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Article

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

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Department of Physics and Earth Sciences, University of Ferrara, 44122 Ferrara, Italy
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INFN, Ferrara Section, 44122 Ferrara, Italy
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Laboratorio Terra&AcquaTech, 44121 Ferrara, Italy
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INFN, Legnaro National Laboratories, 35020 Padua, Italy
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Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy
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Center for Energy and Environment—CIDEA, University of Parma, 43124 Parma, Italy
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Consorzio Bonifica CER, 40137 Bologna, Italy
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Italian Aerospace Research Centre CIRA, Capua, 81043 Caserta, Italy
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GeoExplorer Impresa Sociale S.r.l., 52100 Arezzo, Italy
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Department of Mathematics and Physics, University of Campania “Luigi Vanvitelli”, 81100 Caserta, Italy
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INFN, Napoli Section, Complesso Universitario di Monte S. Angelo, 80126 Napoli, Italy
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Author to whom correspondence should be addressed.
Academic Editors: Chiara Corbari, Kamal Labbassi, Francesco Vuolo and Kaniska Mallick
Remote Sens. 2021, 13(20), 4103; https://doi.org/10.3390/rs13204103
Received: 31 August 2021 / Revised: 29 September 2021 / Accepted: 8 October 2021 / Published: 13 October 2021
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. View Full-Text
Keywords: irrigation scheduling; soil water content; real-time monitoring; agriculture 4.0; maize; tomato irrigation scheduling; soil water content; real-time monitoring; agriculture 4.0; maize; tomato
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MDPI and ACS Style

Serafini, A.; Albéri, M.; Amoretti, M.; Anconelli, S.; Bucchi, E.; Caselli, S.; Chiarelli, E.; Cicala, L.; Colonna, T.; De Cesare, M.; Gentile, S.; Guastaldi, E.; Letterio, T.; Maino, A.; Mantovani, F.; Montuschi, M.; Penzotti, G.; Raptis, K.G.C.; Semenza, F.; Solimando, D.; Strati, V. Proximal Gamma-Ray Spectroscopy: An Effective Tool to Discern Rain from Irrigation. Remote Sens. 2021, 13, 4103. https://doi.org/10.3390/rs13204103

AMA Style

Serafini A, Albéri M, Amoretti M, Anconelli S, Bucchi E, Caselli S, Chiarelli E, Cicala L, Colonna T, De Cesare M, Gentile S, Guastaldi E, Letterio T, Maino A, Mantovani F, Montuschi M, Penzotti G, Raptis KGC, Semenza F, Solimando D, Strati V. Proximal Gamma-Ray Spectroscopy: An Effective Tool to Discern Rain from Irrigation. Remote Sensing. 2021; 13(20):4103. https://doi.org/10.3390/rs13204103

Chicago/Turabian Style

Serafini, Andrea, Matteo Albéri, Michele Amoretti, Stefano Anconelli, Enrico Bucchi, Stefano Caselli, Enrico Chiarelli, Luca Cicala, Tommaso Colonna, Mario De Cesare, Salvatore Gentile, Enrico Guastaldi, Tommaso Letterio, Andrea Maino, Fabio Mantovani, Michele Montuschi, Gabriele Penzotti, Kassandra G.C. Raptis, Filippo Semenza, Domenico Solimando, and Virginia Strati. 2021. "Proximal Gamma-Ray Spectroscopy: An Effective Tool to Discern Rain from Irrigation" Remote Sensing 13, no. 20: 4103. https://doi.org/10.3390/rs13204103

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