Statistical approaches for identification of low-flow drivers: Temporal aspects

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Fangmann, A.; Haberlandt, U.: Statistical approaches for identification of low-flow drivers: Temporal aspects. In: Hydrology and Earth System Sciences 23 (2019), Nr. 1, S. 447-463. DOI:

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Sum total of downloads: 85

The characteristics of low-flow periods, especially regarding their low temporal dynamics, suggest that the dimensions of the metrics related to these periods may be easily related to their meteorological drivers using simplified statistical model approaches. In this study, linear statistical models based on multiple linear regressions (MLRs) are proposed. The study area chosen is the German federal state of Lower Saxony with 28 available gauges used 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. In a second analysis it was assessed whether the formulated models may be eligible for application in climate change impact analysis. The models were therefore 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.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2019
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 49 57.65%
2 image of flag of United States United States 13 15.29%
3 image of flag of China China 6 7.06%
4 image of flag of Taiwan Taiwan 2 2.35%
5 image of flag of Portugal Portugal 2 2.35%
6 image of flag of Switzerland Switzerland 2 2.35%
7 image of flag of Sudan Sudan 1 1.18%
8 image of flag of Poland Poland 1 1.18%
9 image of flag of Japan Japan 1 1.18%
10 image of flag of Italy Italy 1 1.18%
    other countries 7 8.24%

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