Estimating Rainfall Design Values for the City of Oslo, Norway—Comparison of Methods and Quantification of Uncertainty
Due to its location, its old sewage system, and the channelling of rivers, Oslo is highly exposed to urban flooding. Thus, it is crucial to provide relevant and reliable information on extreme precipitation in the planning and design of infrastructure. Intensity-Duration-Frequency (IDF) curves are a...
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| Format: | Article |
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MDPI AG
2020-06-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/12/6/1735 |
| _version_ | 1797564961040367616 |
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| author | Julia Lutz Lars Grinde Anita Verpe Dyrrdal |
| author_facet | Julia Lutz Lars Grinde Anita Verpe Dyrrdal |
| author_sort | Julia Lutz |
| collection | DOAJ |
| description | Due to its location, its old sewage system, and the channelling of rivers, Oslo is highly exposed to urban flooding. Thus, it is crucial to provide relevant and reliable information on extreme precipitation in the planning and design of infrastructure. Intensity-Duration-Frequency (IDF) curves are a frequently used tool for that purpose. However, the computational method for IDF curves in Norway was established over 45 years ago, and has not been further developed since. In our study, we show that the current method of fitting a Gumbel distribution to the highest precipitation events is not able to reflect the return values for the long return periods. Instead, we introduce the fitting of a Generalised Extreme Value (GEV) distribution for annual maximum precipitation in two different ways, using (a) a modified Maximum Likelihood estimation and (b) Bayesian inference. The comparison of the two methods for 14 stations in and around Oslo reveals that the estimated median return values are very similar, but the Bayesian method provides upper credible interval boundaries that are considerably higher. Two different goodness-of-fit tests favour the Bayesian method; thus, we suggest using the Bayesian inference for estimating IDF curves for the Oslo area. |
| first_indexed | 2024-03-10T19:05:12Z |
| format | Article |
| id | doaj.art-87071667dd204e4793d3d866b3b895ce |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-10T19:05:12Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-87071667dd204e4793d3d866b3b895ce2023-11-20T04:10:05ZengMDPI AGWater2073-44412020-06-01126173510.3390/w12061735Estimating Rainfall Design Values for the City of Oslo, Norway—Comparison of Methods and Quantification of UncertaintyJulia Lutz0Lars Grinde1Anita Verpe Dyrrdal2The Norwegian Meteorological Institute (MET Norway), Henrik Mohns plass 1, 0313 Oslo, NorwayThe Norwegian Meteorological Institute (MET Norway), Henrik Mohns plass 1, 0313 Oslo, NorwayThe Norwegian Meteorological Institute (MET Norway), Henrik Mohns plass 1, 0313 Oslo, NorwayDue to its location, its old sewage system, and the channelling of rivers, Oslo is highly exposed to urban flooding. Thus, it is crucial to provide relevant and reliable information on extreme precipitation in the planning and design of infrastructure. Intensity-Duration-Frequency (IDF) curves are a frequently used tool for that purpose. However, the computational method for IDF curves in Norway was established over 45 years ago, and has not been further developed since. In our study, we show that the current method of fitting a Gumbel distribution to the highest precipitation events is not able to reflect the return values for the long return periods. Instead, we introduce the fitting of a Generalised Extreme Value (GEV) distribution for annual maximum precipitation in two different ways, using (a) a modified Maximum Likelihood estimation and (b) Bayesian inference. The comparison of the two methods for 14 stations in and around Oslo reveals that the estimated median return values are very similar, but the Bayesian method provides upper credible interval boundaries that are considerably higher. Two different goodness-of-fit tests favour the Bayesian method; thus, we suggest using the Bayesian inference for estimating IDF curves for the Oslo area.https://www.mdpi.com/2073-4441/12/6/1735IDFextreme precipitationdesign precipitationextreme value distributionGEVBayesian inference |
| spellingShingle | Julia Lutz Lars Grinde Anita Verpe Dyrrdal Estimating Rainfall Design Values for the City of Oslo, Norway—Comparison of Methods and Quantification of Uncertainty Water IDF extreme precipitation design precipitation extreme value distribution GEV Bayesian inference |
| title | Estimating Rainfall Design Values for the City of Oslo, Norway—Comparison of Methods and Quantification of Uncertainty |
| title_full | Estimating Rainfall Design Values for the City of Oslo, Norway—Comparison of Methods and Quantification of Uncertainty |
| title_fullStr | Estimating Rainfall Design Values for the City of Oslo, Norway—Comparison of Methods and Quantification of Uncertainty |
| title_full_unstemmed | Estimating Rainfall Design Values for the City of Oslo, Norway—Comparison of Methods and Quantification of Uncertainty |
| title_short | Estimating Rainfall Design Values for the City of Oslo, Norway—Comparison of Methods and Quantification of Uncertainty |
| title_sort | estimating rainfall design values for the city of oslo norway comparison of methods and quantification of uncertainty |
| topic | IDF extreme precipitation design precipitation extreme value distribution GEV Bayesian inference |
| url | https://www.mdpi.com/2073-4441/12/6/1735 |
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