Sensitivity of in-situ γ-ray spectra to soil density and water content

Groot, A.V. de; Graaf, van der Emiel; Meijer, R.J. de; Maučec, Marko

doi:10.1016/j.nima.2008.12.003

Cited by 37 publications

(16 citation statements)

References 16 publications

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“…The shape and intensity of the spectra are not affected by measurement height (Hendriks, 2002). Soil moisture does affect the signal intensity: an increase of 10% in soil moisture results in a 10% decrease in intensity (De Groot et al , 2009), but this has no effect on the spectral balance. The soil moisture differences during measurement are not expected to be more than 10%.…”

Section: Methodsmentioning

confidence: 99%

Mapping soil clay contents in Dutch marine districts using gamma-ray spectrometry

Klooster

Egmond²,

Sonneveld

2011

European Journal of Soil Science

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Conventional soil sampling methods to obtain high-resolution soil data are labour intensive and costly. Recently, gamma ray spectrometry has emerged as a promising technique to overcome these obstacles. The objective of our study was to investigate the prediction of soil clay contents using gamma-ray spectrometry in three marine clay districts in the Netherlands: the southwestern marine district (SMD), the IJsselmeerpolder district (IJPD) and the northern marine district (NMD). The performance of linear regression models was investigated at field (<1 km 2 ), regional (1-1000 km 2 ) and district (>1000 km 2 ) scales and for all the Dutch marine districts together. For this study, a database was available with 1371 gamma-ray spectra measured on arable fields in marine clay districts during the period 2005-2008 and these were all linked to laboratory analyses of clay contents. At the field scale, linear regression models based on 40 K, 232 Th, or a combination of these revealed much smaller root mean squared error (RMSE) values (2-3%) compared with a model based on the field mean (8-10%). At the district scale, the regression models for the SMD and IJPD, which have comparable sediments, performed better than for the NMD. This indicates that the prediction of clay contents in late Holocene marine sediments may be made with gamma-ray spectrometry provided that the origin of the parent material results in a unique fingerprint. Because of the heterogeneous parent material of all marine districts taken together, our study shows that no unique and precise fingerprint exists, and the RMSE of 6% between clay contents and gamma-ray spectra is not much different from the RMSE of 7% when using the overall mean as a predictor.

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Section: Methodsmentioning

confidence: 99%

Mapping soil clay contents in Dutch marine districts using gamma-ray spectrometry

Klooster

Egmond²,

Sonneveld

2011

European Journal of Soil Science

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“…De Groot et al. () applied Monte‐Carlo simulations and ascertained the influence of soil bulk density and water content changes onto the captured volume. Despite the great usefulness of these simulations, practical field checks should always proof theoretical findings.…”

Section: Fundamentalsmentioning

confidence: 99%

Gamma‐ray spectrometry as versatile tool in soil science: A critical review

Reinhardt

Herrmann

2018

J. Plant Nutr. Soil Sci.

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Gamma‐ray spectrometry is an established method in geo‐sciences. This article gives an overview on fundamentals of gamma‐ray spectrometry that are relevant to soil science including basic technical aspects, and discusses influencing factors, inconsistencies, limitations, and open questions related to the method. Gamma‐ray spectrometry relies on counting gamma quanta during radionuclide decay of 40K, 238U, and 232Th, but secular equilibrium for the decay series of U and Th must be given as decays of their respective daughter radionuclides are used for determination. Secular equilibrium for U and Th decay series, however, is not always given leading to, e.g., anomalies in U concentration measurements. For soil science, gamma‐ray spectrometry is of specific value since it does not only detect a signal from the landscape surface, but integrates information over a certain volume. Besides, different spatial scales can be covered using either ground‐based or airborne sensing techniques. Together with other remote sensing methods, gamma signatures can provide completive information for understanding land forming processes and soil properties distributions. At first, signals depend on bedrock composition. The signals are in second order altered by weathering processes leading to more interpretation opportunities and challenges. Due to their physico‐chemical properties, radionuclides behave differently in soils and their properties can be distinguished via the resulting signatures. Hence, gamma signatures of soils are specific for local environments. Processes like soil erosion can superimpose gamma signals from in situ weathering. Soil mappings, available K and texture determination, or peat and soil erosion mapping are possible applications being discussed in this review.

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“…These effects are of secondary importance, and if we focus on the primary natural source of gamma emissions, i.e., the Earth's near‐surface material, it appears that not only the nature of soils influences the amount of gamma emission. It has been recognized, and this is used in gamma‐ray propagation modeling (e.g., Perrin et al, 2006; de Groot et al, 2009), that both the physical (texture and density), moisture, and chemical (chemistry and mineralogy) properties of the regolith jointly influence gamma propagation. Several studies have attempted to map regolith parameters—mostly in the 0‐ to 50‐cm depth range—based on correlations with gamma‐spectrometric data, but so far, the ones that we could reference in the literature have mostly focused on one or a few soil parameters.…”

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Regional Regolith Parameter Prediction Using the Proxy of Airborne Gamma Ray Spectrometry

Martelet

Drufin

Tourlière

et al. 2013

Vadose Zone Journal

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Interdependence of regolith density, moisture, and chemistry parameters, as well as their influence on natural gamma ray emissions, led us to investigate systematically whether statistical models could be inferred between gamma spectrometric data and regolith parameters. A series of soil sample parameters were analyzed vs. airborne gamma ray data through multiple linear regressions. Among the approximately 20 regolith parameters modeled (chemical, textural, and mineralogical), about 50% (equally distributed in each category) were found to be predictable, with acceptable error (Radj2 > 0.5 and p value < 5%). With an independent set of texture analyses, we validated two of the predicted parameters (sand and clay contents) with fairly low residuals, with standard deviations of 22 and 16%, respectively. Further statistical investigations revealed why a large number of soil parameters could successfully be modeled in this sedimentary environment. We showed that the main gamma emitters are hosted in weathering products and leached detrital materials. Two main mineral assemblages correlate with gamma variables: (i) fine‐grained weathering clays (with correlated Al, Fe, Mn, Mg, Pb, and V elements), and (ii) residual K‐rich minerals, interpreted as feldspar and/or muscovite (correlated with Na and Sr). Additionally, two chemical elements, Si and Ca, have specific behaviors and can scarcely be characterized by the gamma data: they apparently mitigate Ɣ signatures.

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Sensitivity of in-situ γ-ray spectra to soil density and water content

Cited by 37 publications

References 16 publications

Mapping soil clay contents in Dutch marine districts using gamma-ray spectrometry

Mapping soil clay contents in Dutch marine districts using gamma-ray spectrometry

Gamma‐ray spectrometry as versatile tool in soil science: A critical review

Regional Regolith Parameter Prediction Using the Proxy of Airborne Gamma Ray Spectrometry

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