Risk-based standards: integrating top–down and bottom–up approaches

In response to rapidly changing threats posed to increasingly complex socio-technical systems, many in the government and private sector have called for protection through risk-based standards. However, given the nature of these dynamic and uncertain threats, traditional risk assessment techniques may not be sufficient. Instead, there is a critical need for an integrated approach in which decision analytic techniques are used to assess evidence-based data with the values and preferences of decision makers. We point to three examples in the fields of nuclear power regulation, nanotechnology, and cybersecurity, where risk-based approaches (bottom–up) have been combined with decision analysis (top–down) to guide decision makers toward risk management policies that manifest both the best available evidence and the plurality of values within a society.     

Pragmatic Approaches for Water Management Under Climate Change Uncertainty1

Stakhiv, Eugene Z., 2011. Pragmatic Approaches for Water Management Under Climate Change Uncertainty. Journal of the American Water Resources Association (JAWRA) 47(6):1183–1196. DOI: 10.1111/j.1752‐1688.2011.00589.x Abstract: Water resources management is in a difficult transition phase, trying to accommodate large uncertainties associated with climate change while struggling to implement a difficult set of principles and institutional changes associated with integrated water resources management. Water management is the principal medium through which projected impacts of global warming will be felt and ameliorated. Many standard hydrological practices, based on assumptions of a stationary climate, can be extended to accommodate numerous aspects of climate uncertainty. Classical engineering risk and reliability strategies developed by the water management profession to cope with contemporary climate uncertainties can also be effectively employed during this transition period, while a new family of hydrological tools and better climate change models are developed. An expansion of the concept of “robust decision making,” coupled with existing analytical tools and techniques, is the basis for a new approach advocated for planning and designing water resources infrastructure under climate uncertainty. Ultimately, it is not the tools and methods that need to be revamped as much as the suite of decision rules and evaluation principles used for project justification. They need to be aligned to be more compatible with the implications of a highly uncertain future climate trajectory, so that the hydrologic effects of that uncertainty are correctly reflected in the design of water infrastructure.     

Uncertainty characterization approaches for risk assessment of DBPs in drinking water: A review

The management of risk from disinfection by-products (DBPs) in drinking water has become a critical issue over the last three decades. The areas of concern for risk management studies include (i) human health risk from DBPs, (ii) disinfection performance, (iii) technical feasibility (maintenance, management and operation) of treatment and disinfection approaches, and (iv) cost. Human health risk assessment is typically considered to be the most important phase of the risk-based decision-making or risk management studies. The factors associated with health risk assessment and other attributes are generally prone to considerable uncertainty. Probabilistic and non-probabilistic approaches have both been employed to characterize uncertainties associated with risk assessment. The probabilistic approaches include sampling-based methods (typically Monte Carlo simulation and stratified sampling) and asymptotic (approximate) reliability analysis (first- and second-order reliability methods). Non-probabilistic approaches include interval analysis, fuzzy set theory and possibility theory. However, it is generally accepted that no single method is suitable for the entire spectrum of problems encountered in uncertainty analyses for risk assessment. Each method has its own set of advantages and limitations. In this paper, the feasibility and limitations of different uncertainty analysis approaches are outlined for risk management studies of drinking water supply systems. The findings assist in the selection of suitable approaches for uncertainty analysis in risk management studies associated with DBPs and human health risk.     

Increased wind erosion from forest wildfire: implications for contaminant-related risks

Assessments of contaminant-related human and ecological risk require estimation of transport rates, but few data exist on wind-driven transport rates in nonagricultural systems, particularly in response to ecosystem disturbances such as forest wildfire and also relative to water-driven transport. The Cerro Grande wildfire in May of 2000 burned across ponderosa pine (Pinus ponderosa Douglas ex P.&C. Lawson var. scopulorum Englem.) forest within Los Alamos National Laboratory in northern New Mexico, where contaminant transport and associated post-fire inhalation risks are of concern. In response, the objectives of this study were to measure and compare wind-driven horizontal and vertical dust fluxes, metrics of transport related to wind erosion, for 3 yr for sites differentially affected by the Cerro Grande wildfire: unburned, moderately burned (fire mostly confined to ground vegetation), and severely burned (crown fire). Wind-driven dust flux was significantly greater in both types of burned areas relative to unburned areas, by more than one order of magnitude initially and by two to three times 1 yr after the fire. Unexpectedly, the elevated dust fluxes did not decrease during the second and third years in burned areas, apparently because ongoing drought delayed post-fire recovery. Our estimates enable assessment of amplification in contaminant-related risks following a major type of disturbance-wildfire, which is expected to increase in intensity and frequency due to climate change. More generally, our results highlight the importance of considering wind- as well as water-driven transport and erosion, particularly following disturbance, for ecosystem biogeochemistry in general and human and ecological risk assessment in particular.     

