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  • 2020-2022  (5)
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  • 1
    Publication Date: 2021-07-04
    Description: In their study, Dong and Ochsner (2018, https://doi.org/10.1002/2017WR021692) used an extensive data set of 18 cosmic‐ray neutron rover surveys along a 150 km long transect on unpaved roads to assess the influence of precipitation and soil texture on mesoscale soil moisture patterns. Based on their analysis, they concluded that soil texture, represented by sand content, exerted a stronger influence on mesoscale soil moisture variability than precipitation, represented by the antecedent precipitation index, on 17 of the 18 survey days. However, we found that Dong and Ochsner (2018) made a mistake in their calculation of volumetric soil moisture. After correction, the validity of the original conclusions of Dong and Ochsner (2018) was considerably weakened, as soil texture exerted a stronger influence on soil moisture than precipitation on 12 of the 18 survey days only.
    Description: Key Points: Dong and Ochsner (2018) concluded that soil texture exerted a stronger influence on mesoscale soil moisture variability than precipitation. Dong and Ochsner (2018) made a mistake in their calculation of volumetric soil moisture. We found that correlations between soil moisture and soil texture and precipitation were significantly different in only 8 of 18 surveys.
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Keywords: 631.4 ; Cosmic‐Ray Neutron (CRN) Sensing ; CRN Rover ; mesoscale soil moisture ; soil moisture patterns
    Type: article
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  • 2
    Publication Date: 2020-12-10
    Description: 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).
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
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  • 3
    Publication Date: 2021-10-14
    Description: The advance of the cosmic ray neutron (CRN) sensing method for estimating field scale soil moisture relied largely on simulations of the footprint properties of epithermal neutrons (∼0.5 eV–100 keV). Commercially available CRN probes are usually additionally equipped with a thermal neutron (〈0.5 eV) detector. The potential of these measurements is rarely explored because relevant features of thermal neutrons, such as the footprint and the sensitivity to soil moisture are unknown. Here, we used neutron transport modeling and a river crossing experiment to assess the thermal neutron footprint. We found that the horizontal thermal neutron footprint ranges between 43 and 48 m distance from the probe and that the vertical footprint extends to soil depths between 10 and 65 cm depending on soil moisture. Furthermore, we derived weighting functions that quantify the footprint characteristics of thermal neutrons. These results will enable new applications of thermal neutrons.
    Type: info:eu-repo/semantics/article
    Format: application/pdf
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  • 4
    Publication Date: 2021-01-18
    Description: The effects of land use change on the occurrence and frequency of preferential flow (fast water flow through a small fraction of the pore space) and piston flow (slower water flow through a large fraction of the pore space) are still not fully understood. In this study, we used a five year high resolution soil moisture monitoring dataset in combination with a response time analysis to identify factors that control preferential and piston flow before and after partial deforestation in a small headwater catchment. The sensor response times at 5, 20 and 50 cm depths were classified into one of four classes: (1) non-sequential preferential flow, (2) velocity based preferential flow, (3) sequential (piston) flow, and (4) no response. The results of this analysis showed that partial deforestation increased sequential flow occurrence and decreased the occurrence of no flow in the deforested area. Similar precipitation conditions (total precipitation) after deforestation caused more sequential flow in the deforested area, which was attributed to higher antecedent moisture conditions and the lack of interception. At the same time, an increase in preferential flow occurrence was also observed for events with identical total precipitation. However, as the events in the treatment period (after deforestation) generally had lower total, maximum, and mean precipitation, this effect was not observed in the overall occurrence of preferential flow. The results of this analysis demonstrate that the combination of a sensor response time analysis and a soil moisture dataset that includes pre- and post-deforestation conditions can offer new insights in preferential and sequential flow conditions after land use change.
    Description: The effects of land use change on the occurrence and frequency of preferential flow (fast water flow through a small fraction of the pore space) and piston flow (slower water flow through a large fraction of the pore space) are still not fully understood. In this study, we used a five year high resolution soil moisture monitoring dataset in combination with a response time analysis to identify factors that control preferential and piston flow before and after partial deforestation in a small headwater catchment. The sensor response times at 5, 20 and 50 cm depths were classified into one of four classes: (1) non-sequential preferential flow, (2) velocity based preferential flow, (3) sequential (piston) flow, and (4) no response. The results of this analysis showed that partial deforestation increased sequential flow occurrence and decreased the occurrence of no flow in the deforested area. Similar precipitation conditions (total precipitation) after deforestation caused more sequential flow in the deforested area, which was attributed to higher antecedent moisture conditions and the lack of interception. At the same time, an increase in preferential flow occurrence was also observed for events with identical total precipitation. However, as the events in the treatment period (after deforestation) generally had lower total, maximum, and mean precipitation, this effect was not observed in the overall occurrence of preferential flow. The results of this analysis demonstrate that the combination of a sensor response time analysis and a soil moisture dataset that includes pre- and post-deforestation conditions can offer new insights in preferential and sequential flow conditions after land use change.
    Type: info:eu-repo/semantics/article
    Format: application/pdf
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  • 5
    Publication Date: 2020-12-14
    Description: Drought and heat events, such as the 2018 European drought, interact with the exchange of energy between the land surface and the atmosphere, potentially affecting albedo, sensible and latent heat fluxes, as well as CO2 exchange. Each of these quantities may aggravate or mitigate the drought, heat, their side effects on productivity, water scarcity and global warming. We used measurements of 56 eddy covariance sites across Europe to examine the response of fluxes to extreme drought prevailing most of the year 2018 and how the response differed across various ecosystem types (forests, grasslands, croplands and peatlands). Each component of the surface radiation and energy balance observed in 2018 was compared to available data per site during a reference period 2004–2017. Based on anomalies in precipitation and reference evapotranspiration, we classified 46 sites as drought affected. These received on average 9% more solar radiation and released 32% more sensible heat to the atmosphere compared to the mean of the reference period. In general, drought decreased net CO2 uptake by 17.8%, but did not significantly change net evapotranspiration. The response of these fluxes differed characteristically between ecosystems; in particular, the general increase in the evaporative index was strongest in peatlands and weakest in croplands. This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale’.
    Language: English
    Type: info:eu-repo/semantics/article
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