Several sessions at AGU 2017 conference will adress (hydrologic) uncertainty. An overview is given here: http://aguhu.blogspot.nl/2017/07/which-session-to-submit-to-hydrologic.html
DMDU draws on a range of approaches to deal with uncertainty. Methods for living with (deep) uncertainty is a key focus, but not all aspects of a situation are deeply uncertain. Even if we don’t necessarily think about it, we also use methods to reduce uncertainty in model structure, and perhaps to characterise uncertainty in parameters that can be estimated from data without controversy. This context-sensitive approach to uncertainty is a strength of DMDU.
Submissions to any of these sessions are warmly invited (abstracts due 2nd August).
If you have not yet done so, you can sign up for the annual workshop at http://bit.ly/DMDU2017. Here you’ll also find information about the workshop, and this will be updated as the programme is confirmed. This page also provides information about a DMDU training day on Monday 13 November, which may also be of interest to you. Both events will be held at the Oxford Martin School, 34 Broad Street, Oxford OX1 3BD. The workshop will be on 14-15 November 2017, and there will be a conference dinner at the Museum of Natural History on the evening of Tuesday 14 November.
The deadline for submitting abstracts for this years annual meeting is extended to 9th of June.
To register or submit an abstract, please go to the conference website.
By Robert Lempert and Marjolijn Haasnoot
In columnist Bret Stephens’ first blog post for the New York Times, published at the end of April, he highlights the uncertainty surrounding climate change, warns against overconfidence, and issues an invitation to dialogue. We agree that significant uncertainty exists regarding the future impacts of climate change and the costs of avoiding those impacts, that it is dangerous to ignore or downplay that uncertainty, and that acknowledging these uncertainties can provide a strong foundation for dialogue.
A vast literature exists on uncertainty and climate change. Most of it suggests that uncertainty is a reason for action. That said, it remains a significant challenge to determine what actions most effectively balance society’s many goals, in the presence of deep uncertainty about the likelihood of various futures and how our actions are related to consequences.
In exchanges with Stephens, both Andy Revkin and Costa Samaras highlighted the Society for Decision Making Under Deep Uncertainty as a community that brings together researchers and practitioners from all over the world. We develop, apply and exchange experiences on methods, approaches and case studies on decision making under deep uncertainty. Climate change is one of the policy domains (though not the only one) of great interest to many of the Society’s members. Continue reading
Please save the date for the 2017 DMDU meeting. The meeting will be hosted by the Oxford Martin School in Oxford, UK, on 14-15 November 2017, with a training on DMDU methodologies scheduled for 13 November 2017. For more information on the workshop, visit the website. The 2017 annual meeting theme is dealing with deep uncertainty in decision making across multiple scales. The workshop will tackle the challenges of decision making at many different scales, from the perspective of deep uncertainty. The theme of multiple scales embraces spatial scales, temporal scales and scales of governance.
by Julie Rozenberg, Economist at the World Bank in the Chief Economist Office for Sustainable Development.
This blog is a reposted from the World Bank.
In 2015, severe floods washed away a series of bridges in Mozambique’s Nampula province, leaving several small villages completely isolated. Breslau, a local engineer and one of our counterparts, knew that rebuilding those bridges would take months. Breslau took his motorbike and drove the length of the river to look for other roads, trails, or paths to help the villagers avoid months of isolation. He eventually found an old earth path that was quickly cleaned up and restored… After a few days, the villagers had an alternative to the destroyed bridge, reconnecting them to the rest of the network and the country.
What happened in the Nampula province perfectly illustrates how a single weather event can quickly paralyze transport connections, bringing communities and economies to a screeching halt. There are many more examples of this phenomenon, which affects both developing and developed countries. On March 30th, a section of the I-85 interstate collapsed in Atlanta, causing schools to close and forcing many people to work from home. In Peru, food prices increase in Lima when the carretera central is disrupted by landslides because agricultural products can’t be brought to market.
