{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T21:42:59Z","timestamp":1780436579854,"version":"3.54.1"},"reference-count":91,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2019,2,5]],"date-time":"2019-02-05T00:00:00Z","timestamp":1549324800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Department of Education and Training, The Australian Government","award":["2016 Endeavour Australia Cheung Kong Research Fellowship"],"award-info":[{"award-number":["2016 Endeavour Australia Cheung Kong Research Fellowship"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Soil water content is an important parameter in many engineering, agricultural and environmental applications. In practice, there exists a need to measure this parameter rather frequently in both time and space. However, common measurement techniques are typically invasive, time-consuming and labour-intensive, or rely on potentially risky (although highly regulated) nuclear-based methods, making frequent measurements of soil water content impractical. Here we investigate in the laboratory the effectiveness of four new low-cost non-invasive sensors to estimate the soil water content of a range of soil types. While the results of each of the four sensors are promising, one of the sensors, herein called the \u201cAOGAN\u201d sensor, exhibits superior performance, as it was designed based on combining the best geometrical and electronic features of the other three sensors. The performance of the sensors is, however, influenced by the quality of the sensor-soil coupling and the soil surface roughness. Accuracy was found to be within 5% of volumetric water content, considered sufficient to enable higher spatiotemporal resolution contrast for mapping of soil water content.<\/jats:p>","DOI":"10.3390\/s19030651","type":"journal-article","created":{"date-parts":[[2019,2,6]],"date-time":"2019-02-06T03:03:05Z","timestamp":1549422185000},"page":"651","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A Laboratory Study on Non-Invasive Soil Water Content Estimation Using Capacitive Based Sensors"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0544-8448","authenticated-orcid":false,"given":"Amir","family":"Orangi","sequence":"first","affiliation":[{"name":"Department of Infrastructure Engineering, School of Engineering, The University of Melbourne, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1219-5661","authenticated-orcid":false,"given":"Guillermo A.","family":"Narsilio","sequence":"additional","affiliation":[{"name":"Department of Infrastructure Engineering, School of Engineering, The University of Melbourne, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5335-6209","authenticated-orcid":false,"given":"Dongryeol","family":"Ryu","sequence":"additional","affiliation":[{"name":"Department of Infrastructure Engineering, School of Engineering, The University of Melbourne, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Famiglietti, J.S., Ryu, D., Berg, A.A., Rodell, M., and Jackson, T.J. 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