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: 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
Internally-consistent scenarios are increasingly used in social–ecological systems modelling to explore how a complex system might be influenced by deeply uncertain future conditions such as climate, population, and demand and supply of resources and energy. The presence of deep uncertainty requires model diagnostic techniques such as global sensitivity analysis to provide reliable diagnostic insights that are robust to highly uncertain future conditions. We extended the elementary effects method of Morris, which is widely used to screen important model input factors at low computational cost, by incorporating deep uncertainty via the use of scenarios, and evaluated its potential as a robust global sensitivity analysis approach. We applied this robust elementary effects (rEE) method to the highly-parameterised Australian continental Land Use Trade-Offs (LUTO) model—a complex, non-linear model with strong interactions between parameters. We compared rEE sensitivity indicators with robust global sensitivity analysis (RGSA) indicators based on the variance-based eFAST method that imposes relatively high computational demand. We found that the rEE method provided a good approximation of the main effects and was effective in screening the most influential model parameters under deep uncertainty at a greatly reduced computational cost. However, the rEE method was not able to match the accuracy of the eFAST-based method in identifying the most influential parameters in the complex LUTO model based on their total effects. We conclude that the rEE method is well-suited for screening complex models, and possibly for efficient RGSA of models with weak interaction effects, but not for RGSA of complex models. Despite its limitations, rEE is a valuable addition to the robust global sensitivity analysis toolbox, helping to provide insights into model performance under deep uncertainty.
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