Uncertainty modelling in multi-criteria analysis of water safety measures

Water utilities must assess risks and make decisions on safety measures in order to obtain a safe and sustainable drinking water supply. The World Health Organization emphasises preparation of water safety plans, in which risk ranking by means of risk matrices with discretised probability and consequence scales is commonly used. Risk ranking enables prioritisation of risks, but there is currently no common and structured way of performing uncertainty analysis and using risk ranking for evaluating and comparing water safety measures. To enable a proper prioritisation of safety measures and an efficient use of available resources for risk reduction, two alternative models linking risk ranking and multi-criteria decision analysis (MCDA) are presented and evaluated. The two models specifically enable uncertainty modelling in MCDA, and they differ in terms of how uncertainties in risk levels are considered. The need of formal handling of risk and uncertainty in MCDA is emphasised in the literature, and the suggested models provide innovations that are not dependent on the application domain. In the case study application presented here, possible safety measures are evaluated based on the benefit of estimated risk reduction, the cost of implementation and the probability of not achieving an acceptable risk level. Additional criteria such as environmental impact and consumer trust may also be included when applying the models. The case study shows how safety measures can be ranked based on preference scores or cost-effectiveness and how measures not reducing the risk enough can be identified and disqualified. Furthermore, the probability of each safety measure being ranked highest can be calculated. The two models provide a stepwise procedure for prioritising safety measures and enable a formalised handling of uncertainties in input data and results.     

Process design for the environment: A multi-objective framework under uncertainty

Designing chemical processes for the environment requires consideration of several indexes of environmental impact including ozone depletion, global warming potentials, human and aquatic toxicity, photochemical oxidation, and acid rain potentials. Current methodologies, such as the generalized waste reduction algorithm (WAR), provide a first step towards evaluating these impacts. However, to address the issues of accuracy and the relative weights of these impact indexes, one must consider the problem of uncertainties. Environmental impacts must also be weighted and balanced against other concerns, such as their cost and long-term sustainability. These multiple, often conflicting, goals pose a challenging and complex optimization problem, requiring multi-objective optimization under uncertainty. This paper will address the problem of quantifying and analyzing the various objectives involved in process design for the environment. Towards this goal, we proposed a novel multi-objective optimization framework under uncertainty. This framework is based on new and efficient algorithms for multi-objective optimization and for uncertainty analysis. This approach finds a set of potentially optimal designs where trade-offs can be explicitly identified, unlike cost-benefit analysis, which deals with multiple objectives by identifying a single fundamental objective and then converting all the other objectives into this single currency. A benchmark process for hydrodealkylation (HDA) of toluene to produce benzene modeled in the ASPEN simulator is used to illustrate the usefulness of the approach in finding environmentally friendly and cost-effective designs under uncertainty.     

Evaluating a small deposit next to an economically viable gold mine in West Africa from the points of view of the mining company,the government and the local community

This paper addresses the question of evaluating how much the different stakeholders stand to gain from a mining project. By carefully analysing the breakdown of the cash-flows generated, we were able to estimate the amounts received by the local community and by the national community (outside the mining area), the taxes and royalties received by the government and the profits made by the mining company. A real options framework was used to take account of the inherent uncertainty on the commodity price and the reserves, and the operating flexibility (that is, the possibility for the company to stop mining if the commodity price drops and/or the reserves prove to be lower than that had been envisaged). A synthetic case-study of a gold mine in West Africa was used to illustrate how this procedure could be applied in practice. By using the real option framework we were able to envisage scenarios for developing an extension to a deposit as a function of future values of the commodity price. The procedure proposed should provide governments and NGOs with more objective data for making policy decisions.     

How rational are investment decisions in the copper industry?

