Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field
Gamma-ray spectroscopy (GRS) enables continuous estimation of soil water content (SWC) at the subfield scale with a noninvasive sensor. Hydrological applications, including hyper-resolution land surface models and precision agricultural decision making, could benefit greatly from such SWC informatio...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/7/2223 |
| _version_ | 1797211971784802304 |
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| author | Sophia M. Becker Trenton E. Franz Tanessa C. Morris Bailey Mullins |
| author_facet | Sophia M. Becker Trenton E. Franz Tanessa C. Morris Bailey Mullins |
| author_sort | Sophia M. Becker |
| collection | DOAJ |
| description | Gamma-ray spectroscopy (GRS) enables continuous estimation of soil water content (SWC) at the subfield scale with a noninvasive sensor. Hydrological applications, including hyper-resolution land surface models and precision agricultural decision making, could benefit greatly from such SWC information, but a gap exists between established theory and accurate estimation of SWC from GRS in the field. In response, we conducted a robust three-year field validation study at a well-instrumented agricultural site in Nebraska, United States. The study involved 27 gravimetric water content sampling campaigns in maize and soybean and <sup>40</sup>K specific activity (Bq kg<sup>−1</sup>) measurements from a stationary GRS sensor. Our analysis showed that the current method for biomass water content correction is appropriate for our maize and soybean field but that the ratio of soil mass attenuation to water mass attenuation used in the theoretical equation must be adjusted to satisfactorily describe the field data. We propose a calibration equation with two free parameters: the theoretical <sup>40</sup>K intensity in dry soil and <i>a</i>, which creates an “effective” mass attenuation ratio. Based on statistical analyses of our data set, we recommend calibrating the GRS sensor for SWC estimation using 10 profiles within the footprint and 5 calibration sampling campaigns to achieve a cross-validation root mean square error below 0.035 g g<sup>−1</sup>. |
| first_indexed | 2024-04-24T10:34:58Z |
| format | Article |
| id | doaj.art-cbbfb51df3dc469aa13924da7285900d |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-24T10:34:58Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-cbbfb51df3dc469aa13924da7285900d2024-04-12T13:26:31ZengMDPI AGSensors1424-82202024-03-01247222310.3390/s24072223Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural FieldSophia M. Becker0Trenton E. Franz1Tanessa C. Morris2Bailey Mullins3School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68503, USASchool of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68503, USASchool of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68503, USASchool of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68503, USAGamma-ray spectroscopy (GRS) enables continuous estimation of soil water content (SWC) at the subfield scale with a noninvasive sensor. Hydrological applications, including hyper-resolution land surface models and precision agricultural decision making, could benefit greatly from such SWC information, but a gap exists between established theory and accurate estimation of SWC from GRS in the field. In response, we conducted a robust three-year field validation study at a well-instrumented agricultural site in Nebraska, United States. The study involved 27 gravimetric water content sampling campaigns in maize and soybean and <sup>40</sup>K specific activity (Bq kg<sup>−1</sup>) measurements from a stationary GRS sensor. Our analysis showed that the current method for biomass water content correction is appropriate for our maize and soybean field but that the ratio of soil mass attenuation to water mass attenuation used in the theoretical equation must be adjusted to satisfactorily describe the field data. We propose a calibration equation with two free parameters: the theoretical <sup>40</sup>K intensity in dry soil and <i>a</i>, which creates an “effective” mass attenuation ratio. Based on statistical analyses of our data set, we recommend calibrating the GRS sensor for SWC estimation using 10 profiles within the footprint and 5 calibration sampling campaigns to achieve a cross-validation root mean square error below 0.035 g g<sup>−1</sup>.https://www.mdpi.com/1424-8220/24/7/2223soil water contentgamma-ray spectroscopyfield validation |
| spellingShingle | Sophia M. Becker Trenton E. Franz Tanessa C. Morris Bailey Mullins Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field Sensors soil water content gamma-ray spectroscopy field validation |
| title | Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field |
| title_full | Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field |
| title_fullStr | Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field |
| title_full_unstemmed | Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field |
| title_short | Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field |
| title_sort | field testing of gamma spectroscopy method for soil water content estimation in an agricultural field |
| topic | soil water content gamma-ray spectroscopy field validation |
| url | https://www.mdpi.com/1424-8220/24/7/2223 |
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