Planning & Management

Oral

394310 - Combining robust decision frameworks and imperfect probabilistic projections to support climate change adaptation under uncertainty

Monday, June 4
2:00 PM - 3:30 PM
Location: Greenway GH
Co-Authors: Benjamin Zaitchik, Baltimore, MD – Johns Hopkins University

Avoiding negative impacts from climate change will require that water infrastructure is built and upgraded with future climate change in mind, particularly in long-lived systems that will be operating decades into the future. However, one challenge in incorporating climate change into infrastructure planning is the uncertainty surrounding climate change projections generated by global circulation models (GCMs). This uncertainty has been addressed in different ways. For example, some researchers use ensembles of GCMs to generate probabilistic climate change projections, but these projections can be highly sensitive to assumptions about model independence and weighting schemes. Because of these issues, other argue that robustness-based approaches to climate adaptation are more appropriate, since they don’t rely on a precise probabilistic representation of uncertainty. In this research, we present an approach to infrastructure planning under climate change that leverages methods from both robustness-based and probabilistic frameworks. The Scenario Discovery process is used to search across a multi-dimensional space and identify the climate scenarios most associated with system failure, and a Bayesian statistical model informed by GCM projections is then developed to estimate the probability of those scenarios under different assumptions. This provides an important advancement in that it can incorporate various decision-centric climate variables, and multiple statistical model formulations can be used to account for uncertainty in probabilistic estimates in a straightforward way. We demonstrate the methodology using proposed water resources infrastructure in Lake Tana, Ethiopia, where GCM disagreement on changes in future rainfall presents a major challenge for reservoir planning.

Julie Shortridge, Ph.D.

Department of Biological Systems Engineering, Virginia Tech

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394310 - Combining robust decision frameworks and imperfect probabilistic projections to support climate change adaptation under uncertainty



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