Uncertain Future Conditions Research Articles

Optimal soaring via Hamilton-Jacobi-Bellman equations

Competition glider flying is a game of stochastic optimization, in which mathematics and quantitative strategies have historically played an important role. We address the problem of uncertain future atmospheric conditions by constructing a nonlinear Hamilton–Jacobi–Bellman equation for the optimal speed to fly, with a free boundary describing the climb/cruise decision. We consider two different forms of knowledge about future atmospheric conditions, the first in which the pilot has complete foreknowledge and the second in which the state of the atmosphere is a Markov process discovered by flying through it. We compute an accurate numerical solution by designing a robust monotone finite difference method. The results obtained are of direct applicability for glider flight. Copyright © 2014 John Wiley & Sons, Ltd.

Optimal Soaring via Hamilton-Jacobi-Bellman Equations

Competition glider flying is a game of stochastic optimization, in which mathematics and quantitative strategies have historically played an important role. We address the problem of uncertain future atmospheric conditions by constructing a nonlinear Hamilton-Jacobi-Bellman equation for the optimal speed to fly, with a free boundary describing the climb/cruise decision. We consider two different forms of knowledge about future atmospheric conditions, the first in which the pilot has complete foreknowledge and the second in which the state of the atmosphere is a Markov process discovered by flying through it. We compute an accurate numerical solution by designing a robust monotone finite difference method. The results obtained are of direct applicability for glider flight.

Reliability Assessment of the Water Supply Systems under Uncertain Future Extreme Climate Conditions

Abstract Increase in global mean temperature and changes in rainfall amount, pattern, and distribution over the world are all indicative of climate change events. These changes alter the hydroclimatic condition of regions as well as the availability of water resources. In this study, the data generated by 14 general circulation models (GCMs) developed under the Special Report on Emissions Scenarios (SRES) A1B, A2, and B2 are downscaled and utilized to evaluate climate change impact on the hydroclimatic system of the Karaj River basin located in central Iran. The precipitation and temperature of the study region are downscaled using the change factor approach (CFA). The study analyzes future climate data, extreme changes of future climatic conditions of precipitation, and temperature. The Hydrologiska Byråns Vattenbalansavdelning (HBV) model developed by the Swedish Meteorological and Hydrological Institute (SMHI) is used to simulate streamflow under extreme climate change conditions. Two different sources of uncertainty are investigated in this study. First, the model parameters uncertainty is analyzed with the Monte Carlo procedure, and then different datasets of GCMs projection are investigated under the climate of the twentieth-century climate simulation (20C3M). Results show the GCMs projections range can almost capture the historical records during the 1980s through 2000 for the Karaj basin. By applying the HBV model, considerable range of streamflow changes in the future can be projected that will affect the operation scheme of Karaj Reservoir. In this study, the system dynamics (SD) modeling approach is used to simulate the system behavior through time in an integrated fashion and evaluate its overall reliability in supplying water. The results of this study show that the runoff will decrease in the future under the climate change impact. This will result in more than 50% decrease in reliability of the Karaj Reservoir system under the extreme conditions. As a result, this research predicts that the Karaj Reservoir system will face more than 50% decrease in its reliability under the extreme conditions. Consequently, meeting the increasing water demands would be difficult and application of demand management strategies will be unavoidable.

Diversifying the composition and structure of managed, late-successional forests with harvest gaps: What is the optimal gap size?