How can we help countries improve the resilience of their transport networks in a context of scarce resources and rising climate uncertainty?
by: Steven Popper
The Society for Decision Making under Deep Uncertainty held its first annual training day event on 15 November 2016 at World Bank Headquarters in Washington, DC. This was the day prior to the start of the DMDU Society’s annual two-day workshop. The Society’s leadership team has decided that a training day will precede future DMDU workshops under the direction of the chair for education and training in coordination with that year’s workshop organizing committee. This decision is a direct response to an interest expressed through the questionnaire on education and training distributed to the Society’s membership earlier in 2016. The survey disclosed not only an interest in such a session but a willingness to participate on the part of students, DMDU analysts and methodologists, and policy practitioners.
by: Patrick Reed
This blog reports on one of the session of the annual meeting of 2016. The sessoin was organized by Patrick Reed (Cornell University), Jan Kwakkel (TU Delft), Andrea Castelletti (Politecnico di Milano), Laura Bonzanigo (World Bank). Invited speakers were Julie Quinn (Cornell University) and Marc Jaxa-Rozen (TU Delft).
Session Focus: This session explored the interplay between short-term adaptive operations and their influence on long-term planning is particularly relevant for irreversible decisions for long-lived infrastructures that present complex ecological impacts, and must reliably meet multi-sectoral demands (e.g., reservoirs, energy production/transmission, transportation networks, etc.). A core theme throughout this whole session is that current DMDU frameworks that truly seek robustness must better exploit information feedbacks, tailor adaptivity so that triggered actions are contextually appropriate, and minimize lock in. The session was organized into three case study presentations, five posters, and an interactive serious table top game. This suite of multi-sector examples helped clarify emerging innovations and persistent challenges related to bridging the planning and management divide.
by Judy Lawrence and Robert Lempert
At the conclusion of the DMDU workshop at Deltares, The Netherlands in 2015, we identified political scientists as an additional group that could inform the discussions at the next annual workshop. Accordingly, we designed a problem session at the annual workshop at the World Bank in 2016, entitled: Deep Uncertainty and the Long-Term: Time, the policy challenge and enablers for policy persistence. Whether or not decision makers consider the implications of their decisions for future generations under changing conditions depends on a range of institutional, political, behavioural and ethical factors. One of these is the extent to which policy decisions are influenced by short-termism or presentist bias. This in turn, depends on the political context within which decisions are made.
Tools developed for decision making under conditions of uncertainty and change, need to be ‘fit’ for the changing environment and for the political context, to enable policies to persist over time and adapt to changing conditions. Or the political context could be changed using commitment devices. Thus, for successful implementation of policies that can persist over the long term or be adjusted as the world changes, we need to understand the drivers that motivate the actors.
by Marjolijn Haasnoot, Laura Bonzanigo
Tomorrow we will start our 4th annual meeting of the Society for Decision Making under Deep Uncertainty. Like last year we made word cloud of the titles of the presentation, abstract and posters. As expected ‘uncertainty’ is one of the most frequent words this year. However, this has not always been the case. If you look back at the word clouds from previous meetings (see picture below), you see this pops up in the second meeting, and in the third meeting this becomes DEEP uncertainty. Is uncertainty increasing?
Regarding the policy domains and topics that are addressed ‘infrastructure’ and ‘climate’ stand out in this year’s meeting. The topic of ‘water’ follows after that. In previous years water was more present, while in the first meeting that was less of a clear policy topic that stood out. ‘Climate’ as topic for deep uncertainty has always been there, although less apparent in the titles of last years meeting. You might also notice a change from ‘robust decision making/analysis’ in the first meeting towards ‘adaptation/adaptive decision making’. The most outstanding difference the infrastructure in this year’s meeting. We are very much looking forward to hear more …
Word clouds are made with: http://www.wordle.net/create
The World Bank will host the 2016 DMDU workshop in Washington DC, on November 16 and 17, 2016, with a training on DMDU methodologies scheduled for November 15th, 2016. There is still place for the training, but it is running out fast. Please confirm here by October 15 if you have not done that already, to make sure we save you a spot! The annual meeting is fully booked. Please let us know if you will not come so there will be place for others to attend. Download the programme. Continue reading
by Laura Tuck and Julie Rozenberg, Sustainable Development Practice Group, World Bank Group
We all face uncertainties.
What if the train’s late? What if it rains? What if traffic is bad? What if there’s a shift in government before the project starts?
Every day we’re hit by all the “what ifs” especially in our line of work at the World Bank Group, whether in the field or within our organization. But how do we best cope with this? Embracing uncertainties may be the answer.
