Optimal water and waste-load allocations in rivers using a fuzzy transformation technique: a case study

In this paper, a new methodology is developed for integrated allocation of water and waste-loads in river basins utilizing a fuzzy transformation method (FTM). The fuzzy transformation method is used to incorporate the existing uncertainties in model inputs. In the proposed methodology, the FTM, as a simulation model, is utilized in an optimization framework for constructing a fuzzy water and waste-loads allocation model. In addition, economic as well as environmental impacts of water allocation to different water users are considered. For equitable water and waste load allocation, all possible coalition of water users are considered and total benefit of each coalition, which is a fuzzy number, is reallocated to water users who are participating in the coalition. The fuzzy cost savings are reallocated using a fuzzy nucleolus cooperative game and the FTM. As a case study, the Dez River system in south-west of Iran is modeled and analyzed using the methodology developed here. The results show the effectiveness of the methodology in optimal water and waste-loads allocations under uncertainty.     

Application of cooperative and non-cooperative games in large-scale water quantity and quality management: a case study

In this paper, two cooperative and non-cooperative methodologies are developed for a large-scale water allocation problem in Southern Iran. The water shares of the water users and their net benefits are determined using optimization models having economic objectives with respect to the physical and environmental constraints of the system. The results of the two methodologies are compared based on the total obtained economic benefit, and the role of cooperation in utilizing a shared water resource is demonstrated. In both cases, the water quality in rivers satisfies the standards. Comparing the results of the two mentioned approaches shows the importance of acting cooperatively to achieve maximum revenue in utilizing a surface water resource while the river water quantity and quality issues are addressed.     

Urban water resource management for sustainable environment planning using artificial intelligence techniques

In the current era, water is a significant resource for socio-economic growth and the protection of healthy environments. Properly controlled water resources are considered a vital part of development, which reduces poverty and equity. Conventional Water system Management maximizes the existing water flows available to satisfy all competing demands, including on-site water and groundwater. Therefore, Climatic change would intensify the specific challenges in water resource management by contributing to uncertainty. Sustainable water resources management is an essential process for ensuring the earth's life and the future. Nonlinear effects, stochastic dynamics, and hydraulic constraints are challenging in ecological planning for sustainable water development. In this paper, Adaptive Intelligent Dynamic Water Resource Planning (AIDWRP) has been proposed to sustain the urban areas' water environment. Here, an adaptive intelligent approach is a subset of the Artificial Intelligence (AI) technique in which environmental planning for sustainable water development has been modeled effectively. Artificial intelligence modeling improves water efficiency by transforming information into a leaner process, improving decision-making based on data-driven by combining numeric AI tools and human intellectual skills. In AIDWRP, Markov Decision Process (MDP) discusses the dynamic water resource management issue with annual use and released locational constraints that develop sensitivity-driven methods to optimize several efficient environmental planning and management policies. Consequently, there is a specific relief from the engagement of supply and demand for water resources, and substantial improvements in local economic efficiency have been simulated with numerical outcomes.     

Economics of place-based monitoring under the safe drinking water act, part II: Design and development of place-based monitoring strategies

The goals of environmental legislation and associated regulations are to protect public health, natural resources, and ecosystems. In this context, monitoring programs should provide timely and relevant information so that the regulatory community can implement legislation in a cost-effective and efficient manner. The Safe Drinking Water Act (SDWA) of 1974 attempts to ensure that public water systems (PWSs) supply safe water to its consumers. As is the case with many other federal environmental statutes, SDWA monitoring has been implemented in relatively uniform fashion across the United States. In this three part series, spatial and temporal patterns in water quality data are utilized to develop, compare, and evaluate the economic performance of alternative place-based monitoring approaches to current monitoring practice. Part II: Several factors affect the performance of monitoring strategies, including: measurable objectives, required precision in estimates, acceptable confidence levels of such estimates, available budget for sampling. In this paper, we develop place-based monitoring strategies based on extensive analysis of available historical water quality data (1960-1994) of 19 Iowa community water systems. These systems supply potable water to over 350,000 people. In the context of drinking water, the objective is to protect public health by utilizing monitoring resources to characterize contaminants that are detectable, and are close to exceeding health standards. A place-based monitoring strategy was developed in which contaminants were selected based on their historical occurrence, rather than their appearance on the SDWA contaminant list. In a subset of the water systems, the temporal frequency of monitoring for one ubiquitous contaminant, nitrate, was tailored to patterns in its historical occurrence and concentration. Three sampling allocation models (linear, quadratic, and cubic) based on historic patterns in peak occurrence were developed and evaluated. Random and fixed-interval sampling strategies within the context of such models were also developed and evaluated. Strategies were configured to incorporate a variety of options for frequency and number of samples (depending on budget and the desired precision in estimate of peak concentrations).     