Analysis of the prescribed burning practice in the pine forest of northwestern Portugal

The ignition of low-intensity fires in the dormant season in the pine stands of north-western Portugal seeks to reduce the existing fuel hazard without compromising site quality. The purpose of this study is to characterise this practice and assess its effectiveness, based on information resulting from the normal monitoring process at the management level, and using operational guidelines, fire behaviour models and a newly developed method to classify prescribed fire severity. Although the region's humid climate strongly constrains the activity of prescribed fire, 87% of the fires analysed were undertaken under acceptable meteorological and fuel moisture conditions. In fact, most operations achieved satisfactory results. On average, prescribed fire reduces by 96% the potential intensity of a wildfire occurring under extreme weather conditions, but 36% of the treated sites would still require heavy fire fighting resources to suppress such fire, and 17% would still carry it in the tree canopy. Only 10% of the prescribed burns have an excessive impact on trees or the forest floor, while 89% (normal fire weather) or 59% (extreme fire weather) comply with both ecological integrity maintenance and wildfire protection needs. Improved planning and monitoring procedures are recommended in order to overcome the current deficiencies.     

Evaluating Post-Fire Forest Resilience Using GIS and Multi-Criteria Analysis: An Example from Cape Sounion National Park,Greece

Forest fires are one of the major causes of ecological disturbance in the mediterranean climate ecosystems of the world. Despite the fact that a lot of resources have been invested in fire prevention and suppression, the number of fires occurring in the Mediterranean Basin in the recent decades has continued to markedly increase. The understanding of the relationship between landscape and fire lies, among others, in the identification of the system’s post-fire resilience. In our study, ecological and landscape data are integrated with decision-support techniques in a Geographic Information Systems (GIS) framework to evaluate the risk of losing post-fire resilience in Pinus halepensis forests, using Cape Sounion National Park, Central Greece, as a pilot case. The multi-criteria decision support approach has been used to synthesize both bio-indicators (woody cover, pine density, legume cover and relative species richness and annual colonizers) and geo-indicators (fire history, parent material, and slope inclination) in order to rank the landscape components. Judgments related to the significance of each factor were incorporated within the weights coefficients and then integrated into the multicriteria rule to map the risk index. Sensitivity analysis was very critical for assessing the contribution of each factor and the sensitivity to subjective weight judgments to the final output. The results of this study include a final ranking map of the risk of losing resilience, which is very useful in identifying the “risk hotspots”, where post-fire management measures should be applied in priority.     

Situating Hazard Vulnerability: People’s Negotiations with Wildfire Environments in the U.S. Southwest

This article is based on a multimethod study designed to clarify influences on wildfire hazard vulnerability in Arizona’s White Mountains, USA. Findings reveal that multiple factors operating across scales generate socially unequal wildfire risks. At the household scale, conflicting environmental values, reliance on fire insurance and firefighting institutions, a lack of place dependency, and social vulnerability (e.g., a lack of financial, physical, and/or legal capacity to reduce risks) were found to be important influences on wildfire risk. At the regional-scale, the shift from a resource extraction to environmental amenity-based economy has transformed ecological communities, produced unequal social distributions of risks and resources, and shaped people’s social and environmental interactions in everyday life. While working-class locals are more socially vulnerable than amenity migrants to wildfire hazards, they have also been more active in attempting to reduce risks in the aftermath of the disastrous 2002 Rodeo-Chediski fire. Social tensions between locals and amenity migrants temporarily dissolved immediately following the disaster, only to be exacerbated by the heightened perception of risk and the differential commitment to hazard mitigation displayed by these groups over a 2-year study period. Findings suggest that to enhance wildfire safety, environmental managers should acknowledge the environmental benefits associated with hazardous landscapes, the incentives created by risk management programs, and the specific constraints to action for relevant social groups in changing human-environmental context.     

