Project
Managing Water Quality in the Face of Uncertainty: A Robust Decision Making Demonstration for EPA’s National Water Program
Sep 9, 2015
The U.S. Environmental Protection Agency and its partners develop implementation plans to meet water quality standards. Climate change and other key drivers may significantly affect these plans, but are often neglected due to uncertainty. This study uses two case studies to demonstrate how Robust Decision Making (RDM) can help to address future uncertainty by identifying vulnerabilities in water quality plans and suggesting appropriate responses.
A Robust Decision Making Demonstration for EPA's National Water Program
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The U.S. Environmental Protection Agency (USEPA), together with its state and local partners, develops watershed implementation plans designed to meet total maximum daily load (TMDL) water quality standards. Uncertainty regarding the impacts of climate change, future land use, the effectiveness of best management practices, and other drivers may make it difficult for these implementation plans to meet water quality goals. But the methods and processes used to develop implementation plans typically do not address uncertainty in these key drivers of change. In this study, RAND researchers explored how Robust Decision Making (RDM) methods could help USEPA and its partners develop implementation plans that are more robust to such uncertainty. Through two pilot case studies — one on the Patuxent River in Maryland and one on the North Farm Creek tributary of the Illinois River — this study shows how analytic RDM methods can be used to identify future vulnerabilities in TMDL implementation plans and suggest appropriate responses. In both case studies, proposed plans meet their water quality goals under current assumptions, but do not meet water quality goals in many climate and other futures. The study finds that modified plans and adaptive management approaches can often reduce these vulnerabilities. Moving forward, USEPA and its partners can better manage future uncertainty by employing iterative risk management processes and adopting TMDL implementation plans that are robust and flexible.
Chapter One
Water Quality Decisions Are Challenged by Future Uncertainty
Chapter Two
Analytic Tools for Robust Adaptive Water Quality Management
Chapter Three
Managing Storm Water in Maryland's Patuxent River Basin with Climate and Land Use Uncertainty
Chapter Four
Evaluating the Impacts of Climate Change on the Water Quality Implementation Plan for the North Farm Creek Tributary of the Illinois River
Chapter Five
Implications for USEPA Water Quality Management
Appendix A
Iterative Risk Management Process for Setting Water Quality Standards
Appendix B
Criteria for Choosing Case Studies
Appendix C
Supplemental Information for the Patuxent River Case Study
Appendix D
SWAT Model Calibration and Validation
The research reported here was conducted in the RAND Environment, Energy, and Economic Development Program, a part of RAND Justice, Infrastructure, and Environment.
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