A MULTI-BASIN PLANNING STRATEGY1

ABSTRACT. The purpose of this paper is to present and discuss a procedure for finding an optimal staging plan for implementing a multi-basin water resource system-a system that must meet, with tolerable shortages, pre-specified but highly variable demands for water that increase over time-a system such as the proposed Texas Water System. The paper stresses that, in the past, planners have paid little attention to quantifying explicitly the impact that uncertainty has on the decision process, and in that context, presents a means for explicitly evaluating the impact that uncertainty has on finding and evaluating the performance of the optimal and several alternate staging plans. The procedure presented evaluates the impact that uncertainty, in both the hydrologic and the economic variables, has on the decisions that need to be made. The decisions requiring resolution are (1) which of an over-specified set of facilities should be constructed, (2) how large each of the facilities should be at various points in time, and (3) how should the system be operated so as to minimize the capital plus operational costs over the planning period.     

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.     

Environmental portfolio analysis: An integrated strategic approach to environmental management

As businesses strive to reduce costs and become more competitive, environmental costs and potential future liability issues continue to raise overhead expenses. The decision process is further challenged by the various interpretations of existing laws and the uncertainty of future applicable regulations and their interpretation. To make more informed business decisions and bridge the gap between the environmental and business perspective, organizations need to be able to see the overall environmental picture and how it affects the current and future business operation. This article presents a systematic approach to developing an organization's integrated baseline “environmental portfolio” with various business risk levels and expected costs. Utilizing computer simulation, sensitivity iterations are performed to show the results of different scenarios. These scenarios can include various probabilities of cost levels, permitting strategies, and litigation, as well as the success of new technologies. Management can then focus attention on the main driving factors and avoid spending too much attention on lesser items. An additional benefit to this process is that communication between the various segments of an organization are enhanced since their perspectives are clearly articulated as part of the analysis. Sensitivity analysis also provides the framework for a sanity check of the process and results. Are projected levels of success reasonable? What levels would be required to change the decision, and how likely are they to occur? What level of overall business risk associated with environmental issues is prudent? In addition this article shows how computer modeling and simulation can bring a valuable perspective to the decision-making process.     

Structured Decision Making to Meet a National Water Quality Mandate

Water quality criteria are necessary to ensure protection of ecological and human health conditions, but compliance can require complex decisions. We use structured decision making to consider multiple stakeholder objectives in a water quality management process, with a case study in the Three Bays watershed on Cape Cod, Massachusetts. We set a goal to meet or exceed a nitrogen load reduction target for the watershed and four key objectives: minimizing economic costs of implementing management actions, minimizing the complexity of permitting management actions, maximizing stakeholder acceptability of the management actions, and maximizing the provision of ecosystem services (recreational opportunity, erosion and flood control, socio‐cultural amenity). We used multi‐objective optimization and sensitivity analysis to generate many possible solutions that implement different combinations of nitrogen‐removing management actions and reflect tradeoffs between the objectives. Results show technological advances in controlling household nitrogen sources could provide lower cost solutions and positive impacts to ecosystem services. Although this approach is demonstrated with Cape Cod data, the decision‐making process is not specific to any watershed and could be easily applied elsewhere.     

Regulating water quantity and quality in irrigated agriculture

This paper largely applies the theoretical model formulated in an earlier paper by the authors, of an input based approach to control an agricultural non-point-source pollution. The empirical problem includes a groundwater aquifer being polluted by several agricultural producers. In order to prevent degradation of the quality and depletion of the quantity of the water in the aquifer, a regulatory agency must intervene. The regulatory agency does not have all the information needed for decision making. The producers» use of water from a surface supply is recorded and additional water is pumped from the ground aquifer, the amount of which is unknown to the agency. The agency also does not know the physical characteristics of the production process that is factored into the pollution process. The model evaluates two monitoring regimes (central and individual) and two regulatory tools (taxes and quotas) associated with each regime. Individual monitoring was found to be superior to central monitoring, both in terms of the physical characteristics of the problem (water quality and quantity) and in terms of regional income. For both the central and the individual monitoring regimes, the optimal paths of the state variables reach steady-state values relatively early, with values in the individual monitoring reaching the steady-state earlier than in the case of central monitoring. The optimal path of investment in monitoring equipment suggested investment in monitoring equipment as early as possible.1998 Academic Press     

PART I: METHODOLOGY AND PROBLEMS IN AN URBANIZED ARID ENVIRONMENT1

The methodology of operations research is judged in relation to its utility to water resource management in an urbanized arid environment and to the study of worth of data for such management. Conditions for existence of a managerial problem are reviewed as is the multilevel structure of the decision process, including decisions on social goals for Western water use. Worth of data can only be judged in relation to a particular use to meet a social or managerial objective. The role of data uncertainty on the decision process is reviewed in the light of past water decisions and present and future problems.     