This paper examines ex-post 51 investment decisions made in regard to copper mines coming on stream from 1957 through 1999. It discusses two critical variables: investment timing and mine capacity choice. Using a 15% discount rate, results suggest that fewer than half of decisions were made at the right time – i.e., low price periods – confirming countercyclical investment as the optimal policy. In terms of capacity choice, the distortion is even higher, as 36 projects should have entered at least 40% larger or smaller. Realized investment decisions for timing and capacity choice would have caused a 49.1% loss over the NPV potentially achievable under optimal resolutions. Although the difference could be specifically attributed to copper price uncertainty, this paper discusses how investment evaluation methodologies could be contributing to firms not being fully rational (in the neoclassical sense) when investing.     

Remediation of contaminated lands: a decision methodology for site owners

Deciding how to remediate and redevelop contaminated lands should involve more than just selecting remediation techniques to clean a site to meet regulations for a predetermined site use. Owners and their consultants also need to understand aspects such as alternative site uses and liability, and how issues such as uncertainty can affect them. A methodology has been developed that provides a framework for current site owners when making decisions. It clarifies the above issues and details the type of information that is needed. It offers a step-by-step approach to improve decision making when contemplating remediation of contaminated sites by identifying the site use and remedial action combination that maximizes the current owner's net benefits. It examines various factors in decision making--with special emphasis on the timely issues of liability and uncertainty--and how expert opinion can be used to address diverse or incomplete data. Future research should include developing a complementary methodology that incorporates community and ecological objectives, resulting in a unified decision framework.     

ASSESSING ENVIRONMENTAL EFFECTS OF SEVERE SUSTAINED DROUGHT1

ABSTRACT: Evaluation criteria for reservoir and stream resources were developed to provide decision makers with feedback on environmental consequences of water allocation decisions under conditions of severe sustained drought within the Colorado River Basin by using the AZCOL gaming simulation model. Seven categories of flow dependent resources were identified which highlight resource states associated with reservoirs or river reaches within the AZCOL model. AZCOL directly simulates impact of water management decisions on five resource categories: threatened, endangered or sensitive fish; native nonlisted fish; wetland and riparian elements; national or state wildlife refuges; and hatcheries or other flow dependent facilities. Two additional categories - cold and warm water sport fish - are not modeled explicitly but are incorporated in the evaluation of monetary benefits from recreation on Colorado River waters. Each resource category was characterized at each time step in the simulation according to one of four environmental states: stable, threatened, endangered, or extirpated. Changes in resource states were modeled by time and flow-dependent decision criteria tied to either reservoir level or stream flows within the AZCOL model structure. Gaming results using the AZCOL model indicate environmental impacts would be substantial and that water allocation decisions directly impacted environmental resource states.     

MODELING DRINKING WATER QUALITY VIOLATIONS WITH BAYESIAN NETWORKS1

ABSTRACT: Compliance violations at community water systems are rare but represent significant human health risks. These risks are mediated by the decision schema of human operators at water treatment facilities. However, causal uncertainty among physical and human factors involved in water quality problems complicates assessment of their probability and severity. This study uses a probabilistic Bayesian network modeling approach to explore the causes of compliance violations in a sample of water treatment systems in Pennsylvania. The model presented here is one of several created by treatment system operators during an expert elicitation process. The expert model alone predicts violations poorly, suggesting that experts make inaccurate quantitative estimates. However, Bayesian networks are capable of combining the subjective expertise of treatment system operators with the objective compliance histories of the facilities they manage, and the expert model accurately predicts violations when trained with historical compliance data. Analysis of the trained network reveals those components of the treatment process, including environmental and system characteristics as well as operator decisions, that play the greatest role in determining the likelihood of major violation types. Among operator decisions, coagulant dosing and filter backwash frequency are the most important determinants of violation likelihood.     