The World Bank Group has been at the forefront of mainstreaming new methods to deal with uncertainties. In fact, you may not know this, but the World Bank is one of the founding members of the Society for Decision Making Under Deep Uncertainty.
Today’s decision makers face conditions of fast-paced, transformative, and often surprising change. Traditional decision analysis relies on point and probabilistic predictions. But under conditions of deep uncertainty, predictions are often wrong, and relying on them can prove costly and dangerous. Fortunately, new methods and processes now exist to help decision makers identify and evaluate robust and adaptive strategies, thereby making sound decisions in the face of these challenges. Continue reading
by Joseph Guillaume
At the iEMSs2016 conference in Toulouse, the session on Decision Making under Deep Uncertainty (see blog report) was accompanied by a more generic one on “Managing Uncertainty”, organised by Joseph Guillaume (Aalto University), Tony Jakeman (Australian National University), Holger Maier (The University of Adelaide), Jiri Nossent (Flanders Hydraulics Research and Vrije Universiteit Brussel) and Evelina Trutnevyte (ETH Zurich).
The session emphasised the diversity of approaches for managing uncertainty. Contributions notably covered sensitivity analysis, scenario analysis, parameter estimation and uncertainty quantification. While not directly tied to Decision Making under Deep Uncertainty, it is important to remember that these techniques form the foundations of our analyses – the means of addressing any uncertainty that is not treated as deep. As argued in a recent publication in Environmental Modelling and Software (Maier at al. 2016), multiple paradigms for modelling the future tend to co-exist, with different parts of an analysis focussed on capturing best available knowledge, quantifying uncertainty, and exploring multiple plausible futures. Continue reading
by Rob Lempert and Jan Kwakkel,
The 8th International Congress on Environmental Modeling and Software in Toulouse, France, on July 10-14, 2016, featured a track titled Advancing in Environmental Decision Making Under Deep Uncertainty: Emerging Tools and Challenges. The track was co-organized by Jan Kwakkel (Delft University of Technology), Patrick Reed (Cornell), Robert Lempert (RAND Corporation), and Marjolijn Haasnoot (Deltares). The track consisted of four sessions with four papers in each session.
Registration for our annual workshop in Washington DC (November 16-17) is now closed.
This year’s workshop is organized around two key elements. First, the workshop will include 6 “problem-solving” sessions during which we will have group discussions around practical problems our Society members face in their work, and possible solutions. These will not be typical panel sessions since the audience will be actively involved. Second, the workshop will use posters as the primary means for participants to present their current work. The workshop will integrate posters in three ways: (1) pitches in the problem-solving sessions for posters that speak to the problems described; (2) pitches in poster sessions; (3) informal discussions around posters during all breaks and social times. You will find below a short description of the 6 sessions that were selected for group discussions. Continue reading
by Marjolijn Haasnoot (Deltares, Delft University), Judy Lawrence (New Zealand Climate Change Research Institute), Robert Lempert (RAND), Nidhi Kalra (RAND), Jan Kwakkel (Delft University)
In early November 2015 about 100 scientists and practitioners from all over the world shared their experiences and methods at the third annual meeting of the Society for Decision Making Under Deep Uncertainty in Delft, Netherlands. The workshop was hosted by Deltares, Delft University of Technology, and UNESCO-IHE and co-organized with RAND, the World Bank, Victoria University of Wellington’s Climate Change Research Institute, and staff of the Dutch Delta Programme.
Radke, N., Yousefpour, R., von Detten, R., Reifenberg, S., Hanewinkel, M.: Adopting robust decision-making to forest management under climate change. Ann Forest Sci, 2017; 74 (43): . : http://doi:10.1077/s13595-017-0641-s
Multi-objective robust decision making is a promising decision-making method in forest management under climate change as it adequately considers deep uncertainties and handles the long-term, inflexible, and multi-objective character of decisions. This paper provides guidance for application and recommendation on the design.
Recent studies have promoted the application of robust decision-making approaches to adequately consider deep uncertainties in natural resource management. Yet, applications have until now hardly addressed the forest management context.
This paper seeks to (i) assemble different definitions of uncertainty and draw recommendation to deal with the different levels in decision making, (ii) outline those applications that adequately deal with deep uncertainty, and (iii) systematically review the applications to natural resources management in order to (iv) propose adoption in forest management.
