Determining return levels of extreme daily precipitation, reservoir inflow, and dry spells
Return level calculations are widely used to determine the risks that extreme events may pose to infrastructure, including hydropower site operations. Extreme events (e.g., extreme precipitation and droughts) are expected to increase in frequency and intensity in the future, but not necessarily in a...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-07-01
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| Series: | Frontiers in Water |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/frwa.2023.1141786/full |
| _version_ | 1797773410360623104 |
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| author | Tatjana Milojevic Juliette Blanchet Michael Lehning Michael Lehning |
| author_facet | Tatjana Milojevic Juliette Blanchet Michael Lehning Michael Lehning |
| author_sort | Tatjana Milojevic |
| collection | DOAJ |
| description | Return level calculations are widely used to determine the risks that extreme events may pose to infrastructure, including hydropower site operations. Extreme events (e.g., extreme precipitation and droughts) are expected to increase in frequency and intensity in the future, but not necessarily in a homogenous way across regions. This makes localized assessment important for understanding risk changes to specific sites. However, for sites with relatively small datasets, selecting an applicable method for return level calculations is not straightforward. This study focuses on the application of traditional univariate extreme value approaches (Generalized Extreme Value and Generalized Pareto) as well as two more recent approaches (extended Generalized Pareto and Metastatistical Extreme Value distributions), that are specifically suited for application to small datasets. These methods are used to calculate return levels of extreme precipitation at six Alpine stations and high reservoir inflow events for a hydropower reservoir. In addition, return levels of meteorological drought and low inflow periods (dry spells) are determined using a non-parametric approach. Return levels for return periods of 10- and 20- years were calculated using 10-, 20-, and 40- years of data for each method. The results show that even shorter timeseries can give similar return levels as longer timeseries for most methods. However, the GEV has greater sensitivity to sparse data and tended to give lower estimates for precipitation return levels. The MEV is only to be preferred over GPD if the underlying distribution fits the data well. The result is used to assemble a profile of 10- and 20-year return levels estimated with various statistical approaches, for extreme high precipitation/inflow and low precipitation/inflow events. The findings of the study may be helpful to researchers and practitioners alike in deciding which statistical approach to use to assess local extreme precipitation and inflow risks to individual reservoirs. |
| first_indexed | 2024-03-12T22:06:04Z |
| format | Article |
| id | doaj.art-6dd0ef7ded9d40f18061dad22492700f |
| institution | Directory Open Access Journal |
| issn | 2624-9375 |
| language | English |
| last_indexed | 2024-03-12T22:06:04Z |
| publishDate | 2023-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Water |
| spelling | doaj.art-6dd0ef7ded9d40f18061dad22492700f2023-07-24T13:43:37ZengFrontiers Media S.A.Frontiers in Water2624-93752023-07-01510.3389/frwa.2023.11417861141786Determining return levels of extreme daily precipitation, reservoir inflow, and dry spellsTatjana Milojevic0Juliette Blanchet1Michael Lehning2Michael Lehning3Laboratory of Cryospheric Sciences, School of Architecture, Civil and Environmental Engineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne, SwitzerlandUniversité Grenoble Alpes, CNRS, IGE, Grenoble, FranceLaboratory of Cryospheric Sciences, School of Architecture, Civil and Environmental Engineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne, SwitzerlandWSL Institute for Snow and Avalanche Research (SLF), Davos, SwitzerlandReturn level calculations are widely used to determine the risks that extreme events may pose to infrastructure, including hydropower site operations. Extreme events (e.g., extreme precipitation and droughts) are expected to increase in frequency and intensity in the future, but not necessarily in a homogenous way across regions. This makes localized assessment important for understanding risk changes to specific sites. However, for sites with relatively small datasets, selecting an applicable method for return level calculations is not straightforward. This study focuses on the application of traditional univariate extreme value approaches (Generalized Extreme Value and Generalized Pareto) as well as two more recent approaches (extended Generalized Pareto and Metastatistical Extreme Value distributions), that are specifically suited for application to small datasets. These methods are used to calculate return levels of extreme precipitation at six Alpine stations and high reservoir inflow events for a hydropower reservoir. In addition, return levels of meteorological drought and low inflow periods (dry spells) are determined using a non-parametric approach. Return levels for return periods of 10- and 20- years were calculated using 10-, 20-, and 40- years of data for each method. The results show that even shorter timeseries can give similar return levels as longer timeseries for most methods. However, the GEV has greater sensitivity to sparse data and tended to give lower estimates for precipitation return levels. The MEV is only to be preferred over GPD if the underlying distribution fits the data well. The result is used to assemble a profile of 10- and 20-year return levels estimated with various statistical approaches, for extreme high precipitation/inflow and low precipitation/inflow events. The findings of the study may be helpful to researchers and practitioners alike in deciding which statistical approach to use to assess local extreme precipitation and inflow risks to individual reservoirs.https://www.frontiersin.org/articles/10.3389/frwa.2023.1141786/fullreturn levelsextreme value statisticsextreme precipitationreservoir inflowdry spells |
| spellingShingle | Tatjana Milojevic Juliette Blanchet Michael Lehning Michael Lehning Determining return levels of extreme daily precipitation, reservoir inflow, and dry spells Frontiers in Water return levels extreme value statistics extreme precipitation reservoir inflow dry spells |
| title | Determining return levels of extreme daily precipitation, reservoir inflow, and dry spells |
| title_full | Determining return levels of extreme daily precipitation, reservoir inflow, and dry spells |
| title_fullStr | Determining return levels of extreme daily precipitation, reservoir inflow, and dry spells |
| title_full_unstemmed | Determining return levels of extreme daily precipitation, reservoir inflow, and dry spells |
| title_short | Determining return levels of extreme daily precipitation, reservoir inflow, and dry spells |
| title_sort | determining return levels of extreme daily precipitation reservoir inflow and dry spells |
| topic | return levels extreme value statistics extreme precipitation reservoir inflow dry spells |
| url | https://www.frontiersin.org/articles/10.3389/frwa.2023.1141786/full |
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