High and Low Flow Trends in Norway - co-occurrence and causing factors
Climate change has impacted the global water cycle and has changed how streamflow behaves in Norway. Knowledge about high and low flows are important to be prepared for future changes, such as changes in water availability for humans, electricity production, agriculture and more. This thesis investi...
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ftoslouniv:oai:www.duo.uio.no:10852/95722 2023-05-15T16:13:46+02:00 High and Low Flow Trends in Norway - co-occurrence and causing factors Nordeide, Sunniva 2022 http://hdl.handle.net/10852/95722 http://urn.nb.no/URN:NBN:no-98229 eng eng http://urn.nb.no/URN:NBN:no-98229 Nordeide, Sunniva. High and Low Flow Trends in Norway - co-occurrence and causing factors. Master thesis, University of Oslo, 2022 http://hdl.handle.net/10852/95722 URN:NBN:no-98229 Fulltext https://www.duo.uio.no/bitstream/handle/10852/95722/1/High_and_low_flow_trends_in_Norway_cooccurrence_and_causing_factors_Sunniva_Nordeide.pdf high and low flow historical streamflow hydrology trends in norway seasonal streamflow climate low flow machine learning flood hydrologi drought flow trend norway high flow streamflow climate change Master thesis Masteroppgave 2022 ftoslouniv 2022-08-31T22:35:20Z Climate change has impacted the global water cycle and has changed how streamflow behaves in Norway. Knowledge about high and low flows are important to be prepared for future changes, such as changes in water availability for humans, electricity production, agriculture and more. This thesis investigates historical changes (01.01.1991-31.12.2019) in seasonal high and low flow in Norway and their co-occurrence, and uses machine learning to identify which catchment characteristics, climate indices or other trends in seasonal high and low flow are important predictors to explain these trends. Discharge data from the Norwegian Water Resources and Energy Directorate (NVE) is used to calculate trends in high and low flow. Low flow was divided into two periods: summer low flow (June-September) and winter low flow (October-May), and high flow was divided into two periods: spring high flow (March-August) and autumn high flow (September-February). The trends were calculated over smoothing intervals of minimum/maximum discharge over 7 and 30 days. Precipitation, temperature, evaporation and snow data from seNorge is used to create climate indices while catchment characteristics are from NVE. The machine learning methods decision tree and random forest were applied to find the most important predictors for each seasonal trend. The trend results showed a clear divide in trend direction between southern and northern Norway across all seasonal trends. Southern Norway displayed only significantly increasing trends for summer low flow and autumn high flow, where as some decreasing trends showed up in the western part of southern Norway for winter low flow and spring high flow. Northern Norway displayed mostly significantly decreasing trends across all seasons, except for Troms and Finnmark which had increasing trends in winter low flow. The increasing trends in southern Norway may be because southern Norway experienced increased precipitation across all seasons during the research period, while the decreasing trends in northern ... Master Thesis Finnmark Northern Norway Finnmark Troms Universitet i Oslo: Digitale utgivelser ved UiO (DUO) Norway |
institution |
Open Polar |
collection |
Universitet i Oslo: Digitale utgivelser ved UiO (DUO) |
op_collection_id |
ftoslouniv |
language |
English |
topic |
high and low flow historical streamflow hydrology trends in norway seasonal streamflow climate low flow machine learning flood hydrologi drought flow trend norway high flow streamflow climate change |
spellingShingle |
high and low flow historical streamflow hydrology trends in norway seasonal streamflow climate low flow machine learning flood hydrologi drought flow trend norway high flow streamflow climate change Nordeide, Sunniva High and Low Flow Trends in Norway - co-occurrence and causing factors |
topic_facet |
high and low flow historical streamflow hydrology trends in norway seasonal streamflow climate low flow machine learning flood hydrologi drought flow trend norway high flow streamflow climate change |
description |
Climate change has impacted the global water cycle and has changed how streamflow behaves in Norway. Knowledge about high and low flows are important to be prepared for future changes, such as changes in water availability for humans, electricity production, agriculture and more. This thesis investigates historical changes (01.01.1991-31.12.2019) in seasonal high and low flow in Norway and their co-occurrence, and uses machine learning to identify which catchment characteristics, climate indices or other trends in seasonal high and low flow are important predictors to explain these trends. Discharge data from the Norwegian Water Resources and Energy Directorate (NVE) is used to calculate trends in high and low flow. Low flow was divided into two periods: summer low flow (June-September) and winter low flow (October-May), and high flow was divided into two periods: spring high flow (March-August) and autumn high flow (September-February). The trends were calculated over smoothing intervals of minimum/maximum discharge over 7 and 30 days. Precipitation, temperature, evaporation and snow data from seNorge is used to create climate indices while catchment characteristics are from NVE. The machine learning methods decision tree and random forest were applied to find the most important predictors for each seasonal trend. The trend results showed a clear divide in trend direction between southern and northern Norway across all seasonal trends. Southern Norway displayed only significantly increasing trends for summer low flow and autumn high flow, where as some decreasing trends showed up in the western part of southern Norway for winter low flow and spring high flow. Northern Norway displayed mostly significantly decreasing trends across all seasons, except for Troms and Finnmark which had increasing trends in winter low flow. The increasing trends in southern Norway may be because southern Norway experienced increased precipitation across all seasons during the research period, while the decreasing trends in northern ... |
format |
Master Thesis |
author |
Nordeide, Sunniva |
author_facet |
Nordeide, Sunniva |
author_sort |
Nordeide, Sunniva |
title |
High and Low Flow Trends in Norway - co-occurrence and causing factors |
title_short |
High and Low Flow Trends in Norway - co-occurrence and causing factors |
title_full |
High and Low Flow Trends in Norway - co-occurrence and causing factors |
title_fullStr |
High and Low Flow Trends in Norway - co-occurrence and causing factors |
title_full_unstemmed |
High and Low Flow Trends in Norway - co-occurrence and causing factors |
title_sort |
high and low flow trends in norway - co-occurrence and causing factors |
publishDate |
2022 |
url |
http://hdl.handle.net/10852/95722 http://urn.nb.no/URN:NBN:no-98229 |
geographic |
Norway |
geographic_facet |
Norway |
genre |
Finnmark Northern Norway Finnmark Troms |
genre_facet |
Finnmark Northern Norway Finnmark Troms |
op_relation |
http://urn.nb.no/URN:NBN:no-98229 Nordeide, Sunniva. High and Low Flow Trends in Norway - co-occurrence and causing factors. Master thesis, University of Oslo, 2022 http://hdl.handle.net/10852/95722 URN:NBN:no-98229 Fulltext https://www.duo.uio.no/bitstream/handle/10852/95722/1/High_and_low_flow_trends_in_Norway_cooccurrence_and_causing_factors_Sunniva_Nordeide.pdf |
_version_ |
1765999607242817536 |