What factors predict the quality of hazard mitigation plans in Washington State?

Citation metadata

Date: Jan. 2021
From: Climatic Change(Vol. 164, Issue 1-2)
Publisher: Springer
Document Type: Report; Brief article
Length: 267 words

Document controls

Main content

Abstract :

Keywords: Adaptation; Collaboration; Diffusion; Hazard mitigation Abstract Hazard mitigation plans can help to reduce communities' losses when faced with natural hazards, some of which (e.g., floods) are projected to intensify with climate change. A growing body of plan evaluation literature seeks to measure the quality of these plans, given that higher-quality plans may be more likely to achieve their objectives (e.g., reducing a community's losses from flooding). Processes of collaboration (i.e., joint decision-making by various agencies and stakeholders) and diffusion (i.e., the spread of ideas between jurisdictions over time and space), among others, may influence plan quality, although empirical evidence is limited. This study assessed potential predictors of plan quality for 33 county-level hazard mitigation plans in Washington State, using a combination of survey data, county characteristics, and previously determined plan quality scores. Significant predictors of plan quality included indicators of vertical (state-to-county) and horizontal (county-to-county) diffusion, as well as economic capacity, although indicators of collaborative dynamics, along with several other hypothesized predictors, including past disaster experience (i.e., severity) were not significant. Hazard planning professionals at the federal, state, and local levels may benefit from integrating these findings into future work, in conjunction with other climate change adaptation initiatives. Specifically, fostering peer-to-peer interactions between counties might help to produce and disseminate knowledge about climate solutions. Author Affiliation: (1) School of Environmental and Sustainability Sciences, Kean University, 1000 Morris Avenue, 07083, Union, NJ, USA (2) Department of Chemistry and Physics, Monmouth University, 400 Cedar Avenue, 07764, West Long Branch, NJ, USA (a) danielscottfeinberg@gmail.com Article History: Registration Date: 01/07/2021 Received Date: 07/23/2020 Accepted Date: 01/06/2021 Online Date: 01/14/2021 Byline:

Source Citation

Source Citation   

Gale Document Number: GALE|A649299601