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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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Published in: | Earth system science data 2021-08, Vol.13 (8), p.4019-4034 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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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). |
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ISSN: | 1866-3516 1866-3508 1866-3516 |
DOI: | 10.5194/essd-13-4019-2021 |