A geophysical perspective of value of information: examples of spatial decisions for groundwater sustainability

The value of information (VOI) can be used to determine what kind of spatial information maybe relevant and useful for groundwater sustainability decisions. In this paper, the unique challenges for applying VoI to spatial information from geophysical data are described. The uncertainty regarding the spatial structure or continuity of the subsurface properties can be described with geostatistical sample models. Using these models, one can quantify the prior value given our present state of uncertainty and a set of decision alternatives and outcomes. Because geophysical techniques are a type of remote-sensing data, assuming “perfect” information is not realistic since the techniques usually are indirectly sampling the aquifer properties. Therefore, the focus of this paper is describing how the data reliability (the measure of imperfectness) can be quantified. One of the foremost considerations is the non-unique relationship between geological parameters (which determine groundwater flow) and geophysical observables (what determines the response of the technique). Another is to have the information in a form such that it is useful for spatial decisions. This will often require inversion and interpretation of the geophysical data. Inversion reconstructs an image of the subsurface from the raw geophysical data. How closely the image reproduces the true subsurface structure or property of interest depends on the particular technique’s resolution, depth of investigation and sensor locations. Lastly, in some cases, interpretation of the geophysical data or inversion will be necessary to link the data to the variables that determine the outcome of the decision. Three examples are provided that illustrate different approaches and methods for addressing these challenges. In the examples, time-domain electromagnetic and electrical resistivity techniques are evaluated for their ability to assist in spatial decisions for aquifer management. The examples considered address these three situations: aquifer vulnerability to surface–borne contaminants, managed aquifer recharge and CO₂/brine leakage (related to CO₂ geologic sequestration activities). The methods presented here are transferable to other subsurface sciences and decisions that involve risk. Recent work has been applied to geothermal well-siting using electromagnetic techniques. These approaches can also be applied for oil and mining spatial decisions, and they offer advantages over previous VOI work done for oil applications: they explicitly include the geologic uncertainty modeling and simulate the physics of the considered geophysical technique.     

矿业环境治理的经济学分析

当前，我国矿山环境问题突出。重点分析了矿山开采环境问题的特殊性，这些特殊性包括矿业对地域区位的依赖性、破坏的大量不确定性以及不可逆性。根据特殊性，讨论了环境经济学的适用性。不确定问题转化为确定性问题或者风险问题依赖于技术层面学科（如矿山环境影响评价和矿山环境地质学等）的支撑。最后指出随着这些技术学科的发展，矿山环境问题就会更精确地纳入成本——效益分析框架，从而发挥更大的作用。     

PLANNING METHODOLOGY FOR ANALYSIS AND MANAGEMENT ON LAKE EUTROPHICATION1

ABSTRACT: The effects of changing nutrient inputs through land use management, waste water treatment, or effluent diversion are not clear, and managers are discovering that decisions which were effective in reversing eutrophication for one lake are often unsuccessful when applied to another. Simple empirical relationships are often used to predict the impact of management decisions. Errors in estimation could result in either substantial costs for overdesign or failure to meet desired eutrophication levels. This paper presents and illustrates a methodology to evaluate the impact of land use and water resource management decisions on lake eutrophication. The problems of worth of additional information, and uncertainty of estimates were handled within a cost-effectiveness framework. The probability of exceeding a critical level of eutrophication was considered as a measure of effectiveness. The cost criterion is the expected value of opportunity costs, costs of analysis and costs of additional information. Uncertainty analysis techniques were used to estimate the effectiveness of various management alternatives. Bayesian methods can be utilized to determine the worth of additional information. The methodology was applied to Beseck Lake, Connecticut, and the cost and effectiveness measures estimated for a number of land management alternatives. Worth of additional information was not determined in this initial effort in uncertainty analysis for lake eutrophication management.     

