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Comparison of Baseflow Separation Methods in the German Low Mountain Range

Kissel, Michael ; Schmalz, Britta (2021)
Comparison of Baseflow Separation Methods in the German Low Mountain Range.
In: Water, 2020, 12 (6)
doi: 10.26083/tuprints-00017529
Article, Secondary publication, Publisher's Version

Copyright Information: CC BY 4.0 International - Creative Commons, Attribution.

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Item Type: Article
Type of entry: Secondary publication
Title: Comparison of Baseflow Separation Methods in the German Low Mountain Range
Language: English
Date: 2021
Year of primary publication: 2020
Publisher: MDPI
Journal or Publication Title: Water
Volume of the journal: 12
Issue Number: 6
DOI: 10.26083/tuprints-00017529
Corresponding Links:
Origin: Secondary publication via sponsored Golden Open Access

The last several years in southern Germany brought below average precipitation and high temperatures, leading to considerable challenges in water resource management. Deriving a plausible baseflow estimate is important as it affects aspects of integrated water resource management such as water usage and low flow predictions. The aim of this study is to estimate baseflow in a representative catchment in the German low mountain range and identify suitable baseflow estimation methods for this region. Several different baseflow separation methods, including digital filters, a mass balance filter (MBF) and non-continuous estimation methods were applied and compared to estimate baseflow. Using electric conductivity (EC) for the MBF, June to September and November to May were found to be suitable to estimate the EC of the baseflow and runoff component, respectively. Both weekly and continuous EC monitoring can derive similar EC value component estimates. However, EC estimation of the runoff component requires more careful consideration. The baseflow index (BFI) is estimated to be in the range of 0.4 to 0.5. The Chapman and Maxwell filter, Kille method and the Q90/Q50 ratio are recommended for baseflow estimation in the German low mountain range as they give similar results to the MBF. The Eckhardt filter requires further calibration before application.

Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-175293
Classification DDC: 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 13 Department of Civil and Environmental Engineering Sciences > Institute of Hydraulic and Water Resources Engineering > Engineering Hydrology and Water Management
Date Deposited: 16 Feb 2021 13:14
Last Modified: 16 Feb 2021 13:14
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/17529
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