Andreas Lindhe

Fault tree analysis for integrated and probabilistic risk analysis of drinking water systems.

Drinking water systems are vulnerable and subject to a wide range of risks. To avoid sub-optimisation of risk-reduction options, risk analyses need to include the entire drinking water system, from source to tap. Such an integrated approach demands tools that are able to model interactions between different events. Fault tree analysis is a risk estimation tool with the ability to model interactions between events. Using fault tree analysis on an integrated level, a probabilistic risk analysis of a large drinking water system in Sweden was carried out. The primary aims of the study were: (1) to develop a method for integrated and probabilistic risk analysis of entire drinking water systems; and (2) to evaluate the applicability of Customer Minutes Lost (CML) as a measure of risk. The analysis included situations where no water is delivered to the consumer (quantity failure) and situations where water is delivered but does not comply with water quality standards (quality failure). Hard data as well as expert judgements were used to estimate probabilities of events and uncertainties in the estimates. The calculations were performed using Monte Carlo simulations. CML is shown to be a useful measure of risks associated with drinking water systems. The method presented provides information on risk levels, probabilities of failure, failure rates and downtimes of the system. This information is available for the entire system as well as its different sub-systems. Furthermore, the method enables comparison of the results with performance targets and acceptable levels of risk. The method thus facilitates integrated risk analysis and consequently helps decision-makers to minimise sub-optimisation of risk-reduction options.

Approximate dynamic fault tree calculations for modelling water supply risks

Traditional fault tree analysis is not always sufficient when analysing complex systems. To overcome the limitations dynamic fault tree (DFT) analysis is suggested in the literature as well as different approaches for how to solve DFTs. For added value in fault tree analysis, approximate DFT calculations based on a Markovian approach are presented and evaluated here. The approximate DFT calculations are performed using standard Monte Carlo simulations and do not require simulations of the full Markov models, which simplifies model building and in particular calculations. It is shown how to extend the calculations of the traditional OR- and AND-gates, so that information is available on the failure probability, the failure rate and the mean downtime at all levels in the fault tree. Two additional logic gates are presented that make it possible to model a systems ability to compensate for failures. This work was initiated to enable correct analyses of water supply risks. Drinking water systems are typically complex with an inherent ability to compensate for failures that is not easily modelled using traditional logic gates. The approximate DFT calculations are compared to results from simulations of the corresponding Markov models for three water supply examples. For the traditional OR- and AND-gates, and one gate modelling compensation, the errors in the results are small. For the other gate modelling compensation, the error increases with the number of compensating components. The errors are, however, in most cases acceptable with respect to uncertainties in input data. The approximate DFT calculations improve the capabilities of fault tree analysis of drinking water systems since they provide additional and important information and are simple and practically applicable.

Cost-effectiveness analysis of risk-reduction measures to reach water safety targets

Identifying the most suitable risk-reduction measures in drinking water systems requires a thorough analysis of possible alternatives. In addition to the effects on the risk level, also the economic aspects of the risk-reduction alternatives are commonly considered important. Drinking water supplies are complex systems and to avoid sub-optimisation of risk-reduction measures, the entire system from source to tap needs to be considered. There is a lack of methods for quantification of water supply risk reduction in an economic context for entire drinking water systems. The aim of this paper is to present a novel approach for risk assessment in combination with economic analysis to evaluate risk-reduction measures based on a source-to-tap approach. The approach combines a probabilistic and dynamic fault tree method with cost-effectiveness analysis (CEA). The developed approach comprises the following main parts: (1) quantification of risk reduction of alternatives using a probabilistic fault tree model of the entire system; (2) combination of the modelling results with CEA; and (3) evaluation of the alternatives with respect to the risk reduction, the probability of not reaching water safety targets and the cost-effectiveness. The fault tree method and CEA enable comparison of risk-reduction measures in the same quantitative unit and consider costs and uncertainties. The approach provides a structured and thorough analysis of risk-reduction measures that facilitates transparency and long-term planning of drinking water systems in order to avoid sub-optimisation of available resources for risk reduction.

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.

