Researching the future: scenarios to explore the future of human genome editing

BACKGROUND

Forward-looking, democratically oriented governance is needed to ensure that human genome editing serves rather than undercuts public values. Scientific, policy, and ethics communities have recognized this necessity but have demonstrated limited understanding of how to fulfill it. The field of bioethics has long attempted to grapple with the unintended consequences of emerging technologies, but too often such foresight has lacked adequate scientific grounding, overemphasized regulation to the exclusion of examining underlying values, and failed to adequately engage the public.

METHODS

This research investigates the application of scenario planning, a tool developed in the high-stakes, uncertainty-ridden world of corporate strategy, for the equally high-stakes and uncertain world of the governance of emerging technologies. The scenario planning methodology is non-predictive, looking instead at a spread of plausible futures which diverge in their implications for different communities' needs, cares, and desires.

RESULTS

In this article we share how the scenario development process can further understandings of the complex and dynamic systems which generate and shape new biomedical technologies and provide opportunities to re-examine and re-think questions of governance, ethics and values. We detail the results of a year-long scenario planning study that engaged experts from the biological sciences, bioethics, social sciences, law, policy, private industry, and civic organizations to articulate alternative futures of human genome editing.

CONCLUSIONS

Through sharing and critiquing our methodological approach and results of this study, we advance understandings of anticipatory methods deployed in bioethics, demonstrating how this approach provides unique insights and helps to derive better research questions and policy strategies.

Managing uncertainty in forecasting health workforce demand using the Robust Workforce Planning Framework: the example of midwives in Belgium

BACKGROUND

In Belgium, the Planning Commission for Medical Supply is responsible for monitoring human resources for health (HRH) and ultimately proposing workforce quotas. It is supported by the Planning Unit for the Supply of the Health Professions. This Unit quantifies and forecasts the workforce in the healthcare professions on the basis of a stock and flow model, based on trends observed in the past. In 2019, the Planning Unit asked the KCE (Belgian Health Care Knowledge Centre) to develop additional forecasting scenarios for the midwifery workforce, to complement the standard historical trend approach. The aim of this paper is to present the development of such forecasting scenarios.

METHODS

The Robust Workforce Planning Framework, developed by the Centre for Workforce Intelligence in the UK was used to develop alternative midwifery workforce scenarios. The framework consists of four steps (Horizon scanning, Scenario generation, Workforce modelling, and Policy analysis), the first two of which were undertaken by KCE, using two online surveys and five workshops with stakeholders.

RESULTS

Three alternative scenarios are proposed. The first scenario (close to the current situation) envisages pregnancy and maternity care centred on gynaecologists working either in a hospital or in private practice. The second scenario describes an organisation of midwife-led care in hospitals. In the third scenario, care is primarily organised by primary care practitioners (midwives and general practitioners) in outpatient settings.

CONCLUSIONS

The Robust Workforce Planning Framework provides an opportunity to adjust the modelling of the health workforce and inform decision-makers about the impact of their future decisions on the health workforce.

Geodesign for multi-scalar consensus: Lessons from flood adaptation pathways planning

Geodesign is an iterative process for cycling through representation, evaluation, change, impact, and decision models to forge consensus typically across disciplinary more so than geographic boundaries. Multi-scalar integration of blue, green, and human infrastructure is necessary for adapting communities to large-scale extreme flooding scenarios timely and effectively. This project explored the feasibility of using multi-scalar geodesign to converge geographic perspectives from smaller-scale units of analysis (networks of water resources regions (WRRs)) into a higher-order consensus at the continental level to facilitate adaptation pathways planning for instantaneous flooding events, including flash flooding from dam breaks, tidal surges from polar reversal, and rapid sea level rise due to extreme solar events. Participants were initially organized based on their disciplines and geographical familiarity with a particular network of WRRs. Each team helped inventory priority intervention types and sites for blue, green, and human infrastructure components within its respective network of WRRs. Participants were then reorganized into continental teams with an equal number of representatives from each of the four network teams to integrate regional inventories of priority intervention sites and types into continental framework alternatives. Interrater reliability test indicated high reliability (ICC>0.9) in the response patterns of two independent raters (non-participants) that compared convergeability of each pair of alternatives into one: The pairs with the alternative generated without all representatives led to less converge-ability than those pairs containing alternatives generated with all representatives. The finding suggests the importance of integrated teaming in generating consensus-based, multi-scalar adaptation plans for disruptive flooding scenarios more rapidly.

Drivers, uncertainties, and future scenarios of the Iranian health system

BACKGROUND

Health promotion is an essential dimension of sustainable development in any country. It has a high degree of complexity, with numerous components interacting both inside and outside of the system, so having a systemic and forward-looking approach is essential to planning for the future.

