A multi-disciplinary framework to monetize financial consequences arising from CCS projects and motivate effective financial responsibility

Carbon dioxide capture and storage (CCS) holds promise as a safe and effective approach for addressing climate change. However, concern about potential “liability” associated with CCS often is cited as a significant barrier to project deployment. The authors contend that, in this context, the term “liability” is poorly defined and conflates concerns about the uncertainty in the timing and magnitude of potential damages with the need for financial responsibility for long-term stewardship of certified closed sites. This paper offers an analytic framework drawn from damages estimation methodologies used in comparable contexts and incorporates risk-based probabilistic modeling to assist stakeholders in evaluating the potential environmental, human health and financial consequences of CCS projects. Application of the proposed framework will achieve four distinct objectives. First, the outputs of the analyses – monetized damages estimates for adverse impact scenarios coupled with expected loss calculations that reflect scenario probabilities and identify the statistical range of possible outcomes, including “most likely” loss estimates – will help interested stakeholders consider the viability of various investment and financial risk management strategies. Second, the results can be used to develop or negotiate financial assurance instruments for analyzed projects. Third, the results will inform the public policy debate regarding the degree and magnitude of potential financial consequences resulting over the long-term, beyond an established post-closure period. And, fourth, while the detailed conceptual framework, resulting models, impact calculations and valuation analyses may be applied on a site-by-site basis, the site-specific results could be pooled to assess regional and national implications of various risk mitigation and financial risk management policies.     

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.     

POLLUTANT RUNOFF MODELS: SELECTION AND USE IN DECISION MAKING1

Models for pollutant runoff can be useful in water quality management planning if appropriately structured for the problem at hand. Accordingly, a “top-down” approach is proposed for the examination of extant pollutant runoff models. The approach consists of the identification of objectives and attributes that reflect the needs of planners and decision makers when these models are used for water quality management planning. Ideally, the attributes should concern the effect of model information on improved decision making and the cost of model application. Practical difficulties with the first attribute necessitates substitution of surrogate attributes reflecting model appropriateness, resolution, and uncertainty. Common pollutant runoff models, in particular export coefficients and hydrology-driven simulation models, are found to have serious weaknesses on some of the attribute scales. The “top-down” approach leads to a set of desirable pollutant runoff model attributes; alternate modeling techniques are thus examined in order to identify promising future directions for model development. The focus of this examination is phosphorus, due to its importance in the eutrophication of surface waters. Models for both sediment-attached and dissolved phosphorus are considered. Among the conclusions is the belief that the partial contributing area concept can yield an effective yet simple simulation despite the variable and complex nature of runoff.     

Forecasting the number of soil samples required to reduce remediation cost uncertainty

Sampling scheme design is an important step in the management of polluted sites. It largely controls the accuracy of remediation cost estimates. In practice, however, sampling is seldom designed to comply with a given level of remediation cost uncertainty. In this paper, we present a new technique that allows one to estimate of the number of samples that should be taken at a given stage of investigation to reach a forecasted level of accuracy. The uncertainty is expressed both in terms of volume of polluted soil and overall cost of remediation. This technique provides a flexible tool for decision makers to define the amount of investigation worth conducting from an environmental and financial perspective. The technique is based on nonlinear geostatistics (conditional simulations) to estimate the volume of soil that requires remediation and excavation and on a function allowing estimation of the total cost of remediation (including investigations). The geostatistical estimation accounts for support effect, information effect, and sampling errors. The cost calculation includes mainly investigation, excavation, remediation, and transportation. The application of the technique on a former smelting work site (lead pollution) demonstrates how the tool can be used. In this example, the forecasted volumetric uncertainty decreases rapidly for a relatively small number of samples (20-50) and then reaches a plateau (after 100 samples). The uncertainty related to the total remediation cost decreases while the expected total cost increases. Based on these forecasts, we show how a risk-prone decision maker would probably decide to take 50 additional samples while a risk-averse decision maker would take 100 samples.     

OPTIMIZING WELL PLACEMENT IN A COASTAL AQUIFER: OUTER CAPE COD,MASSACHUSETTS1

ABSTRACT: An inverse‐simulation approach is used to determine optimal strategies for developing public water‐supply systems in a shallow, coastal aquifer on the outermost arm of the Cape Cod peninsula in Massachusetts. Typically a forward simulation (or “trial and error”) approach is used to find best pumping strategies, but the chances of finding success with this tact diminish as the number of potential options grows large. Well locations and pumping rates are optimized with respect to: (1) providing sufficient water to areas of water‐quality impairment, (2) minimizing impacts to nearby surface waters, (3) preventing saltwater contamination due to overpumping, and (4) minimizing financial cost of well development. Potential well sites and water‐supply scenarios are separated into “politically‐based” and “resource‐based” categories to gain insight into the degree that pre‐existing political boundaries hinder best management practices. The approach provides a promising tool in transboundary water‐resources settings because it allows stakeholders to find solutions that best meet everyone's goals, as opposed to pursuing options that will create conflict, or are less than optimal.     

