Variability and Uncertainty Meet Risk Management and Risk Communication

In the past decade, the use of probabilistic risk analysis techniques to quantitatively address variability and uncertainty in risks increased in popularity as recommended by the 1994 National Research Council that wrote Science and Judgment in Risk Assessment. Under the 1996 Food Quality Protection Act, for example, the U.S. EPA supported the development of tools that produce distributions of risk demonstrating the variability and/or uncertainty in the results. This paradigm shift away from the use of point estimates creates new challenges for risk managers, who now struggle with decisions about how to use distributions in decision making. The challenges for risk communication, however, have only been minimally explored. This presentation uses the case studies of variability in the risks of dying on the ground from a crashing airplane and from the deployment of motor vehicle airbags to demonstrate how better characterization of variability and uncertainty in the risk assessment lead to better risk communication. Analogies to food safety and environmental risks are also discussed. This presentation demonstrates that probabilistic risk assessment has an impact on both risk management and risk communication, and highlights remaining research issues associated with using improved sensitivity and uncertainty analyses in risk assessment.     

Perceived Risks of Conventional and Organic Produce: Pesticides, Pathogens, and Natural Toxins

Public risk perceptions and demand for safer food are important factors shaping agricultural production practices in the United States. Despite documented food safety concerns, little attempt has been made to elicit consumers' subjective risk judgments for a range of food safety hazards or to identify factors most predictive of perceived food safety risks. In this study, over 700 conventional and organic fresh produce buyers in the Boston area were surveyed for their perceived food safety risks. Survey results showed that consumers perceived relatively high risks associated with the consumption and production of conventionally grown produce compared with other public health hazards. For example, conventional and organic food buyers estimated the median annual fatality rate due to pesticide residues on conventionally grown food to be about 50 per million and 200 per million, respectively, which is similar in magnitude to the annual mortality risk from motor vehicle accidents in the United States. Over 90% of survey respondents also perceived a reduction in pesticide residue risk associated with substituting organically grown produce for conventionally grown produce, and nearly 50% perceived a risk reduction due to natural toxins and microbial pathogens. Multiple regression analyses indicate that only a few factors are consistently predictive of higher risk perceptions, including feelings of distrust toward regulatory agencies and the safety of the food supply. A variety of factors were found to be significant predictors of specific categories of food hazards, suggesting that consumers may view food safety risks as dissimilar from one another. Based on study findings, it is recommended that future agricultural policies and risk communication efforts utilize a comparative risk approach that targets a range of food safety hazards.     

Compressed Natural Gas Bus Safety: A Quantitative Risk Assessment

This study assesses the fire safety risks associated with compressed natural gas (CNG) vehicle systems, comprising primarily a typical school bus and supporting fuel infrastructure. The study determines the sensitivity of the results to variations in component failure rates and consequences of fire events. The components and subsystems that contribute most to fire safety risk are determined. Finally, the results are compared to fire risks of the present generation of diesel-fueled school buses. Direct computation of the safety risks associated with diesel-powered vehicles is possible because these are mature technologies for which historical performance data are available. Because of limited experience, fatal accident data for CNG bus fleets are minimal. Therefore, this study uses the probabilistic risk assessment (PRA) approach to model and predict fire safety risk of CNG buses. Generic failure data, engineering judgments, and assumptions are used in this study. This study predicts the mean fire fatality risk for typical CNG buses as approximately 0.23 fatalities per 100-million miles for all people involved, including bus passengers. The study estimates mean values of 0.16 fatalities per 100-million miles for bus passengers only. Based on historical data, diesel school bus mean fire fatality risk is 0.091 and 0.0007 per 100-million miles for all people and bus passengers, respectively. One can therefore conclude that CNG buses are more prone to fire fatality risk by 2.5 times that of diesel buses, with the bus passengers being more at risk by over two orders of magnitude. The study estimates a mean fire risk frequency of 2.2 x 10(-5) fatalities/bus per year. The 5% and 95% uncertainty bounds are 9.1 x 10(-6) and 4.0 x 10(-5), respectively. The risk result was found to be affected most by failure rates of pressure relief valves, CNG cylinders, and fuel piping.     