Managing forests for resilience is crucial in the face of uncertain future environmental conditions. Because harvest gap size alters the species diversity and vertical and horizontal structural heterogeneity, there may be an optimum range of gap sizes for conferring resilience to environmental uncertainty. We examined the impacts of different harvest gap sizes on structure and composition in northern hardwood forests of the upper Great Lakes region, USA using a robustly-designed experiment consisting of six harvest gap sizes replicated 12 times with over a decade of repeated measurements. We found that germinant (trees<0.15m tall) densities were greatest in year 2 (71.6stemsm−2) but were present in all measurement years (0, 2, 6, and 12years post-harvest), suggesting a continuous influx of tree seedlings on site. Sapling (>0.6m tall) densities were greatest (3.9stemsm−2) at the end of the study period (year 12) and were composed primarily of three species (Acer saccharum, Fraxinus americana, Ostrya virginiana) already present on site. The 6 and 10m diameter (dia.) harvest gaps had, on average, the minimum number of saplings (∼2stemsm−2) needed to fill dominant positions in small canopy openings, but, by year 12, small gaps were closed by crown extension of mature edge trees. Medium (20m dia.) to large harvest gaps (30 and 46m dia.) had fewer saplings than small gaps. The understory layer of medium and large gaps were dominated by shrubs (Rubus sp.) that dampened growth of species such as F. americana. Consequently, gap-filling from the sapling layer would not occur in the near future, and, from a management perspective, would be considered a regeneration failure within larger gaps. Our study suggests that the optimum gap size does not exist and using harvest gaps to create resilient forests with structural and compositional diversity alone is challenging on productive habitats. In particular, medium to large gaps will likely require microsite specific placement of desired advance regeneration or additional treatments (e.g., vegetation control) to cultivate a dense sapling layer in an acceptable timeframe after harvest.

Modeling climate change impacts on tidal marsh birds: Restoration and conservation planning in the face of uncertainty

The large uncertainty surrounding the future effects of sea‐level rise and other aspects of climate change on tidal marsh ecosystems exacerbates the difficulty in planning effective conservation and restoration actions. We addressed these difficulties in the context of large‐scale wetland restoration activities underway in the San Francisco Estuary (Suisun, San Pablo and San Francisco Bays). We used a boosted regression tree approach to project the future distribution and abundance of five marsh bird species (through 2110) in response to changes in habitat availability and suitability as a result of projected sea‐level rise, salinity, and sediment availability in the Estuary. To bracket the uncertainty, we considered four future scenarios based on two sediment availability scenarios (high or low), which varied regionally, and two rates of sea‐level rise (0.52 or 1.65 m/100 yr). We evaluated three approaches for using model results to inform the selection of potential restoration projects: (1) Use current conditions only to prioritize restoration. (2) Use a single future scenario (among the four referred to above) in combination with current conditions to select priority restoration projects. (3) Combine current conditions with all four future scenarios, while incorporating uncertainty among future scenarios into the selection of restoration projects. We found that simply using current conditions resulted in the poorest performing restoration projects selected in terms of providing habitat for tidal marsh birds in light of possible future scenarios. The most robust method for selecting restoration projects, the “combined” strategy, used projections from all future scenarios with a discounting of areas with high levels of variability among future scenarios. We show that uncertainty about future conditions can be incorporated in site prioritization algorithms and should motivate the selection of adaptation measures that are robust to uncertain future conditions. These results and data have been made available via an interactive decision support tool at www.prbo.org/sfbayslr.

Many objective robust decision making for complex environmental systems undergoing change

This paper introduces many objective robust decision making (MORDM). MORDM combines concepts and methods from many objective evolutionary optimization and robust decision making (RDM), along with extensive use of interactive visual analytics, to facilitate the management of complex environmental systems. Many objective evolutionary search is used to generate alternatives for complex planning problems, enabling the discovery of the key tradeoffs among planning objectives. RDM then determines the robustness of planning alternatives to deeply uncertain future conditions and facilitates decision makers' selection of promising candidate solutions. MORDM tests each solution under the ensemble of future extreme states of the world (SOW). Interactive visual analytics are used to explore whether solutions of interest are robust to a wide range of plausible future conditions (i.e., assessment of their Pareto satisficing behavior in alternative SOW). Scenario discovery methods that use statistical data mining algorithms are then used to identify what assumptions and system conditions strongly influence the cost-effectiveness, efficiency, and reliability of the robust alternatives. The framework is demonstrated using a case study that examines a single city's water supply in the Lower Rio Grande Valley (LRGV) in Texas, USA. Results suggest that including robustness as a decision criterion can dramatically change the formulation of complex environmental management problems as well as the negotiated selection of candidate alternatives to implement. MORDM also allows decision makers to characterize the most important vulnerabilities for their systems, which should be the focus of ex post monitoring and identification of triggers for adaptive management.