Reaching environmental decisions: Making subjective and objective judgments

Objective judgments, external to the judge, are compared with subjective, internal judgments. This analysis is made in the context of reaching regulatory decisions affecting the human environment. Examples given include evaluating the potential risk of industrial chemicals and comparing the potential effects of short- and long-term changes in land use. The analysis deals not with the decisions themselves, but rather with the kinds of questions that must be posed in orderto reach such decisions. Decision makers may spuriously distinguish objective from subjective types of judgment, though these are rarely wholly separate. Judges can hardly dispute about objective statements, if truly identical definitions are used. But subjective statements can reasonably be voted upon. Scientists, engineers, and economists represent logical or objective decision makers, tending to work in groups. Subjective thinkers include artists and performers, and others who often work alone. Moral and aesthetic aspects of questions, usually seen as intangible, are treated as if subjective. Financial decisions, usually viewed as tangible, are handled as objective problems. This mechanism for making decisions is well-established in environmental assessment. Though objective questions can be treated well in the monetary terms of cost-benefit analysis, subjective ones cannot. Mathematical and other variants are discussed in relation to the comparison of alternative types of tests.     

A multi-objective optimisation approach to water management

The management of river basins is complex especially when decisions about environmental flows are considered in addition to those concerning urban and agricultural water demand. The solution to these complex decision problems requires the use of mathematical techniques that are formulated to take into account conflicting objectives. Many optimization models exist for water management systems but there is a knowledge gap in linking bio-economic objectives with the optimum use of all water resources under conflicting demands. The efficient operation and management of a network of nodes comprising storages, canals, river reaches and irrigation districts under environmental flow constraints is challenging. Minimization of risks associated with agricultural production requires accounting for uncertainty involved with climate, environmental policy and markets. Markets and economic criteria determine what crops farmers would like to grow with subsequent effect on water resources and the environment. Due to conflicts between multiple goal requirements and the competing water demands of different sectors, a multi-criteria decision-making (MCDM) framework was developed to analyze production targets under physical, biological, economic and environmental constraints. This approach is described by analyzing the conflicts that may arise between profitability, variable costs of production and pumping of groundwater for a hypothetical irrigation area.     

Development of a water quality loading index based on water quality modeling

Water quality modeling is an ideal tool for simulating physical, chemical, and biological changes in aquatic systems. It has been utilized in a number of GIS-based water quality management and analysis applications. However, there is considerable need for a decision-making process to translate the modeling result into an understandable form and thereby help users to make relevant judgments and decisions. This paper introduces a water quality index termed QUAL2E water quality loading index (QWQLI). This new WQI is based on water quality modeling by QUAL2E, which is a popular steady-state model for the water quality of rivers and streams. An experiment applying the index to the Sapgyo River in Korea was implemented. Unlike other WQIs, the proposed index is specifically used for simulated water quality using QUAL2E to mainly reflect pollutant loading levels. Based on the index, an iterative modeling-judgment process was designed to make decisions to decrease input pollutants from pollutant sources. Furthermore, an indexing and decision analysis can be performed in a GIS framework, which can provide various spatial analyses. This can facilitate the decision-making process under various scenarios considering spatial variability. The result shows that the index can evaluate and classify the simulation results using QUAL2E and that it can effectively identify the elements that should be improved in the decision-making process. In addition, the results imply that further study should be carried out to automate algorithms and subsidiary programs supporting the decision-making process.     

INVESTMENT SEQUENCING RECOGNIZING EXTERNALITIES IN WATER DESALTING1

ABSTRACT. The failure to recognize the learning process in new technologies such as desalting may lead to incorrect water resource investment decisions for two reasons. First, to neglect cost reductions stemming from “learning by doing” implies an overestimation of desalting costs. Second, since learning in a particular plant may result in external (learning) benefits to other plants, these may serve as the basis for a subsidy intended to internalize such benefits. Accordingly, the research reported below includes an estimation of learning functions for desalting and the results of a formulation designed to measure external benefits on the basis of these learning functions. These results are then incorporated into a decision framework for water resource investments which recognizes uncertainty in determining optimal timing of desalting construction.     