Use of Acute Toxicity to Estimate Carcinogenic Risk

Data on the effects of human exposure to carcinogens are limited, so that estimation of the risks of carcinogens must be obtained indirectly. Current risk estimates are generally based on lifetime animal bioassays which are expensive and which take more than two years to complete. We here show how data on acute toxicity can be used to make a preliminary estimate of carcinogenic risk and give an idea of the uncertainty in that risk estimate. The estimates obtained are biased upwards, and so are useful for setting interim standards and determining whether further study is worthwhile. A general scheme which incorporates the use of such estimates is outlined, and it is shown by example how adoption of the procedures suggested could have prevented regulatory hiatus in the past.     

Vehicle Emission Unit Risk Factors for Transportation Risk Assessments

When the transportation risk posed by shipments of hazardous chemical and radioactive materials is being assessed, it is necessary to evaluate the risks associated with both vehicle emissions and cargo-related risks. Diesel exhaust and fugitive dust emissions from vehicles transporting hazardous shipments lead to increased air pollution, which increases the risk of latent fatalities in the affected population along the transport route. The estimated risk from these vehicle-related sources can often be as large or larger than the estimated risk associated with the material being transported. In this paper, data from the U.S. Environmental Protection Agency's Motor Vehicle-Related Air Toxics Study are first used to develop latent cancer fatality estimates per kilometer of travel in rural and urban areas for all diesel truck classes. These unit risk factors are based on studies investigating the carcinogenic nature of diesel exhaust. With the same methodology, the current per-kilometer latent fatality risk factor used in transportation risk assessments for heavy diesel trucks in urban areas is revised and the analysis expanded to provide risk factors for rural areas and all diesel truck classes. These latter fatality estimates may include, but are not limited to, cancer fatalities and are based primarily on the most recent epidemiological data available on mortality rates associated with ambient air PM-10 concentrations.     

Residential Radon in Canada: An Uncertainty Analysis of Population and Individual Lung Cancer Risk

Following a comprehensive evaluation of the health risks of radon, the U.S. National Research Council (US-NRC) concluded that the radon inside the homes of U.S. residents is an important cause of lung cancer. To assess lung cancer risks associated with radon exposure in Canadian homes, we apply the new (US-NRC) techniques, tailoring assumptions to the Canadian context. A two-dimensional uncertainty analysis is used to provide both population-based (population attributable risk, PAR; excess lifetime risk ratio, ELRR; and life-years lost, LYL) and individual-based (ELRR and LYL) estimates. Our primary results obtained for the Canadian population reveal mean estimates for ELRR, PAR, and LYL are 0.08, 8%, and 0.10 years, respectively. Results are also available and stratified by smoking status (ever versus never). Conveniently, the three indices (ELRR, PAR, and LYL) reveal similar output uncertainty (geometric standard deviation, GSD approximately 1.3), and in the case of ELRR and LYL, comparable variability and uncertainty combined (GSD approximately 4.2). Simplifying relationships are identified between ELRR, LYL, PAR, and the age-specific excess rate ratio (ERR), which suggest a way to scale results from one population to another. This insight is applied in scaling our baseline results to obtain gender-specific estimates, as well as in simplifying and illuminating sensitivity analysis.     

A Framework for Understanding Uncertainty in Seismic Risk Assessment

A better understanding of the uncertainty that exists in models used for seismic risk assessment is critical to improving risk-based decisions pertaining to earthquake safety. Current models estimating the probability of collapse of a building do not consider comprehensively the nature and impact of uncertainty. This article presents a model framework to enhance seismic risk assessment and thus gives decisionmakers a fuller understanding of the nature and limitations of the estimates. This can help ensure that risks are not over- or underestimated and the value of acquiring accurate data is appreciated fully. The methodology presented provides a novel treatment of uncertainties in input variables, their propagation through the model, and their effect on the results. The study presents ranges of possible annual collapse probabilities for different case studies on buildings in different parts of the world, exposed to different levels of seismicity, and with different vulnerabilities. A global sensitivity analysis was conducted to determine the significance of uncertain variables. Two key outcomes are (1) that the uncertainty in ground-motion conversion equations has the largest effect on the uncertainty in the calculation of annual collapse probability; and (2) the vulnerability of a building appears to have an effect on the range of annual collapse probabilities produced, i.e., the level of uncertainty in the estimate of annual collapse probability, with less vulnerable buildings having a smaller uncertainty.     

