New flood frequency estimates for the largest river in Norway based on the combination of short and long time series
The Glomma River is the largest in Norway, with a catchment area of 154 450 km 2 . People living near the shores of this river are frequently exposed to destructive floods that impair local cities and communities. Unfortunately, design flood predictions are hampered by uncertainty since the standard...
Published in: | Hydrology and Earth System Sciences |
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Main Authors: | , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Copernicus Publications
2020
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Subjects: | |
Online Access: | https://doi.org/10.5194/hess-24-5595-2020 https://doaj.org/article/d18ea2b93a1a42318b4298e219b0568e |
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author | K. Engeland A. Aano I. Steffensen E. Støren Ø. Paasche |
author_facet | K. Engeland A. Aano I. Steffensen E. Støren Ø. Paasche |
author_sort | K. Engeland |
collection | Directory of Open Access Journals: DOAJ Articles |
container_issue | 11 |
container_start_page | 5595 |
container_title | Hydrology and Earth System Sciences |
container_volume | 24 |
description | The Glomma River is the largest in Norway, with a catchment area of 154 450 km 2 . People living near the shores of this river are frequently exposed to destructive floods that impair local cities and communities. Unfortunately, design flood predictions are hampered by uncertainty since the standard flood records are much shorter than the requested return period and the climate is also expected to change in the coming decades. Here we combine systematic historical and paleo information in an effort to improve flood frequency analysis and better understand potential linkages to both climate and non-climatic forcing. Specifically, we (i) compile historical flood data from the existing literature, (ii) produce high-resolution X-ray fluorescence (XRF), magnetic susceptibility (MS), and computed tomography (CT) scanning data from a sediment core covering the last 10 300 years, and (iii) integrate these data sets in order to better estimate design floods and assess non-stationarities. Based on observations from Lake Flyginnsjøen, receiving sediments from Glomma only when it reaches a certain threshold, we can estimate flood frequency in a moving window of 50 years across millennia revealing that past flood frequency is non-stationary on different timescales. We observe that periods with increased flood activity (4000–2000 years ago and <1000 years ago) correspond broadly to intervals with lower than average summer temperatures and glacier growth, whereas intervals with higher than average summer temperatures and receding glaciers overlap with periods of reduced numbers of floods (10 000 to 4000 years ago and 2200 to 1000 years ago). The flood frequency shows significant non-stationarities within periods with increased flood activity, as was the case for the 18th century, including the 1789 CE (“Stor-Ofsen”) flood, the largest on record for the last 10 300 years at this site. Using the identified non-stationarities in the paleoflood record allowed us to estimate non-stationary design floods. In particular, we found ... |
format | Article in Journal/Newspaper |
genre | glacier |
genre_facet | glacier |
geographic | Norway |
geographic_facet | Norway |
id | ftdoajarticles:oai:doaj.org/article:d18ea2b93a1a42318b4298e219b0568e |
institution | Open Polar |
language | English |
op_collection_id | ftdoajarticles |
op_container_end_page | 5619 |
op_doi | https://doi.org/10.5194/hess-24-5595-2020 |
op_relation | https://hess.copernicus.org/articles/24/5595/2020/hess-24-5595-2020.pdf https://doaj.org/toc/1027-5606 https://doaj.org/toc/1607-7938 doi:10.5194/hess-24-5595-2020 1027-5606 1607-7938 https://doaj.org/article/d18ea2b93a1a42318b4298e219b0568e |
op_source | Hydrology and Earth System Sciences, Vol 24, Pp 5595-5619 (2020) |
publishDate | 2020 |
publisher | Copernicus Publications |
record_format | openpolar |
spelling | ftdoajarticles:oai:doaj.org/article:d18ea2b93a1a42318b4298e219b0568e 2025-01-16T22:03:09+00:00 New flood frequency estimates for the largest river in Norway based on the combination of short and long time series K. Engeland A. Aano I. Steffensen E. Støren Ø. Paasche 2020-11-01T00:00:00Z https://doi.org/10.5194/hess-24-5595-2020 https://doaj.org/article/d18ea2b93a1a42318b4298e219b0568e EN eng Copernicus Publications https://hess.copernicus.org/articles/24/5595/2020/hess-24-5595-2020.pdf https://doaj.org/toc/1027-5606 https://doaj.org/toc/1607-7938 doi:10.5194/hess-24-5595-2020 1027-5606 1607-7938 https://doaj.org/article/d18ea2b93a1a42318b4298e219b0568e Hydrology and Earth System Sciences, Vol 24, Pp 5595-5619 (2020) Technology T Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350 article 2020 ftdoajarticles https://doi.org/10.5194/hess-24-5595-2020 2022-12-31T03:03:28Z The Glomma River is the largest in Norway, with a catchment area of 154 450 km 2 . People living near the shores of this river are frequently exposed to destructive floods that impair local cities and communities. Unfortunately, design flood predictions are hampered by uncertainty since the standard flood records are much shorter than the requested return period and the climate is also expected to change in the coming decades. Here we combine systematic historical and paleo information in an effort to improve flood frequency analysis and better understand potential linkages to both climate and non-climatic forcing. Specifically, we (i) compile historical flood data from the existing literature, (ii) produce high-resolution X-ray fluorescence (XRF), magnetic susceptibility (MS), and computed tomography (CT) scanning data from a sediment core covering the last 10 300 years, and (iii) integrate these data sets in order to better estimate design floods and assess non-stationarities. Based on observations from Lake Flyginnsjøen, receiving sediments from Glomma only when it reaches a certain threshold, we can estimate flood frequency in a moving window of 50 years across millennia revealing that past flood frequency is non-stationary on different timescales. We observe that periods with increased flood activity (4000–2000 years ago and <1000 years ago) correspond broadly to intervals with lower than average summer temperatures and glacier growth, whereas intervals with higher than average summer temperatures and receding glaciers overlap with periods of reduced numbers of floods (10 000 to 4000 years ago and 2200 to 1000 years ago). The flood frequency shows significant non-stationarities within periods with increased flood activity, as was the case for the 18th century, including the 1789 CE (“Stor-Ofsen”) flood, the largest on record for the last 10 300 years at this site. Using the identified non-stationarities in the paleoflood record allowed us to estimate non-stationary design floods. In particular, we found ... Article in Journal/Newspaper glacier Directory of Open Access Journals: DOAJ Articles Norway Hydrology and Earth System Sciences 24 11 5595 5619 |
spellingShingle | Technology T Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350 K. Engeland A. Aano I. Steffensen E. Støren Ø. Paasche New flood frequency estimates for the largest river in Norway based on the combination of short and long time series |
title | New flood frequency estimates for the largest river in Norway based on the combination of short and long time series |
title_full | New flood frequency estimates for the largest river in Norway based on the combination of short and long time series |
title_fullStr | New flood frequency estimates for the largest river in Norway based on the combination of short and long time series |
title_full_unstemmed | New flood frequency estimates for the largest river in Norway based on the combination of short and long time series |
title_short | New flood frequency estimates for the largest river in Norway based on the combination of short and long time series |
title_sort | new flood frequency estimates for the largest river in norway based on the combination of short and long time series |
topic | Technology T Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350 |
topic_facet | Technology T Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350 |
url | https://doi.org/10.5194/hess-24-5595-2020 https://doaj.org/article/d18ea2b93a1a42318b4298e219b0568e |