SENSITIVITY ANALYSIS: A NECESSITY IN WATER PLANNING1

ABSTRACT In water planning activities, major emphasis has been placed on the development of procedures for devising “optimum plans.” These plans are defined as those which meet prespecified demands for water at “minimum cost.” However, all plans are developed subject to postulated conditions regarding the state of the physical system and of nature. Because planning takes place in a dynamic and uncertain environment in which postulated conditions are known to change, it is imperative that the planner be apprised in the planning phase of the effect of changes which can occur. Using “this information, a planner can temper his judgment with a knowledge of the effect of the uncertainty resulting from changes in the system state variables. This paper presents results of the use of a computer simulation and optimization model to quantify possible variations in system response which could occur as a result of uncertainty in the postulated physical and economic conditions under which the proposed water development system was to perform. The possible effects of these variable responses on planning decision-making is discussed.     

APPLICATION OF ENHANCED ANNEALING TO GROUND WATER REMEDIATION DESIGN1

ABSTRACT: A methodology for ground water remediation design has been developed that interfaces ground water simulation models with an enhanced annealing optimizer. The ground water flow and transport simulators provide the ability to consider site‐specific contamination and geohydrologic conditions directly in the assessment of alternative remediation system designs. The optimizer facilitates analysis of tradeoffs between technical, environmental, regulatory, and financial risks for alternative design and operation scenarios. A ground water management model using an optimization method referred to as “enhanced annealing” (simulated annealing enhanced to include “directional search” and “memory” mechanisms) has been developed and successfully applied to an actual restoration problem. The demonstration site is the contaminated unconfined aquifer referred to as N‐Springs located at Han‐ford, Washington. Results of the demonstration show the potential for improving groundwater restoration system performance while reducing overall system cost.     

FARMERS’ATTITUDES TOWARD GOVERNMENT INVOLVEMENT IN PREVENTING AGRICULTURAL NONPOINT SOURCE WATER POLLUTION1

ABSTRACT: Concern over the pollution of our lakes and streams has become a major issue in the United States. Sedimentation from sigricultural lands has been identified as a significant factor in water pollution. Some citizens suggest that government should force compliance with soil loss standards, while others suggest that we ask farmers to voluntarily comply. Related questions are “DO farmers think government should be involved in controlling erosion and protecting water quality?”“To what extent should government be involved?” What level of government should be involved? Federal? State? Local?“Why should pay for water quality projects?” Farmers from a small watershed in northeastern Indiana were interviewed before and after a major demonstration project. Their responses suggest that farmers feel that individual landowners should be responsible for controlling erosion and agricultural nonpoint source water pollution. However, over 60 percent of the study fanners indicated that the federal government should play an important role, in terms of both technical and financial assistance.     

ESTIMATION OF POTENTIAL REDUCTIONS IN RECREATIONAL BENEFITS DUE TO SEDIMENTATION1

ABSTRACT: A travel cost model is developed to estimate the potential reductions in recreational benefits from sedimentation in Reelfoot Lake in northwestern Tennessee. In addition to the consumer surplus estimates generated by the model, three other aspects of the study were significant. First, the study applied a relatively untested methodology for deriving the opportunity cost of travel time. The study resulted in a value that is less than one-half of the Water Resource Council's “one-third of the wage rate” rule-of-thumb. Second, water quality perceptions were unsuccessfully incorporated into the model as a demand shifter. This raised questions as to the appropriate manner in which perceptions could be included in a travel cost model. Finally, a simple methodology was outlined by which estimates of the recreational value of Reelfoot Lake could be used to suggest how much cost could be justified for soil erosion control on agricultural land surrounding the lake.     

Flood Risk Reduction from Agricultural Best Management Practices

Best management practices (BMPs) play an important role in improving impaired water quality from conventional row crop agriculture. In addition to reducing nutrient and sediment loads, BMPs such as fertilizer management, reduced tillage, and cover crops could alter the hydrology of agricultural systems and reduce surface water runoff. While attention is devoted to the water quality benefits of BMPs, the potential co‐benefits of flood loss reduction are often overlooked. This study quantifies the effects of selected commonly applied BMPs on expected flood loss to agricultural and urban areas in four Iowa watersheds. The analysis combines a watershed hydrologic model, hydraulic model outputs, and a loss estimation model to determine relationships between hydrologic changes from BMP implementations and annual economic flood loss. The results indicate a modest reduction in peak discharge and economic loss, although loss reduction is substantial when urban centers or other high‐value assets are located downstream in the watershed. Among the BMPs, wetlands, and cover crops reduce losses the most. The research demonstrates that watershed‐scale implementation of agricultural BMPs could provide benefits of flood loss reduction in addition to water quality improvements.     

