Statistical approaches for assessment of climate change impacts on low flows: temporal aspects

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dc.identifier.uri http://dx.doi.org/10.15488/5205
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/5252
dc.contributor.author Fangmann, Anne
dc.contributor.author Haberlandt, Uwe
dc.date.accessioned 2019-08-15T11:35:02Z
dc.date.available 2019-08-15T11:35:02Z
dc.date.issued 2019
dc.identifier.citation Fangmann, Anne; Haberlandt, Uwe: Statistical approaches for assessment of climate change impacts on low flows: temporal aspects. In: Hydrology and Earth System Sciences 23 (2019), S. 447-463. DOI: https://doi.org/10.5194/hess-23-447-2019
dc.description.abstract The characteristics of low flow periods, especially regarding their low temporal dynamics, suggest that estimation of metrics related to these periods may be carried out using simplified statistical model approaches that base on a rudimentary input of aggregated local meteorological information. Compared to physically-based or even strongly conceptualized hydrological models, such approaches may have the advantage of being easily set up, applicable over large study areas in a fraction of the time, and easily transferrable between regions, given that predictions are made with the accuracy required for a given purpose. In this study, simplified statistical models based on multiple linear regressions for the use in regional climate change impact analysis are proposed. Study area is the German Federal State of Lower Saxony with 28 available gauges for analysis. A number of regression approaches are evaluated. An approach using principal components of local meteorological indices as input appeared to show the best performance. This model type was eventually applied to a climate model ensemble based on the RCP8.5 scenario. Analyses in the baseline period revealed that some of the meteorological indices needed for model input could not be fully reproduced by the climate models. The predictions for the future show an overall increase in the lowest average 7-day flow (NM7Q), projected by the majority of ensemble members and for the majority of stations. eng
dc.language.iso eng
dc.publisher Göttingen : Copernicus GmbH
dc.relation.ispartofseries Hydrology and Earth System Sciences 23 (2019)
dc.rights CC BY 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject Statistical model eng
dc.subject Geology eng
dc.subject Climate change eng
dc.subject Econometrics eng
dc.subject Climate model eng
dc.subject Principal component analysis eng
dc.subject Linear regression eng
dc.subject Climatology eng
dc.subject.ddc 550 | Geowissenschaften ger
dc.subject.ddc 551 | Geologie, Hydrologie, Meteorologie ger
dc.title Statistical approaches for assessment of climate change impacts on low flows: temporal aspects eng
dc.type article
dc.type Text
dc.relation.issn 1812-2116
dc.relation.doi https://doi.org/10.5194/hess-23-447-2019
dc.bibliographicCitation.volume 23
dc.bibliographicCitation.firstPage 447
dc.bibliographicCitation.lastPage 463
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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