Dealing with uncertainty in collaborative planning: developing adaptive strategies for the IJsselmeer

Adaptive strategies to deal with uncertainty in water management are often collaboratively developed. So far, however, little attention has been paid to the influence of collaboration on handling uncertainty through adaptive planning. In this paper, we study how collaboration has influenced the handling of uncertainty through adaptive planning for water management strategies for the IJsselmeer area in the Netherlands. We show how a fixation on certainty, different perspectives among actors and unclear responsibilities between arenas affect the handling of uncertainty, and found that it is adversely affected by collaboration. The use of adaptive planning challenged current water uses and system functions, creating resistance from actors. We conclude that developing a shared problem perception, creating a common understanding of uncertainties and ensuring a clear demarcation between the water system, its societal functions and water usage, are necessary to make adaptive planning successful in handling uncertainty.     

THE NATURE OF LONG RUN COST SAVINGS DUE TO WATER CONSERVATION1

Savings in capital, operation, and maintenance costs of new water supply facilities are referred to as “long run foregone costs.” Any conservation measure leads to reduction of water use or loss, however, significant long run foregone costs are realized only when reductions in size or delays in construction of facilities result. In order to accurately evaluate these costs it is necessary to know which facilities are affected and how they are affected (i.e., eliminated, downsized, or delayed). The effects of several levels of conservation on long run fore gone costs for an actual study are presented and some easy to use equations that may be used to calculate such savings are then derived. Some rules are presented to determine if it is more economical to delay construction or downsize facilities.     

WATER SHORTAGES,DEVELOPMENT, AND DROUGHT IN ROCKLAND COUNTY,NEW YORK1

Knowledge of the historical variability of regional climate is an essential element of successful water resource planning. Lacking such perspective, planners and managers can be deceived as to the severity of a recent climate extreme, such as drought, and place a disproportionate blame on the climate, not the integrity of the supply system should water restrictions become necessary to avoid shortages. Presented here is a vivid example of how development, a lack of adequate planning, and climate variability have converged to produce three water emergencies in Rockland County, New York, since 1995. An examination of climate data over the past century indicates that the severity of the recent droughts was well within the range of past variability. Rather than climate alone, the recent water emergencies have highlighted a significant mismatch between supply and demand that has been developing in Rockland County over the past three decades. Substantial development, largely in the form of single‐family homes, has not been matched with a corresponding enhancement of the county's water system. Realistic plans for meeting current water demand will require cooperation among all stakeholders, beginning with an acknowledgement that climate variations are inevitable, not the sole source of blame when water shortages arise.     

测定水样中化学需氧量的不确定度

对化学需氧量测定的不确定度进行合理评定,应充分考虑测定过程中的不确定度来源。建立了重铬酸钾法测定水样中化学需氧量不确定度的数学模型,对组成化学需氧量的各个因子的不确定度分量进行了详尽的分析和计算,得出了本次样品CODCr的测定结果为72.2mg/L,扩展不确定度为3.8mg/L。     

WATER QUALITY ALLOCATED COST FOR MULTIPURPOSE RESERVOIRS1

ABSTRACT: Low flow augmentation from multipurpose reservoirs may yield significant water quality benefits. Cost allocation assigns a portion of reservoir expense to water quality consumers, waste water dischargers who benefit from increased receiving flow. Whereas such allocation currently is not authorized for Federal projects, the procedure is increasingly appropriate for efficient multiobjective management. Waste water treatment costs, multipurpose reservoir costs, and water quality are modeled for Oregon's Willamette River. Water quality is expressed as a function of treatment and augmentation levels. Treatment cost necessary to achieve a given water quality without augmentation less treatment cost with augmentation is an alternative cost of water quality maintenance. With a cost allocation procedure, this alternative cost is used to determine water quality's share of reservoir cost. Under current conditions, water quality beneficiaries could be charged approximately seven percent of annualized reservoir expense. This charge is one-fourth the expense of additional treatment facilities required were augmentation not provided.     

