Published July 21, 2022
| Version
v1
Dataset
Open
LTER Zöbelboden, Austria, Soil moisture data 2018-2020
Description
Soil water content and soil water potentials from the intensive monitoring plot (IP2) at LTER Zöbelboden, AT.
Methods
Soil water potential (kPa) was collected at the so-called intensive monitoring plot IP2, a plot with condensed field measurement equipment at the LTER Zöbelboden site, Austria. IP2 is situated on a steep north facing slope (30–60°) extending from 850 m down to 550 m a.s.l. Triassic dolomite is the predominant bedrock material, partly interspersed with limestone plate layers. Soils at IP2 are mainly lithic or rendzic leptosols (rendsina) with patches of chromic cambisols (Food and Agriculture Organization of the United Nations 2006). Soil water potential was measured using MPS-2 sensors (Decagon Devices, Inc., USA). In total, six sensors were installed at 5 cm depths at station 0687P02 (sensor 10.2), 0685P06 (sensor 10.3), 0683P04 (sensor 10.4), 0674P04 (sensor 10.5), 0675P10 (sensor 10.6) and 0677P08 (sensor 10.7) on IP2. Soil water content (SWC in %) was calculated from measured soil water potentials (kPa) by using Van Genuchten Parameters for the corresponding soil types and depths (https://deims.org/dataset/cfb5581f-be40-484f-9b94-46d42a801d5b). Half-hourly soil moisture data are available from May 2018 onwards. The data-controlling tool of the Austrian national air quality data-base (LHDB - Lufthygienedatenbank) supports graphical features to process the data. Data processing comprised outlier detection by visual assessment based on expert knowledge. Missing or unrealistic values due to malfunction of the devices are expressed as NAs.
Sampling Time Unit: minutes
Sampling Time Span: half-hourly
Files
ATZOE_soilwatercontent_IP2.csv
Files
(8.4 MB)
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Checksum: md5:e04d1ed594c2011f58108ae20ad905e0
PID: http://hdl.handle.net/11304/f22569d5-0a03-4169-ac45-00693c249ea5 |
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Additional details
Identifiers
- B2SHARE Legacy Record ID
- bac0fb70641d4bfbbd90537c4ec89de4
LTER metadata
- Metadata URL
- https://deims.org/dataset/2e63463e-b1bb-499e-a42c-32a0bb9fd7d8