdrawal from the river and aquifer in different months to maximize the socio-economic indices of stakeholders within the environmental constraints. The proposed model is used in Zayandehrood water resource system in Iran, which suffers from water supply and pollution problems. Model analysis results show that conjunctive water use in the Zayandehrood water basin reduces salinity by 50 % in the wetland and keeps water supply reduction during a drought under 10 % of irrigation demand.     

区域用水需求驱动因子诊断研究

用水需求增加与水资源短缺之间的矛盾使得水资源成为制约区域社会经济发展的瓶颈。在明确给定供水量的前提下,通过提高用水效率和效益,防止水质污染来满足用水需求,实现从传统的供水管理向需水管理转变的新治水思路。在需水管理视阈下以江苏省为研究对象,采用德尔菲法从生产、生活和生态用水3方面分析影响用水需求的关键指标,运用因子分析法诊断出驱动用水需求的公共因子包括农业因子、经济发展因子、人口因子和生态因子。研究结论将为区域优化用水结构、落实最严格水资源管理制度提供决策依据。     

Conjunctive Operation of Reservoirs and Ponds Using a Simulation-Optimization Model of Irrigation Systems

Water resource management in arid agricultural irrigation regions is a great challenge for managers and decision makers. In some of those regions, many ponds have been built to ensure an adequate water supply for irrigation. Therefore, reservoirs and ponds should be managed conjunctively to minimize shortages of water. In this study, a new integrated mathematical model of conjunctive, or integrated, operation of reservoirs and ponds to maximize the water supply has been proposed for a reservoir-pond irrigation system. This objective has been achieved via the use of two models: an optimal model, which is used to determine the optimal discharge of reservoirs, and a simulation model, which considers the regulatory role of ponds and reservoirs and simulates their water supply to the irrigation system. An adaptive genetic algorithm has been employed in this study to solve the nonlinear and multi-dimensional reservoirs optimization problem. This methodology has been applied to the Yarkant River Basin to demonstrate its applicability, and three scenarios are presented. The main objective of the simulation-optimization model in the Yarkant River Basin is to minimize shortages in meeting irrigation demands for nine sub-irrigation systems subject to the constraint of ecological water transfer to the Tarim River. The optimizing effect of the model was particularly prominent under the third scenario, i.e., the XBD, MMK, and ART Reservoirs and 16 ponds conjunctively operated to meet the water demand of the YKB. The frequency of success (FS) in meeting agricultural water demands reaches up to 75%, and the value for ecological demand is 50.98%. The results demonstrate the importance of the conjunctive combined use approach for management of water resources in irrigation system of arid regions.     

Conjunctive Use of Surface Water and Groundwater: Application of Support Vector Machines (SVMs) and Genetic Algorithms

Combined simulation-optimization models have been widely used to address the management of water resources issues. This paper presents a simulation-optimization model for conjunctive use of surface water and groundwater at a basin-wide scale, the Zayandehrood river basin in west central Iran. In the Zayandehrood basin, in the past 10 years, a historical low rainfall in the head of the basin, combined with growing demand for water, has triggered great changes in water management at basin and irrigation system level. The conjunctive use model that coupled numerical simulation with nonlinear optimization is used to minimize shortages of water in meeting irrigation demands for four irrigation systems. Constraints guarantee the maximum/minimum cumulative groundwater drawdown and maximum capacity of irrigation systems. A support vector machines (SVMs) model is developed as a simulator of surface water and groundwater interaction model while a genetic algorithm (GA) is used as the optimization model. Conjunctive use model runs for three scenarios. Results show that the accuracy of SVMs as a simulator for surface water and groundwater interaction model is good and that it is possible to decrease the water shortage for irrigation systems with application of proposed SVMs-GA model.     

Distributed Simulation‐optimization Model for Conjunctive Use of Groundwater and Surface Water Under Environmental and Sustainability Restrictions

Evolving optimal management strategies are essential for the sustainable development of water resources. A coupled simulation-optimization model that links the simulation and optimization models internally through a response matrix approach is developed for the conjunctive use of groundwater and surface water in meeting irrigation water demand and municipal water supply, while ensuring groundwater sustainability and maintaining environmental flow in river. It incorporates the stream-aquifer interactions, and the aquifer response matrix is generated from a numerical groundwater model. The optimization model is solved by using MATLAB. The developed model has been applied to the Hormat-Golina valley alluvial stream-aquifer system, Ethiopia, and the optimal pumping schedules were obtained for the existing 43 wells under two different scenarios representing with and without restrictions on stream flow depletion, and satisfying the physical, operational and managerial constraints arising due to hydrological configuration, sustainability and ecological services. The study reveals that the total annual optimal pumping is reduced by 19.75?% due to restrictions on stream flow depletion. It is observed that the groundwater pumping from the aquifer has a significant effect on the stream flow depletion and the optimal conjunctive water use plays a great role in preventing groundwater depletion caused by the extensive pumping for various purposes. The groundwater contribution in optimal conjunctive water use is very high having a value of 92?% because of limited capacity of canal. The findings would be useful to the planners and decision makers for ensuring long-term water sustainability.