Modeling postfire conifer mortality for long-range planning

A model is presented for predicting mortality of conifers after wildfire. The model requires stand data inputs and is linked with a mathematical fire behavior model that calculates fireline intensity. Fraction of crown volume killed is calculated for each species in a stand based on mensurational data. Duration of lethal heat at the base of trees is calculated from fuel consumption and burning time values. Fraction of crown volume killed and the ratio of critical time for cambial kill to duration of lethal heat are independent variables in a function that calculates probability of mortality. The model produces reasonable estimates of stand mortality for fire and site characteristics found in the northern Rocky Mountains, USA. It has a broad resolution appropriate for use in fire management planning and has potential applications for coniferous forests throughout the United States.     

‘Learning by doing’: adaptive planning as a strategy to address uncertainty in planning

Adaptive management, an established method in natural resource and ecosystem management, has not been widely applied to landscape planning due to the lack of an operational method that addresses the role of uncertainty and standardized monitoring protocols and methods. A review of adaptive management literature and practices reveals several key concepts and principles for adaptive planning: (1) management actions are best understood and practiced as experiments; (2) several plans/experiments can be implemented simultaneously; (3) monitoring of management actions are key; and (4) adaptive management can be understood as ‘learning by doing’. The paper identifies various uncertainties in landscape planning as the major obstacles for the adoption of an adaptive approach. To address the uncertainty in landscape planning, an adaptive planning method is proposed where monitoring plays an integral role to reduce uncertainty. The proposed method is then applied to a conceptual test in water resource planning addressing abiotic-biotic-cultural resources. To operationalize adaptive planning, it is argued that professionals, stakeholders and researchers need to function in a genuinely transdisciplinary mode where all contribute to, and benefit from, decision making and the continuous generation of new knowledge.     

Info-Gap Decision Theory for Assessing the Management of Catchments for Timber Production and Urban Water Supply

While previous studies have examined how forest management is influenced by the risk of fire, they rely on probabilistic estimates of the occurrence and impacts of fire. However, nonprobabilistic approaches are required for assessing the importance of fire risk when data are poor but risks are appreciable. We explore impacts of fire risk on forest management using as a case study a water catchment in the Australian Capital Territory (ACT) (southeastern Australia). In this forested area, urban water supply and timber yields from exotic plantations are potential joint but also competing land uses. Our analyses were stimulated by extensive wildfires in early 2003 that burned much of the existing exotic pine plantation estate in the water catchment and the resulting need to explore the relative economic benefits of revegetating the catchment with exotic plantations or native vegetation. The current mean fire interval in the ACT is approximately 40 years, making the establishment of a pine plantation economically marginal at a 4% discount rate. However, the relative impact on water yield of revegetation with native species and pines is very uncertain, as is the risk of fire under climate change. We use info-gap decision theory to account for these nonprobabilistic sources of uncertainty, demonstrating that the decision that is most robust to uncertainty is highly sensitive to the cost of native revegetation. If costs of native revegetation are sufficiently small, this option is more robust to uncertainty than revegetation with a commercial pine plantation.     

Land Resources Allocation Strategies in an Urban Area Involving Uncertainty: A Case Study of Suzhou,in the Yangtze River Delta of China

A large number of mathematical models have been developed to support land resource allocation decisions and land management needs; however, few of them can address various uncertainties that exist in relation to many factors presented in such decisions (e.g., land resource availabilities, land demands, land-use patterns, and social demands, as well as ecological requirements). In this study, a multi-objective interval-stochastic land resource allocation model (MOISLAM) was developed for tackling uncertainty that presents as discrete intervals and/or probability distributions. The developed model improves upon the existing multi-objective programming and inexact optimization approaches. The MOISLAM not only considers economic factors, but also involves food security and eco-environmental constraints; it can, therefore, effectively reflect various interrelations among different aspects in a land resource management system. Moreover, the model can also help examine the reliability of satisfying (or the risk of violating) system constraints under uncertainty. In this study, the MOISLAM was applied to a real case of long-term urban land resource allocation planning in Suzhou, in the Yangtze River Delta of China. Interval solutions associated with different risk levels of constraint violation were obtained. The results are considered useful for generating a range of decision alternatives under various system conditions, and thus helping decision makers to identify a desirable land resource allocation strategy under uncertainty.     

