Design metrics for extreme events in a non-stationary world. [Abstract oly]
Society is increasingly concerned with how climate, land use and other anthropogenic influences are impacting their watersheds. Traditional probabilistic approaches for defining risk, reliability and return periods under stationary hydrologic conditions assume that extreme events are serially indepe...
| Main Authors: | , , |
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| Format: | Conference Paper |
| Language: | Inglés |
| Published: |
2014
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/67633 |
| _version_ | 1855532209522343936 |
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| author | Read, L. Vogel, R. Lacombe, Guillaume |
| author_browse | Lacombe, Guillaume Read, L. Vogel, R. |
| author_facet | Read, L. Vogel, R. Lacombe, Guillaume |
| author_sort | Read, L. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Society is increasingly concerned with how climate, land use and other anthropogenic influences are impacting their watersheds. Traditional probabilistic approaches for defining risk, reliability and return periods under stationary hydrologic conditions assume that extreme events are serially independent with a probability distribution whose moments and associated parameters are fixed. However, when non-stationary conditions lead to trends in the moments and parameters of extreme value processes, new methods for understanding the impacts of such changes on traditional design metrics are needed to insure sensible planning and design efforts. We document the general behavior of various metrics of return period, risk, and reliability assuming extreme events follow a nonstationary lognormal distribution. Our results provide guidance on the value, application and caveats associated with such metrics for water resources planning in a nonstationary world. |
| format | Conference Paper |
| id | CGSpace67633 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2014 |
| publishDateRange | 2014 |
| publishDateSort | 2014 |
| record_format | dspace |
| spelling | CGSpace676332025-03-11T09:50:20Z Design metrics for extreme events in a non-stationary world. [Abstract oly] Read, L. Vogel, R. Lacombe, Guillaume statistical methods design water resources planning Society is increasingly concerned with how climate, land use and other anthropogenic influences are impacting their watersheds. Traditional probabilistic approaches for defining risk, reliability and return periods under stationary hydrologic conditions assume that extreme events are serially independent with a probability distribution whose moments and associated parameters are fixed. However, when non-stationary conditions lead to trends in the moments and parameters of extreme value processes, new methods for understanding the impacts of such changes on traditional design metrics are needed to insure sensible planning and design efforts. We document the general behavior of various metrics of return period, risk, and reliability assuming extreme events follow a nonstationary lognormal distribution. Our results provide guidance on the value, application and caveats associated with such metrics for water resources planning in a nonstationary world. 2014 2015-07-30T06:07:51Z 2015-07-30T06:07:51Z Conference Paper https://hdl.handle.net/10568/67633 en Limited Access Read, L.; Vogel, R.; Lacombe, Guillaume. 2014. Design metrics for extreme events in a non-stationary world. [Abstract oly] Paper presented at the World Environmental and Water Resources Congress, Portland, Oregon, USA, 1-5 June 2014. 1p. |
| spellingShingle | statistical methods design water resources planning Read, L. Vogel, R. Lacombe, Guillaume Design metrics for extreme events in a non-stationary world. [Abstract oly] |
| title | Design metrics for extreme events in a non-stationary world. [Abstract oly] |
| title_full | Design metrics for extreme events in a non-stationary world. [Abstract oly] |
| title_fullStr | Design metrics for extreme events in a non-stationary world. [Abstract oly] |
| title_full_unstemmed | Design metrics for extreme events in a non-stationary world. [Abstract oly] |
| title_short | Design metrics for extreme events in a non-stationary world. [Abstract oly] |
| title_sort | design metrics for extreme events in a non stationary world abstract oly |
| topic | statistical methods design water resources planning |
| url | https://hdl.handle.net/10568/67633 |
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