Automated Strategic Prioritization Matchmaking Tool to Facilitate Federal–Community Adaptation Implementation

Abstract

Lack of available resources has been identified as a significant barrier for community implementation of climate adaptation actions. Although a broad array of federal resources exists, it is difficult for communities to match their specific needs with appropriate agency programs. We produced an automated, easy-to-use, decision-support tool to facilitate communities’ finding of appropriate federal partners. The Automated StrAtegic Prioritization (ASAP) tool combines engineering design methods with semantic vector space models (VSMs) to calculate a similarity score between community climate vulnerabilities and related US federal agency strategic plans (SPs) based on their latent semantic similarities. The VSMs were trained using federal SPs and verified using the corresponding federal agencies’ climate change adaptation plans (CCAPs). Two commonly used VSM weighting schemes were tested, and the superior scheme was used in the final ASAP model. The ASAP model was then tested using sector-specific vulnerability statements developed by the community of Keene, New Hampshire for their CCAP. ASAP’s results compared well to published records of federal funding data for Keene. ASAP should be a useful tool for communities involved in adaptation planning. The results of ASAP will also be helpful for federal agencies seeking to collaborate on disaster relief efforts. The results presented here demonstrate synergies in community–federal partnerships and federal–federal partnerships that will enable more effective implementation of climate adaptation plans, improve community climate preparedness and resilience, and can help reduce the nation’s overall vulnerability to climate change.