METHODS

The research has been designed based on scenario-based planning in three main stages. The data gathering was qualitative by working group meetings and compiling an importance-uncertainty questionnaire to complete the cross-impact analysis matrix. The MicMac and scenario Wizard has been used for data analysis.

RESULTS

The scoping review and upstream document evaluation lead to 54 key variables for analyzing the Iranian health system (HS). The MicMac analysis ends by determining seven key variables: power, politics, and communication network; lifestyle and behavioral factors; quality of human resources training and education; environmental and occupational risk factors, payment and tariff system, and allocation pattern; support society / individuals health; and services effectiveness, especially para-clinical and outpatient ones. Finally, six main scenario spaces are depicted using Scenario Wizard. collective equity was the priority of the HS vision in the desirable scenario, consisting of the most favorable state of the uncertainties. The second, third, and fourth scenarios are also considered desirable. In the disaster scenario, which is the most pessimistic type of consistent scenario in this study, health and equity are not significant either in the social or individual dimensions. In the sixth scenario, the individual dimension of health and equity is the most critical perspective of the HS.

CONCLUSIONS

Due to the unsustainability and high complexity of the Iran's HS, the development and excellence of the HS governance based on the Iran context and health advocacy improvement (applying good governance); creating sustainable financial resources and rational consumption; and human resources training and education are three main principles leading the HS to the images of the desired scenarios.

The value of mass-produced COVID-19 scenarios: A quality evaluation of development processes and scenario content

Hundreds of scenarios were developed across the world in 2020, aimed at generating forward-looking conversations, better understanding for COVID-19 transmission rates, trialling economic outcomes, and stress-testing existing systems in light of the developing pandemic. In response, Cairns & Wright (2020) questioned the value of these mass-produced scenarios created retroactively to existing crises. We address their concerns by evaluating 213 COVID-19 scenarios developed in the first wave of the pandemic. We use two yardsticks as guiding maps against which we plot each scenario's profile and test for values of high-quality process and content. Our analyses reveal various points of high and low qualities, in both process and content. Though most reported processes fell towards lower quality standards, and content largely carried generic applications, the prolific levels of exploratory narratives reflected a mixture of high and low-quality values. Together, our papers develop and reinforce the message that scenario interventions, especially in times of crisis, should reflect more proactive efforts and ensure powerful stakeholders, decision-makers, and affected community members are included in the development of scenarios.

Contrasting the efficiency of landscape versus community protection fuel treatment strategies to reduce wildfire exposure and risk

We examined the financial efficiency and effectiveness of landscape versus community protection fuel treatments to reduce structure exposure and loss to wildfire on a large fire-prone area of central Idaho (USA). The study area contained 63,707 structures distributed in 20 rural communities and resorts, encompassing 13,804 km². We used simulation modeling to estimate expected structure loss based on burn probability and characteristics of the home ignition zone. We then designed three fuel management strategies that targeted treatments to: 1) the surrounding areas predicted to be the source of exposure to communities from large fires, 2) the home ignition zone, and 3) a combination of the landscape and home ignition zone. We evaluated each treatment scenario in terms of exposure and expected structure loss compared to a no-treatment scenario. The potential revenue from wood products was estimated for each scenario to assess the cost-efficiency. We found that the combined landscape and home ignition zone treatment scenario which treated 5.7% of the study area resulted in the highest overall reduction in predicted exposure (47.5%, 100 structures yr^-1) and predicted loss (69.1%, 57 structures yr^-1). Home ignition zone treatments provided the best predicted economic and per area treated performance where exposure and loss were reduced by one structure by treating 89 and 111 ha per year, respectively, with an annual cost of $33,645 and $73,672. Revenue from thinning was the highest for landscape fuel treatments and covered 16% of the required investment. This work highlighted economic and risk tradeoffs associated with alternative fuel treatment strategies to protect developed areas from large wildland fires.

A Value Sensitive Scenario Planning Method for Adaptation to Uncertain Future Sea Level Rise

Value sensitive design (VSD) aims at creating better technology based on social and ethical values. However, VSD has not been applied to long-term and uncertain future developments, such as societal planning for climate change. This paper describes a new method that combines elements from VSD with scenario planning. The method was developed for and applied to a case study of adaptation to sea level rise (SLR) in southern Sweden in a series of workshops. The participants of the workshops found that the method provided a framework for discussing long-term planning, enabled identification of essential values, challenged established planning practices, helped find creative solutions, and served as a reminder that we do not know what will happen in the future. Finally, we reflect on the limitations of the method and suggest further research on how it can be improved for value sensitive design of adaptation measures to manage uncertain future sea level rise.