四川省毛河流域污染综合治理方案探讨

分析了四川省毛河流域各类污染源分布状况及水质现状,采用一维稳态单组分水质模型、多宾斯-坎普稳态模型,引入水文数据、水质监测数据、环境统计数据、社会统计公报数据,以Excel作为数据平台,对毛河水环境进行了动态模拟,反演出主要污染物降解系数。总结了毛河水环境目前存在的问题,并模拟计算了2种污染综合治理方案实施后对毛河水质的影响,确定了毛河流域水污染综合治理的重点以及制约因子。     

Investments in Power Generation Under Uncertainty—a MIP Specification and Large-Scale Application for EU

Investments in power generation constitute a typical budget allocation problem in the context of multiple objectives, while all factors influencing investor’s decisions for power plants are subject to considerable uncertainties. The paper introduces a multi-objective stochastic model designed to optimize budget allocation decisions for power generation in the context of risk aversion taking into account several sources of uncertainty, especially with regard to volatility of fossil fuel and electricity prices, technological costs, and climate policy variability. Probability distributions for uncertain factors influencing investment decisions are directly derived from the stochastic global energy model PROMETHEUS and thus they take into account complex interactions between variables in the systemic context. In order to fully incorporate stochastic characteristics of the problem, the model is specified as an optimization problem in which the probability that an objective exceeds a given threshold is maximized (risk aversion) subject to a set of deterministic and probabilistic constraints. The model is formulated as a mixed integer program providing complete flexibility on the joint distributions of rates of return of technologies competing for investments, as it can handle non-symmetric distributions and take automatically into account complex covariance patterns as emerging from comprehensive PROMETHEUS stochastic results. The analysis shows that risk is a crucial factor for power generation investments with investors not opting for technologies subject to uncertainty related to climate policies and fossil fuel prices. On the other hand, combination of options with negative covariance tends to benefit in the context of risk-hedging behavior.     

Temporal and spatial variability in water quality of wetlands in the Minneapolis/St. Paul,MN metropolitan area: Implications for monitoring strategies and designs

Temporal and spatial variability in wetland water-quality variables were examined for twenty-one wetlands in the Minneapolis/St. Paul metropolitan area and eighteen wetlands in adjacent Wright County. Wetland water quality was significantly affected by contact with the sediment (surface water vs. groundwater), season, degree of hydrologic isolation, wetland class, and predominant land-use in the surrounding watershed (p<0.05). Between years, only nitrate and particulate nitrogen concentrations varied significantly in Wright County wetland surface waters. For eight water-quality variables, the power of a paired before-and-after comparison design was greater than the power of a completely randomized design. The reverse was true for four other water-quality variables. The power of statistical tests for different classes of water-quality variables could be ranked according to the predominant factors influencing these: climate factors>edaphic factors>detritivory>land-use factors>biotic-redox or other multiple factors.For two wetlands sampled intensively, soluble reactive phosphate and total dissolved phosphorus were the most spatially variable (c.v.=76–249%), while temperature, color, dissolved organic carbon, and DO were least variable (c.v.=6–43%). Geostatistical analyses demonstrated that the average distance across which water-quality variables were spatially correlated (variogram range) was 61–112% of the mean radius of each wetland. Within the shallower of the two wetlands, nitrogen speciation was explained as a function of dissolved oxygen, while deeper marsh water-quality variables were explained as a function of water depth or distance from the wetland edge. Compositing water-quality samples produced unbiased estimates of individual sample means for all water quality variables examined except for ammonium.     

