TY  - JOUR
A1  - Heistermann, Maik
A1  - Francke, Till
A1  - Scheiffele, Lena
A1  - Petrova, Katya Dimitrova
A1  - Budach, Christian
A1  - Schrön, Martin
A1  - Trost, Benjamin
A1  - Rasche, Daniel
A1  - Güntner, Andreas
A1  - Doepper, Veronika
A1  - Förster, Michael
A1  - Köhli, Markus
A1  - Angermann, Lisa
A1  - Antonoglou, Nikolaos
A1  - Zude, Manuela
A1  - Oswald, Sascha
T1  - Three years of soil moisture observations by a dense cosmic-ray neutron sensing cluster at an agricultural research site in north-east Germany
T2  - Earth system science data : ESSD
N2  - Cosmic-ray neutron sensing (CRNS) allows for the estimation of root-zone soil water content (SWC) at the scale of several hectares. In this paper, we present the data recorded by a dense CRNS network operated from 2019 to 2022 at an agricultural research site in Marquardt, Germany - the first multi-year CRNS cluster. Consisting, at its core, of eight permanently installed CRNS sensors, the cluster was supplemented by a wealth of complementary measurements: data from seven additional temporary CRNS sensors, partly co-located with the permanent ones; 27 SWC profiles (mostly permanent); two groundwater observation wells; meteorological records; and Global Navigation Satellite System reflectometry (GNSS-R). Complementary to these continuous measurements, numerous campaign-based activities provided data by mobile CRNS roving, hyperspectral im-agery via UASs, intensive manual sampling of soil properties (SWC, bulk density, organic matter, texture, soil hydraulic properties), and observations of biomass and snow (cover, depth, and density). The unique temporal coverage of 3 years entails a broad spectrum of hydro-meteorological conditions, including exceptional drought periods and extreme rainfall but also episodes of snow coverage, as well as a dedicated irrigation experiment. Apart from serving to advance CRNS-related retrieval methods, this data set is expected to be useful for vari-ous disciplines, for example, soil and groundwater hydrology, agriculture, or remote sensing. Hence, we show exemplary features of the data set in order to highlight the potential for such subsequent studies. The data are available at doi.org/10.23728/b2share.551095325d74431881185fba1eb09c95 (Heistermann et al., 2022b).
Y1  - 2023
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/64393
SN  - 1866-3508
SN  - 1866-3516
VL  - 15
IS  - 7
SP  - 3243
EP  - 3262
PB  - Copernics Publications
CY  - Katlenburg-Lindau
ER  -