A WATERSHED-LEVEL ECOLOGICAL RISK ASSESSMENT METHODOLOGY1

ABSTRACT: We present an ecological risk assessment methodology at the watershed level for freshwater ecosystems. The major component is a pollutant transport and fate model (a modified EUTROMOD) with an integrated uncertainty analysis utilizing a two-phase Monte Carlo procedure. The uncertainty analysis methodology distinguishes between knowledge uncertainty and stochastic variability. The model assesses the ecological risk of lentic (lake) ecosystems in response to the stress of excess phosphorus resulting in eutrophication. The methodology and model were tested on the Wister Lake watershed in Oklahoma with the lake and its trophic state as the endpoint for ecological risk assessment. A geographic information system was used to store, manage, and manipulate spatially referenced data for model input.     

Applying Ecological Risk Principles to Watershed Assessment and Management

Considerable progress in addressing point source (end of pipe) pollution problems has been made, but it is now recognized that further substantial environmental improvements depend on controlling nonpoint source pollution. A watershed approach is being used more frequently to address these problems because traditional regulatory approaches do not focus on nonpoint sources. The watershed approach is organized around the guiding principles of partnerships, geographic focus, and management based on sound science and data. This helps to focus efforts on the highest priority problems within hydrologically-defined geographic areas. Ecological risk assessment is a process to collect, organize, analyze, and present scientific information to improve decision making. The U.S. Environmental Protection Agency (EPA) sponsored three watershed assessments and found that integrating the watershed approach with ecological risk assessment increases the use of environmental monitoring and assessment data in decision making. This paper describes the basics of the watershed approach, the ecological risk assessment process, and how these two frameworks can be integrated. The three major principles of watershed ecological risk assessment found to be most useful for increasing the use of science in decision making are (1) using assessment endpoints and conceptual models, (2) holding regular interactions between scientists and managers, and (3) developing a focus for multiple stressor analysis. Examples are provided illustrating how these principles were implemented in these assessments.     

Conflict on the Coast: Using Geographic Information Systems to Map Potential Environmental Disputes in Matagorda Bay,Texas

The sustainable management of coastal natural resources inevitably involves identifying stakeholder conflicts and developing planning processes that prevent these conflicts from becoming intractable disputes. This study links environmental conflict to specific areas within a large ecological system. Specifically, we use Geographic Information Systems (GIS) to map potentially competing stakeholder values associated with establishing protected areas in Matagorda Bay, Texas. By overlaying multiple values associated with a range of stakeholders across space, we are able to identify hotspots of potential conflict as well as areas of opportunity for maximizing joint gains. Mapping stakeholder conflict is an approach to proactively locate potential controversy in response to a specific environmental management proposal and guide decision makers in crafting planning processes that mitigate the possibility of intractable disputes and facilitate the implementation of sustainable coastal policies. Results indicate that under different management scenarios, protected area proposals will generate more conflict in specific areas. Most notably, regulated uses would produce the greatest degree of conflict on or near shore, particularly at the mouth of the Colorado River. Additionally, of all the management scenarios evaluated, the prohibition of coastal structural development would generate the overall highest level of conflict within the Bay. Based on the results, we discuss the policy implications for environmental managers and provide guidance for future research on location-based conflict management within the coastal margin.     

A response surface methodology to address uncertainties in cap rock failure assessment for CO2 geological storage in deep aquifers

Cap rock failure assessment, either tensile fracturing or shear slip reactivation of pre-existing fault, is a key issue for preventing CO₂ leakage from deep aquifer reservoirs up to the surface. For an appropriate use in risk management, the uncertainties associated with such studies should be investigated. Nevertheless, uncertainty analysis requires multiple simulations and a direct use of conventional numerical approaches might be too computer time consuming. An alternative is to use conventional analytical models, but their assumptions appear to be too conservative. An intermediate approach is then proposed based on the response surface methodology, consisting in estimating the effective stress state after CO₂ injection as a linear combination of the most influential site properties based on a limited number of numerical simulations. The decision maker is provided with three levels of information: (1) the identification of the most important site properties; (2) an analytical model for a quick assessment of the maximal sustainable overpressure and (3) a simplified model to be used in a computationally intensive uncertainty analysis framework. This generic methodology is illustrated with the Paris Basin case using a large-scale hydromechanical model to assess cap rock failure in the injector zone.     

