Risk-Based Decisionmaking in Water Resources IX

This paper addresses flaws in metrics when used in modeling water-resources systems without discrimination, and also the unqualified use of model optimization as a surrogate to system optimization. The five points discussed are: cost-benefit analysis, expected value of risk, present value of money, reliability analysis as a surrogate to risk analysisn, and the fallacy of optimization.

A point of view is presented from which the Hierarchical Holographic Modeling (HHM) method of Y.Y. Haimes can be seen as a method for identifying risk scenarios. The key idea is to view the HHM diagram as a depiction of the "success scenario" S₀. Each box in the HHM then represents a set of actions or results that must occur as part of the definition of success. By the same token then, the box can represent the set of risk scenarios in which one or more of these actions/results fail to be accomplished. The union of all these sets thus represents a complete set of risk scenarios, S_i. Thus, HHM can be seen as one more method within the Theory of Scenario Structuring and takes its place there alongside the well-known methods of FMEA, HAZOP, scenario trees, and AFD.

Risk evaluation criteria can serve a useful role in developing a business case for justifying dam safety risk-reduction measures for individual dams and for portfolios of dams. This paper discusses the limitations of simple threshold criteria and the use of estimates of the cost-effectiveness of risk-reduction measures to evaluate ALARP (as low as reasonably practicable) considerations, which play a role in assessing the owner's duty of care and due diligence. It also describes an emerging approach to using risk estimates to formulate and justify a dam safety improvement program and for strengthening ongoing dam safety management activities.

Critical infrastructures are central to our national defense and our economic well being, but many are taken for granted. Presidential Decision Directive (PDD) 63 highlights the importance of eight of our critical infrastructures and outlines a plan for action. Greatly enhanced physical security systems will be required to protect these national assets from new and emerging threats. Sandia National Laboratories has been the lead laboratory for the Department of Energy (DOE) in developing and deploying physical security systems for the past twenty-five years. Many of the tools, processes, and systems employed in the protection of high-consequence facilities can be adapted to the civilian infrastructure.

Results of fuzzy-rule-based modeling are presented for linking atmospheric circulation patterns (CP) and El Niño- Southern Oscillation (ENSO) to local climatic factors with the ultimate goal of long-term forecasting. Two important climatic factors will be considered. These are monthly precipitation and drought index over three remote locations of different climate: Arizona, Nebraska, and Hungary. CP is represented by the daily geopotential height maps classified either with cluster analysis using the k-means method used in Arizona and Nebraska, or the Hess and Brezowsky scheme for the European continent. The ENSO phenomena are represented by time series of the Southern Oscillation Index (SOI). In every case, the fuzzy-rule-based approach reproduces the statistical properties of monthly precipitation and drought index. The best results require considering the joint forcing of CP and ENSO information. Separate use of either the relative frequencies of CP types as premises or the lagged SOI shows that neither formulation can reproduce the empirical frequency distributions. Statistical measures of dependence between CP, ENSO, and the precipitation/drought index are relatively weak, precluding the use of other techniques such as multivariate regression. In every case, the calculated time series reproduces the observed time series for the calibration period. In Arizona the calculated precipitation time series, and in Nebraska the calculated drought index reproduces fairly well the observed time series even for the validation periods. In Hungary the observed time series for the validation periods are not reproduced.

The issue of global warming has prompted an examination of hydrologic time series for trends. Trend assessment is pursued here in conjunction with an assessment of flow series persistence. The analysis of trend and persistence is carried out in the Upper Mississippi and Missouri River basins. In the investigation, flood sequences are considered as elements of the spectrum of extreme flows, where the spectrum extends from the low to the high flows. Most gages in the Upper Mississippi basin show significant positive trends and persistence in low flows, with larger trends in the more northern part of the basin. There is also a consistent pattern of significant positive trends and persistence in the annual mean flows throughout the basin. Longer-duration high flows showed less propensity toward trend and persistence. There is not a strong propensity toward trend and persistence in the 1-day high flow.

Evidence accumulates that climate has changed, is changing, and will continue to do so. As our understanding of these processes improves, how should water resources planning and flood-risk management evolve? Using the upper Mississippi River Basin as an example, this paper investigates how flood risk estimation and risk forecasting might be done in a world with variable flood risk. Four alternative forecasting approaches are developed using reasonable models for climate variability, and the resulting estimates of average flood risk and the equivalent economic risk are compared.