Presenting Uncertainty in Health Risk Assessment: Initial Studies of Its Effects on Risk Perception and Trust

Some analysts suggest that discussing uncertainties in health risk assessments might reduce citizens'perceptions of risk and increase their respect for the risk-assessing agency. We tested this assumption with simulated news stories varying simple displays of uncertainty (e.g., a range of risk estimates, with and without graphics). Subjects from Eugene, Oregon, read one story each, and then answered a questionnaire. Three studies tested between 180 and 272 subjects each. Two focus groups obtained more detailed responses to these stories. The results suggested that (1) people are unfamiliar with uncertainty in risk assessments and in science; (2) people may recognize uncertainty when it is presented simply; (3) graphics may help people recognize uncertainty; (4) reactions to the environmental problems in the stories seemed affected less by presentation of uncertainty than by general risk attitudes and perceptions; (5) agency discussion of uncertainty in risk estimates may signal agency honesty and agency incompetence for some people; and (6) people seem to see lower risk estimates (10^-6, as opposed to 10^-3) as less credible. These findings, if confirmed, would have important implications for risk communication.     

Should Persons with Diabetes Be Licensed to Drive Trucks?—Risk Management

How should a regulatory agency interpret a risk analysis that concludes there is a small increase in risk? The agency must decide on behalf of society whether the increased risk is large enough to justify banning the risky activity or taking some other step to lessen the risks. In a companion paper (Songer et al.), we conclude that licensing insulin using persons to drive commercial motor vehicles in interstate commerce would result in 42 additional crashes each year. Here we address risk management issues by interpreting the number of additional crashes and the relative risks of the prospective handicapped drivers. Are the number of additional crashes (42) significant? Is the increase in the annual crash risk (from 0.00785 to 0.032 for non-insulin dependent and 0.048 for insulin dependent persons) significant? Are the relative risks significant for all insulin using drivers (4.7)? For drivers with a history of severe hypoglycemic reactions (19.8)? How should society tradeoff risk increases for increases in opportunity for these handicapped persons? We review other social decisions concerning highway safety: Accepting the increasing risks of letting 16 year olds drive, allowing extremely light cars, allowing some unsafe highways, and allowing extremely unsafe driving conditions at some times of day. We conclude that the additional risks from insulin using persons are well within the current accepted range of risks. Currently, 70% of states permit insulin using persons to drive trucks within their state. Nonetheless, the social cost, due to fatalities, injuries, and property damage from allowing a person with a history of severe hypoglycemic reactions to drive is more than $19,700 per year.     

Predictive Genetic Testing for Alzheimer''s Disease: Impact upon Risk Perception

The aim of this study was to determine the impact on risk perceptions of disclosing genetic test results used to estimate the risk of Alzheimer's disease (AD). Adult children (n = 149) of people with AD were randomized to one of two groups--Intervention group: lifetime risk estimates of AD based on age, gender, family history, and Apolipoprotein E (APOE) genotype; Control group: lifetime risk estimates of AD based on the same risk factors excluding APOE genotype. Perceptions of personal risk (PPR) for AD were assessed six weeks after risk assessments. PPR were correlated with actual lifetime risk estimates (r = 0.501; p < 0.0001). After controlling for lifetime risks communicated to participants, age, and number of affected relatives, PPR scores among those with an epsilon4-positive test result (the test result associated with increased AD susceptibility) (adjusted mean: 3.4 (SD: 0.7)) were not different from the PPR scores in the Control group (adjusted mean: 3.4 (SD: 0.7) (F1,91= 1.98; p = 0.162). Again, controlling for lifetime risk estimates, age, and number of affected relatives, the PPR score of those receiving an epsilon4-negative test result was significantly lower (adjusted mean: 3.1 (SD: 0.8)) than those in the Control group (adjusted mean: 3.4 (SD: 0.7) (F1,95 = 6.23; p = 0.014). Perceptions of risk of developing AD are influenced by genetic test disclosure in those receiving epsilon4-negative, but not those receiving epsilon4-positive test results. Despite the reduced perceptions of risk in the former group, there was no evidence of false reassurance (i.e., perceiving risks as equal to or lower than population risks of AD), although this possibility should be assessed in other testing contexts.     