Optimal charges on river effluent from lumped and distributed sources

We propose a modelling framework for the design of a Pigouvian effluent tax, in an environmental management problem implicating several economic agents located in a river basin. The proposed charging system allows for the agents' geographical position relative to the river's sections, at which environmental standards are to be enforced, and takes into account the possible different market structures within which the agents are operating. In particular, we consider industrial agents competing on an oligopolistic market, and a set of farmers acting as price takers on a large market. A regional authority's goal is to induce agents to some sort of cooperation which would result in the satisfaction of the common environmental constraints. The economic process on one side, and the pollution transport and accumulation on the other, constitute two dynamic processes in two different time scales. As the economic process is much slower than the other process we can neglect the latter's transients and concentrate on the time invariant steady state solutions to the transportation equation. The model thus constructed has some noncooperative game and optimal control problem's features with space being the ‘running’ variable. This revised version was published online in July 2006 with corrections to the Cover Date.     

Measuring the spatial impacts of urbanization on the surface water resource basins in Istanbul via remote sensing

Istanbul is one of the largest metropolitan cities in the World. The city has experienced rapid industrialization and urbanization in the second half of the twentieth century. Between 1950 and 2000, the city has grown by an average of 4.5% annually. Given the scale of the growth, neither local nor the central governments have shown capability of controlling the influx of migration, most of which settled illegally on public lands. Most of the settlements lack the basic sewerage facilities, and a significant portion of which are on the major water resource basins. As of today, Istanbul Metropolitan Municipality (IMM) not only has to cope with the infrastructure problems, but also has to find ways of solving the problem of illegal occupations of public lands and water resource basins. This paper presents the land use changes in the water resource basins providing water to the Istanbul Metropolitan Area. Using four consecutive Landsat images between 1990 and 2005, the changes in 12 different land use categories are obtained via overlay operations by GIS for water resource basins surrounding the City of Istanbul. It has been observed that the most critical land use changes are in the nearest basins to the city. The capability of Landsat and IKONOS images in determining the alterations in the macro form of the city are also discussed. Finally, possibility of utilization of new technologies in policy making regarding environmental management in Istanbul is discussed.     

Multi-objective, decision-based assessment of a water quality monitoring network in a river system

Water quality monitoring network design has historically tended to use experience, intuition and subjective judgement in locating monitoring stations. Better design procedures to optimize monitoring systems need to simultaneously identify significant planning objectives and consider a number of social, economic and environmental constraints. The consideration of multiple objectives may require further decision analysis to determine the preference weights associated with the objectives to aid in the decision-making process. This may require the application of an optimization study to extract such information from decision makers or experts and to evaluate the overall effectiveness of locating strategies. This paper assesses the optimal expansion and relocation strategies of a water quality monitoring network using a two-stage analysis. The first stage focuses on the information retrieval of preference weights with respect to the designated planning objectives. With the aid of a pre-emptive goal programming model, data analysis is applied to obtain the essential information from the questionnaire outputs. The second stage then utilizes a weighted multi-objective optimization approach to search for the optimal locating strategies of the monitoring stations in the river basin. Practical implementation is illustrated by a case study in the Kao-Ping River Basin, south Taiwan.     

An Oligopoly Game of CDR Strategy Deployment in a Steady-State Net-Zero Emission Climate Regime

In this paper, we propose a simple oligopoly game model to represent the interactions between coalitions of countries in deploying carbon dioxide removal (CDR) strategies in a steady-state net-zero emission climate regime that could take place by the end of the twenty-first century. The emission quotas and CDR activities obtained in the solution of this steady-state model could then be used as a target for end-of-period conditions in a dynamic integrated assessment analysis studying the transition to 2100. More precisely, we analyze a steady-state situation where m coalitions exist and behave as m players in a game of supplying emission rights on an international emission trading system. The quotas supplied by a coalition must correspond to the amount of CO₂ captured through CDR activities in the corresponding world region. We use an extension of the computable general equilibrium model GEMINI-E3 to calibrate the payoff functions and compute an equilibrium solution in the noncooperative game.

     

Information theoretic perspective on coastal water-quality monitoring and management near an offshore industrial park

A semi-continuous water-quality monitoring system was installed in Yunlin Offshore Industrial Park (YOIP), the largest industrial park in Taiwan, in 2007 to provide real-time water-quality information such as pH, water depth, dissolved oxygen, temperature, turbidity, conductivity, and chlorophyll. To interpret the large quantities of high-frequency data generated by this system, information theory was applied for data analysis and extraction of useful information for further coastal water-quality management. Information theory is a branch of applied mathematics that involves the quantification of information. Shannon entropy is a key measure of information that was calculated in this study to reveal the inherent uncertainty of water-quality information. The applicability of Shannon entropy for signaling possible coastal pollution events in the YOIP was explored and results showed that it provides new insight into the inherent uncertainty or randomness of the original data. Specially, when Shannon entropy was high, multiple instable readings were observed for turbidity and salinity. This indicates that Shannon entropy may be a useful new tool for exploratory data analysis. It can be used as a supplementary indicator along with the original environmental data to signify some episodes of water-quality degradation.     