THE OPTIMAL TIME TO START THE OPERATION OF A DESALTING PLANT IN ISRAEL1

The study contains the methodology of finding the optimal time to start the operation of a desalting plant or any other non conventional source of water for agricultural use in Israel. The essence of the methodology is the moving equilibrium price and quantity of agricultural products. The market of agricultural products is represented by a single demand curve and a supply curve which is derived from the agricultural sector production function. Both the demand for and the supply of agricultural products functions are shifting over time. The marginal value product of water is the critical value that determines the optimal time of a desalting plant. The study is static in the sense that dynamic aspects per se are not dealt with-e.g. learning by doing of building and operating desalting plants. The empirical results although used for illustrative purposes can be used as reference points for other detailed and more ‘exact’ studies on water desalination.     

The values of biological diversity: a travelogue

Biological diversity is an abstract, scientific concept and both evaluating its condition and, to great extent, justifying its conservation requires expert knowledge. Accordingly, regulating and managing biological diversity presupposes standardisation and methods for managing uncertainty. To be acted on, the concept must be promoted, passing, in this process, through various institutions, such as intergovernmental organisations and national administrations. This paper examines how the principle of biological diversity conservation is defined, focusing on the values of biological diversity and how this notion has ‘travelled the world’. The paper includes a study of how the principle of biological diversity was applied in a specific case of insect control in Sweden.     

A comparative analysis of methods to represent uncertainty in estimating the cost of constructing wastewater treatment plants

Prediction of construction cost of wastewater treatment facilities could be influential for the economic feasibility of various levels of water pollution control programs. However, construction cost estimation is difficult to precisely evaluate in an uncertain environment and measured quantities are always burdened with different types of cost structures. Therefore, an understanding of the previous development of wastewater treatment plants and of the related construction cost structures of those facilities becomes essential for dealing with an effective regional water pollution control program. But deviations between the observed values and the estimated values are supposed to be due to measurement errors only in the conventional regression models. The inherent uncertainties of the underlying cost structure, where the human estimation is influential, are rarely explored. This paper is designed to recast a well-known problem of construction cost estimation for both domestic and industrial wastewater treatment plants via a comparative framework. Comparisons were made for three technologies of regression analyses, including the conventional least squares regression method, the fuzzy linear regression method, and the newly derived fuzzy goal regression method. The case study, incorporating a complete database with 48 domestic wastewater treatment plants and 29 industrial wastewater treatment plants being collected in Taiwan, implements such a cost estimation procedure in an uncertain environment. Given that the fuzzy structure in regression estimation may account for the inherent human complexity in cost estimation, the fuzzy goal regression method does exhibit more robust results in terms of some criteria. Moderate economy of scale exists in constructing both the domestic and industrial wastewater treatment plants. Findings indicate that the optimal size of a domestic wastewater treatment plant is approximately equivalent to 15,000 m3/day (CMD) and higher in Taiwan. Yet the optimal size of an industrial wastewater treatment plant could fall in between 6000 CMD and 20,000 CMD.     

Making framing of uncertainty in water management practice explicit by using a participant-structured approach

By now, the need for addressing uncertainty in the management of water resources is widely recognized, yet there is little expertise and experience how to effectively deal with uncertainty in practice. Uncertainties in water management practice so far are mostly dealt with intuitively or based on experience. That way decisions can be quickly taken but analytic processes of deliberate reasoning are bypassed. To meet the desire of practitioners for better guidance and tools how to deal with uncertainty more practice-oriented systematic approaches are needed. For that purpose we consider it important to understand how practitioners frame uncertainties. In this paper we present an approach where water managers developed criteria of relevance to understand and address uncertainties. The empirical research took place in the Doñana region of the Guadalquivir estuary in southern Spain making use of the method of card sorting. Through the card sorting exercise a broad range of criteria to make sense of and describe uncertainties was produced by different subgroups, which were then merged into a shared list of criteria. That way framing differences were made explicit and communication on uncertainty and on framing differences was enhanced. In that, the present approach constitutes a first step to enabling reframing and overcoming framing differences, which are important features on the way to robust decision-making. Moreover, the elaborated criteria build a basis for the development of more structured approaches to deal with uncertainties in water management practice.