Land-use Decisions in Complex Commons: Engaging Multiple Stakeholders through Foresight and Scenario Building in Indonesia

In the midst of global change uncertainties, Indonesian spatial planning authorities are developing 20-year strategies. However, the lack of collaborative engagement of stakeholders and unclear methodology around using futures studies in addressing land management undermine such plans and affect environmental governance. A crucial question is how to link a future-oriented process with governance transformation processes, particularly related to land-use planning and management. To address this issue, we used a co-elaborative scenario-building approach, referred to as participatory prospective analysis (PPA), to facilitate the creation of local multistakeholder platforms considering future-oriented perspectives. The PPA design combines equally the knowledge of local communities, technical experts and decision-makers, and was applied in a series of sequential multistakeholder workshops in two regencies in Indonesia, followed by public consultations on the main results. In both regencies, participants agreed on a common topic related to spatial planning in their jurisdiction to be explored with a 20-year time horizon. They reached consensus on relevant variables, analyzed their dependence/influence, and developed several plausible yet contrasting scenarios for land management and road maps with guidelines for the implementation of desired outcomes. The PPA approach stimulated stakeholder engagement and ensured that more local voices were not only heard but also duly included in the process. It allowed participants to consider strategies that would otherwise have been less readily accepted by their respective organizations. It showed that it is possible to improve existing spatial planning processes in Indonesia by integrating tools for a more inclusive and long-term future-oriented collaborative approach.

A business retrieval model using scenario planning and analytics for life during and after the pandemic crisis

The COVID-19 pandemic crisis has fundamentally changed the way we live and work forever. The business sector is forecasting and formulating different scenarios associated with the impact of the pandemic on its employees, customers, and suppliers. Various business retrieval models are under construction to cope with life after the COVID-19 Pandemic Crisis. However, the proposed plans and scenarios are static and cannot address the dynamic pandemic changes worldwide. They also have not considered the peripheral in-between scenarios to propel the shifting paradigm of businesses from the existing condition to the new one. Furthermore, the scenario drivers in the current studies are generally centered on the economic aspects of the pandemic with little attention to the social facets. This study aims to fill this gap by proposing scenario planning and analytics to study the impact of the Coronavirus pandemic on large-scale information technology-led Companies. The primary and peripheral scenarios are constructed based on a balanced set of business continuity and employee health drivers. Practical action plans are formulated for each scenario to devise plausible responses. Finally, a damage management framework is developed to cope with the mental disorders of the employees amid the disease.

Paratransit services for people with disabilities in the Seattle region during the COVID-19 pandemic: Lessons for recovery planning

INTRODUCTION

Along with all public transit services, paratransit services for people with disabilities experienced substantially reduced demand and an increased need to provide equitable services while protecting their clients and staff's safety during the COVID-19 pandemic. Paratransit services provide a lifeline for their clients' essential mobility needs, including access to medical appointments and grocery stores. In the absence of pre-existing pandemic response plans, examining transit agencies' responses to provide paratransit services during the pandemic can help inform planning for post-pandemic recovery and future disruptive events.

METHODS

In September 2020, we conducted semi-structured interviews with 15 decision-makers, planners, and drivers working for the primary transit agency in the Seattle region - King County Metro - and its paratransit contractors. Interview questions were designed to identify current services, policy gaps, and critical challenges for recovery planning and post-pandemic paratransit services. Interview transcripts were analyzed using NVivo software to obtain essential themes.

RESULTS

The interviewees provided insights about (1) paratransit service changes in response to the pandemic, (2) anticipated impacts of a returning demand on paratransit service efficiency, equity, and quality during the recovery period, and (3) innovative approaches for maintaining post-pandemic equitable paratransit services while balancing safety measures with available resources.

CONCLUSIONS

Study findings suggest that paratransit service providers should consider (1) developing guidelines for future disruptive events, (2) examining alternative methods for food delivery to clients, (3) planning scenarios for delivering equitable services in the post-pandemic recovery period, and (4) increasing resilience possibly by establishing partnerships with transportation network companies.

Exploring the potential for planning support systems to bridge the research-translation gap between public health and urban planning

BACKGROUND

There is consensus that planning professionals need clearer guidance on the features that are likely to produce optimal community-wide health benefits. However, much of this evidence resides in academic literature and not in tools accessible to the diverse group of professionals shaping our cities. Incorporating health-related metrics into the planning support systems (PSS) provides an opportunity to apply empirical evidence on built environment relationships with health-related outcomes to inform real-world land use and transportation planning decisions. This paper explores the role of planning support systems (PSS) to facilitate the translation and application of health evidence into urban planning and design practices to create healthy, liveable communities.

