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Rosalia: an experimental research site to study hydrological processes in a forest catchment

Experimental watersheds have a long tradition as research sites in hydrology and have been used since the late nineteenth and early twentieth centuries. The University of Natural Resources and Life Sciences Vienna (BOKU) recently extended its experimental research forest site “Rosalia” with an area...

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Bibliographic Details
Published in:Earth system science data 2021-08, Vol.13 (8), p.4019-4034
Main Authors: Fürst, Josef, Nachtnebel, Hans Peter, Gasch, Josef, Nolz, Reinhard, Stockinger, Michael Paul, Stumpp, Christine, Schulz, Karsten
Format: Article
Language:English
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Summary:Experimental watersheds have a long tradition as research sites in hydrology and have been used since the late nineteenth and early twentieth centuries. The University of Natural Resources and Life Sciences Vienna (BOKU) recently extended its experimental research forest site “Rosalia” with an area of 950 ha towards the creation of a full ecological-hydrological experimental watershed. The overall objective is to implement a multi-scale, multi-disciplinary observation system that facilitates the study of water, energy and solute transport processes in the soil–plant–atmosphere continuum. This article describes the characteristics of the site and the monitoring network and its instrumentation that has been installed since 2015, as well as the datasets. The network includes four discharge gauging stations and seven rain gauges along with observations of air and water temperature, relative humidity, and electrical conductivity. In four profiles, soil water content and temperature are recorded at different depths. In addition, since 2018, nitrate, TOC and turbidity have been monitored at one gauging station. In 2019, a programme to collect isotopic data in precipitation and discharge was initiated. All data collected since 2015, including, in total, 56 high-resolution time series (with 10 min sampling intervals), are provided to the scientific community on a publicly accessible repository. The datasets are available at https://doi.org/10.5281/zenodo.3997140 (Fürst et al., 2020).
ISSN:1866-3516
1866-3508
1866-3516
DOI:10.5194/essd-13-4019-2021