Handling Uncertainty in Models of Seismic and Postseismic Hazards: Toward Robust Methods and Resilient Societies.

Earthquakes, tsunamis, and landslides take a devastating toll on human lives, critical infrastructure, and ecosystems. Harnessing the predictive capacities of hazard models is key to transitioning from reactive approaches to disaster management toward building resilient societies, yet the knowledge that these models produce involves multiple uncertainties. The failure to properly account for these uncertainties has at times had important implications, from the flawed safety measures at the Fukushima power plant, to the reliance on short-term earthquake prediction models (reportedly at the expense of mitigation efforts) in modern China. This article provides an overview of methods for handling uncertainty in probabilistic seismic hazard assessment, tsunami hazard analysis, and debris flow modeling, considering best practices and areas for improvement. It covers sensitivity analysis, structured approaches to expert elicitation, methods for characterizing structural uncertainty (e.g., ensembles and logic trees), and the value of formal decision-analytic frameworks even in situations of deep uncertainty.

The application of frameworks for measuring social vulnerability and resilience to geophysical hazards within developing countries: A systematic review and narrative synthesis.

Quantifying and mapping resilience and social vulnerability is a widely used technique to support risk management, with recent years seeing a proliferation of applications across the Global South. To synthesise this emerging literature, we conducted a systematic review of applications of social vulnerability and resilience frameworks in Lower and Middle Income Countries (LMICs) using the PRISMA methodology. 2152 papers were extracted from 15 databases and then screened according to our pre-defined criteria, leaving 68 studies for full text analysis. Our analysis revealed that: (1) Most studies consider vulnerability or resilience to be generic properties of social systems; (2) Few papers measured vulnerability or resilience in a way that tests whether they are relatively stable or dynamic features of social systems; (3) Many applications rely on stock applications of existing frameworks, with little adaptation to specific cultural, societal or economic contexts; (4) There is a lack of systematic validation; (5) More hypothesis-driven studies (as opposed to descriptive mapping exercises) are required in order to develop a better understanding of the mechanisms through which vulnerability and resilience shape the capacity to prepare for, respond and recover from disasters.

Systems approaches for localising the SDGs: co-production of place-based case studies.

BACKGROUND: Localisation is a pervasive challenge in achieving sustainable development. Contextual particularities may render generalized strategies to achieve the Sustainable Development Goals (SDGs) unfeasible, impractical, or ineffective. Furthermore, many localities are resource- and data-poor, limiting applicability of the global SDG indicator framework. Tools to enable local actors to make sense of complex problems, communicate this understanding, and act accordingly hold promise in their ability to improve results. AIM: Systems approaches can help characterise local causal systems, identify useful leverage points, and foster participation needed to localise and catalyse development action. Critically, such efforts must be deeply rooted in place, involving local actors in mapping decision-processes and causation within local physical, social and policy environments. Given that each place has a unique geographical or spatial extent and therein lies its unique characters and problems, we term these activities "placially explicit." We describe and reflect on a process used to develop placially explicit, systems-based (PESB) case studies on issues that intersect with and impact urban health and wellbeing, addressing the perspectives of various actors to produce place-based models and insights that are useful for SDG localisation. METHODS: Seven case studies were co-produced by one or more Partners with place-based knowledge of the case study issue and a Systems Thinker. In each case, joint delineation of an appropriate framing was followed by iterative dialogue cycles to uncover key contextual factors, with attention to institutional and societal structures and paradigms and the motivations and constraints of other actors. Casual loop diagrams (CLDs) were iteratively developed to capture complex narratives in a simple visual way. RESULTS: Case study development facilitated transfer of local knowledge and development of systems thinking capacity. Partners reported new insights, including a shifting of problem frames and corresponding solution spaces to higher systems levels. Such changes led partners to re-evaluate their roles and goals, and thence to new actions and strategies. CLD-based narratives also proved useful in ongoing communications. CONCLUSION: Co-production of PESB case studies are a useful component of transdisciplinary toolsets for local SDG implementation, building the capacity of local actors to explore complex problems, identify new solutions and indicators, and understand the systemic linkages inherent in SDG actions across sectors and scales.

Null Hypothesis Testing ≠ Scientific Inference: A Critique of the Shaky Premise at the Heart of the Science and Values Debate, and a Defense of Value-Neutral Risk Assessment.

Many philosophers and statisticians argue that risk assessors are morally obligated to evaluate the probabilities and consequences of methodological error, and to base their decisions of whether to adopt a given parameter value, model, or hypothesis on those considerations. This argument is couched within the rubric of null hypothesis testing, which I suggest is a poor descriptive and normative model for risk assessment. Risk regulation is not primarily concerned with evaluating the probability of data conditional upon the null hypothesis, but rather with measuring risks, estimating the consequences of available courses of action and inaction, formally characterizing uncertainty, and deciding what to do based upon explicit values and decision criteria. In turn, I defend an ideal of value-neutrality, whereby the core inferential tasks of risk assessment-such as weighing evidence, estimating parameters, and model selection-should be guided by the aim of correspondence to reality. This is not to say that value judgments be damned, but rather that they should be accounted for within a structured approach to decision analysis, rather than embedded within risk assessment in an informal manner.

Characterising bias in regulatory risk and decision analysis: An analysis of heuristics applied in health technology appraisal, chemicals regulation, and climate change governance.