METHODS

A review of PSS software and a literature review of studies featuring a PSS modelling built environmental features and health impact assessment for designing and creating healthy urban areas was undertaken. Customising existing software, a health impact PSS (the Urban Health Check) was then piloted with a real-world planning application to evaluate the usefulness and benefits of a health impact PSS for demonstrating and communicating potential health impacts of design scenarios in planning practice.

RESULTS

Eleven PSS software applications were identified, of which three were identified as having the capability to undertake health impact analyses. Three studies met the inclusion criteria of presenting a planning support system customised to support health impact assessment with health impacts modelled or estimated due to changes to the built environment. Evaluation results indicated the Urban Health Check PSS helped in four key areas: visualisation of how the neighbourhood would change in response to a proposed plan; understanding how a plan could benefit the community; Communicate and improve understanding health of planning and design decisions that positively impact health outcomes.

CONCLUSIONS

The use of health-impact PSS have the potential to be transformative for the translation and application of health evidence into planning policy and practice, providing those responsible for the policy and practice of designing and creating our communities with access to quantifiable, evidence-based information about how their decisions might impact community health.

Scenario Planning: Embracing the Potential for Extreme Events in the Colorado River Basin

Scenario planning (SP) has been increasingly utilized by water managers and planners in the 21st century as climate and other uncertainties have challenged traditional planning approaches. This paper discusses the potential for scenario planning processes in the Colorado River Basin in the southwestern United States to build collective understanding of compound and cascading risks, and to identify possible solutions at multiple scales. Under the Colorado River Conversations Project, we convened a series of conferences and scenario planning workshops over the past 3 years to explore the potential to enhance the use of social and physical sciences in river management, and to broaden the community of people and entities engaged in discussions about managing the Colorado River. Working with a group of thirty water managers and other interested parties representing all 7 basin states, several Tribes, NGO's and Mexico, we used a participatory, mixed-methods approach to scenario planning that identified multiple drivers of change and developed eight science-based storylines from the intersection of these drivers. The development of the storylines and the subsequent conversations with participants about impacts and solutions resulted in a framework for understanding low probability-high consequence climate and other risks across the Colorado River Basin. We highlight three lessons that speak to the value and role of SP for fostering collaboration and creativity. These lessons include: (1) the importance of process in SP in fostering deliberate community building across sectors and geographies; (2) identifying challenges with engaging with uncertainty, complexity, and risk; and (3) determining what these findings mean for future SP in the Colorado River Basin and beyond.

Scenario Planning: Embracing the Potential for Extreme Events in the Colorado River Basin

Scenario planning (SP) has been increasingly utilized by water managers and planners in the 21st century as climate and other uncertainties have challenged traditional planning approaches. This paper discusses the potential for scenario planning processes in the Colorado River Basin in the southwestern United States to build collective understanding of compound and cascading risks, and to identify possible solutions at multiple scales. Under the Colorado River Conversations Project, we convened a series of conferences and scenario planning workshops over the past 3 years to explore the potential to enhance the use of social and physical sciences in river management, and to broaden the community of people and entities engaged in discussions about managing the Colorado River. Working with a group of thirty water managers and other interested parties representing all 7 basin states, several Tribes, NGO's and Mexico, we used a participatory, mixed-methods approach to scenario planning that identified multiple drivers of change and developed eight science-based storylines from the intersection of these drivers. The development of the storylines and the subsequent conversations with participants about impacts and solutions resulted in a framework for understanding low probability-high consequence climate and other risks across the Colorado River Basin. We highlight three lessons that speak to the value and role of SP for fostering collaboration and creativity. These lessons include: (1) the importance of process in SP in fostering deliberate community building across sectors and geographies; (2) identifying challenges with engaging with uncertainty, complexity, and risk; and (3) determining what these findings mean for future SP in the Colorado River Basin and beyond.

Predicting stream water quality under different urban development pattern scenarios with an interpretable machine learning approach

Urban development pattern significantly impacts stream water quality by influencing pollutant generation, build-up, and wash-off processes. It is thus necessary to understand and predict stream water quality in accordance with different urban development patterns to effectively advise urban growth planning and policies. To do so, we collected pollutant concentration data on nitrate (NO₃^--N), total phosphate (TP), and Escherichia coli (E. coli) from 1047 sampling stations in the Texas Gulf Region. We utilized a Random Forest (RF) machine learning model to predict stream water quality under four planning scenarios with different urban densities and configurations. SHapley Additive exPlanations (SHAP) was used to prove the importance of urban development pattern in influencing stream water quality. The spatial variations of the impact of these patterns were explored with Geographically Weighted Regression (GWR). SHAP results indicated that Largest Patch Index (LPI), Patch Cohesion Index (COHESION), Splitting Index (SPLIT), and Landscape Division Index (DIVISION) were the most important urban development pattern metrics affecting stream water quality. The spatial variations of such patterns were shown to impact stream water quality depending on pollutants, seasonality, climate, and urbanization level. RF prediction results suggested that high density aggregated development was more effective in reducing TP and NO₃^--N concentrations than the current sprawl development, but had the potential risk of increasing E. coli pollution in the wet season. The results of this study provide empirical evidence and a potential mechanistic explanation that stream water quality degradation is a consequence of urban sprawl. Lastly, machine learning is a powerful tool for scenario prediction in land use planning to forecast environmental impacts under different urban development pattern scenarios.