Spatial heterogeneity of climate change in an Afromontane centre of endemism

Broad‐scale assessments of how climate change might impact mountain ecosystems, especially in areas of high biodiversity and endemism, are compromised by the lack of localised climate feedback in global circulation models. Here, we use regionally downscaled climate models to highlight how spatial variation in forecast change could impact rare plant distributions differentially across the Eastern Arc Mountains of Tanzania and Kenya, part of the Eastern Afromontane Biodiversity Hotspot. Concordant with the theory that climatic stability facilitates the accumulation of rare species, we find significant positive correlations between endemic plant richness and future climatic persistence within the dispersal‐limiting sky islands of this mountain archipelago. Further, we explore the hypothesis that mountain plants will move upslope in response to climate change and find that, conversely, some species are predicted to tend downslope, despite warmer annual conditions, driven by changes in seasonality and water availability. Importantly, two thirds of the modelled plant species are predicted to respond in different directions in different parts of their ranges, exemplifying the potential for individualistic responses of species and disjunct populations to environmental change, and the need for regional focus in climate change impact assessment. Conservation planners, and more broadly those charged with developing climate adaption policy, are advised to take caution in inferring local patterns of change from zoomed perspectives of broad‐scale models. Moreover, a preoccupation with mean annual temperature as the principal driver of ecosystem change is misguided and could compromise efforts to make conservation plans resilient to future climate change. Faced with spatially complex and inherently uncertain future conditions, sensible priorities are to restore forest connectivity and to underpin adaption strategies with knowledge of how ecosystems and people have adapted to previous episodes of rapid change.

Issues and Challenges in Flood Risk Management—Editorial for the Special Issue on Flood Risk Management

Recent flood-related disasters (Japan, Thailand, US, Australia) emphasize the need for an effective management of flood risks. As an introduction to this special issue, this editorial summarizes some of the key challenges in the field. Flood risk management needs to recognize the interconnections between infrastructures, economic systems and the role of human factors in assessing and managing the risk. The challenge for flood management in the future is to develop robust and resilient solutions that perform well in uncertain future conditions.

Discovering plausible energy and economic futures under global change using multidimensional scenario discovery

The use of scenarios has proven valuable for global change analysis as a means for organizing and communicating information about uncertain future socioeconomic conditions. A small group of well-defined scenarios can provide a set of standard reference cases for assessing the performance of candidate policies under alternative futures. However, traditional methods of defining scenarios may yield storylines that do not align well with the capabilities of downstream models. It can also be difficult to assess whether the number and scope of constructed scenarios most effectively cover the space of possible outcomes. Model-based methods of ‘scenario discovery’ have recently been proposed that apply statistical data-mining algorithms to a large number of model simulations to identify regions of the stochastic parameter space that lead to unacceptable policy performance. These regions then delineate practically relevant and internally consistent ‘discovered scenarios’. To distinguish ‘acceptable’ from ‘unacceptable’ policy outcomes, existing methods require pre-specification of a threshold value on a single performance metric. We believe this requirement may present a barrier when decision-makers hold differing views on the relative importance of multiple policy objectives. Therefore, we describe a scenario discovery method that is multidimensional in the outcome space, thus precluding the need for users to agree on a single performance threshold or set of tradeoff weights. We demonstrate application of our approach to the results of ENGAGE, an agent-based model (ABM) of economic growth, energy technology, and carbon emissions. We believe that scenario discovery can add particular value to agent-based modeling, as ABMs typically generate a wider array of possible futures than aggregate-scale models. For this reason, a systematic method for sorting through the many stochastic model simulations to identify policy vulnerabilities and opportunities is essential. We conclude by discussing how our methodology might be applicable to the development of socioeconomic scenarios under the ‘representative concentration pathways’ (RCP) framework.

