15 research outputs found
Training Future Engineers to Be Ghostbusters: Hunting for the Spectral Environmental Radioactivity
Although environmental radioactivity is all around us, the collective public
imagination often associates a negative feeling to this natural phenomenon. To
increase the familiarity with this phenomenon we have designed, implemented,
and tested an interdisciplinary educational activity for pre-collegiate
students in which nuclear engineering and computer science are ancillary to the
comprehension of basic physics concepts. Teaching and training experiences are
performed by using a 4" x 4" NaI(Tl) detector for in-situ and laboratory
{\gamma}-ray spectroscopy measurements. Students are asked to directly assemble
the experimental setup and to manage the data-taking with a dedicated Android
app, which exploits a client-server system that is based on the Bluetooth
communication protocol. The acquired {\gamma}-ray spectra and the experimental
results are analyzed using a multiple-platform software environment and they
are finally shared on an open access Web-GIS service. These all-round
activities combining theoretical background, hands-on setup operations, data
analysis, and critical synthesis of the results were demonstrated to be
effective in increasing students' awareness in quantitatively investigating
environmental radioactivity. Supporting information to the basic physics
concepts provided in this article can be found at
http://www.fe.infn.it/radioactivity/educational
Modelling soil water conent in a tomato field: proximal gamma ray spectroscopy and soil-crop system models
Proximal soil sensors are taking hold in the understanding of soil
hydrogeological processes involved in precision agriculture. In this context,
permanently installed gamma ray spectroscopy stations represent one of the best
space-time trade off methods at field scale. This study proved the feasibility
and reliability of soil water content monitoring through a seven-month
continuous acquisition of terrestrial gamma radiation in a tomato test field.
By employing a 1 L sodium iodide detector placed at a height of 2.25 m, we
investigated the gamma signal coming from an area having a ~25 m radius and
from a depth of approximately 30 cm. Experimental values, inferred after a
calibration measurement and corrected for the presence of biomass, were
corroborated with gravimetric data acquired under different soil moisture
conditions, giving an average absolute discrepancy of about 2%. A quantitative
comparison was carried out with data simulated by AquaCrop, CRITeRIA, and
IRRINET soil-crop system models. The different goodness of fit obtained in bare
soil condition and during the vegetated period highlighted that CRITeRIA showed
the best agreement with the experimental data over the entire data-taking
period while, in presence of the tomato crop, IRRINET provided the best
results.Comment: 18 pages, 9 Figures, 3 Table
Accuracy of flight altitude measured with low-cost GNSS, radar and barometer sensors: Implications for airborne radiometric surveys
Flight height is a fundamental parameter for correcting the gamma signal produced by terrestrial radionuclides measured during airborne surveys. The frontiers of radiometric measurements with UAV require light and accurate altimeters flying at some 10 m from the ground. We equipped an aircraft with seven altimetric sensors (three low-cost GNSS receivers, one inertial measurement unit, one radar altimeter and two barometers) and analyzed ~3 h of data collected over the sea in the (35–2194) m altitude range. At low altitudes (H 80 m in terms of both altitude median standard deviation and agreement between the reconstructed and measured GPS antennas distances. Flying at 100 m the estimated uncertainty on the ground total activity due to the uncertainty on the flight height is of the order of 2%
Filling the gap between punctual and satellite soil moisture measurements through proximal gamma-ray spectroscopy
Filling the gap between punctual (∼cm^2) and catchment (∼10 ha) soil moisture measurements is an urgent open issue that recently boosted the development of nuclear based monitoring techniques hinging on the detection of cosmic-ray neutrons and gamma-rays. Indeed, despite the increasing number of satellite missions and the growing availability of open access satellite images repositories, calibration ground-truth measurements are required for a comprehensive interpretation of hyperspectral data. The fate of the sparse and sporadic punctual measurements performed with electromagnetic and gravimetric methods is to be overcome by innovative technologies for a non-invasive, contactless and continuous monitoring of soil moisture at field scale. In this scenario, proximal gamma-ray spectroscopy is identified as a promising tool for a full exploitation of high quality satellite data, with the perspective of realizing tangible applications in the field of sustainable agriculture, threatened by relentless effects due to climate changes. The terrestrial gamma signal measured with a spectrometer installed at a few meters above the ground is inversely correlated with soil water content and is basically insensitive to variations in cosmic radiation and soil chemical composition. With a dedicated experiment carried out in a tomato agricultural test field, we hourly collected gamma-ray spectra over a period of 7 months covering the entire crop growing season. We obtained reliable non-stop estimates of top soil (∼ 30 cm) moisture levels with a ∼2·10^3 m^2 footprint by calibrating and correcting with a Monte Carlo based approach the gamma signal due to the naturally occurring potassium radioisotope (40K) detected during the entire crop season. Proximal gamma-ray spectroscopy with permanent stations is one of the best space-time trade-off methods which can provide accurate time series of soil moisture, concurrently minimizing time costs and manpower thanks to the employment of real-time and remotely controlled sensors. This proof of concept experiment demonstrates that networks of proximal gamma-ray spectroscopy stations can potentially fulfill the spatiotemporal requirements for the calibration of satellite observations, as well as provide a support decision tool for a rational use of water resources
Challenges, solutions and benefits of natural radioactivity mapping