A Structured Approach to Incidental Take Decision Making

Decision making related to incidental take of endangered species under U.S. law lends itself well to a structured decision making approach. Incidental take is the permitted killing, harming, or harassing of a protected species under the law as long as that harm is incidental to an otherwise lawful activity and does not “reduce appreciably the probability of survival and recovery in the wild.” There has been inconsistency in the process used for determining incidental take allowances across species and across time for the same species, and structured decision making has been proposed to improve decision making. I use an example decision analysis to demonstrate the process and its applicability to incidental take decisions, even under significant demographic uncertainty and multiple, competing objectives. I define the example problem, present an objectives statement and a value function, use a simulation model to assess the consequences of a set of management actions, and evaluate the tradeoffs among the different actions. The approach results in transparent and repeatable decisions.     

Importance of scientific uncertainty in decision making

Uncertainty in environmental decision making should not be thought of as a problem that is best ignored. In fact, as is illustrated in a simple example, we often informally make use of awareness of uncertainty by hedging decisions away from large losses. This hedging can be made explicit and formalized using the methods of decision analysis. While scientific uncertainty is undesirable, it can still be useful in environmental management as it provides a basis for the need to fund additional monitoring, experimentation, or information acquisition to improve the scientific basis for decisions.     

Environmental cost accounting: The bottom line for environmental quality management

Recent years have seen the environment emerge as one of the most pressing issues facing American business. Eventually, environmental costs will affect the bottom line of every American company. A recent study in the National Law Journal estimates that cleanup of the nation's known hazardous wastes sites will cost $752 billion over thirty years under current environmental policies. Environmental legislation and regulations impose annual compliance costs estimated by the Environmental Protection Agency at more than $30 billion. In the near future, environmental expenses for cleanup, regulatory compliance, and management are anticipated to grow to between 2.5 and 3 percent of GNP. Corporations that wish to be competitive must successfully manage these costs while maintaining or improving their role as responsible corporate citizens. Implementing a comprehensive system for identifying and managing environmental costs requires a multidisciplinary team effort. Environmental costs impact product selection, design and pricing, capital budgeting, and future strategic direction. In order to make informed and meaningful managerial decisions on environmental programs, real cost data are vital. An environmental management systems (EMS) requires information to set goals and then monitor progress towards those goals over time. This article will discuss the current cost accounting systems (CASs) available to support the myriad goals of environmental management systems. In addition, the article will outline a framework for plotting the location of your current EMS on a matrix of regulatory and information requirements and evaluating whether your corporation's CAS is adequate to support the goals and objectives set by your environmental management program. By anticipating future regulatory and information requirements, flexible systems can be developed to adapt to new and more stringent regulations and more complex information requirements.     

ECOSYSTEM MODELING OF A FORESTED RIVER BASIN1

ABSTRACT: A present concern in decision making processes for forest land use is the environmental effects of land use activities on water, air, and the land itself. Criteria for evaluating the magnitude and detriment of environmental impacts are not definite since it is often difficult to isolate a particular activity as the cause of a particular impact. Instead, interactions between various forest practices must be considered along with their integrated impacts. In order to provide an effective decision tool, the College of Forest Resources, University of Washington, is modeling the forest ecosystem of the Snohomish River Basin located in the Cascade Mountains of western Washington. The project consists of a general system model comprised of subsystem models dealing with product conversion processes, forest production processes, recreation supply processes, wildlife and fisheries supply processes, and the interactions of these processes with water and the atmosphere. The system model is interfaced with a computerized multiple player management game which enables land managers, manufacturing managers, and regulation agency personnel to make management decisions and respond to indications of lack of environmental control. Responses of the hydrologic system to various management decisions are simulated by the water subsystem model. The responses being considered include surface flow quantity and water quality. The model emphasizes the monitoring of non-point as well as point source impacts rather than predicting short-term hydrographs. The significance of impacts vary with land use patterns and the goals of the game player. Therefore, the model has flexible resolution and is able to predict hydrologic conditions for both large and small scale. The water subsystem model responds to management decisions by interpreting the effects of management options selected by game players for 40-acre cells within the Basin. The model then determines which streams are immediately affected, defines the watersheds contributing to these streams, and extracts from a resource data bank the information needed to define model parameters. Using these parameters and precipitation inputs, mean flow discharge on a montly and annual basis is calculated for the impactcd sub watersheds as well as 21 major watersheds of the Basin. Water quality responses predicted for these watersheds include suspended sediment concentration, temperature increases due to stream exposure, dissolved oxygen concentrations, the effects of fertilization on nitrogen content, biocide and herbicide effects, and residues from product conversion processes.     

