Author(s): P. G. Kathleen O’Neil; David Yates
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Keywords: No Keywords
Abstract: A method of scenario based planning is used to explore the resilience of water management strategies across plausible ranges of uncertainty in key driving variables (e.g., climate, population, emission requirements, etc.). With stakeholders, this method is combined with dynamic systems simulation, mulit-criteria decision analysis, and triple bottom line accounting techniques. Various types of uncertainty can be identified in planning, modeling, and policy decision making. A few types include: model parameter variability, uncertainty or error propagated within a model, classic risk analysis, and “future uncertainties” or variables whose future trends are not easily predicted based on past observations. Traditional models rely on historic data and historic trends to calibrate present conditions and to project paths for future conditions. However, a new paradigm is emerging where decision makers are realizing that it may not be valid to assume historic trends will be consistent into the future. An awareness of the dynamic and non-linear nature of systems has led to new methods in planning that look across a range of sets of plausible future conditions. Policy makers are often faced with the dilemma of comitting to large capital investments, over long planning horizons, without a “whole system” framework to evaluate the efficiency and sustainA¬ability of alternatives. With a multi-disciplinary team, this project builds on prior projects sponsored by Palm Beach County Water Utility, AwwaRF, and NCAR including a Dynamic Decision Support System and climate-based scenarios using SEI's Water Evaluation and Planning (WEAP) tool. The output supports “Triple Bottom Line” accounting, ranking alternatives against social, environmental, and economic sustainability criteria. These tools address emerging issues such as: Linking dynamic scenarios to decision analysis, Scenario planning processes in stakeholder mediation, and Planning under a range of possible futures (uncertainty in key drivers).
Year: 2009