Managers of community water systems in South Carolina and the Susquehanna River Basin of Pennsylvania report more frequent drought emergencies than flood emergencies in the past five years. They expect to continue to have more problems with droughts than with floods in the next 10 years. Lightning strikes also cause extensive damage, especially in South Carolina. Water managers seem to base their expectations of future weather effects on their recent experiences with weather conditions. Most managers do not expect a flood emergency in the next 10 years and if there is a flood emergency, they do not expect financial, health, or water-supply problems. This sanguine view of flood emergencies seems surprising in light of the 20^th century experiences of devastating floods in both states. Formal risk assessments might support the view of the majority of managers who report that planning for flood emergencies is not adequate. The implication is that many water systems may be more vulnerable to flood emergencies than would be the case if risk-based decisionmaking were more widely practiced.

The deployment of US military forces to conduct operations other than war (OOTW) has become increasingly common over the past two decades. The deployment mission subsumes a critical and often under-performed task: set up and occupy a base camp that projects, sustains, and protects the force. Military operational-level planners currently lack a decision support tool that provides necessary information to aid the commander in determining the best locations for base camps. Decisions on location are based primarily on tactical considerations, specifically the employment of tactical units given their OOTW mission. Once a unit arrives and occupies an assembly area, the location becomes, over time, a de facto base camp location. Additionally, military planners would benefit from a decision support tool that optimizes a facilities layout for a base camp. This paper presents our research in identifying base camp functions inherent to site-selection and facility layout decisions. The paper concludes with a discussion about future research, highlighting system requirements for a decision support system.

Risk assessment involves many uncertain quantities, only some fraction of which are amenable to statistics and modeling. Even when uncertainties are difficult to model, however, experts may have well-founded opinions about them. The use of judgmental probability allows for the inclusion of these types of uncertainties in risk assessment. The quantification of expert opinion in the form of judgmental probabilities and consequences of failure has become known as "expert-opinion elicitation." The rigor of such expert-opinion elicitation in practice varies from casual to careful, as does the veracity of resulting numbers. Uncertainties associated with the process of expert-opinion elicitation and its results will be described and discussed. A process of elicitation that is appropriate for risk studies will be outlined and its components described. The paper discusses example techniques for eliciting judgmental probabilities and consequences for dam safety studies for the purposes of simulation-based design and verification and validation (V&V) necessity for computational methods.

The use of cost risk assessment for decisionmaking in evaluating public works projects is demonstrated with a Monte Carlo simulation model. The analysis shows that the risk of cost overruns can be quantitatively described and characterized. The results of the risk assessment can be used to identify the extent of exposure and the likelihood of an overrun, and to choose a desired level of protection from cost overruns, heretofore not an option with traditional cost contingencies. The information provided by cost risk assessment can be put to different uses. This is shown by a benefit-cost analysis that utilizes the distribution of total costs rather than the official point estimate of costs to demonstrate economic efficiency, which a point estimate would have failed to do.

In early stages of problem-solving, knowledge of extreme scenarios, protection alternatives, and perspectives of impacts may be limited and emerging. Some considerations are presented for the selection of (i) extreme scenarios and (ii) protection alternatives that are meaningful in support of cost/benefit/risk analysis.

A common feature of many of the current environmental issues is that the immediate impacts or risks, although considered to be small by many scientists, are uncertain and potentially widespread and significant in the long term. Thus, they are of concern to potentially affected groups. The need to formulate decisions and commit major resources in the face of these uncertainties has led to the introduction of new environmental decisionmaking frameworks. These have as central features consideration of the broader environmental context and a greater involvement of the affected parties in the process. Various research activities and case studies are described which are targeted at aiding further development of the decisionmaking frameworks into a more widely useable and effective approach.

