Determining the optimal set of storm response centers Climate Resilient PVD Determining the optimal set of storm response centers I developed a methodology for determining the optimal set of storm response centers out of pre-existent community hubs around Providence

Background Coastal cities have always been vulnerable to storms and flooding Climate change may increase the risk of extreme weather events Some effects include loss of electricity, disruptions to vital infrastructure, blocked roads, property damage 1:30 Hurricane Irene in 2011, Hurricane Sandy in 2012. While Sandy caused more damage in the upper Mid-Atlantic, Irene hit New England pretty hard. The storm resulted in 100s of downed trees and power lines, leaving 10,000s of Providence resident without electricity. Climate change is estimated to cause local sea level rise of 2.6–4’ by 2100 under intermediate/high pollution scenarios. These prediction do not account for non-linear dynamics in Antarctic ice sheet melting, which is a distinct possibility. Sea level rise would greatly increase the frequency and intensity of storm surge flooding. Climate change is also predicted to increase weather variability -> more intense storms. This is partly the result of greater energy availability due to warm ocean Storms can lead to loss of electricity and damage to property/roads, which can have potentially devastating effects on vital infrastructure like hospitals, grocery stores (food availability), and fresh water. Driving conditions might be dangerous Photo via U.S. Army Corps of Engineers Photo via Climate Central

Background Providence Design and Resilient Team Report – February, 2016 Interdisciplinary public service program of the AIA and New England Municipal Sustainability Network Emphasis on community hubs (i.e. schools, libraries, rec centers) that can be equipped with storm response plans and emergency supplies Due to limited city resources and funding, a subset of community hubs would need to be identified as the optimal combination of storm response centers 30 sec (2:00) Providence DART was a multidisciplinary, cross-scale program that convened members of the AIA, New England Municipal Sustainability Network, Arup, City of Providence, and local residents. Resulted in a framework for future climate change resilience and urban development Community hubs are identified as an important resource Photos via Wikipedia, Providence DART, and Mapping Arts Project

Overview Two service areas were produced for each hub: high access ( <0.5 mile) and moderate access ( <1 mile) Scores are produced for every combination of n community hubs based on the total population served (P), multiplied by a weighted mean flood risk index (FRI) and a social vulnerability index (SVI) ScoreH,M = (P) (mean FRI) (mean SVI) Final Score = C1 (ScoreH) + C2 (ScoreM) 1 min (3:00)

Data All geographic data (roads, municipal boundaries, libraries, schools, buildings, flood surfaces) acquired from RIGIS. All population and demographic data acquired from the 2015 American Communities Survey via the U.S. Census Bureau. List of 114 community hubs was compiled from libraries, schools, and recreation/community centers Network Analyst was used to define service areas for each hub using only local roads (no highway) Population and weighted SVI/FRI attributes were assigned to all residential buildings in Providence 30 s (3:30)

ScoreH,M = (P) (mean FRI) (mean SVI) Population Every residential building is assigned a population value by: P = (census tract population)/ (# of residential buildings in census tract) 30 s (4:00) ScoreH,M = (P) (mean FRI) (mean SVI)

ScoreH,M = (P) (mean FRI) (mean SVI) Flood Risk Index Every building is assigned an FRI based on distance from the 100-yr flood plane 30 s (4:30) ScoreH,M = (P) (mean FRI) (mean SVI)

Social Vulnerability Index Every building is assigned an SVI based on their census tract Each census tract has an SVI calculated as the sum of five factors: persons under 5, persons over 65, median income, reliance on public transportation, and non-white population. Each is normalized to a maximum value of 1 1 min (5:30) ScoreH,M = (P) (mean FRI) (mean SVI)

1 min (6:30)

Case Study Number of storm response centers, n, equals 3 (240,464 unique combinations) Scores are combined by: Final Score = 0.4 (ScoreH) + 0.6 (ScoreM) A) Selim Rogers Rec Center, Brown, and Joslin Community Center B) S. Providence Library, Brown, Blessed Sacrament School C) Providence Public Library, Blessed Sacrament School, Harry Kizirian Elementary 1.5 min (8:00)

Combination C Final Score: 81.5 PM = 51,060 Also well-suited to solar panel installation, access, and community outreach 30 s (8:30) Photos via Google Maps

Suggestions for toolset use Designed to be modified by the user The relative weight of different variables can be changed Assess the benefit of more or fewer designated storm response centers (ex. compare the pre-normalized scores for a combination of 3 vs. 4 hubs) Should be supplemented with due research and consideration Capacity, solar access, community outreach potential, and storage are all important factors to consider Future work could potentially integrate these factors into the scoring algorithm 1 min (9:30)

Works Cited Providence Design and Resilient Team Report (2016). American Institute of Architects and New England Municipal Sustainability Network Social Vulnerability Analysis: A Comparison of Tools (2013). U.S. Army Corps of Engineers RIGIS 2015 American Community Survey (2015). U.S. Census Bureau Stoller, Gary. “Irene leaves up to half of Rhode Island without power” (2011). USA Today.