Integrating Robust Decision Making (RDM) and Dynamic Adaptive Policy Pathways (DAPP): Towards a Unified Decision Making Framework under Deep Uncertainty

With exogenous factors such as climate change, future demand, resource options, technological and economic constraints, water agency plans should be robust and able to be adapted over time to meet agency goals over a wide range of plausible future conditions. A variety of new approaches and computational tools are being put forward to aid decision making under deep uncertainty (DMDU). Robust Decision Making (RDM) and Dynamic Adaptive Policy Pathways (DAPP) are the two frameworks that have been applied recently to a variety of problems. While RDM facilitates the analysis of trade-offs and the iterative learning about a policy problem, DAPP offers a map of possible routes into the future giving insight into future actions that can be taken if the initial actions prove to be insufficient, thus, alleviating the irreversibility of decisions. This paper first investigates into both approaches, and then suggest a way to combine elements from both so as to produce a more unified decision making framework under deep uncertainty. Integrated Resource Plan (IRP) 2013 submitted by British Columbia Hydro and Power Authority (BC Hydro) is considered for the analyses. Main focus is on identification of scenarios that highlight the vulnerabilities of IRP strategies in different state of the world using RDM approach and then employing DAPP to identify demand and climate-related signposts. This work will inform decision makers and stakeholders to adapt robust plans in upcoming IRP 2018.