Bounding Analysis of Drinking Water Health Risks from a Spill of Hydraulic Fracturing Flowback Water

A bounding risk assessment is presented that evaluates possible human health risk from a hypothetical scenario involving a 10,000‐gallon release of flowback water from horizontal fracturing of Marcellus Shale. The water is assumed to be spilled on the ground, infiltrates into groundwater that is a source of drinking water, and an adult and child located downgradient drink the groundwater. Key uncertainties in estimating risk are given explicit quantitative treatment using Monte Carlo analysis. Chemicals that contribute significantly to estimated health risks are identified, as are key uncertainties and variables to which risk estimates are sensitive. The results show that hypothetical exposure via drinking water impacted by chemicals in Marcellus Shale flowback water, assumed to be spilled onto the ground surface, results in predicted bounds between 10⁻¹⁰ and 10⁻⁶ (for both adult and child receptors) for excess lifetime cancer risk. Cumulative hazard indices (HI_CUMULATIVE) resulting from these hypothetical exposures have predicted bounds (5th to 95th percentile) between 0.02 and 35 for assumed adult receptors and 0.1 and 146 for assumed child receptors. Predicted health risks are dominated by noncancer endpoints related to ingestion of barium and lithium in impacted groundwater. Hazard indices above unity are largely related to exposure to lithium. Salinity taste thresholds are likely to be exceeded before drinking water exposures result in adverse health effects. The findings provide focus for policy discussions concerning flowback water risk management. They also indicate ways to improve the ability to estimate health risks from drinking water impacted by a flowback water spill (i.e., reducing uncertainty).     

Cognitive Components of Risk Ratings

This study examined what lay people mean when they judge the "risk" of activities that involve the potential for accidental fatalities (e.g., hang gliding, living near a nuclear reactor). A sample of German and American students rated the "overall risk" of 14 such activities and provided 3 fatality estimates: the number of fatalities in an "average year," the individual yearly fatality probability (or odds), and the number of fatalities in a "disastrous accident." Subjects' fatality estimates were reasonably accurate and only moderately influenced by attitudes towards nuclear energy. Individual fatality probability correlated most highly with intuitive risk ratings. Disaster estimates correlated positively with risk ratings for those activities that had a low fatality probability and a relatively high disaster potential. Annual average fatality rates did not correlate with risk ratings at all. These findings were interpreted in terms of a two-dimensional cognitive structure. Subjective notions of risk were determined primarily by the personal chance of death; for some activities, "disaster potential" played a secondary role in shaping risk perception.     

Risk to Groundlings of Death Due to Airplane Accidents: A Risk Communication Tool

During the period 1975-85 in the United States the 70 year lifetime risk of dying from being hit by an airplane when the individual is on the ground was 4.2 per million people. In contrast to many other risks used for comparison purposes, risk to those on the ground from an airplane crash is not a function of our own skills; is not optional; provides no benefit to anyone involved; and is not an act of nature. As a risk comparison tool it also has the useful characteristics of being something about which we can agree that regulatory action, such as control of airplane use and traffic, is warranted; but that no significant change in personal behavior, such as living in the basement to protect against dying from a plane hitting the home, is commensurate with the extent of risk.     

Uncertainty in Cancer Risk Estimates

Several existing databases compiled by Gold et al.^(1–3) for carcinogenesis bioassays are examined to obtain estimates of the reproducibility of cancer rates across experiments, strains, and rodent species. A measure of carcinogenic potency is given by the TD₅₀ (daily dose that causes a tumor type in 50% of the exposed animals that otherwise would not develop the tumor in a standard lifetime). The lognormal distribution can be used to model the uncertainty of the estimates of potency (TD₅₀) and the ratio of TD₅₀'s between two species. For near-replicate bioassays, approximately 95% of the TD₅₀'s are estimated to be within a factor of 4 of the mean. Between strains, about 95% of the TD₅₀'s are estimated to be within a factor of 11 of their mean, and the pure genetic component of variability is accounted for by a factor of 6.8. Between rats and mice, about 95% of the TD₅₀'s are estimated to be within a factor of 32 of the mean, while between humans and experimental animals the factor is 110 for 20 chemicals reported by Allen et al.⁽⁴⁾ The common practice of basing cancer risk estimates on the most sensitive rodent species-strain-sex and using interspecies dose scaling based on body surface area appears to overestimate cancer rates for these 20 human carcinogens by about one order of magnitude on the average. Hence, for chemicals where the dose-response is nearly linear below experimental doses, cancer risk estimates based on animal data are not necessarily conservative and may range from a factor of 10 too low for human carcinogens up to a factor of 1000 too high for approximately 95% of the chemicals tested to date. These limits may need to be modified for specific chemicals where additional mechanistic or pharmacokinetic information may suggest alterations or where particularly sensitive subpopu-lations may be exposed. Supralinearity could lead to anticonservative estimates of cancer risk. Underestimating cancer risk by a specific factor has a much larger impact on the actual number of cancer cases than overestimates of smaller risks by the same factor. This paper does not address the uncertainties in high to low dose extrapolation. If the dose-response is sufficiently nonlinear at low doses to produce cancer risks near zero, then low-dose risk estimates based on linear extrapolation are likely to overestimate risk and the limits of uncertainty cannot be established.     