The spatial interpolation of punctual radiometric data for the realization of natural radioactivity maps poses several challenges associated to the integration of information referred to different measurement techniques, measurement errors, detectors’ field of view and morphological features. Indeed, the elaboration of a unique cartographic product with an appropriate descriptive legend from laboratory, in-situ and airborne gamma-ray spectroscopy data cannot be pursued without critically dealing with some delicate issues. Gamma ray surveys allow for monitoring the spatial distribution of terrestrial radioelements (K, U and Th) and in turn provide valuable insights on geological mapping, structural geology and soil surveying. The high efficiency and relatively good spectral resolution make Sodium Iodide (NaI) detectors particularly suitable for real-time insitu and airborne measurements, respectively characterized by a spatial footprint of ∼m^2 and ∼10^5 m^2. On the other hand, Hyper Pure Germanium (HPGe) detectors, thanks to the optimal spectral resolution combined with low radiation background, are ideal for achieving very low uncertainties in gamma-ray measurements performed in laboratory on rock and soil samples. We dealt with these problematic aspects proposing operative solutions regarding the statistical treatment of analyzed datasets, the heterogeneous experimental uncertainties and the spatial resolution of the measurements. The results obtained from the rigorous study of statistical distributions and the spatial correlation were integrated based on appropriated geostatistical interpolators. Taking on the challenge to treat heterogeneous input uncertainties data, the degree of confidence associated with two different gamma-ray techniques is considered, giving value to the spatial data represented in the map. Multivariate spatial interpolation enhances the estimation of radioelements distribution taking advantage of the correlation existing between the under-sampled gamma-ray measurements and the continuous distributions of geological formations. The described methods were validated through several surveys that cover approximately 50000 km^2 of the Italian territory: specific case studies will be presented and discussed
Biomass water content effect on soil moisture assessment via proximal gamma-ray spectroscopy
Proximal gamma-ray spectroscopy supported by adequate calibration and correction for growing biomass is an
effective field scale technique for a continuous monitoring of top soil water content dynamics to be potentially
employed as a decision support tool for automatic irrigation scheduling. This study demonstrates that this approach
has the potential to be one of the best space–time trade-off methods, representing a joining link between
punctual and satellite fields of view. The inverse proportionality between soil moisture and gamma signal is
theoretically derived taking into account a non-constant correction due to the presence of growing vegetation
beneath the detector position. The gamma signal attenuation due to biomass is modelled with a Monte Carlobased
approach in terms of an equivalent water layer which thickness varies in time as the crop evolves during
its life-cycle. The reliability and effectiveness of this approach is proved through a 7 months continuous acquisition
of terrestrial gamma radiation in a 0.4 ha tomato (Solanum lycopersicum) test field. We demonstrate that
a permanent gamma station installed at an agricultural field can reliably probe the water content of the top soil
only if systematic effects due to the biomass shielding are properly accounted for. Biomass corrected experimental
values of soil water content inferred from radiometric measurements are compared with gravimetric data
acquired under different soil moisture levels, resulting in an average percentage relative discrepancy of about
3% in bare soil condition and of 4% during the vegetated period. The temporal evolution of corrected soil water
content values exhibits a dynamic range coherent with the soil hydraulic properties in terms of wilting point,
field capacity and saturation
Investigating the potentialities of Monte Carlo simulation for assessing soil water content via proximal gamma-ray spectroscopy
Proximal gamma-ray spectroscopy recently emerged as a promising technique for non-stop monitoring of soil water content with possible applications in the field of precision farming. The potentialities of the method are investigated by means of Monte Carlo simulations applied to the reconstruction of gamma-ray spectra collected by a NaI scintillation detector permanently installed at an agricultural experimental site. A two steps simulation strategy based on a geometrical translational invariance is developed. The strengths of this approach are the reduction of computational time with respect to a direct source-detector simulation, the reconstruction of 40K, 232Th and 238U fundamental spectra, the customization in relation to different experimental scenarios and the investigation of effects due to individual variables for sensitivity studies. The reliability of the simulation is effectively validated against an experimental measurement with known soil water content and radionuclides abundances. The relation between soil water content and gamma signal is theoretically derived and applied to a Monte Carlo synthetic calibration performed with the specific soil composition of the experimental site. Ready to use general formulae and simulated coefficients for the estimation of soil water content are also provided adopting standard soil compositions. Linear regressions between input and output soil water contents, inferred from simulated 40K and 208Tl gamma signals, provide excellent results demonstrating the capability of the proposed method in estimating soil water content with an average uncertainty <1%
Accuracy of flight altitude measured with low-cost GNSS, radar and barometer sensors: Implications for airborne radiometric surveys
Flight height is a fundamental parameter for correcting the gamma signal produced by terrestrial radionuclides measured during airborne surveys. The frontiers of radiometric measurements with UAV require light and accurate altimeters flying at some 10 m from the ground. We equipped an aircraft with seven altimetric sensors (three low-cost GNSS receivers, one inertial measurement unit, one radar altimeter and two barometers) and analyzed ~3 h of data collected over the sea in the (35â\u80\u932194) m altitude range. At low altitudes (H 80 m in terms of both altitude median standard deviation and agreement between the reconstructed and measured GPS antennas distances. Flying at 100 m the estimated uncertainty on the ground total activity due to the uncertainty on the flight height is of the order of 2%