The six scenario archetypes framework: A systematic investigation of science fiction films set in the future

We propose a new scenario archetypes method generated by extracting a set of archetypal images of the future from a sample of 140 science fiction films set in the future using a grounded theory analytical procedure. Six archetypes emerged from the data, and were named Growth & Decay, Threats & New Hopes, Wasteworlds, The Powers that Be, Disarray, and Inversion. The archetypes in part overlap with and confirm previous research, and in part are novel. They all involve stress-point critical conditions in the external environment. We explain why the six archetypes, as a foresight framework, is more transformational and nuanced than previously developed scenario archetypes frameworks, making it particularly suited to the current necessity to think the unthinkable more systematically. We explain how the six archetypes framework can be used as predetermined images of the future to create domain specific scenarios, making organizations more resilient to critical, disruptive futures. We finally present and discuss a case study of the application of the method to create scenarios of post-Covid-19 futures of work. (https://www.youtube.com/watch?v=q82_X7fN_XA).

Active travel and social justice: Addressing disparities and promoting health equity through a novel approach to Regional Transportation Planning

Public health impacts of transportation policies and infrastructure investment are becoming better understood, particularly for those associated with physical activity. Yet health impacts are not routinely evaluated within the context of the development of a Regional Transportation Plan (RTP) and subsequent programming and investment processes. This is particularly concerning because the spatial distribution of planned transportation infrastructure potentially has significant health equity implications for vulnerable populations at greater risk of chronic disease. This study discusses the application of the National Public Health Assessment Model (NPHAM) - a new approach that expands several scenario planning tools to include health - for the San Joaquin Council of Governments 2018 RTP. It demonstrates how quantifying health impacts at a finer spatial scale (census block groups) helps assess the extent to which RTP strategies are likely to benefit or harm health. It further enables a spatial form of health equity analysis that can help planners understand where infrastructure is most needed to meet social equity goals. To the knowledge of the authors, this is the first example of a quantified, health equity analysis of transport physical activity and a health outcome - body mass index - associated with an RTP; it demonstrates significant advancement in transportation planning practice and policy.

The future of manufacturing: A Delphi-based scenario analysis on Industry 4.0

Industry 4.0 is expected to impart profound changes to the configuration of manufacturing companies with regards to what their value proposition will be and how their production network, supplier base and customer interfaces will develop. The literature on the topic is still fragmented; the features of the emerging paradigm appear to be a contested territory among different academic disciplines. This study assumes a value chain perspective to analyze the evolutionary trajectories of manufacturing companies. We developed a Delphi-based scenario analysis involving 76 experts from academia and practice. The results highlight the most common expectations as well as controversial issues in terms of emerging business models, size, barriers to entry, vertical integration, rent distribution, and geographical location of activities. Eight scenarios provide a concise outlook on the range of possible futures. These scenarios are based on four main drivers which stem from the experts' comments: demand characteristics, transparency of data among value chain participants, maturity of additive manufacturing and advanced robotics, and penetration of smart products. Researchers can derive from our study a series of hypotheses and opportunities for future research on Industry 4.0. Managers and policymakers can leverage the scenarios in long-term strategic planning.

The future of manufacturing: A Delphi-based scenario analysis on Industry 4.0

Industry 4.0 is expected to impart profound changes to the configuration of manufacturing companies with regards to what their value proposition will be and how their production network, supplier base and customer interfaces will develop. The literature on the topic is still fragmented; the features of the emerging paradigm appear to be a contested territory among different academic disciplines. This study assumes a value chain perspective to analyze the evolutionary trajectories of manufacturing companies. We developed a Delphi-based scenario analysis involving 76 experts from academia and practice. The results highlight the most common expectations as well as controversial issues in terms of emerging business models, size, barriers to entry, vertical integration, rent distribution, and geographical location of activities. Eight scenarios provide a concise outlook on the range of possible futures. These scenarios are based on four main drivers which stem from the experts' comments: demand characteristics, transparency of data among value chain participants, maturity of additive manufacturing and advanced robotics, and penetration of smart products. Researchers can derive from our study a series of hypotheses and opportunities for future research on Industry 4.0. Managers and policymakers can leverage the scenarios in long-term strategic planning.