A fault tree model to assess probability of contaminant discharge from shipwrecks

Shipwrecks on the sea floor around the world may contain hazardous substances that can cause harm to the marine environment. Today there are no comprehensive methods for environmental risk assessment of shipwrecks, and thus there is poor support for decision-making on prioritization of mitigation measures. The purpose of this study was to develop a tool for quantitative risk estimation of potentially polluting shipwrecks, and in particular an estimation of the annual probability of hazardous substance discharge. The assessment of the probability of discharge is performed using fault tree analysis, facilitating quantification of the probability with respect to a set of identified hazardous events. This approach enables a structured assessment providing transparent uncertainty and sensitivity analyses. The model facilitates quantification of risk, quantification of the uncertainties in the risk calculation and identification of parameters to be investigated further in order to obtain a more reliable risk calculation.

VRAKA—A Probabilistic Risk Assessment Method for Potentially Polluting Shipwrecks

Shipwrecks around the world contain unknown volumes of hazardous substances which, if discharged, could harm the marine environment. Shipwrecks can deteriorate for a number of reasons, including corrosion and physical impact from trawling and other activities, and the probability of a leakage increases with time. Before deciding on possible mitigation measures, there are currently few comprehensive methods for assessing shipwrecks with respect to pollution risks. A holistic method for estimating environmental risks from shipwrecks should be based on well-established risk assessment methods and should take into account both the probability of discharge and the potential consequences. The purpose of this study was therefore to present a holistic risk assessment method for potentially polluting shipwrecks. The focus is set to developing a method for estimating the environmental consequences of potential discharges of hazardous substances from shipwrecks and to combine this with earlier research on a tool for estimating the probability of discharge of hazardous substances. Risk evaluation should also be included in a full risk assessment and is the subject of further research. The consequence assessment was developed for application in three tiers. In Tier 1, the probability of discharge and possible amount of discharge are compared to other shipwrecks. In Tier 2, a risk matrix, including a classification of potential consequences, is suggested as a basis for assessment and comparison. The most detailed level, Tier 3, is based on advanced tools for oil spill trajectory modeling and sensitivity mapping of the Swedish coast. To illustrate the method an example application on two wrecks is presented. Wreck number 1 present a lower probability of discharge and a lower consequence in a Tier 1 and Tier 3 assessment. For the Tier 2 consequence assessment, the two example wrecks present equal consequence. The tool for estimating the probability of discharge of hazardous substances from shipwrecks, and the approach for consequence estimation, offers a comprehensive method for assessing the risks presented by potentially polluting shipwrecks. The method is known as VRAKA (short for shipwreck risk assessment in Swedish) and provides decision support, facilitating prioritization of risk mitigation measures enabling efficient use of available resources.

Bayesian updating in a fault tree model for shipwreck risk assessment

Shipwrecks containing oil and other hazardous substances have been deteriorating on the seabeds of the world for many years and are threatening to pollute the marine environment. The status of the wrecks and the potential volume of harmful substances present in the wrecks are affected by a multitude of uncertainties. Each shipwreck poses a unique threat, the nature of which is determined by the structural status of the wreck and possible damage resulting from hazardous activities that could potentially cause a discharge. Decision support is required to ensure the efficiency of the prioritisation process and the allocation of resources required to carry out risk mitigation measures. Whilst risk assessments can provide the requisite decision support, comprehensive methods that take into account key uncertainties related to shipwrecks are limited. The aim of this paper was to develop a method for estimating the probability of discharge of hazardous substances from shipwrecks. The method is based on Bayesian updating of generic information on the hazards posed by different activities in the surroundings of the wreck, with information on site-specific and wreck-specific conditions in a fault tree model. Bayesian updating is performed using Monte Carlo simulations for estimating the probability of a discharge of hazardous substances and formal handling of intrinsic uncertainties. An example application involving two wrecks located off the Swedish coast is presented. Results show the estimated probability of opening, discharge and volume of the discharge for the two wrecks and illustrate the capability of the model to provide decision support. Together with consequence estimations of a discharge of hazardous substances, the suggested model enables comprehensive and probabilistic risk assessments of shipwrecks to be made.

