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The spatial and temporal distribution of soil water is a key constituent for the coupled moisture processes between the land surface and the atmospheric boundary layer. The scales of soil moisture observations and simulations with land-surface models are typically mismatching with respect to spatial support. Cosmic-ray neutron sensing (CRNS) offers a competitive method to observe soil moisture at the spatial scales of modern LSMs as typically used in local area climate and atmospheric models. In our study, we investigate how the assimilation of CRNS observations helps to improve the spatial structures of soil moisture in these models and the local soil moisture – atmospheric boundary layer interaction. The modeling chain consists of Noah-MP LSM, the WRF-Hydro model in both, observation driven and fully WRF coupled configuration, and the Data Assimilation Research Testbed (DART) coupled to WRF-Hydro (Hydro-DART). The data assimilation is based on Ensemble-Kalman Fitler (EnKF) with the fully coupled WRF-Hydro-Dart model system.Extensive observations from the Terrestrial Environmental Observatories (TERENO, www.tereno.net), will be used along with data from MOSES (Helmholtz Modular Observation Solutions for Earth Science https://moses.eskp.de/), and with data from the DFG research unit Cosmic Sense. We present the structure and a first evaluation of the model system for the Ammer river catchment in southern Germany based on observations from the TERENO preAlpine network. [ABSTRACT FROM AUTHOR]

Cosmic-ray neutron sensing (CRNS) has become an effective method to measure soil moisture at a horizontal scale of hundreds of metres and a depth of decimetres. Recent studies proposed operating CRNS in a network with overlapping footprints in order to cover root-zone water dynamics at the small catchment scale and, at the same time, to represent spatial heterogeneity. In a joint field campaign from September to November 2020 (JFC-2020), five German research institutions deployed 15 CRNS sensors in the 0.4 km 2 Wüstebach catchment (Eifel mountains, Germany). The catchment is dominantly forested (but includes a substantial fraction of open vegetation) and features a topographically distinct catchment boundary. In addition to the dense CRNS coverage, the campaign featured a unique combination of additional instruments and techniques: hydro-gravimetry (to detect water storage dynamics also below the root zone); ground-based and, for the first time, airborne CRNS roving; an extensive wireless soil sensor network, supplemented by manual measurements; and six weighable lysimeters. Together with comprehensive data from the long-term local research infrastructure, the published data set (available at 10.23728/b2share.756ca0485800474e9dc7f5949c63b872;) will be a valuable asset in various research contexts: to advance the retrieval of landscape water storage from CRNS, wireless soil sensor networks, or hydrogravimetry; to identify scale-specific combinations of sensors and methods to represent soil moisture variability; to improve the understanding and simulation of land–atmosphere exchange as well as hydrological and hydrogeological processes at the hillslope and the catchment scale; and to support the retrieval of soil water content from airborne and spaceborne remote sensing platforms. [ABSTRACT FROM AUTHOR]

Cosmic Ray Neutron Sensing (CRNS) has become an effective method to measure soil moisture at a horizontal scale of hundreds of meters and a depth of decimeters. Recent studies proposed to operate CRNS in a network with overlapping footprints in order to cover root-zone water dynamics at the small catchment scale, and, at the same time, to represent spatial heterogeneity. In a joint field campaign from September to November 2020 (JFC-2020), five German research institutions deployed 15 CRNS sensors in the 0.4 km2 Wüstebach catchment (Eifel mountains, Germany). The catchment is dominantly forested (but includes a substantial fraction of open vegetation), and features a topographically distinct watershed. In addition to the dense CRNS coverage, the campaign featured a unique combination of additional instruments and techniques: hydro-gravimetry (to detect water storage dynamics also below the root zone); ground-based and, for the first time, airborne CRNS roving; an extensive wireless soil sensor network, supplemented by manual measurements; and six weighable lysimeters. Together with comprehensive data from the long-term local research infrastructure, the published dataset (available at https://doi.org/10.23728/b2share.afb20a34a6ac429ca6b759238d842765) will be a valuable asset in various research contexts: to advance the retrieval of landscape water storage from CRNS, wireless soil sensor networks, or hydrogravimetry; to identify scale-specific combinations of sensors and methods to represent soil moisture variability; to improve the understanding and simulation of land-atmosphere exchange as well as hydrological and hydrogeological processes at the hill-slope and the catchment scale; and to support the retrieval soil water content from airborne and spaceborne remote sensing platforms. [ABSTRACT FROM AUTHOR]

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 km 2 : 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: 10.23728/b2share.282675586fb94f44ab2fd09da0856883 and 10.23728/b2share.bd89f066c26a4507ad654e994153358b. [ABSTRACT FROM AUTHOR]

Monitoring soil moisture is still a challenge: it varies strongly in space and time and at various scales while well established sensors typically suffer from a small spatial support. With a sensor footprint up to several hectares, Cosmic-Ray Neutron Sensing (CRNS) is an emerging 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, that 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 to study soil moisture variability at various spatial scales: roving (mobile) CRNS units, remotely sensed thermal images from Unmanned Areal Systems (UAS), permanent and temporary wireless sensor networks, profile probes as well as 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 dataset 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 spatio-temporal 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 EUDAT, splitted into the two subsets https://doi.org/10.23728/b2share.85fe0f9dac0f48df9215c17e65d1f1e1 (Fersch et al., 2020a) and https://doi.org/10.23728/b2share.93ed99e486904d48a8a6a68083066198 (Fersch et al., 2020b). [ABSTRACT FROM AUTHOR]