We conducted a systematic literature review of robust decision-making approaches and their applications in natural resource management. Different levels of uncertainty were categorized depending on available knowledge in order to provide recommendations on dealing with deep uncertainty. Robust decision-making approaches and their applications to natural resources management were evaluated based on different analysis steps. A simplified application to a hypothetical tree species selection problem illustrates that distinct robustness formulations may lead to different conclusions. Finally, robust decision-making applications to forest management under climate change uncertainty were evaluated and recommendations drawn.
Deep uncertainty is not adequately considered in the forest management literature. Yet, the comparison of robust decision-making approaches and their applications to natural resource management provide guidance on applying robust decision making in forest management regarding decision contexts, decision variables, robustness metrics, and how uncertainty is depicted.
As forest management is characterized by long decision horizons, inflexible systems, and multiple objectives, and is subject to deeply uncertain climate change, the application of a robust decision-making framework using a global, so-called satisficing robustness metric is recommended. Further recommendations are distinguished depending on the decision context.
Gao, L., Bryan, B.A., 2017. Finding pathways to national-scale land-sector sustainability. Nature 544(7649) 217–222. https://www.nature.com/nature/journal/v544/n7649/abs/nature21694.html
The 17 Sustainable Development Goals (SDGs) and 169 targets under Agenda 2030 of the United Nations map a coherent global sustainability ambition at a level of detail general enough to garner consensus amongst nations. However, achieving the global agenda will depend heavily on successful national-scale implementation, which requires the development of effective science-driven targets tailored to specific national contexts and supported by strong national governance. Here we assess the feasibility of achieving multiple SDG targets at the national scale for the Australian land-sector. We scaled targets to three levels of ambition and two timeframes, then quantitatively explored the option space for target achievement under 648 plausible future environmental, socio-economic, technological and policy pathways using the Land-Use Trade-Offs (LUTO) integrated land systems model. We show that target achievement is very sensitive to global efforts to abate emissions, domestic land-use policy, productivity growth rate, and land-use change adoption behaviour and capacity constraints. Weaker target-setting ambition resulted in higher achievement but poorer sustainability outcomes. Accelerating land-use dynamics after 2030 changed the targets achieved by 2050, warranting a longer-term view and greater flexibility in sustainability implementation. Simultaneous achievement of multiple targets is rare owing to the complexity of sustainability target implementation and the pervasive trade-offs in resource-constrained land systems. Given that hard choices are needed, the land-sector must first address the essential food/fibre production, biodiversity and land degradation components of sustainability via specific policy pathways. It may also contribute to emissions abatement, water and energy targets by capitalizing on co-benefits. However, achieving targets relevant to the land-sector will also require substantial contributions from other sectors such as clean energy, food systems and water resource management. Nations require globally coordinated, national-scale, comprehensive, integrated, multi-sectoral analyses to support national target-setting that prioritizes efficient and effective sustainability interventions across societies, economies and environments.
McCurdy, A. and W. Travis (2017) Simulated climate adaptation in stormwater systems: evaluating the efficiency of adaptation strategies. Environment Systems and Decisions. Published online: http://link.springer.com/article/10.1007/s10669-017-9631-z
Adaptations in infrastructure may be necessitated by changes in temperature and precipitation patterns to avoid losses and maintain expected levels of service. A roster of adaptation strategies has emerged in the climate change literature, especially with regard to timing: anticipatory, concurrent, or reactive. Significant progress has been made in studying climate change adaptation decision making that incorporates uncertainty, but less work has examined how strategies interact with existing infrastructure characteristics to influence adaptability. We use a virtual testbed of highway drainage crossings configured with a selection of actual culvert emplacements in Colorado, USA, to examine the effect of adaptation strategy and culvert characteristics on cost efficiency and service level under varying rates of climate change. A meta-model approach with multinomial regression is used to compare the value of better climate change predictions with better knowledge of existing crossing characteristics. We find that, for a distributed system of infrastructural units like culverts, knowing more about existing characteristics can improve the efficacy of adaptation strategies more than better projections of climate change. Transportation departments choosing climate adaptation strategies often lack detailed data on culverts, and gathering that data could improve the efficiency of adaptation despite climate uncertainty.
Su H, Dong F, Liu Y, Zou R, and Guo H. 2017. Robustness-Optimality Tradeoff for Watershed Load Reduction Decision Making under Deep Uncertainty. Water Resour Manag:1-14.
Practical and optimal reduction of watershed loads under deep uncertainty requires sufficient search alternatives and direct evaluation of robustness. These requirements contribute to the understanding of the tradeoff between cost and robustness; while they are not well addressed in previous studies. This study thereby (a) uses preconditioning technique in Evolutionary Algorithm to reduce unnecessary search space, which enables a sufficient search; and (b) derives Robustness Index (RI) as a second-tier optimization objective function to achieve refined solutions (solved by GA) that address both robustness and optimality. Uncertainty-based Refined Risk Explicit Linear Interval Programming is used to generate alternatives (solved by Controlled elitist NSGA-II). The robustness calculation error is also quantified. Proposed approach is applied to Lake Dianchi, China. Results demonstrate obvious improvement in robustness after conducting sufficient search and negative robustness-optimality trade-offs, and provides a detailed characteristic of robustness that can serve as references for decision-making.
Robustness index Deep uncertainty Tradeoff Optimality Load reduction
Quinn, J. D., P. M. Reed and K. Keller (2017). “Direct policy search for robust multi-objective management of deeply uncertain socio-ecological tipping points.” Environmental Modelling & Software 92, http://dx.doi.org/10.1016/j.envsoft.2017.02.017: 125-141.
Managing socio-ecological systems is a challenge wrought by competing societal objectives, deep uncertainties, and potentially irreversible tipping points. A classic, didactic example is the shallow lake problem in which a hypothetical town situated on a lake must develop pollution control strategies to maximize its economic benefits while minimizing the probability of the lake crossing a critical phosphorus (P) threshold, above which it irreversibly transitions into a eutrophic state. Here, we explore the use of direct policy search (DPS) to design robust pollution control rules for the town that account for deeply uncertain system characteristics and conflicting objectives. The closed loop control formulation of DPS improves the quality and robustness of key management tradeoffs, while dramatically reducing the computational complexity of solving the multi-objective pollution control problem relative to open loop control strategies. These insights suggest DPS is a promising tool for managing socio-ecological systems with deeply uncertain tipping points.
Trindade, B. C., P. M. Reed, J. D. Herman, H. B. Zeff and G. W. Characklis (2017). “Reducing regional drought vulnerabilities and multi-city robustness conflicts using many-objective optimization under deep uncertainty.” Advances in Water Resources 104, https://doi.org/10.1016/j.advwatres.2017.03.023: 195-209.
Emerging water scarcity concerns in many urban regions are associated with several deeply uncertain factors, including rapid population growth, limited coordination across adjacent municipalities and the increasing risks for sustained regional droughts. Managing these uncertainties will require that regional water utilities identify coordinated, scarcity-mitigating strategies that trigger the appropriate actions needed to avoid water shortages and financial instabilities. This research focuses on the Research Triangle area of North Carolina, seeking to engage the water utilities within Raleigh, Durham, Cary and Chapel Hill in cooperative and robust regional water portfolio planning. Prior analysis of this region through the year 2025 has identified significant regional vulnerabilities to volumetric shortfalls and financial losses. Moreover, efforts to maximize the individual robustness of any of the mentioned utilities also have the potential to strongly degrade the robustness of the others. This research advances a multi-stakeholder Many-Objective Robust Decision Making (MORDM) framework to better account for deeply uncertain factors when identifying cooperative drought management strategies. Our results show that appropriately designing adaptive risk-of-failure action triggers required stressing them with a comprehensive sample of deeply uncertain factors in the computational search phase of MORDM. Search under the new ensemble of states-of-the-world is shown to fundamentally change perceived performance tradeoffs and substantially improve the robustness of individual utilities as well as the overall region to water scarcity. Search under deep uncertainty enhanced the discovery of how cooperative water transfers, financial risk mitigation tools, and coordinated regional demand management must be employed jointly to improve regional robustness and decrease robustness conflicts between the utilities. Insights from this work have general merit for regions where adjacent municipalities can benefit from cooperative regional water portfolio planning.