Exploring the Role of Interactive Computer Simulations in Public Administration Education

Preparing public administration students for complex challenges that involve high uncertainty, stakeholder interdependencies, policy resistance, and slow feedback cycles presents unique challenges for educators. Those in the field of public administration and public policy can broaden their educational toolbox by embracing new technologies for educating future public administration practitioners. This research demonstrates that interactive computer simulations provide dynamic contexts and creative learning environments for students to individually and collectively apply systems thinking in information-rich environments with instant feedback channels. Across a series of exploratory studies using an interactive simulation focused on water uncertainty and policy options, this research has consistently found strong learning outcomes. The findings showed that students were able to quickly grasp the complexity associated with interdependent stakeholders with divergent interests, uncertain future conditions, and policy options that reflect competing values. However, this research also discovered some unintended consequences. Using interaction simulations may limit the scope of deliberation topics to only those that were highlighted by the simulation. Thus the research concludes with a discussion of some ethical concerns related to the use of computer simulations as part of an educational exercise.1

The near-term risk of climate uncertainty among the U.S. states

This article describes a study employing a risk-assessment methodology for evaluating uncertain future climatic conditions. To understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions, the study estimated the impacts from responses to climate change on U.S. state- and national-level economic activity. The study used results of the climate-model CMIP3 dataset developed for the Intergovernmental Panel on Climate Change’s (IPCC) Fourth Assessment Report to 1) estimate a proxy for representing climate uncertainty over the next 40 years, 2) map the simulated weather from the climate models hydrologically to the county level to determine the physical consequences on economic activity at the state level, and 3) perform a detailed, economy-wide, 70-industry analysis of economic impacts among the interdependent lower-48 states for the years 2010 through 2050. The analysis determined the interacting industry-level effects, employment impacts at the state level, interstate population migration, consequences to personal income, and ramifications for the U.S. trade balance. When compared to a baseline economic forecast, the calculations produced an average risk of damage of $1 trillion to the U.S. economy from climate change over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs. Added uncertainty would increase the estimated risk.

Shifting thresholds and changing degradation patterns: climate change effects on the simulated long‐term response of a semi‐arid savanna to grazing

Summary1. The complex, nonlinear response of dryland systems to grazing and climatic variations is a challenge to management of these lands. Predicted climatic changes will impact the desertification of drylands under domestic livestock production. Consequently, there is an urgent need to understand the response of drylands to grazing under climate change.2. We enhanced and parameterized an ecohydrological savanna model to assess the impacts of a range of climate change scenarios on the response of a semi‐arid African savanna to grazing. We focused on the effects of temperature and CO2 level increase in combination with changes in inter‐ and intra‐annual precipitation patterns on the long‐term dynamics of three major plant functional types.3. We found that the capacity of the savanna to sustain livestock grazing was strongly influenced by climate change. Increased mean annual precipitation and changes in intra‐annual precipitation pattern have the potential to slightly increase carrying capacities of the system. In contrast, decreased precipitation, higher interannual variation and temperature increase are leading to a severe decline of carrying capacities owing to losses of the perennial grass biomass.4. Semi‐arid rangelands will be at lower risk of shrub encroachment and encroachment will be less intense under future climatic conditions. This finding holds in spite of elevated levels of atmospheric CO2 and irrespective of changes in precipitation pattern, because of the drought sensitivity of germination and establishment of encroaching species.5. Synthesis and applications. Changes in livestock carrying capacities, both positive and negative, mainly depend on the highly uncertain future rainfall conditions. However, independent of the specific changes, shrub encroachment becomes less likely and in many cases less severe. Thus, managers of semi‐arid rangelands should shift their focus from woody vegetation towards perennial grass species as indicators for rangeland degradation. Furthermore, the resulting reduced competition from woody vegetation has the potential to facilitate ecosystem restoration measures such as re‐introduction of desirable plant species that are only little promising or infeasible under current climatic conditions. On a global scale, the reductions in standing biomass resulting from altered degradation dynamics of semi‐arid rangelands can have negative impacts on carbon sequestration.

