A dense network of cosmic-ray neutron sensors for soil moisture observation in a highly instrumented pre-Alpine headwater catchment in Germany

Abstract

Abstract. Monitoring soil moisture is still a challenge: it varies strongly in space and time and at various scales while conventional sensors typically suffer from small spatial support. With a sensor footprint up to several hectares, cosmic-ray neutron sensing (CRNS) is a modern technology to address that challenge. So far, the CRNS method has typically been applied with single sensors or in sparse national-scale networks. This study presents, for the first time, a dense network of 24 CRNS stations that covered, from May to July 2019, an area of just 1 km2: the pre-Alpine Rott headwater catchment in Southern Germany, which is characterized by strong soil moisture gradients in a heterogeneous landscape with forests and grasslands. With substantially overlapping sensor footprints, this network was designed to study root-zone soil moisture dynamics at the catchment scale. The observations of the dense CRNS network were complemented by extensive measurements that allow users to study soil moisture variability at various spatial scales: roving (mobile) CRNS units, remotely sensed thermal images from unmanned areal systems (UASs), permanent and temporary wireless sensor networks, profile probes, and comprehensive manual soil sampling. Since neutron counts are also affected by hydrogen pools other than soil moisture, vegetation biomass was monitored in forest and grassland patches, as well as meteorological variables; discharge and groundwater tables were recorded to support hydrological modeling experiments. As a result, we provide a unique and comprehensive data set to several research communities: to those who investigate the retrieval of soil moisture from cosmic-ray neutron sensing, to those who study the variability of soil moisture at different spatiotemporal scales, and to those who intend to better understand the role of root-zone soil moisture dynamics in the context of catchment and groundwater hydrology, as well as land–atmosphere exchange processes. The data set is available through the EUDAT Collaborative Data Infrastructure and is split into two subsets: https://doi.org/10.23728/b2share.282675586fb94f44ab2fd09da0856883 (Fersch et al., 2020a) and https://doi.org/10.23728/b2share.bd89f066c26a4507ad654e994153358b (Fersch et al., 2020b).

A profile shape correction to reduce the vertical sensitivity of cosmic‐ray neutron sensing of soil moisture

“…In the last decade, cosmic‐ray neutron sensing (CRNS) has evolved to a well‐established, noninvasive method for monitoring soil moisture at high temporal resolution (hourly to daily values), and it is now applied in several monitoring networks and at many research stations around the world (Andreasen, Jensen, Desilets, Zreda, et al., 2017; Baatz et al., 2014; Evans et al., 2016; Fersch et al., 2020; Hawdon, McJannet, & Wallace, 2014; Zreda et al., 2012). Cosmic‐ray neutron sensing uses the natural occurring background neutron flux and its inverse proportional relationship with hydrogen abundance (present mainly as soil moisture) at the land surface (Zreda, Desilets, Ferré, & Scott, 2008; Zreda et al., 2012).…”

Comment on hess-2021-25

“…This section gives a brief summary of the data that has actually been used in the present analysis. As already pointed out, Fersch et al (2020a) have provided a comprehensive description that should serve as a detailed reference.…”

“…The soil water content is mostly inferred from the intensity of epithermal neutrons by using a transfer function such as the one suggested by Desilets et al (2010), and requires the calibration of a parameter N 0 on independent measurements of soil water content in the footprint of a neutron detector (see Schrön et al, 2017, for a recent synthesis). The value of N 0 is affected by a variety of factors, including topography, spatial heterogeneity of soil water content, and the sensitivity of the detector (Fersch et al, 2020a;, but also the occurrence of hydrogen in snow (Schattan et al, 2017), vegetation (Baroni and Oswald, 2015), lattice water, litter (Bogena et al, 2013), or soil organic carbon.…”

“…Recently, all data collected in this JFC have been made available to the public (Fersch et al, 2020a). The present study is the first to explore this unique data set regarding its potential to retrieve space-time representations of soil water content at the hectometer scale.…”

“…The manuscript is structured as follows: Fersch et al (2020a) have already provided a comprehensive and detailed scientific and technical description of the study site and the data set collected during the JFC. That is why we will just provide a very brief summary of the Upper Rott catchment (section 2), and the data that was actually used in the present study (section 3).…”