Regional natural hazard risk modeling: incorporating a dynamic housing inventory model
| Author(s) | Williams, Caroline J. | |
| Date Accessioned | 2023-10-09T17:44:28Z | |
| Date Available | 2023-10-09T17:44:28Z | |
| Publication Date | 2023 | |
| SWORD Update | 2023-09-20T19:10:40Z | |
| Abstract | Today's regional natural hazards loss models rarely incorporate changes in a region's built environment over time, and thus likely misestimate a region's natural hazard risk. Of the existing natural hazard loss models that incorporate changes in the built environment, none are developed at an adequately granular spatiotemporal scale that is appropriate for regional (multi-county) natural hazards loss modeling. Therefore, this dissertation presents new methods for estimating changes in a region's housing inventory for natural hazards loss modeling purposes. First, a method for estimating changes in the number of housing units across a multi-county region over multiple decades is presented and applied to a study area in southeastern Texas to compare the economic impacts experienced following Hurricane Harvey in 2017 versus the expected economic impacts in 2039 under a Hurricane Harvey-type event. A separate method is also presented that estimates the location of new housing units over a subcounty grid space and is applied to a study area in the eastern half of North Carolina to investigate the expected changes in the number of houses impacted by a Hurricane Florence-type event in 2049. Alternative development scenarios are then compared using a new analysis method that assists in understanding how different regional risk-informed land use policy scenarios are projected to affect the spatial distribution of future housing construction, future expected natural hazard losses, as well as changes in expected property tax revenues. The method is illustrated by comparing projected housing development patterns and hurricane loss impacts under a business-as-usual land use scenario and three risk-informed land use policy scenarios in the eastern half of North Carolina over a 30-year projection period. The method identifies where natural hazard losses are highest and where property tax revenue is expected to shift due to changes in development patterns, which can allow planners and risk managers to understand long-term expected impacts under different land use policy alternatives. The methods can be adapted to allow investigation of other regions, hazards, and land use policies. | |
| Advisor | Davidson, Rachel A. | |
| Degree | Ph.D. | |
| Department | University of Delaware, Department of Civil and Environmental Engineering | |
| DOI | https://doi.org/10.58088/k4r3-bn25 | |
| Unique Identifier | 1410123933 | |
| URL | https://udspace.udel.edu/handle/19716/33474 | |
| Language | en | |
| Publisher | University of Delaware | |
| URI | https://login.udel.idm.oclc.org/login?url=https://www.proquest.com/dissertations-theses/regional-natural-hazard-risk-modeling/docview/2868525511/se-2?accountid=10457 | |
| Keywords | Housing projections | |
| Keywords | Land use | |
| Keywords | Natural hazards | |
| Keywords | Risk modeling | |
| Keywords | Housing development patterns | |
| Title | Regional natural hazard risk modeling: incorporating a dynamic housing inventory model | |
| Type | Thesis |