Flood-Damage-Reduction Project Evaluation with Explicit Consideration of Damage Cost Uncertainty

AbstractFacing uncertain future conditions, flood-damage-reduction alternatives with large positive expected net benefits may be accompanied with high uncertainty. In decision-making under uncertainty, not only failure probability and failure consequences but also the cost of lost opportunity should be considered so as to enhance risk-informed decision-making for hydrosystem design, planning, and management. This paper proposes a risk measure, i.e., the expected opportunity loss (EOL), in a risk-based framework for flood-damage-reduction project design. The opportunity loss for a chosen alternative is the difference between the payoffs of this alternative and the best payoff of all alternatives. The risk measure of EOL can quantify the adverse consequences associated with making a wrong decision due to the uncertain state of nature and it can also capture the correlation effect of the net benefits of two competing design alternatives. Using EOL, alternatives can be ranked by the minimax regret principle. ...

A methodology for the risk assessment of climate variability and change under uncertainty. A case study: coffee production in Veracruz, Mexico

Existing methods for the assessment of the potential impacts of climate change in productive activities and sectors are usually limited to point estimates that do not consider the inherent variability and uncertainty of climatic and socioeconomic variables. This is a major drawback given that only a limited and potentially misleading estimation of risk can be expected when ignoring such determinant factors. In this paper, a new methodology is introduced that is capable of integrating the agent’s beliefs and expert judgment into the assessment of the potential impacts of climate change in a quantitative manner by means of an objective procedure. The goal is to produce tailor-made information to assist decision-making under uncertainty in a way that is consistent with the current state of knowledge and the available subjective “expert” information. Time-charts of the evolution of different risk measures, that can be relevant for assisting decision-making and planning, can be constructed using this new methodology. This methodology is illustrated with a case study of coffee production in Mexico. Time-dependent probabilistic scenarios for coffee production and income, conditional on the agent’s beliefs and expert judgment, are developed for the average producer under uncertain future conditions. It is shown that variability in production and income, generated by introducing climate variability and uncertainty are important factors affecting decision-making and the assessment of economic viability that are frequently ignored. The concept of Value at Risk, commonly applied in financial risk management, is introduced as a means for estimating the maximum expected loss for a previously chosen confidence level. Results are tailor-made for agents that have incomplete information and different beliefs. In this case study, the costs of climate change for coffee production in Veracruz are estimated to have a present value representing from 3 to 14 times the current annual value of coffee production in the state.

Resisting Diversity: a Long-Term Archaeological Study

The value of “diversity” in social and ecological systems is frequently asserted in academic and policy literature. Diversity is thought to enhance the resilience of social-ecological systems to varied and potentially uncertain future conditions. Yet there are trade-offs; diversity in ecological and social domains has costs as well as benefits. In this paper, we examine social diversity, specifically its costs and benefits in terms of decision making in middle range or tribal societies, using archaeological evidence spanning seven centuries from four regions of the U.S. Southwest. In these nonstate societies, social diversity may detract from the capacity for collective action. We ask whether as population density increases, making collective action increasingly difficult, social diversity declines. Further, we trace the cases of low diversity and high population density across our long-temporal sequences to see how they associate with the most dramatic transformations. This latter analysis is inspired by the claim in resilience literature that reduction of diversity may contribute to reduction in resilience to varied conditions. Using archaeological data, we examine social diversity and conformity through the material culture (pottery styles) of past societies. Our research contributes to an enhanced understanding of how population density may limit social diversity and suggests the role that this association may play in some contexts of dramatic social transformation.

