Biomass water content effect on soil moisture assessment via proximal gamma-ray spectroscopy

Modelling Soil Water Content in a Tomato Field: Proximal Gamma Ray Spectroscopy and Soil–Crop System Models

Agriculture ◽

10.3390/agriculture8040060 ◽

2018 ◽

Vol 8 (4) ◽

pp. 60 ◽

Cited By ~ 16

Author(s):

Virginia Strati ◽

Matteo Albéri ◽

Stefano Anconelli ◽

Marica Baldoncini ◽

Marco Bittelli ◽

...

Keyword(s):

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Gamma Ray ◽

System Models ◽

Tomato Field ◽

Gamma Ray Spectroscopy ◽

Crop System

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Investigating the potentialities of Monte Carlo simulation for assessing soil water content via proximal gamma-ray spectroscopy

Journal of Environmental Radioactivity ◽

10.1016/j.jenvrad.2018.06.001 ◽

2018 ◽

Vol 192 ◽

pp. 105-116 ◽

Cited By ~ 12

Author(s):

Marica Baldoncini ◽

Matteo Albéri ◽

Carlo Bottardi ◽

Enrico Chiarelli ◽

Kassandra Giulia Cristina Raptis ◽

...

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Gamma Ray ◽

Gamma Ray Spectroscopy

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Proximal Gamma-Ray Spectroscopy: An Effective Tool to Discern Rain from Irrigation

Remote Sensing ◽

10.3390/rs13204103 ◽

2021 ◽

Vol 13 (20) ◽

pp. 4103

Author(s):

Andrea Serafini ◽

Matteo Albéri ◽

Michele Amoretti ◽

Stefano Anconelli ◽

Enrico Bucchi ◽

...

Keyword(s):

Soil Moisture ◽

Gamma Ray ◽

Soil Conditions ◽

Test Field ◽

Field Scale ◽

Simultaneous Observation ◽

New Developments ◽

Gamma Ray Spectroscopy ◽

Single Detector ◽

Crop Types

Proximal gamma-ray spectroscopy is a consolidated technology for a continuous and real‑time tracing of soil water content at field scale. New developments have shown that this method can also act as an unbiased tool for remotely distinguishing rainwater from irrigation without any meteorological support information. Given a single detector, the simultaneous observation in a gamma spectrum of a transient increase in the 214Pb signal, coupled with a decrease in the 40K signal, acts as an effective proxy for rainfall. A decrease in both 214Pb and 40K signals is, instead, a reliable fingerprint for irrigation. We successfully proved this rationale in two data-taking campaigns performed on an agricultural test field with different crop types (tomato and maize). The soil moisture levels were assessed via the 40K gamma signal on the basis of a one-time setup calibration. The validation against a set of gravimetric measurements showed excellent results on both bare and vegetated soil conditions. Simultaneously, the observed rain-induced increase in the 214Pb signal permitted to identify accurately the rain and irrigation events occurred in the 8852 h of data taking.

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Soil moisture as a potential variable for tracking and quantifying irrigation: A case study with proximal gamma-ray spectroscopy data

Advances in Water Resources ◽

10.1016/j.advwatres.2019.103502 ◽

2020 ◽

Vol 136 ◽

pp. 103502 ◽

Cited By ~ 5

Author(s):

Paolo Filippucci ◽

Angelica Tarpanelli ◽

Christian Massari ◽

Andrea Serafini ◽

Virginia Strati ◽

...

Keyword(s):

Soil Moisture ◽

Gamma Ray ◽

Spectroscopy Data ◽

Gamma Ray Spectroscopy

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Discriminating biomass and soil water content with proximal gamma-ray spectroscopy

10.5194/egusphere-egu2020-22370 ◽

2020 ◽

Author(s):

Fabio Mantovani ◽

Matteo Albéri ◽

Carlo Bottardi ◽

Enrico Chiarelli ◽

Kassandra Giulia Cristina Raptis ◽

...

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Life Cycle ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Gamma Ray ◽

Irrigation Scheduling ◽

Shielding Effect ◽

Gamma Ray Spectroscopy

The exceptional capabilities of proximal radiometric measurements to estimate Soil Water Content (SWC) have recently been proven effective for precision farming applications. The water contained in the growing vegetation (i.e. Biomass Water Content, BWC) attenuates the terrestrial gamma signal acquired by a permanent station in a crop field and it represents the most relevant source of systematic bias. In the perspective of employing proximal gamma-ray spectroscopy for automatic irrigation scheduling, the Biomass Water Content (BWC) correction is mandatory for assessing crop water demand and for a sustainable use of water.In this study we model the time dependent gamma signal attenuation due to BWC and we demonstrate that the SWC estimated through the corrected spectrometric data during a crop life-cycle agrees on average within 4% with the measurements obtained by gravimetric sampling campaigns. A reliable Monte Carlo simulation of the gamma photon generation, propagation and detection phenomena permits to evaluate the shielding effect due to the linear increase of BWC associated to stems, leaves and fruits of the tomatoes during their crop life-cycle. Compared to a SWC gamma estimation in the case of bare soil, the percentage overestimation &#948; is linearly correlated with the thickness of a biomass equivalent water layer (Tk) as &#948; (%) = 9.7 &#183; Tk (mm), with a coefficient of determination r2 = 0.99.Generalizing this approach, we can conclude that the plant growth curve is a fundamental input for correcting the SWC estimates in proximal gamma-ray spectroscopy via Monte Carlo simulation, in the perspective of filling the gap between punctual and satellite soil moisture measurements using this technique.

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