The future of manufacturing: A Delphi-based scenario analysis on Industry 4.0

Industry 4.0 is expected to impart profound changes to the configuration of manufacturing companies with regards to what their value proposition will be and how their production network, supplier base and customer interfaces will develop. The literature on the topic is still fragmented; the features of the emerging paradigm appear to be a contested territory among different academic disciplines. This study assumes a value chain perspective to analyze the evolutionary trajectories of manufacturing companies. We developed a Delphi-based scenario analysis involving 76 experts from academia and practice. The results highlight the most common expectations as well as controversial issues in terms of emerging business models, size, barriers to entry, vertical integration, rent distribution, and geographical location of activities. Eight scenarios provide a concise outlook on the range of possible futures. These scenarios are based on four main drivers which stem from the experts' comments: demand characteristics, transparency of data among value chain participants, maturity of additive manufacturing and advanced robotics, and penetration of smart products. Researchers can derive from our study a series of hypotheses and opportunities for future research on Industry 4.0. Managers and policymakers can leverage the scenarios in long-term strategic planning.

Advancing Scenario Planning through Integrating Urban Growth Prediction with Future Flood Risk Models

High uncertainty about future urbanization and flood risk conditions limits the ability to increase resiliency in traditional scenario-based urban planning. While scenario planning integrating urban growth prediction modeling is becoming more common, these models have not been effectively linked with future flood plain changes due to sea level rise. This study advances scenario planning by integrating urban growth prediction models with flood risk scenarios. The Land Transformation Model, a land change prediction model using a GIS based artificial neural network, is used to predict future urban growth scenarios for Tampa, Florida, USA, and future flood risks are then delineated based on the current 100-year floodplain using NOAA level rise scenarios. A multi-level evaluation using three urban prediction scenarios (business as usual, growth as planned, and resilient growth) and three sea level rise scenarios (low, high, and extreme) is conducted to determine how prepared Tampa's current land use plan is in handling increasing resilient development in lieu of sea level rise. Results show that the current land use plan (growth as planned) decreases flood risk at the city scale but not always at the neighborhood scale, when compared to no growth regulations (business as usual). However, flood risk when growing according to the current plan is significantly higher when compared to all future growth residing outside of the 100-year floodplain (resilient growth). Understanding the potential effects of sea level rise depends on understanding the probabilities of future development options and extreme climate conditions.

Possibilities for the future of global mental health: a scenario planning approach

BACKGROUND

Global mental health is a widely used term describing initiatives in policies, research and practice to improve the mental health of people worldwide. It has been gaining momentum over the last 10 years, reflected in increasing funding opportunities, training programmes, and publications. In light of the rising importance of global mental health and the various uncertainties about its future directions, this paper explores what the future may hold for global mental health in 30 years' time.

METHOD

A scenario planning method was used, involving a workshop with experts from four continents and a range of backgrounds, including clinical and academic psychiatry, psychology, art and music therapy, service user advisory role, funder of global health research and post-graduate students.

RESULTS

Six distinct scenarios that describe potential future situations were developed: universal standards for care; worldwide coordination of research; making use of diversity; focus on social factors; globalised care through technology; mental health as a currency in global politics.

CONCLUSIONS

These scenarios consider different social, economic, scientific and technological drivers and focus on distinct aspects. Some reflect a global application of possible trends in mental health, whilst others apply general global developments to mental health care. They are not fixed forecasts, but instead may help to promote discussion and debate about further developments and decisions.

A runoff trading system to meet watershed-level stormwater reduction goals with parcel-level green infrastructure installation

Green infrastructure (GI) has been recommended widely to reduce runoff from the built environment. However, reliance on public land for GI implementation could cause a heavy financial burden on local governments. Although economic incentives and market-based mechanisms may encourage public participation in managing stormwater by installing GI on private parcels, a runoff trading market has not been fully developed in practice. To establish a market, in part, requires a watershed-based planning framework and fully informed parcel owners in regard to tradable credits, costs, and benefits. We propose a scenario-based Stormwater Management Planning Support System for Trading Runoff Abatement Credits (SMPSS-TRAC) to facilitate the calculation and allocation of stormwater runoff abatement credits in order to assist the decision-making of GI investment. We apply SMPSS-TRAC to a watershed located in Hamilton County, Ohio, USA and develop five scenarios representing increasing use of GI. We test the scenarios under a 5-year rainfall intensity and set a cap of runoff for each scenario at a level that is equal to the runoff from an undeveloped status (1.03-inch runoff depth for the watershed). With the proposed SMPSS-TRAC, the watershed authority could encourage all parcel owners to install suitable GI or purchase credits from the market. When detention basins are needed to meet a stated goal, the watershed authority would build them on vacant lots and share costs with all parcels within the same sub-catchment. The last scenario with four types of GI installed, shows that the watershed reaches market equilibrium and generates 15,358 m³ credit surplus. SMPSS-TRAC has the potential for including multiple stakeholders' preferences and concerns in searching for preferable scenarios.