USING CONTINGENT VALUATION AND BENEFIT TRANSFER TO EVALUATE WATER SUPPLY IMPROVEMENT BENEFITS1

ABSTRACT: Many water systems in small cities and rural areas throughout the United States are facing water quality and supply problems. These problems are typically not the result of an unexpected event, but are the result of growth trends or decreasing water quality experienced over several years. This analysis uses the contingent valuation and benefit transfer methods to evaluate the willingness to pay for a rural water system in northcentral Montana. Both of the procedures resulted in similar values, ranging from about $4.05 to $7.50 per household per month for urban residents and $5.40 to $11.50 per household per month for rural residents, which is equal to 11 percent to 23 percent of current average water costs. The willingness to pay estimates do not include non-household water users. This analysis shows that useful planning information can be obtained from relatively inexpensive contingent valuation mail survey data and the benefit transfer method as long as the limitations of the data are understood. The willingness to pay for ensuring good quality rural water supplies in the future is likely to be low compared to the costs of extensive diversion and treatment systems. Willingness to pay estimates provide decision makers with information that can be used to avoid building a large water supply system that water users do not want to connect to because of high costs.     

CONFLICTS IN ATTAINING NATIONAL GOALS FOR BOTH WATER QUALITY AND ENERGY PRODUCTION1

ABSTRACT: The “policy environment” is defined herein as the institutional setting in which planning is conducted and policy decisions are made with regard to meeting two of the Nation's high priority goals: water quality protection and energy independence. The simultaneous pursuit of these goals has resulted in numerous conflicts among the energy industry, environmentalists, and government. An analysis of selected energy development-water quality conflicts shows that these conflicts can be described in terms of one or more of the following policy environment characteristics: resource scarcity, sense of urgency, lack of experience, administrative complexity, uncertainty about future policies and regulations, technological complexity, and uncertainty about impacts. These characterics provide a useful framework for formulating potential strategies for the resolution of energy development-water quality conflicts.     

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.     

SUBJECTIVE DECISION-MAKING FOR URBAN WATER RESOURCES DEVELOPMENT1

ABSTRACT: Bayesian decision theory provides a procedure for the use of subjective data in a decision-making situation related to urban water resources development. This procedure is effectual in pursuing a set of goals and in transforming individual or group indecisiveness into satisfactory decisions. This approach is highlighted due to its capability to incorporate seemingly unquantifiable, abstract factors into the decision-making process. It is realized that the soliciting of expert and general public opinion is indispensable in making choices for the welfare of the general public from alternative courses of action under uncertainty. The analysis presented here considers engineering alternatives, quality, quantity, cost and the intangible public response in an integrated effort for the selection of optimum strategies in urban water resources development.     

PUBLIC INFORMATION AND CITIZEN INVOLVEMENT1

ABSTRACT: Public information, an important contributer to citizen involvement in the governmental decision making process, has traditionally been given a low priority by government agencies. However, citizens are becoming increasingly concerned about governmental decisions that affect their lives and are demanding more information about governmental activities, including information about water resource issues, Because of this active citizen interest and involvement, the role of public information in increasing citizen awareness is becoming more important. Government officials and professionals should recognize that public information efforts also play an important role in achieving increased credibility and respect for their agencies. Once an agency recognizes the importance of public information and decides to initiate a public information program, careful planning is required to develop a program that addresses the needs of both the citizens and the agency. Two of the most flexible and cost effective ways to get information to the publié are through publications and public meetings. Both can be easily adapted to suit the needs of specific audiences and projects. A successful public information program can be carried out at a relatively low cost, but it requires a substantial amount of time and energy. The commitment of time and energy for this purpose is a good investment, however, because an effective public information program can play a significant role in improving the quality of governmental decisions through the increased involvement of the citizenry.     

A STATISTICAL APPROACH FOR PERFORMING WATER QUALITY IMPAIRMENT ASSESSMENTS1

ABSTRACT: A statistical approach for making Total Maximum Daily Load (TMDL) impairment decisions is developed as an alternative to the simple tally of the number of measurements that happen to exceed the standard. The method ensures that no more than a small (e.g., 10 percent) percentage of water quality samples will exceed a regulatory standard with a high level of confidence (e.g., 95 percent). The method is based on the 100(1‐α) percent lower confidence limit on an upper percentile of the concentration distribution. Advantages of the method include: (1) it provides a direct test of the hypothesis that a prespecified percentage of the true concentration distribution exceeds a regulatory standard, (2) it is applicable to a wide variety of different statistical concentration distributions, (3) it directly incorporates the magnitude of the measured concentrations unlike traditional approaches, and (4) it has explicit statistical power characteristics (i.e., what is the probability of missing an environmental impact). Detailed study of the simple tally approach reveals that it achieves high statistical power at the expense of unacceptably high false positive rates (30 to 40 percent false positive results). By contrast, the statistical approach results in similar statistical power while achieving a nominal false positive rate of 5 percent.