In many environmental and public health domains, heuristic methods of risk and decision analysis must be relied upon, either because problem structures are ambiguous, reliable data is lacking, or decisions are urgent. This introduces an additional source of uncertainty beyond model and measurement error - uncertainty stemming from relying on inexact inference rules. Here we identify and analyse heuristics used to prioritise risk objects, to discriminate between signal and noise, to weight evidence, to construct models, to extrapolate beyond datasets, and to make policy. Some of these heuristics are based on causal generalisations, yet can misfire when these relationships are presumed rather than tested (e.g. surrogates in clinical trials). Others are conventions designed to confer stability to decision analysis, yet which may introduce serious error when applied ritualistically (e.g. significance testing). Some heuristics can be traced back to formal justifications, but only subject to strong assumptions that are often violated in practical applications. Heuristic decision rules (e.g. feasibility rules) in principle act as surrogates for utility maximisation or distributional concerns, yet in practice may neglect costs and benefits, be based on arbitrary thresholds, and be prone to gaming. We highlight the problem of rule-entrenchment, where analytical choices that are in principle contestable are arbitrarily fixed in practice, masking uncertainty and potentially introducing bias. Strategies for making risk and decision analysis more rigorous include: formalising the assumptions and scope conditions under which heuristics should be applied; testing rather than presuming their underlying empirical or theoretical justifications; using sensitivity analysis, simulations, multiple bias analysis, and deductive systems of inference (e.g. directed acyclic graphs) to characterise rule uncertainty and refine heuristics; adopting "recovery schemes" to correct for known biases; and basing decision rules on clearly articulated values and evidence, rather than convention.

Heuristics structure and pervade formal risk assessment.

Lay perceptions of risk appear rooted more in heuristics than in reason. A major concern of the risk regulation literature is that such "error-strewn" perceptions may be replicated in policy, as governments respond to the (mis)fears of the citizenry. This has led many to advocate a relatively technocratic approach to regulating risk, characterized by high reliance on formal risk and cost-benefit analysis. However, through two studies of chemicals regulation, we show that the formal assessment of risk is pervaded by its own set of heuristics. These include rules to categorize potential threats, define what constitutes valid data, guide causal inference, and to select and apply formal models. Some of these heuristics lay claim to theoretical or empirical justifications, others are more back-of-the-envelope calculations, while still more purport not to reflect some truth but simply to constrain discretion or perform a desk-clearing function. These heuristics can be understood as a way of authenticating or formalizing risk assessment as a scientific practice, representing a series of rules for bounding problems, collecting data, and interpreting evidence (a methodology). Heuristics are indispensable elements of induction. And so they are not problematic per se, but they can become so when treated as laws rather than as contingent and provisional rules. Pitfalls include the potential for systematic error, masking uncertainties, strategic manipulation, and entrenchment. Our central claim is that by studying the rules of risk assessment qua rules, we develop a novel representation of the methods, conventions, and biases of the prior art.

Understanding the mismatch between the demands of risk assessment and practice of scientists--the case of Deca-BDE.

This review describes how a mismatch between the knowledge produced by scientists and the evidence demanded by regulators has emerged, and how society has struggled to find definitive answers to questions of safety, for an important flame retardant chemical in current use - Deca-BDE. This has involved two key disciplines: analytical chemistry and toxicology. Within the chemistry, a lack of standardized methodologies among scientists has resulted in a persistent yet largely undeclared failure to replicate results within the discipline. Within the toxicology, the quest for innovative, curiosity-driven research by university scientists in preference to using validated standard protocols, designed to promote consistency within the risk assessment process, has prompted questions about the credibility and relevance of scientific findings. Yet scientific laboratories have compelling reasons to do things the way they do in the cause of producing new knowledge, pointing to a sustained gap between the aims and practices of research scientists and those of risk management. A more rigorous scientific process that treats different elements of input data as discrete pieces of evidence is needed to ensure that science rather than politics will always define chemical safety.

What can water utilities do to improve risk management within their business functions? An improved tool and application of process benchmarking.

We present a model for benchmarking risk analysis and risk based decision making practice within organisations. It draws on behavioural and normative risk research, the principles of capability maturity modelling and our empirical observations. It codifies the processes of risk analysis and risk based decision making within a framework that distinguishes between different levels of maturity. Application of the model is detailed within the selected business functions of a water and wastewater utility. Observed risk analysis and risk based decision making practices are discussed, together with their maturity of implementation. The findings provide academics, utility professionals, and regulators a deeper understanding of the practical and theoretical underpinnings of risk management, and how distinctions can be made between organisational capabilities in this essential business process.

The long-term environmental behaviour of strontium and barium released from former mine workings in the granites of the Sunart region of Scotland, UK.

The concentrations of strontium and barium have been measured in water, sediment and the shells of mussels (Mytilus edulis) from a river system in the Sunart region of Scotland, UK. The aim was to establish the fate and mobility of these elements, which are slowly being released from old mine workings on the Strontian granites. Enhanced strontium (1500-2000 microg l(-1) and 250-290 microg l(-1)) and barium concentrations (316 microg l(-1) and 83 microg l(-1)) were found in the waters originating from the two mine drains studied. Both element were also found at significant levels in the river sediments taken from the vicinity of each drainage site (Sr: 225 microg g(-1) and 120-125 microg g(-1); Ba: 1380 microg g(-1) and 126-170 microg g(-1)). The data suggests that the sediments are acting as a reservoir for these group II cations from where they become distributed throughout the river system. Strontium is found to be incorporated into the shells (3.16-3.46 microg g(-1)) and pearls (3.57 microg g(-1)) of the blue mussel, located at the estuarine margin some 10 km downstream, at values close to the maximum expected (3.3% by weight of the calcium content). The study presents a view of the fate of barium and strontium in a river system over a prolonged period of time. As such it provides valuable information for studies that seek to model the impact of the accidental release of barium and strontium (including the important radionuclide 90Sr) into the environment.