This paper discusses the development of a reliability model for the alkali-aggregate reaction (AAR) of mass concrete structures. AAR growth is caused by chemical reaction in concrete between the aggregate and the cements. This creates an unlimited swelling and volumetric expansion of mass concrete, which causes substantial cracking within mass concrete structures. Since constitutive models for AAR growth are not readily available in the literature, the reliability analysis was implemented using a response surface methodology based on finite element analysis. The finite element analysis was calibrated to field measurements for strains and displacements at Chickamauga Lock and Dam. The time-dependent reliability was developed around the "life cycle" methods presented in Patev et al. A Monte Carlo simulation program was developed to determine the reliability and hazard function for the miter gate monolith, Block 47. The reliability results from the simulations show that replacement or repair to the miter gate monoliths at Chickamauga Lock and Dam will be needed in the short term to avoid any potential failure. The applications to other AAR growth problems in a variety of engineering structures are readily adaptable using the methods presented in this paper. Conclusions are drawn and additional finite element and response surface modeling are to be developed for other monoliths at Chickamauga Lock, and rock anchors are to be included into the time-dependent AAR reliability problems as well.

Petra is located in the southwest region of Jordan about 200 km south of Amman between the Dead Sea and the Gulf of Aqaba. Petra was carved in sandstone canyons by the Nabatean Arabs over 2,000 years ago. It is a major tourism attraction, as its monuments are considered the jewels of Jordan. Floods pose a serious threat to the tourist-activities as well as to the monuments themselves. To alleviate the impact of flood risk in Petra, different flood mitigation measures are investigated. The impact of these measures on flood-peak flow and volume is evaluated. They include afforestation, terracing, and the construction of check and storage dams, as well as various combinations of these measures. A flood simulation model depicts reductions of up to 70% in flood-peak flows and volumes due to these flood mitigation strategies.

The unavailability of empirical information that is simultaneously relevant and complete enough to fully specify the analysis is a ubiquitous problem in probabilistic risk and safety assessments (PRAs and PSAs). There is commonly uncertainty about the distributions of input variables and their mutual dependencies. In some cases, even details about the mathematical model that should be used to combine the input variables may be in dispute. However, to obtain any answer at all from a traditional probabilistic assessment such as a Monte Carlo simulation, the assessment model, all the distribution shapes, parameters and dependence structures, and correlation coefficients must be fully specified at the start. Therefore, an analyst generally needs to make many assumptions that go considerably beyond what can be justified empirically. Naturally, these assumptions of convenience diminish the credibility of the final conclusions derived from the assessments. Probability bounds analysis allows assessors to sidestep uncertainty about the precise specifications of input variables, imperfect information about the correlation and dependency structure among the variables, and even dispute about the form of the risk model itself. The package RAMAS Risk Calc implements probability bounds analysis under the Windows operating system. The convenient interface offers a powerful array of standard functions, which are extensible by means of user-written programs. The uses of probability bounds analysis and the features of the software are described.

Risk analysis is a necessary component of project planning and maintenance. Among other facets, risk analysis includes evaluation of loads (demands) and responses (capacities), or the reliability of a structure. Reliability assessment is based on a logical format for analyzing the probability of unsatisfactory performance using probabilistic estimates of loadings and responses. This paper discusses specific aspects of structural reliability assessment related to the current condition of constructed structures. The most accurate application of reliability relies on historical performance data for identical structures under like conditions. Rarely is such data readily available, however. Differences in environment, construction quality, design, loadings, maintenance, etc. can have substantial impact on the performance of a structure. This impact can be initially estimated, but divergences from initial estimates during the life of the structure are more difficult to determine and quantify. Condition assessment information can be used as an informative tool and more formally to create a performance-correlated database. This database can be used for adjusting the reliability assessments as a structure's condition deviates from the predictions made for a structure of the current age and loading history.

The Information Value Analysis Process (IVAP) is a formal process address uncertainty in decision analysis prior to undertaking the actual analysis and then making the decision. The premise for the IVAP is that the acquisition of data must be cost-effective in terms of the value of the decision to be made, even when the data is from heterogeneous sources with different levels of integrity and uncertainty. IVAP is a generic process, since there are many ways to implement it. Tools have been developed to facilitate the process, but they don't dictate the choice of method. As envisioned here, IVAP addresses uncertainty in estimates of: benefits, performance, costs, risks, and other related parameters. The process is outlined, and an example, using a dam safety (risk) model, is demonstrated.