Feature Figure 1: A no-adaptation action scenario modeled for downtown Mystic in Groton, Connecticut. Expected losses in real property and building contents damage from a simulated 10-year flood event projected for 2070 with 1 m of SLR are shown as extruded polygons. About the Authors Sam Merrill, Ph.D., has been with the Muskie School of Public Service for nine years. Previously, he worked for the Minnesota Department of Natural Resources. His graduate work was in the area of GPS radiotelemetry on large carnivores. Damon Yakovleff is a graduate student studying community planning and development at the University of Southern Maine's Muskie School of Public Service. David Holman is an MBA candidate at the University of Southern Maine's School of Business. Joe Cooper is a utility engineer technician; a supervisor for the City of Saco, Maine; and a freelance GIS analyst. Dr. Paul Kirshen joined Battelle as research leader in June 2009 after 13 years at Tufts University as cofounder and director of the Tufts University Water: Systems, Science, and Society (WSSS) Interdisciplinary Research and Graduate Education Program and research professor in civil and environmental engineering. He has 30 years of experience in the management of complex, interdisciplinary, stakeholder-driven projects and research with many investigators and institutions related to climate variability and change, the coastal zone, and water resources. age to real property and building contents. The adaptive actions modeled for this location include installing a hurricane barrier, elevating a road, and building dikes. Each action could provide some protection to the vulnerable areas. Visually, each action is represented in these maps using the same perspective and showing polygon extrusion for each adaptation action being considered. This is an effective way of showing up-front and maintenance costs of hard-structure approaches versus expected damages from particular inundation events. Soft-structure approaches can also be modeled, such as floodproofing and rezoning over time. More important, this approach also allows modeling of ranges of SLR heights and storm surge frequency and intensity. Combined outputs of multiple future scenarios provide an opportunity for stakeholders to select future conditions that match their expectations and visualize the predicted damages using both action and no-action scenarios. Benefits of This Approach The COAST approach also encompasses more than single event modeling. For multidecade periods, the approach produces cumulative expected damage tallies in tabular form for a given set of conditions and adaptation actions. This allows expected damages from increased flood frequency to be quantified over time as www.esri.com well as identifying robust adaptation strategies that may function acceptably and save money under any climate scenario. Early applications suggest that parcelbased, graphic display of local vulnerabilities illustrating the likely benefits of taking adaptive actions is a powerful new way to engage local communities in proactive planning in protecting vulnerable economic assets. Work to date has been supported primarily by the U.S. Environmental Protection Agency, in collaboration with ICLEI—Local Governments for Sustainability USA; the Connecticut Department of Environmental Protection; officials in Old Orchard Beach, Maine; and other organizations. Further applications to broaden the suite of expected damage profiles are in development with the U.S. EPA; NOAA; and several cities, including Portland, Maine. For more information, contact Sam Merrill, Ph.D. Director, New England Environmental Finance Center Assistant Research Professor Muskie School of Public Service University of Southern Maine Portland, Maine 04069 Tel.: 207-228-8596 E-mail: smerrill@usm.maine.edu ArcUser Fall 2010 29