Description: In addition to stationary measurements, mobile CRNS campaigns extended the utility of this method by mapping the spatial distribution of soil moisture and snowpack in the whole region. Mounted on vehicles, mobile neutron detectors can cover extensive terrains, sensing average water content at a distance of up to 100 m from the road and revealing its spatial variation due to factors like topography, vegetation, and land use (Schrön et al., 2018). During this campaign, a custom made mobile CRNS Sensor with 32 neutron counting tubes, constructed by StyX Neutronica GmbH was used. By providing high-resolution data on water distribution, mobile CRNS measurements have the potential to improve our understanding of hydrological dynamics and support better decision-making in water resource management and extreme weather events. In the present study, several mobile CRNS campaigns have been conducted with a car across the Lindach catchment and beyond before and after prospective rain events to obtain information on soil moisture along transects towards regional scales. In order to obtain data from the hydrological winter half-year, a further CRNS roving campaign was conducted in February 2024.
Global identifier:
Doi(
"10.1594/PANGAEA.984639",
)
DataMeasurements(
DataMeasurements {
domain: Unspecified,
station: None,
measured_variables: [
"Cosmic-ray neutron counts",
"Cosmic-ray neutron counts, uncertainty",
"DATE/TIME",
"Density, wet bulk",
"ELEVATION",
"Event label",
"Footprint size",
"Humidity, relative",
"LATITUDE",
"LONGITUDE",
"Penetration depth",
"Pressure, atmospheric",
"Soil moisture",
"Soil moisture, uncertainty",
"Temperature, air",
],
methods: [
"Absolute stochastic uncertainty of the neutron measurement calculation according to Jakobi et al. (2020)",
"Calculation according to Schrön et al. (2017)",
"Cosmic ray neutron sensing (CRNS) sensor, StyX Neutronica GmbH, vehicle mounted sensor",
"Gravimetric soil moisture calculation according to Schrön et al. (2018)",
"Stochastic uncertainty of the gravimetric soil moisture calculation according to Jakobi et al. (2020)",
"Stochastic uncertainty of the soil moisture calculation according to Jakobi et al. (2020)",
"Volumetric soil moisture calculation according to Schrön et al. (2018)",
"based on SoilGRIDS (Hengl et al., 2017)",
],
},
)
Tags: Sensor ? Geografische Koordinaten ? Lufttemperatur ? Topographie ? U-Bahn ? Flächennutzung ? Messdaten ? Regen ? Studie ? Wassergehalt ? Bodenfeuchte ? Extremwetter ? Gewässerbewirtschaftung ? Daten ?
Region: Baden-Württemberg
Bounding boxes: 8.34765° .. 12.55413° x 47.82036° .. 51.37066°
License: Creative Commons Namensnennung 4.0 (Data access requires registration)
Language: Englisch/English
Modified: 2026-01-08
Last harvest: 01.01.1970 00:00
Time ranges: 2023-06-01 - 2024-02-29
Accessed 2 times.