Show simple item record

dc.contributor.advisorFrisvold, George
dc.contributor.authorDew, Taylor J.
dc.creatorDew, Taylor J.
dc.date.accessioned2022-02-23T21:06:17Z
dc.date.available2022-02-23T21:06:17Z
dc.date.issued2021
dc.identifier.citationDew, Taylor J. (2021). It is a Dry Heat: Econometric Model of Historic Fires (Master's thesis, University of Arizona, Tucson, USA).
dc.identifier.urihttp://hdl.handle.net/10150/663407
dc.description.abstractSeveral studies have applied regression analysis to measure factors contributing to larger wildfire suppression costs. They often include acres burned, variables that are functions of acres burned, or both. This can create problems of simultaneity bias. While it is common for studies to use instrumental variable methods to address simultaneity, they in general do not evaluate the strength or weakness of their instruments. Another drawback of using acres burned as an explanatory variable is that regression models have limited value in forecasting suppression costs ahead of time, because suppression and burning occur at the same time. This study takes a different approach, relying on variables that can be used as soon as fire starts. It attempts to answer the question, given that a fire has started, what accounts for it having higher suppression costs and more burned acres? Data from the Burned Area Emergency Response (BAER) reports are combined with other geo-coded variables to examine wildfires in Arizona’s national forests from 2002-2019. Regressions were run for three different variables: (a) natural log of suppression costs, (b) natural log of acres burned, and (c) a binary variable that equaled one if the fire was greater than 30,000 acres and zero otherwise. The regression results suggest that Arizona wildfires that start in May and June are positively associated with higher suppression costs and more acres burned. This suggests benefits of increased vigilance of fire managers during these months. This variable was less able to predict the occurrence of the very largest fires, however. The amount of land in the Wildland Urban Interface (WUI) was negatively associated with fire suppression costs and not a significant predictor of fire size. Past empirical results regarding the WUI have been mixed. Average relative humidity was a significant (negative) predictor of both suppression costs and of very large fires. This variable has not been much used in previous studies and may become important if aridity in Arizona increases with climate change.
dc.language.isoen
dc.publisherThe University of Arizona.
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.titleIt is a Dry Heat: Econometric Model of Historic Fires
dc.typetext
dc.typeElectronic Thesis
thesis.degree.grantorUniversity of Arizona
thesis.degree.levelmasters
dc.contributor.committeememberThompson, Gary
dc.contributor.committeememberScheitrum, Daniel
thesis.degree.disciplineGraduate College
thesis.degree.disciplineAgricultural & Resource Economics
thesis.degree.nameM.S.
refterms.dateFOA2022-02-23T21:06:17Z


Files in this item

Thumbnail
Name:
azu_etd_19377_sip1_m.pdf
Size:
1.894Mb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record