Fuel Reduction Management Practices in Riparian Areas of the Western USA

Two decades of uncharacteristically severe wildfires have caused government and private land managers to actively reduce hazardous fuels to lessen wildfire severity in western forests, including riparian areas. Because riparian fuel treatments are a fairly new management strategy, we set out to document their frequency and extent on federal lands in the western U.S. Seventy-four USDA Forest Service Fire Management Officers (FMOs) in 11 states were interviewed to collect information on the number and characteristics of riparian fuel reduction treatments in their management district. Just under half of the FMOs surveyed (43%) indicated that they were conducting fuel reduction treatments in riparian areas. The primary management objective listed for these projects was either fuel reduction (81%) or ecological restoration and habitat improvement (41%), though multiple management goals were common (56%). Most projects were of small extent (93% < 300 acres), occurred in the wildland-urban interface (75%), and were conducted in ways to minimize negative impacts on species and habitats. The results of this survey suggest that managers are proceeding cautiously with treatments. To facilitate project planning and implementation, managers recommended early coordination with resource specialists, such as hydrologists and fish and wildlife biologists. Well-designed monitoring of the consequences of riparian fuel treatments on fuel loads, fire risk, and ecological effects is needed to provide a scientifically-defensible basis for the continued and growing implementation of these treatments.     

Using expert judgments to understand spatial patterns of forest-based camping: a values-at-risk application

Fire management agencies in Canada are mandated with protecting multiple forest values from wildfire. Deciding where to reduce fire hazard and how to allocate resources and fire suppression efforts requires an understanding of the values-at-risk from wildfire. The protection of recreation infrastructure is often assumed to provide adequate protection of recreation values. We use an expert judgment approach to provide a spatial distribution of recreation values-at-risk in the forested eastern slopes of the Rocky Mountain region of Alberta, Canada. Data were collected in 2004 from 11 land managers responsible for public lands management and wildfire prevention in the region. Expert assessments showed that recreation values were not confined to areas with publicly funded infrastructure. Exploratory spatial analysis of the ratings identified hotspots and cold spots of recreation activity. Maps resulting from these efforts will provide guidance to fire managers in the prioritization of fire management activities.     

A Streamflow Forecasting Framework using Multiple Climate and Hydrological Models1

Abstract: Water resources planning and management efficacy is subject to capturing inherent uncertainties stemming from climatic and hydrological inputs and models. Streamflow forecasts, critical in reservoir operation and water allocation decision making, fundamentally contain uncertainties arising from assumed initial conditions, model structure, and modeled processes. Accounting for these propagating uncertainties remains a formidable challenge. Recent enhancements in climate forecasting skill and hydrological modeling serve as an impetus for further pursuing models and model combinations capable of delivering improved streamflow forecasts. However, little consideration has been given to methodologies that include coupling both multiple climate and multiple hydrological models, increasing the pool of streamflow forecast ensemble members and accounting for cumulative sources of uncertainty. The framework presented here proposes integration and offline coupling of global climate models (GCMs), multiple regional climate models, and numerous water balance models to improve streamflow forecasting through generation of ensemble forecasts. For demonstration purposes, the framework is imposed on the Jaguaribe basin in northeastern Brazil for a hindcast of 1974‐1996 monthly streamflow. The ECHAM 4.5 and the NCEP/MRF9 GCMs and regional models, including dynamical and statistical models, are integrated with the ABCD and Soil Moisture Accounting Procedure water balance models. Precipitation hindcasts from the GCMs are downscaled via the regional models and fed into the water balance models, producing streamflow hindcasts. Multi‐model ensemble combination techniques include pooling, linear regression weighting, and a kernel density estimator to evaluate streamflow hindcasts; the latter technique exhibits superior skill compared with any single coupled model ensemble hindcast.