A theory of chemicals regulation and testing

Risk management of chemicals requires information about their adverse effects such as toxicity and persistence, for example. Testing of chemicals allows for improving the information base for regulatory decision‐making on chemicals' production and use. Testing a large number of chemicals with limited time and resources forces a prioritization of chemicals. This paper proposes a decision model that provides a ranking of chemicals according to “urgency to test”. The model adopts a value‐of‐information approach describing the expected welfare gains from regulatory actions that respond to test information. We determine the value‐of‐information of tests revealing chemicals' levels of toxicity and persistence. We compare our findings to the prioritization of chemicals in the new European Chemicals Regulation “REACH”, where several tens of thousands of chemicals are to be tested in order to fill existing information gaps and to implement more effective risk management. We find that the main lines of chemicals' prioritization under REACH receive backing from our decision model. However, prioritization for testing can be further improved by accounting for testing costs and the sensitivity of regulatory action with respect to the test information.     

WATER USE DATA – WHO NEEDS IT?1

ABSTRACT: This paper addresses problems in the design of a water use data base and valuation of water use data. An examination of the economic efficiency and distributional aspects of selected water management problems indicates that there are benefits to be obtained from water use information and, thus, there is a potential value to water use data. Water use information is viewed as being produced by combining water use data with other data in a modeling context suggested by theory relevant to the problem at hand, and a well designed water use data base will facilitate this synthesis. Data “needs” in the production of water use information via economic modeling are described to illustrate the relationship between theory and data. Some of the desirable characteristics of a water use data base and inadequacies of the existing water use data “base” are described. The fugitive nature of the water use data resource and a lack of understanding of both the information “production function” and the role of water use information in decisionmaking complicates the water use data valuation problem.     

Value of information analysis for adequate monitoring of carbon dioxide storage in geological reservoirs under uncertainty

As monitoring is essential for the proper management of geological storage of carbon dioxide (CO₂), the ability to value information from monitoring is indispensable to adequately design a monitoring program. It is necessary to judge whether the expected improvement in management is worth the cost of monitoring. The value of information (VOI) is closely related to the possible increase in expected utility gained by gathering the information, the concept of which can be applied to such judgement. Although VOI analysis has been extensively studied in the context of decision analysis, its application to the management of carbon dioxide capture and storage (CCS) operations is rare. This paper introduces and discusses the methodology of VOI analyses in the context of monitoring CO₂ storage. A motivating problem with discrete probabilities is used to illustrate the concept of VOI. It is demonstrated that information is not always of value; for information to be worthwhile, monitoring under uncertainty must satisfy certain conditions. This concept is then extended to continuous probability distributions. The effects of prior uncertainty and information reliability on the VOI are examined. It is shown that an excessive improvement in information accuracy yields little value and that the optimal level of reliability can be inferred. VOI analyses provide quantitative insights into the value of information-gathering activities and therefore can be an objective means to adequately design and impartially justify a monitoring program.     

ELEMENTS OF A WATER QUALITY INFORMATION SYSTEM FOR THE STATE OF ILLINOIS1

ABSTRACT: A great deal of information can be derived from study of standard stream monitoring data, if these are properly ordered and organized. This information may then be used to make decisions about water quality management. Among critical information items are evaluation of performance to standards, determination of seasonality and time-trends of water quality conditions, and estimation of the effects on water quality to be expected from load reductions or standards modifications. Additional information on the magnitude of individual pollution sources is also critical to water quality management. Each of these items can be derived within the water quality information system which is currently under development for the State of Illinois.     

Benchmark Criteria: A Tool for Selecting Appropriate Models in the Field of Water Management

A milestone in the field of European water protection policy is the European Union’s Water Framework Directive (WFD), which came into force in December 2000 and which integrates the management of European waters in many ways. In this study, we start by focusing on management issues connected to the implementation of the WFD and pose a question: “what type of models would be the most suitable for use in the context of the WFD?” With this question in mind, we aim to establish a set of operational and functional selection criteria for (computer) models whose application is intended to support decision-making related to a particular water management issue. These so-called “benchmark criteria” should help water managers and other model users in choosing appropriate models, e.g., for the WFD implementation purposes. We first describe models and their use in general and then propose an approach for setting the benchmark criteria for models, basing it on the concept of uncertainty management, while keeping firmly in mind the important role of citizens and citizen organizations in water management. The suggested benchmark criteria are in the form of 14 questions through which each model can be evaluated. Finally, the process for testing and refining the benchmark criteria is highlighted.     