Enhancing the Characterization of Epistemic Uncertainties in PM2.5 Risk Analyses

The Environmental Benefits Mapping and Analysis Program (BenMAP) is a software tool developed by the U.S. Environmental Protection Agency (EPA) that is widely used inside and outside of EPA to produce quantitative estimates of public health risks from fine particulate matter (PM_2.5). This article discusses the purpose and appropriate role of a risk analysis tool to support risk management deliberations, and evaluates the functions of BenMAP in this context. It highlights the importance in quantitative risk analyses of characterization of epistemic uncertainty, or outright lack of knowledge, about the true risk relationships being quantified. This article describes and quantitatively illustrates sensitivities of PM_2.5 risk estimates to several key forms of epistemic uncertainty that pervade those calculations: the risk coefficient, shape of the risk function, and the relative toxicity of individual PM_2.5 constituents. It also summarizes findings from a review of U.S.‐based epidemiological evidence regarding the PM_2.5 risk coefficient for mortality from long‐term exposure. That review shows that the set of risk coefficients embedded in BenMAP substantially understates the range in the literature. We conclude that BenMAP would more usefully fulfill its role as a risk analysis support tool if its functions were extended to better enable and prompt its users to characterize the epistemic uncertainties in their risk calculations. This requires expanded automatic sensitivity analysis functions and more recognition of the full range of uncertainty in risk coefficients.     

One Agency's Use of Risk Assessment and Risk Communication1

Few organizations have the courage to evaluate their own use of risk assessment (identifying hazards and estimating their probability and magnitude) and risk communication (interacting with internal and external stakeholder groups about risks). The USDA Animal and Plant Health Inspection Service (APHIS) wants to enhance its overall risk analysis process for managing a wide range of risks to animals, plants, and human health. We gathered survey data for a baseline of APHIS professionals’ understanding and use of risk assessment and risk communication. APHIS professionals spend a surprisingly large share of their time communicating about risks. They perceive that risk estimates influence decisions, but that risk estimates should have more influence. Respondents reported little opposition to APHIS risk management decisions, and little use of channels such as USDA Extension Service for disseminating risk messages. Substantial variance across responses is explained mostly by differences in the roles of the 11 work units (now 10) within the agency. Location also contributes to the variance. Demographic variables seem less important.     

Communicating Low‐Probability High‐Consequence Risk,Uncertainty and Expert Confidence: Induced Seismicity of Deep Geothermal Energy and Shale Gas

Subsurface energy activities entail the risk of induced seismicity including low‐probability high‐consequence (LPHC) events. For designing respective risk communication, the scientific literature lacks empirical evidence of how the public reacts to different written risk communication formats about such LPHC events and to related uncertainty or expert confidence. This study presents findings from an online experiment (N = 590) that empirically tested the public's responses to risk communication about induced seismicity and to different technology frames, namely deep geothermal energy (DGE) and shale gas (between‐subject design). Three incrementally different formats of written risk communication were tested: (i) qualitative, (ii) qualitative and quantitative, and (iii) qualitative and quantitative with risk comparison. Respondents found the latter two the easiest to understand, the most exact, and liked them the most. Adding uncertainty and expert confidence statements made the risk communication less clear, less easy to understand and increased concern. Above all, the technology for which risks are communicated and its acceptance mattered strongly: respondents in the shale gas condition found the identical risk communication less trustworthy and more concerning than in the DGE conditions. They also liked the risk communication overall less. For practitioners in DGE or shale gas projects, the study shows that the public would appreciate efforts in describing LPHC risks with numbers and optionally risk comparisons. However, there seems to be a trade‐off between aiming for transparency by disclosing uncertainty and limited expert confidence, and thereby decreasing clarity and increasing concern in the view of the public.     