Development of a scenario-based stormwater management planning support system for reducing combined sewer overflows (CSOs)

Using combined sewer systems to handle excess stormwater runoff is common in older urban areas. Combined sewer overflow (CSO) events occur when hydraulic capacity is exceeded, and untreated wastewater discharges to surface waters. As urban population density increases, and more demand is placed on infrastructure, CSO events happen more often and cause serious environmental problems and public-health risks. Recently, green infrastructure (GI) has been integrated with existing gray infrastructure (GrayI) to reduce CSO events. However, there lacks a goal-oriented planning framework for eliminating CSOs at a watershed/sewershed scale. Moreover, existing stormwater simulations based on catchments or other geographic units, do not consider spatial variation within the unit, such as distribution, attribution, ownership, and management of GI. We propose a scenario-based Stormwater Management Planning Support System for CSOs (SMPSS-CSO) to provide a platform for reducing CSO events by coordinating parcel-based installations of GI. We applied the SMPSS-CSO to a sewershed with a single CSO location in Cincinnati, Ohio and developed four scenarios representing increased use of GI (rain barrels, green roofs, porous pavements, and detention basin) based on its cost, difficulty of installation, and property ownership. Runoff quantity, time of concentration, and peak flow rate were simulated using the curve number method. Our analysis shows a 41% reduction in stormwater runoff is necessary to eliminate CSO events for a two-year rainfall, required 97.25% of private and 27.59% of public parcels to install GI. GI alone cannot eliminate CSO events in this sewershed and must be incorporated with additional GrayI (e.g., storage tanks, pipes). The SMPSS-CSO has the potential for including multiple stakeholders' preferences and concerns in the searching for preferable scenarios.

Review of scenario analyses to reduce agricultural nitrogen and phosphorus loading to the aquatic environment

Nutrient loadings of nitrogen (N) and phosphorus (P) to aquatic environments are of increasing concern globally for managing ecosystems, drinking water supply and food production. There are often multiple sources of these nutrients in the landscape, and the different hydrological flow patterns within stream or river catchments have considerable influence on nutrient transport, transformation and retention processes that all eventually affect loadings to vulnerable aquatic environments. Therefore, in order to address options to reduce nutrient loadings, quantitative assessment of their effects in real catchments need to be undertaken. This involves setting up scenarios of the possible nutrient load reduction measures and quantifying their impacts via modelling. Over the recent two decades there has been a great increase in the use of scenario-based analyses of strategies to combat excessive nutrient loadings. Here we review 130 published papers extracted from Web of Science for 1995 to 2014 that have applied models to analyse scenarios of agricultural impacts on nutrients loadings at catchment scale. The review shows that scenario studies have been performed over a broad range of climatic conditions, with a large focus on measures targeting land cover/use and land management for reducing the source load of N and P in the landscape. Some of the studies considered how to manage the flows of nutrients, or how changes in the landscape may be used to influence both flows and transformation processes. Few studies have considered spatially targeting measures in the landscape, and such studies are more recent. Spatially differentiated options include land cover/use modification and application of different land management options based on catchments characteristics, cropping conditions and climatic conditions. Most of the studies used existing catchment models such as SWAT and INCA, and the choice of the models may also have influenced the setup of the scenarios. The use of stakeholders for designing scenarios and for communication of results does not seem to be a widespread practice, and it would be recommendable for future scenario studies to have a more in-depth involvement of stakeholders for the elaboration and interpretation of scenarios, in particular to enhance their relevance for farm and catchment management and to foster better policies and incentives.