River water quality management under incomplete information: application of an N-person iterated signaling game

One of the important issues in river quality management is to provide pollution control strategies which are acceptable for all stakeholders. When there is only one water quality checkpoint in a reach of a river which receives pollution loads of several dischargers and dischargers are penalized for any water quality violation, the game theory can be used for modeling the natural process of bargaining among load dischargers considering the assimilative capacity of a river. There are also some types of uncertainties in river water quality management which should be incorporated throughout the bargaining process. Signaling games can be utilized for modeling the bargaining among dischargers and developing perfect Bayesian equilibrium (PBE) strategies for pollution control. In this paper, a new methodology called N-person iterated signaling game is developed for river quality management considering the existing uncertainties in pollution loads of dischargers. The methodology can provide the stable PBE waste load allocation strategies. The practical utility of the proposed methodology is illustrated by applying it to a reach of the Zarjub River in Iran. This reach includes seven pollution load dischargers.     

清河流域水质目标管理技术应用示范

针对清河流域三级水生态功能分区功能定位和水质保护目标,按照"分类、分区、分级、分期"理念,应用流域水质目标管理技术方法,研究清河流域控制单元污染负荷核定、水环境容量计算与分配、污染负荷削减、污染物总量控制等关键技术应用示范,完善流域水质目标管理技术,为清河流域水环境管理提供科技支撑。     

Assessing disproportionate costs to achieve good ecological status of water bodies in a Mediterranean river basin

Water management is becoming increasingly important as the demand for water grows, diversifies, and includes more complex environmental concerns. The Water Framework Directive (WFD) seeks to achieve a good ecological status for all European Community water bodies by 2015. To achieve this objective, economic consideration of water management must be given to all decision-making processes. Exemption (time or level of stringency) from the objectives of the EU Directive can be justified by proving that the cost of implementing measures is disproportionate to the benefits. This paper addresses the issue of disproportionate costs through a cost-benefit analysis (CBA). To predict the costs, the function costs method is used. The quantification of environmental benefits is more complex, because they are not determined by the market. As an alternative to stated preference methods, we use the distance function approach to estimate the environmental benefits of improving water quality. We then apply this methodological approach to a Mediterranean River Basin in Spain. The results show that the achievement of good status could not be rejected based on the criterion of disproportionate costs in this river basin. This paper illustrates that CBA is a useful tool to inform policy and decision making. Furthermore, it is shown that economics, particularly the valuation of environmental benefits, plays a crucial role in fulfilling the environmental objectives of the WFD.     

Using the analytical hierarchy process to assess the environmental vulnerabilities of basins in Taiwan

Every year, Taiwan endures typhoons and earthquakes; these natural hazards often induce landslides and debris flows. Therefore, watershed management strategies must consider the environmental vulnerabilities of local basins. Because many factors affect basin ecosystems, this study applied multiple criteria analysis and the analytical hierarchy process (AHP) to evaluate seven criteria in three phases (geographic phase, hydrologic phase, and societal phase). This study focused on five major basins in Taiwan: the Tan-Shui River Basin, the Ta-Chia River Basin, the Cho-Shui River Basin, the Tseng-Wen River Basin, and the Kao-Ping River Basin. The objectives were a comprehensive examination of the environmental characteristics of these basins and a comprehensive assessment of their environmental vulnerabilities. The results of a survey and AHP analysis showed that landslide area is the most important factor for basin environmental vulnerability. Of all these basins, the Cho-Shui River Basin in central Taiwan has the greatest environmental vulnerability.     

