All in order: distribution of serially correlated order statistics with applications to hydrological extremes
- Submitting institution
-
University of Newcastle upon Tyne
- Unit of assessment
- 12 - Engineering
- Output identifier
- 267976-133487-1293
- Type
- D - Journal article
- DOI
-
10.1016/j.advwatres.2020.103686
- Title of journal
- Advances in Water Resources
- Article number
- 103686
- First page
- -
- Volume
- 144
- Issue
- -
- ISSN
- 0309-1708
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2020
- URL
-
https://doi.org/10.1016/j.advwatres.2020.103686
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The work presents a fundamental analysis and new modelling approach to better represent and understand sequences of flooding accounting for clustering in time. The work was sponsored by the insurance industry Willis Research Network and informs their analysis of time varying flood risk and portfolio exposure.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -