Journal article
On the use of Cox regression to examine the temporal clustering of flooding and heavy precipitation across the central United States
Global and planetary change, Vol.155, pp.98-108
08/2017
DOI: 10.1016/j.gloplacha.2017.07.001
Abstract
The central United States is plagued by frequent catastrophic flooding, such as the flood events of 1993, 2008, 2011, 2013, 2014 and 2016. The goal of this study is to examine whether it is possible to describe the occurrence of flood and heavy precipitation events at the sub-seasonal scale in terms of variations in the climate system. Daily streamflow and precipitation time series over the central United States (defined here to include North Dakota, South Dakota, Nebraska, Kansas, Missouri, Iowa, Minnesota, Wisconsin, Illinois, West Virginia, Kentucky, Ohio, Indiana, and Michigan) are used in this study. We model the occurrence/non-occurrence of a flood and heavy precipitation event over time using regression models based on Cox processes, which can be viewed as a generalization of Poisson processes. Rather than assuming that an event (i.e., flooding or precipitation) occurs independently of the occurrence of the previous one (as in Poisson processes), Cox processes allow us to account for the potential presence of temporal clustering, which manifests itself in an alternation of quiet and active periods. Here we model the occurrence/non-occurrence of flood and heavy precipitation events using two climate indices as time-varying covariates: the Arctic Oscillation (AO) and the Pacific-North American pattern (PNA). We find that AO and/or PNA are important predictors in explaining the temporal clustering in flood occurrences in over 78% of the stream gages we considered. Similar results are obtained when working with heavy precipitation events. Analyses of the sensitivity of the results to different thresholds used to identify events lead to the same conclusions. The findings of this work highlight that variations in the climate system play a critical role in explaining the occurrence of flood and heavy precipitation events at the sub-seasonal scale over the central United States.
•Examination of the climate controls on floods across the central US•Analyses performed at the subseasonal scale using Cox regression.•Artic Oscillation and Pacific North American pattern are important predictors.•Similar results for heavy precipitation
Details
- Title: Subtitle
- On the use of Cox regression to examine the temporal clustering of flooding and heavy precipitation across the central United States
- Creators
- Iman Mallakpour - University of IowaGabriele Villarini - University of IowaMichael P Jones - University of IowaJames A Smith - Princeton University
- Resource Type
- Journal article
- Publication Details
- Global and planetary change, Vol.155, pp.98-108
- Publisher
- Elsevier B.V
- DOI
- 10.1016/j.gloplacha.2017.07.001
- ISSN
- 0921-8181
- eISSN
- 1872-6364
- Grant note
- DOI: 10.13039/100000001, name: National Science Foundation, award: AGS-1349827; name: Broad Agency Announcement; DOI: 10.13039/100006505, name: Engineer Research and Development Center; DOI: 10.13039/100006752, name: USACE, award: W913E5-16-C-0002; name: IIHR; name: Iowa Flood Center
- Language
- English
- Date published
- 08/2017
- Academic Unit
- Statistics and Actuarial Science; Biostatistics; Civil and Environmental Engineering; Public Policy Center (Archive)
- Record Identifier
- 9984197178902771
Metrics
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