A simplified model for reservoir operation considering the water quality issues: Application of the Young conflict resolution theory

In this study, an algorithm combining a multi-objective genetic algorithm (GA)-based optimization model and a water quality simulation model is developed for determining a trade-off curve between objectives related to the allocated water quantity and quality. To reduce the run-time of the GA-based optimization model, the main problem is decomposed to long-term and annual optimization models. The reliability of water supply is considered to be the objective function in the long-term stochastic optimization model, but the objective functions of the annual models are related to both the allocated water quantity and quality. The operating policies obtained using this long-term model provide the time series of the optimum reservoir water storages at the beginning and the end of each water year. In the next step, these optimal reservoir storage values are considered as constraints for water storage in the annual reservoir operation optimization models. The epsilon-constraint method is then used to develop a trade-off curve between the reliability of water supply and the average allocated water quality. The Young conflict resolution theory, which incorporates the existing conflicts among decision-makers and stakeholders, is used for selecting the best solution on the trade-off curve. The monthly reservoir operating rules are then calculated using an Adaptive Neuro-Fuzzy Inference System, which is trained using the optimal operating policies. The proposed model is applied to the 15-Khordad Reservoir in the central part of Iran. The results show that this simplified procedure does not reduce the accuracy of the reservoir operating policies and it can effectively reduce the computational burden of the previously developed models.     

A hybrid model of external environmental benefits compensation to practitioners for the application of prefabricated construction

As the creators of the external benefits of prefabricated construction implementation, the government, real estate developers, and homebuyers have the right to allocate the external benefits. However, there is no effective quantitative method for achieving this goal. Therefore, this study aims to develop a quantitative analysis model for the reasonable allocation of the external benefits among the creators. The externality theory and bargaining theory were introduced to this study as the research foundation. Through literature review, the environmental benefit quantification index was defined. A bargaining model including Game 1 and Game 2 was designed for determining the external benefits allocation ratios for each player. In Game 1, the government was considered as the agent of homebuyers to conduct the bargaining game with real estate developers. Game 2 reflected the bargaining game process between the government and homebuyers for sharing the ratio of external benefits achieved from Game 1. The powerful position in bargaining game and discount factors of each player were considered as the critical factors influencing the distribution ratio because the value will change with the development of prefabricated construction. A prefabricated construction building was selected as a case to illustrate the applicability of this proposed model. The distribution result is that the government, the real estate developers, and homebuyers should share the external benefits of prefabrication implementation by 38%, 35%, and 27% respectively. This study contributes to aiding the creators to achieve optimal benefits allocation and thus motivates the enthusiasm of practitioners in prefabricated construction implementation.     

A soil-site evaluation index of productivity in intensively managed Pinus radiata (D. Don) plantations in South Australia

A limiting-factor, environmental model for radiata pine (Pinus radiata (D. Don)) has been developed using landform and soil morphological features that influence site productivity. The model focuses on soil and landscape constraints to productivity and predicts the native productivity of land and tree species. It permits the integration of land-use objectives for a catchment through forest management and use of silvicultural practices which increase productivity. The soil site evaluation index (SSEI) is an index of forest productivity found when silviculture extends only to the minimum amount of site disturbance needed to establish a plantation of radiata pine. The impacts of intensive silvicultural practices were deducted from the Site Quality productivity survey rating to calculate the unimproved yield class (uYC). We calculated SSEI by range standardising uYC values from 0 to 1. SSEI was correlated with the environmental factors in a regression tree model using readily available analytical software. The model accurately predicts unimproved forest productivity from observed soil horizon and land surface properties. The environmental constraints in low lying areas relate to waterlogging, soil sodicity and gravel content. In elevated areas, plant available water storage, rock weathering, landform, ironstone gravel and aspect are recognised factors for pine growth.     

Time-Consistent Equilibria in Common Access Resource Games with Asymmetric Players Under Partial Cooperation

Given a differential game, if agents have different time preference rates, cooperative (Pareto optimum) solutions obtained by applying Pontryagin’s maximum principle become time inconsistent. We derive a set of dynamic programming equations in continuous time whose solutions are time-consistent equilibria for problems in which agents differ in their utility functions and also in their time preference rates. The solution assumes cooperation between agents at every time. Since coalitions at different times have different time preferences, equilibrium policies are calculated by looking for Markov (subgame perfect) equilibria in a (noncooperative) sequential game. The results are applied to the study of a cake-eating problem describing the management of a common property exhaustible natural resource. The extension of the results to a simple common property renewable natural resource model in infinite horizon is also discussed.