A scenario-based MCDA framework for wastewater infrastructure planning under uncertainty

Wastewater infrastructure management is increasingly important because of urbanization, environmental pollutants, aging infrastructures, and climate change. We propose a scenario-based multi-criteria decision analysis (MCDA) framework to compare different infrastructure alternatives in terms of their sustainability. These range from the current centralized system to semi- and fully decentralized options. Various sources of uncertainty are considered, including external socio-economic uncertainty captured by future scenarios, uncertainty in predicting outcomes of alternatives, and incomplete preferences of stakeholders. Stochastic Multi-criteria Acceptability Analysis (SMAA) with Monte Carlo simulation is performed, and rank acceptability indices help identify robust alternatives. We propose step-wise local sensitivity analysis, which is useful for practitioners to effectively elicit preferences and identify major sources of uncertainty. The approach is demonstrated in a Swiss case study where ten stakeholders are involved throughout. Their preferences are quantitatively elicited by combining an online questionnaire with face-to-face interviews. The trade-off questions reveal a high concern about environmental and an unexpectedly low importance of economic criteria. This results in a surprisingly good ranking of high-tech decentralized wastewater alternatives using urine source separation for most stakeholders in all scenarios. Combining scenario planning and MCDA proves useful, as the performance of wastewater infrastructure systems is indeed sensitive to socio-economic boundary conditions and the other sources of uncertainty. The proposed sensitivity analysis suggests that a simplified elicitation procedure is sufficient in many cases. Elicitation of more information such as detailed marginal value functions should only follow if the sensitivity analysis finds this necessary. Moreover, the uncertainty of rankings can be considerably reduced by better predictions of the outcomes of alternatives. Although the results are case based, the proposed decision framework is generalizable to other decision contexts.

Importance of anthropogenic climate impact, sampling error and urban development in sewer system design

Urban drainage design relying on observed precipitation series neglects the uncertainties associated with current and indeed future climate variability. Urban drainage design is further affected by the large stochastic variability of precipitation extremes and sampling errors arising from the short observation periods of extreme precipitation. Stochastic downscaling addresses anthropogenic climate impact by allowing relevant precipitation characteristics to be derived from local observations and an ensemble of climate models. This multi-climate model approach seeks to reflect the uncertainties in the data due to structural errors of the climate models. An ensemble of outcomes from stochastic downscaling allows for addressing the sampling uncertainty. These uncertainties are clearly reflected in the precipitation-runoff predictions of three urban drainage systems. They were mostly due to the sampling uncertainty. The contribution of climate model uncertainty was found to be of minor importance. Under the applied greenhouse gas emission scenario (A1B) and within the period 2036-2065, the potential for urban flooding in our Swiss case study is slightly reduced on average compared to the reference period 1981-2010. Scenario planning was applied to consider urban development associated with future socio-economic factors affecting urban drainage. The impact of scenario uncertainty was to a large extent found to be case-specific, thus emphasizing the need for scenario planning in every individual case. The results represent a valuable basis for discussions of new drainage design standards aiming specifically to include considerations of uncertainty.

Integrating ecosystem services analysis into scenario planning practice: accounting for street tree benefits with i-Tree valuation in Central Texas

Scenario planning continues to gain momentum in the United States as an effective process for building consensus on long-range community plans and creating regional visions for the future. However, efforts to integrate more sophisticated information into the analytical framework to help identify important ecosystem services have lagged in practice. This is problematic because understanding the tradeoffs of land consumption patterns on ecological integrity is central to mitigating the environmental degradation caused by land use change and new development. In this paper we describe how an ecosystem services valuation model, i-Tree, was integrated into a mainstream scenario planning software tool, Envision Tomorrow, to assess the benefits of public street trees for alternative future development scenarios. The tool is then applied to development scenarios from the City of Hutto, TX, a Central Texas Sustainable Places Project demonstration community. The integrated tool represents a methodological improvement for scenario planning practice, offers a way to incorporate ecosystem services analysis into mainstream planning processes, and serves as an example of how open source software tools can expand the range of issues available for community and regional planning consideration, even in cases where community resources are limited. The tool also offers room for future improvements; feasible options include canopy analysis of various future land use typologies, as well as a generalized street tree model for broader U.S. application.

Strategic rehabilitation planning of piped water networks using multi-criteria decision analysis

To overcome the difficulties of strategic asset management of water distribution networks, a pipe failure and a rehabilitation model are combined to predict the long-term performance of rehabilitation strategies. Bayesian parameter estimation is performed to calibrate the failure and replacement model based on a prior distribution inferred from three large water utilities in Switzerland. Multi-criteria decision analysis (MCDA) and scenario planning build the framework for evaluating 18 strategic rehabilitation alternatives under future uncertainty. Outcomes for three fundamental objectives (low costs, high reliability, and high intergenerational equity) are assessed. Exploitation of stochastic dominance concepts helps to identify twelve non-dominated alternatives and local sensitivity analysis of stakeholder preferences is used to rank them under four scenarios. Strategies with annual replacement of 1.5-2% of the network perform reasonably well under all scenarios. In contrast, the commonly used reactive replacement is not recommendable unless cost is the only relevant objective. Exemplified for a small Swiss water utility, this approach can readily be adapted to support strategic asset management for any utility size and based on objectives and preferences that matter to the respective decision makers.