     

基于人工生态系统优化算法的组合生长需水预测模型

为提高需水预测精度,拓展生长模型在需水预测中的应用,提出基于人工生态系统优化(AEO)算法的组合生长需水预测模型。结合实例,选取6个标准测试函数在不同维度条件下对AEO算法进行仿真验证,并与鲸鱼优化算法(WOA)、灰狼优化(GWO)算法、教学优化(TLBO)算法和传统粒子群优化(PSO)算法的仿真结果进行比较。基于Weibull、Richards、Usher 3种单一生长模型构建Weibull-Richards-Usher、Weibull-Richards、Weibull-Usher、Richards-Usher 4种组合生长模型,利用AEO算法同时对组合模型参数和权重系数进行优化,提出AEO-Weibull-Richards-Usher、AEO-Weibull-Richards、AEO-Weibull-Usher、AEO-Richards-Usher需水预测模型,并构建AEO-Weibull、AEO-Richards、AEO-Usher、AEO-SVM、AEO-BP模型作对比,以上海市需水预测为例进行实例验证,利用实例前30组和后8组统计资料对各组合模型进行训练和预测。结果表明,在不同维度条件下,AEO算法寻优精度优于WOA、GWO、TLBO、PSO算法,具有较好的寻优精度和全局搜索能力。4种组合模型对实例预测的平均相对误差绝对值、平均绝对误差分别在0.94%~1.17%、0.30亿~0.37亿m³之间,预测精度优于AEO-Weibull等其他5种模型。4种组合模型均具有较好的预测精度和泛化能力,表明AEO算法能同时有效优化组合生长模型参数和权重系数,基于AEO算法的组合生长模型用于需水预测是可行和有效的。     

Simulation and Multi-Objective Management of Coastal Aquifers in Semi-Arid Regions

Groundwater is the main water resource in many semi-arid coastal regions and water demand, especially in summer months, can be very high. Groundwater withdrawal for meeting this demand often causes seawater intrusion and degradation of water quality of coastal aquifers. In order to satisfy demand, a combined management plan is proposed and is under consideration for the island of Santorini. The plan involves: (1) desalinization (if needed) of pumped water to a potable level using reverse osmosis and (2) injection into the aquifer of biologically-treated waste water. The management plan is formulated in a multi-objective, optimization framework, where simultaneous minimization of economic and environmental costs is desired, subject to a constraint so that cleaned water satisfies demand. The decision variables concern the well locations and the corresponding pumping and recharging rates. The problem is solved using a computationally efficient, multi-objective, genetic algorithm (NSGAII). The constrained multi-objective, optimization problem is transformed to an unconstrained one using a penalty function proportional to constraint violation. This extends the definition of the objective function outside the domain of feasibility. The impact of prolonged droughts on coastal aquifers is investigated by assuming various scenarios of reduced groundwater recharge. Water flow and quality in the coastal aquifer is simulated using a three-dimensional, variable density, finite difference model (SEAWAT). The method is initially applied to a test aquifer and the trade-off curves (Pareto fronts) are determinedl for each drought scenario. The trade-off curves indicate an increase on the economic and environmental cost as groundwater recharge reduces due to climate change.     

An alternative approach to the operation of multinational reservoir systems: Application to the Amistad &; Falcon system (Lower Rio Grande/Río Bravo)

An optimization approach for the operation of international multi-reservoir systems is presented. The approach uses Stochastic Dynamic Programming (SDP) algorithms – both steady-state and real-time – to develop two models. In the first model, the reservoirs and flows of the system are aggregated to yield an equivalent reservoir, and the obtained operating policies are disaggregated using a non-linear optimization procedure for each reservoir and for each nation's water balance. In the second model a multi-reservoir approach is applied, disaggregating the releases for each country's water share in each reservoir. The non-linear disaggregation algorithm uses SDP-derived operating policies as boundary conditions for a local time-step optimization. Finally, the performance of the different approaches and methods is compared. These models are applied to the Amistad-Falcon International Reservoir System as part of a binational dynamic modeling effort to develop a decision support system tool for a better management of the water resources in the Lower Rio Grande Basin, currently enduring a severe drought.