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Neutrons on rails
(2021)
Large-scale measurements of the spatial distribution of water content in soils and snow are challenging for state-of-the-art hydrogeophysical methods. Cosmic-ray neutron sensing (CRNS) is a noninvasive technology that has the potential to bridge the scale gap between conventional in situ sensors and remote sensing products in both, horizontal and vertical domains. In this study, we explore the feasibility and potential of estimating water content in soils and snow with neutron detectors in moving trains. Theoretical considerations quantify the stochastic measurement uncertainty as a function of water content, altitude, resolution, and detector efficiency. Numerical experiments demonstrate that the sensitivity of measured water content is almost unperturbed by train materials. Finally, three distinct real-world experiments provide a proof of concept on short and long-range tracks. With our results a transregional observational soil moisture product becomes a realistic vision within the next years.
Purpose
Root growth, respiration, water uptake as well as root exudation induce biogeochemical patterns in the rhizosphere that can change dynamically over time. Our aim is to develop a method that provides complementary information on 3D root system architecture and biogeochemical gradients around the roots needed for the quantitative description of rhizosphere processes.
Methods
We captured for the first time the root system architecture of maize plants grown in rectangular rhizotrons in 3D using neutron computed laminography (NCL). Simultaneously, we measured pH and oxygen concentration using fluorescent optodes and the 2D soil water distribution by means of neutron radiography. We co-registered the 3D laminography data with the 2D oxygen and pH maps to analyze the sensor signal as a function of the distance between the roots and the optode.
Results
The 3D root system architecture was successfully segmented from the laminographic data. We found that exudation of roots in up to 2 mm distance to the pH optode induced patterns of local acidification or alkalization. Over time, oxygen gradients in the rhizosphere emerged for roots up to a distance of 7.5 mm.
Conclusion
Neutron computed laminography allows for a three-dimensional investigation of root systems grown in laterally extended rhizotrons as the ones designed for 2D optode imaging studies. The 3D information on root position within the rhizotrons derived by NCL explained measured 2D oxygen and pH distribution. The presented new combination of 3D and 2D imaging methods facilitates systematical investigations of a wide range of dynamic processes in the rhizosphere.
Küstennahe Niedermoore wurden durch den Menschen verändert, bspw. durch das Anlegen von Entwässerungsgräben, dem Bau von Küstenschutzdeichen oder aktuell einer Renaturierung. Außerdem ist es wichtig die komplexe Interaktion mit der See zu verstehen, um Aussagen über die zukünftige Entwicklung treffen zu können. In der vorliegenden Studie wurde die ober- und unterirdische Strömung in einem Feuchtgebiet an der mecklenburgischen Ostseeküste nahe Warnemünde
(Deutschland) untersucht, um dessen wechselseitigen Austausch mit der Ostsee zu quantifizieren und zu analysieren, wie sich ein Sturmhochwasserereignis auf den Salzeintrag ins Gebiet auswirkt. Hierfür wurde ein dreidimensionales
instationäres Grundwassermodell erstellt, mit einem eindimensionalen Modell des Grabensystems gekoppelt und mit Messungen im Gebiet kalibriert und verglichen. Die Ergebnisse zeigen, dass neben der oberirdischen Entwässerung auch der
Grundwasserabstrom in Richtung Ostsee eine wesentliche Komponente der Wasserbilanz darstellt. Das Verhalten entlang der Küste wird deutlich durch die Dynamik der Ostseewasserstände geprägt, wobei ein Grundwasserabstrom mit einem
Zustrom von Ostseewasser bei hohen Küstenwasserständen innerhalb täglicher bis wöchentlicher Zeitskalen wechselt.
Purpose Microplastics have become a ubiquitous pollutant in marine, terrestrial and freshwater systems that seriously affects aquatic and terrestrial ecosystems. Common methods for analysing microplastic abundance in soil or sediments are based on destructive sampling or involve destructive sample processing. Thus, substantial information about local distribution of microplastics is inevitably lost. Methods Tomographic methods have been explored in our study as they can help to overcome this limitation because they allow the analysis of the sample structure while maintaining its integrity. However, this capability has not yet been exploited for detection of environmental microplastics. We present a bimodal 3D imaging approach capable to detect microplastics in soil or sediment cores non-destructively. Results In a first pilot study, we demonstrate the unique potential of neutrons to sense and localize microplastic particles in sandy sediment. The complementary application of X-rays allows mineral grains to be discriminated from microplastic particles. Additionally, it yields detailed information on the 3D surroundings of each microplastic particle, which supports its size and shape determination. Conclusion The procedure we developed is able to identify microplastic particles with diameters of approximately 1 mm in a sandy soil. It also allows characterisation of the shape of the microplastic particles as well as the microstructure of the soil and sediment sample as depositional background information. Transferring this approach to environmental samples presents the opportunity to gain insights of the exact distribution of microplastics as well as their past deposition, deterioration and translocation processes.
Root water uptake is an essential process for terrestrial plants that strongly affects the spatiotemporal distribution of water in vegetated soil. Fast neutron tomography is a recently established non-invasive imaging technique capable to capture the 3D architecture of root systems in situ and even allows for tracking of three-dimensional water flow in soil and roots. We present an in vivo analysis of local water uptake and transport by roots of soil-grown maize plants—for the first time measured in a three-dimensional time-resolved manner. Using deuterated water as tracer in infiltration experiments, we visualized soil imbibition, local root uptake, and tracked the transport of deuterated water throughout the fibrous root system for a day and night situation. This revealed significant differences in water transport between different root types. The primary root was the preferred water transport path in the 13-days-old plants while seminal roots of comparable size and length contributed little to plant water supply. The results underline the unique potential of fast neutron tomography to provide time-resolved 3D in vivo information on the water uptake and transport dynamics of plant root systems, thus contributing to a better understanding of the complex interactions of plant, soil and water.
Cosmic-ray neutron sensing (CRNS) is a powerful technique for retrieving representative estimates of soil water content at a horizontal scale of hectometres (the “field scale”) and depths of tens of centimetres (“the root zone”). This study demonstrates the potential of the CRNS technique to obtain spatio-temporal patterns of soil moisture beyond the integrated volume from isolated CRNS footprints. We use data from an observational campaign carried out between May and July 2019 that featured a dense network of more than 20 neutron detectors with partly overlapping footprints in an area that exhibits pronounced soil moisture gradients within one square kilometre. The present study is the first to combine these observations in order to represent the heterogeneity of soil water content at the sub-footprint scale as well as between the CRNS stations. First, we apply a state-of-the-art procedure to correct the observed neutron count rates for static effects (heterogeneity in space, e.g. soil organic matter) and dynamic effects (heterogeneity in time, e.g. barometric pressure). Based on the homogenized neutron data, we investigate the robustness of a calibration approach that uses a single calibration parameter across all CRNS stations. Finally, we benchmark two different interpolation techniques for obtaining spatio-temporal representations of soil moisture: first, ordinary Kriging with a fixed range; second, spatial interpolation complemented by geophysical inversion (“constrained interpolation”). To that end, we optimize the parameters of a geostatistical interpolation model so that the error in the forward-simulated neutron count rates is minimized, and suggest a heuristic forward operator to make the optimization problem computationally feasible. Comparison with independent measurements from a cluster of soil moisture sensors (SoilNet) shows that the constrained interpolation approach is superior for representing horizontal soil moisture gradients at the hectometre scale. The study demonstrates how a CRNS network can be used to generate coherent, consistent, and continuous soil moisture patterns that could be used to validate hydrological models or remote sensing products.