Risk Comparisons, Conflict, and Risk Acceptability Claims

Despite many claims for and against the use of risk comparisons in risk communication, few empirical studies have explored their effect. Even fewer have examined the public's relative preferences among different kinds of risk comparisons. Two studies, published in this journal in 1990 and 2003, used seven measures of "acceptability" to examine public reaction to 14 examples of risk comparisons, as used by a hypothetical factory manager to explain risks of his ethylene oxide plant. This study examined the effect on preferences of scenarios involving low or high conflict between the factory manager and residents of the hypothetical town (as had the 2003 study), and inclusion of a claim that the comparison demonstrated the risks' acceptability. It also tested the Finucane et al. (2000) affect hypothesis that information emphasizing low risks-as in these risk comparisons-would raise benefits estimates without changing risk estimates. Using similar but revised scenarios, risk comparison examples (10 instead of 14), and evaluation measures, an opportunity sample of 303 New Jersey residents rated the comparisons, and the risks and benefits of the factory. On average, all comparisons received positive ratings on all evaluation measures in all conditions. Direct and indirect measures showed that the conflict manipulation worked; overall, No-Conflict and Conflict scenarios evoked scores that were not significantly different. The attachment to each risk comparison of a risk acceptability claim ("So our factory's risks should be acceptable to you.") did not worsen ratings relative to conditions lacking this claim. Readers who did or did not see this claim were equally likely to infer an attempt to persuade them to accept the risk from the comparison. As in the 2003 article, there was great individual variability in inferred rankings of the risk comparisons. However, exposure to the risk comparisons did not reduce risk estimates significantly (while raising benefit estimates), and Conflict-Claim respondents found the risk of the hypothetical factory less acceptable than No-Conflict respondents. Results suggest that neither risk comparisons nor risk acceptability claims are automatically anathema to audiences, but they may have tiny or unintended effects on audience judgments about risky situations.     

Risk Criteria for Nuclear Power Plants: A Pragmatic Proposal1

Criteria are proposed for both an acceptable upper bound of nuclear power plant risk and a lower bound as a design target. Recognizing that the public risk associated with a power plant can be estimated only by probabilistic analysis of the design features, the spread between the lower design target and the upper bound provides a margin for uncertainty in th probabilistic estimate. The combination of a low probabilistic design target and this margin provides a reasonable expectation that the overall performance will be in the domain of an acceptable risk level. Because the exposure to potential risk is chiefly in the locality of the nuclear station, it is also proposed that compensatory benefits should be provided locally and that these be included as a cost of operation. It is suggested that the upper bound be set at a risk level equivalent to those risks of routine living which are normally accepted, i.e., about 10^-4 deaths per year per person (100 deaths/yr/million). The proposed lower design target is 10^-8 (0.1 deaths/yr/million), about one-hundredth of the minimal risk from the natural hazards all people are exposed to.     

Flash Flood Risks and Warning Decisions: A Mental Models Study of Forecasters,Public Officials,and Media Broadcasters in Boulder,Colorado

Timely warning communication and decision making are critical for reducing harm from flash flooding. To help understand and improve extreme weather risk communication and management, this study uses a mental models research approach to investigate the flash flood warning system and its risk decision context. Data were collected in the Boulder, Colorado area from mental models interviews with forecasters, public officials, and media broadcasters, who each make important interacting decisions in the warning system, and from a group modeling session with forecasters. Analysis of the data informed development of a decision‐focused model of the flash flood warning system that integrates the professionals’ perspectives. Comparative analysis of individual and group data with this model characterizes how these professionals conceptualize flash flood risks and associated uncertainty; create and disseminate flash flood warning information; and perceive how warning information is (and should be) used in their own and others’ decisions. The analysis indicates that warning system functioning would benefit from professionals developing a clearer, shared understanding of flash flood risks and the warning system, across their areas of expertise and job roles. Given the challenges in risk communication and decision making for complex, rapidly evolving hazards such as flash floods, another priority is development of improved warning content to help members of the public protect themselves when needed. Also important is professional communication with members of the public about allocation of responsibilities for managing flash flood risks, as well as improved system‐wide management of uncertainty in decisions.