An Efficient Statistical Approach to Develop Intensity-Duration-Frequency Curves for Precipitation and Runoff under Future Climate
Ongoing and potential future changes in precipitation will affect water management infrastructure. Urban drainage systems are particularly vulnerable. Design standards for many stormwater practices rely on precipitation intensity-duration-frequency (IDF) curves based on extreme value analysis. General Circulation Models (GCMs) project increases in future average temperature but are less clear on changes in precipitation. In many areas, climate projections suggest relatively small changes in total precipitation volume, but also suggest increased magnitude of extreme events. Model skill in predicting extreme precipitation events, however, is limited. We develop an approach for estimating future IDF curves that is efficient, uses widely available statistically downscaled GCM output, and is consistent with published IDF curves for the United States that are often incorporated into local stormwater regulations and design guides (and are GCM model agnostic). The method provides a relatively simple way to develop scenarios in a format directly useful to assessing risk to stormwater management infrastructure. Model biases are addressed through equidistant quantile mapping, in which the modeled change in the cumulative distribution of storm events from historical to future conditions is used to adjust the extreme value fit used for IDF curve development. The approach is efficient because it requires only annual maxima and is readily automated, allowing rapid examination of results across projections. We estimate future IDF curves at locations throughout the United States and link IDF-derived design storms to a rainfall-runoff model to evaluate the potential change in storage volume requirements for capture-based stormwater management practices by 2065.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:164 |
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| Enthalten in: |
Climatic change - 164(2021), 1-2 vom: 16. Jan., Seite 1-3 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Butcher, Jonathan B [VerfasserIn] |
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| Links: |
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| Themen: |
Future precipitation |
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| Anmerkungen: |
Date Revised 17.01.2022 published: Print Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1007/s10584-021-02963-y |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM328793914 |
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| 520 | |a Ongoing and potential future changes in precipitation will affect water management infrastructure. Urban drainage systems are particularly vulnerable. Design standards for many stormwater practices rely on precipitation intensity-duration-frequency (IDF) curves based on extreme value analysis. General Circulation Models (GCMs) project increases in future average temperature but are less clear on changes in precipitation. In many areas, climate projections suggest relatively small changes in total precipitation volume, but also suggest increased magnitude of extreme events. Model skill in predicting extreme precipitation events, however, is limited. We develop an approach for estimating future IDF curves that is efficient, uses widely available statistically downscaled GCM output, and is consistent with published IDF curves for the United States that are often incorporated into local stormwater regulations and design guides (and are GCM model agnostic). The method provides a relatively simple way to develop scenarios in a format directly useful to assessing risk to stormwater management infrastructure. Model biases are addressed through equidistant quantile mapping, in which the modeled change in the cumulative distribution of storm events from historical to future conditions is used to adjust the extreme value fit used for IDF curve development. The approach is efficient because it requires only annual maxima and is readily automated, allowing rapid examination of results across projections. We estimate future IDF curves at locations throughout the United States and link IDF-derived design storms to a rainfall-runoff model to evaluate the potential change in storage volume requirements for capture-based stormwater management practices by 2065 | ||
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| 700 | 1 | |a Zi, Tan |e verfasserin |4 aut | |
| 700 | 1 | |a Pickard, Brian R |e verfasserin |4 aut | |
| 700 | 1 | |a Job, Scott C |e verfasserin |4 aut | |
| 700 | 1 | |a Johnson, Thomas E |e verfasserin |4 aut | |
| 700 | 1 | |a Groza, Bryan A |e verfasserin |4 aut | |
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