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.     

CURVE NUMBER HYDROLOGY IN WATER QUALITY MODELING: USES,ABUSES, AND FUTURE DIRECTIONS1

ABSTRACT: Although the curve number method of the Natural Resources Conservation Service has been used as the foundation of the hydrology algorithms in many nonpoint source water quality models, there are significant problematic issues with the way it has been implemented and interpreted that are not generally recognized. This usage is based on misconceptions about the meaning of the runoff value that the method computes, which is a likely fundamental cause of uncertainty in subsequent erosion and pollutant loading predictions dependent on this value. As a result, there are some major limitations on the conclusions and decisions about the effects of management practices on water quality that can be supported with current nonpoint source water quality models. They also cannot supply the detailed quantitative and spatial information needed to address emerging issues. A key prerequisite for improving model predictions is to improve the hydrologic algorithms contained within them. The use of the curve number method is still appropriate for flood hydrograph engineering applications, but more physically based algorithms that simulate all streamflow generating processes are needed for nonpoint source water quality modeling. Spatially distributed hydrologic modeling has tremendous potential in achieving this goal.     

WATER QUALITY MONITORING: WHERE'S THE BEEF?1

ABSTRACT: Water quality monitoring, as a function of society's efforts to manage the environment, is the contact mechanism that management and the public has with the actual water quality in the environment. Water quality monitoring has been studied extensively for many years to ensure that it produces information about water quality conditions. Current efforts to reduce government spending will have negative impacts on those government functions deemed to be non-responsive to the needs of the public. How well does water quality monitoring inform taxpayers about the status and trends in water quality conditions in the United States? This paper reviews a number of past efforts to “improve” water quality monitoring, discusses barriers to such improvement, and suggests ways that monitoring can be made more accountable for the information it should be producing for public understanding of water quality conditions. In particular, the need for standardization in data analysis and reporting of information to the public, is highlighted.     

A Question of Boundaries: The Importance of “Revenuesheds” for Watershed Protection1

Patterson, Lauren A., Jeffrey Hughes, Glenn Barnes, and Stacey I. Berahzer, 2012. A Question of Boundaries: The Importance of “Revenuesheds” for Watershed Protection. Journal of the American Water Resources Association (JAWRA) 48(4): 838‐848. DOI: 10.1111/j.1752‐1688.2012.00655.x Abstract: Watersheds transcend jurisdictional boundaries; raising important questions of who should pay for watershed protection, and how can watershed governance be funded? The responsibility and cost for watershed protection has progressively devolved to local governments, resulting in additional negative externalities and financing challenges. Watershed governance structures have formed at the scale of the watershed, but they often lack the financing mechanisms needed to achieve policy goals. Financing mechanisms via local governments provide a reliable source of revenue and the flexibility to address watershed specific issues. We develop a “revenueshed” approach to access the initial challenges local governments face when seeking to finance trans‐jurisdictional watershed governance. The revenueshed approach engages local governments into discussion and implementation of financial strategies for collaborative watershed governance. Legislation places water quality regulations primarily on local governments inside the watershed. The revenueshed approach extends the financial and stewardship discussion to include local governments outside the watershed that benefit from the watershed. We applied the revenueshed approach to the Mills River and Upper Neuse watersheds in North Carolina. Mills River had a partnership governance seeking revenue for specific projects, whereas the Upper Neuse sought long‐term financial stability to meet new water quality legislation.     

DESIGN AND IMPLEMENTATION OF A COOPERATIVE WATER QUALITY MONITORING PROGRAM IN COLORADO'S BIG THOMPSON WATERSHED1

ABSTRACT: In 1996, the Big Thompson Watershed Forum (BTWF) was formed “to assess and protect the quality of water” in the Big Thompson Watershed in northern Colorado. However, until 1999, water quality monitoring in the watershed was performed by many state, local, and federal agencies with no coordination among programs and with few efforts toward efficiency, data comparability, or information exchange. To better meet the needs of its stakeholders, the BTWF since 1999 has been actively pursuing the design and implementation of a cooperative water quality monitoring program. The program design involved consensus building among the funding participants, primarily drinking water providers. The final design included 38 parameters to be sampled 15 times per year at 24 stream and canal locations plus two reservoirs. Although the collaborative consensus based approach has been successful for the BTWF, this approach has its drawbacks; most notable among these are the time and labor this approach requires. Also, the BTWF struggled with achieving equal representation of all interests, since those agencies that provided funding had the greatest voice in the final product. While a collaborative approach may not always be best for monitoring program design, it should be appropriate for many watershed organizations that face the common problem of severe financial constraints.