Risk-based cost-benefit analysis for evaluating microbial risk mitigation in a drinking water system

Waterborne outbreaks of gastrointestinal diseases can cause large costs to society. Risk management needs to be holistic and transparent in order to reduce these risks in an effective manner. Microbial risk mitigation measures in a drinking water system were investigated using a novel approach combining probabilistic risk assessment and cost-benefit analysis. Lake Vomb in Sweden was used to exemplify and illustrate the risk-based decision model. Four mitigation alternatives were compared, where the first three alternatives, A1-A3, represented connecting 25, 50 and 75%, respectively, of on-site wastewater treatment systems in the catchment to the municipal wastewater treatment plant. The fourth alternative, A4, represented installing a UV-disinfection unit in the drinking water treatment plant. Quantitative microbial risk assessment was used to estimate the positive health effects in terms of quality adjusted life years (QALYs), resulting from the four mitigation alternatives. The health benefits were monetised using a unit cost per QALY. For each mitigation alternative, the net present value of health and environmental benefits and investment, maintenance and running costs was calculated. The results showed that only A4 can reduce the risk (probability of infection) below the World Health Organization guidelines of 10-4 infections per person per year (looking at the 95th percentile). Furthermore, all alternatives resulted in a negative net present value. However, the net present value would be positive (looking at the 50th percentile using a 1% discount rate) if non-monetised benefits (e.g. increased property value divided evenly over the studied time horizon and reduced microbial risks posed to animals), estimated at 800-1200 SEK (€100-150) per connected on-site wastewater treatment system per year, were included. This risk-based decision model creates a robust and transparent decision support tool. It is flexible enough to be tailored and applied to local settings of drinking water systems. The model provides a clear and holistic structure for decisions related to microbial risk mitigation. To improve the decision model, we suggest to further develop the valuation and monetisation of health effects and to refine the propagation of uncertainties and variabilities between the included methods.

Sustainability assessments of regional water supply interventions – Combining cost-benefit and multi-criteria decision analyses

To cope with present and future challenges, a growing number of water utilities in Sweden, Europe and elsewhere initiate various forms of inter-municipal cooperations creating a new regional level of drinking water governance. In order to reach viable decisions of alternative ways forward, there is an international consensus that sustainability needs to be addressed in water supply planning, design and decision-making. There are, however, few decision aids focusing on assessing the sustainability of inter-municipal cooperations and the inter-municipal policies and interventions that regional decision-makers are faced with. This paper presents a decision support model based on a combination of cost-benefit analysis and multi-criteria decision analysis for assessing the sustainability of regional water supply interventions, including formations of inter-municipal cooperations. The proposed decision support model integrates quantitative and semi-quantitative information on sustainability criteria. It provides a novel way of presenting monetized benefits and costs, capturing utilitarian aspects of alternative interventions, with non-monetized social and environmental effects, capturing aspects based in the deontological theories of moral ethics. The model is based on a probabilistic approach where uncertainties are defined by statistical probability distributions. A case study is used to exemplify and evaluate model application in decision situations regarding regionalization, (de)centralization, source water quality and redundancy. All evaluated alternatives were expected to contribute to a slightly improved social sustainability, whereas the results were more varying in the economic and environmental domains. A structured and transparent treatment of uncertainties facilitates a better understanding of the results as well as communication between decision-makers, stakeholders and the community.

Methodology for Integrated Socio-economic Assessment of Multi-use Offshore Platforms

This chapter presents the methodology employed for the Integrated Socio-Economic Assessment (MISEA) of different designs of Multi-Use Offshore Platforms (MUOPs). The methodology allows for the identification, the valuation and the assessment of the potential impacts and their magnitude. The analysis considers a number of feasible designs of MUOP investments, and the likely responses of those impacted by the investment project. The approach provides decision-makers with a valuable tool to assess whether a MUOP project increases the overall social welfare and hence should be undertaken. This is performed under alternative specifications regarding platform design, the discount rate and the stream of net benefits, if a Cost-Benefit Analysis (CBA) is to be followed or a sensitivity analysis of selected criteria in a Multi-Criteria Decision Analysis (MCDA) framework. The methodology can support the implementation of policies aiming at achieving a good environmental status of the EU’s marine waters and the protection of the resource base upon which marine-related economic and social activities depend.