Suspending disbelief: Influencing engagement in scenarios of forest futures

Scenario analysis is an approach to long-term planning that informs decision-making in contexts of highly uncertain future conditions. Scenario-based studies are rapidly growing in popularity, yet many aspects of the method are not fully understood. Participants' willingness to suspend disbelief in possible futures is an integral component of scenario-based studies, essential for considering alternative future scenarios, yet little is known about the factors that affect it. Participation in a scenario project does not necessarily imply willingness or ability to suspend disbelief; participants may not suspend disbelief simply upon request. However, the scenario literature says little about the aspects of scenario-based studies that influence suspension of disbelief. This article explores the factors that influenced the suspension of disbelief in one scenario exercise about the future of Canada's forests. Participants differed in their abilities to suspend disbelief in the scenarios in part because of their past experiences and expertise in particular areas, and their assessments of probable and desired future outcomes. Elements of the project design and implementation influenced participants' abilities to engage the scenarios. The results have implications for those interested in using scenarios for helping people and communities envision possible – and sustainable – futures.

Narratives of the future: Suspending disbelief in forest-sector scenarios

Scenario analysis considers highly uncertain future conditions. The method involves developing and analyzing plausible narratives of the future and evaluating them for a range of implications. The power of scenarios lies in creating and considering compelling stories about the future. Thus, narrative, defined as an account of a series of events, is central to the process and plays a pivotal role in engaging participants in a scenario analysis exercise. While a good scenario story can engage individuals and influence their suspension of disbelief, we know little about how participants actually respond to the scenarios so they can, and will, suspend disbelief in scenario outcomes. We explored the role of narrative in suspension of disbelief in a scenario-based study of the long-term future of Canada's forests and forest sector. We discovered that specific aspects of the scenario narratives themselves influenced participants’ suspension of disbelief. While interacting with the scenario narratives, participants actively worked to suspend disbelief by creating new narratives or accessing other existing ones, and by projecting themselves into the scenarios as characters in the stories. Our results may help scenario writers, practitioners, and researchers understand what, in one project, cued people's abilities to suspend disbelief and engage productively in discussions about possible futures.

Basin‐scale water system operations with uncertain future climate conditions: Methodology and case studies

The old and useful paradigm used by water resource engineers, that hydrology in a given place is stationary, and hence it is sufficient to look into the past to plan for the future, does not hold anymore, according to climate change projections. This becomes especially true in snow‐dominated regions like California, where not only the magnitude but also the timing of streamflow could be affected by changes in precipitation and temperature. To plan and operate water resources systems at the basin scale, it is necessary to develop new tools that are suited for this nonstationary world. In this paper we develop an optimization algorithm that can be used for different studies related to climate change and water resources management. Three applications of this algorithm are developed for the Merced River basin. The first of these gives an assessment of the climate change effects on the operations of this basin considering an adaptive management strategy embedded in the optimization algorithm. In a second application we explore different long‐term adaptation strategies intended to mitigate the effects of climate change. A final application is developed to determine how beneficial it is to build a new reservoir considering explicitly the uncertainty about future climate projections.

Climate Change, Sustainability, and Ground Water Remediation: The Connection

Climate Change, Sustainability, and Ground Water Remediation: The Connection

Application of the fuzzy performance measures to the City of London water supply system

Most engineering systems are subject to a wide range of possible uncertain future conditions. The probabilistic reliability analysis usually fails to address the problems of human error, subjectivity, and lack of system performance history and records. This paper explores the utility of the following fuzzy performance measures for evaluating the performance of a complex water supply system: (i) combined reliability–vulnerability, (ii) robustness, and (iii) resiliency. The regional water supply system for the City of London, Ontario, Canada, is used as the case study. The computational requirements for the implementation of the fuzzy performance measures and their sensitivity to different shapes of fuzzy membership functions are investigated. The study illustrates the capability of the fuzzy performance measures to handle uncertainty and identify critical system components. This can be of value in identifying the optimal level of improvement that will increase the overall system performance.Key words: water supply, fuzzy sets, risk, performance indicators.