The Potsdam Soil Moisture Observatory: High-coverage reference observations at kilometer scale

Abstract. Cosmic-ray neutron sensing (CRNS) has gained popularity for estimating soil water content (SWC) due to its innovative capability to measure at an intermediate scale – a notable advantage over point-scale sensors, which are often sparsely installed and due to small-scale heterogeneity result in uncertain absolute values. CRNS serves as a crucial link between small and large scales and has been emerging as a reference measurement for remote sensing algorithm validation for its ability to link the small and large scales. Yet, the sparse availability of long-term datasets limits use of this possibility. Within the framework of project SoMMet (21GRD08), multi-scale soil moisture monitoring was implemented to integrate CRNS with complementary in-situ observations. In this paper, we present harmonized soil moisture data from different sensor types including a CRNS cluster, shallow soil moisture measurements and soil moisture profile data, creating a ready-to-use dataset as reference observation for remote sensing products, covering a highly-instrumented agricultural site in the northeast of Germany. The data include 16 stationary CRNS sensors, with co-located point-scale SWC sensors (mostly permanent), two groundwater observation wells, meteorological records, and data from intensive manual sampling campaigns (covering SWC, bulk density, organic matter, etc.). This dataset distinguishes itself from prior studies by the increased area of approx. 1 km² while still having a high sensor density and overlapping footprints of CRNS. This allows a reasonable degree of geostatistical interpolation to obtain complete coverage. The data are available under the (https://doi.org/10.23728/b2share.db88e149f7924919be376909856739f1) (Grosse et al., 2025), providing a new reference data set for remote sensing products, hydrological or land-surface models and for other products linked to soil water balance.

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Published
2025-09-22
DOI
https://doi.org/10.5194/essd-2025-546
Primary Topic
Soil Moisture and Remote Sensing
Type
article
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article

The Potsdam Soil Moisture Observatory: High-coverage reference observations at kilometer scale

Anna Balenzano, Peter Martin Grosse, Lena Scheiffele, Matthias Kunz et al.
Soil Moisture and Remote Sensing
article

The Potsdam Soil Moisture Observatory: High-coverage reference observations at kilometer scale

Anna Balenzano, Peter Martin Grosse, Lena Scheiffele, Matthias Kunz, Till Francke, Mohammadmehdi Saberioon, Daniel Altdorff, M. Zbořil, Katya Dimitrova‐Petrova, Daniel Scheffler, Marcel Reginatto, Sascha E. Oswald, Daniel Rasche, Maik Heistermann, Benjamin Trost, Christine Stumpp, Carsten Neumann, Jonas Marach, Merlin Schiel, Elodie Marret
article en

Abstract

Abstract. Cosmic-ray neutron sensing (CRNS) has gained popularity for estimating soil water content (SWC) due to its innovative capability to measure at an intermediate scale – a notable advantage over point-scale sensors, which are often sparsely installed and due to small-scale heterogeneity result in uncertain absolute values. CRNS serves as a crucial link between small and large scales and has been emerging as a reference measurement for remote sensing algorithm validation for its ability to link the small and large scales. Yet, the sparse availability of long-term datasets limits use of this possibility. Within the framework of project SoMMet (21GRD08), multi-scale soil moisture monitoring was implemented to integrate CRNS with complementary in-situ observations. In this paper, we present harmonized soil moisture data from different sensor types including a CRNS cluster, shallow soil moisture measurements and soil moisture profile data, creating a ready-to-use dataset as reference observation for remote sensing products, covering a highly-instrumented agricultural site in the northeast of Germany. The data include 16 stationary CRNS sensors, with co-located point-scale SWC sensors (mostly permanent), two groundwater observation wells, meteorological records, and data from intensive manual sampling campaigns (covering SWC, bulk density, organic matter, etc.). This dataset distinguishes itself from prior studies by the increased area of approx. 1 km² while still having a high sensor density and overlapping footprints of CRNS. This allows a reasonable degree of geostatistical interpolation to obtain complete coverage. The data are available under the (https://doi.org/10.23728/b2share.db88e149f7924919be376909856739f1) (Grosse et al., 2025), providing a new reference data set for remote sensing products, hydrological or land-surface models and for other products linked to soil water balance.

Physikalisch-Technische Bundesanstalt (DE), Helmholtz Centre for Environmental Research (DE), University of Potsdam (DE), Bologna Research Area (IT), Leibniz Institute for Agricultural Engineering and Bioeconomy (DE), GFZ Helmholtz Centre for Geosciences (DE), BOKU University (AT)
Openalex Percentile: Top 77%
Soil Moisture and Remote Sensing
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