Determining Near-Surface Soil Heat Flux Density Using the Gradient Method: A Thermal Conductivity Model–Based Approach

dc.contributor.author Peng, Xiaoyang
dc.contributor.author Heitman, Joshua
dc.contributor.author Horton, Robert
dc.contributor.author Horton, Robert
dc.contributor.author Ren, Tusheng
dc.contributor.department Agronomy
dc.date 2020-09-11T15:28:59.000
dc.date.accessioned 2021-02-24T19:25:22Z
dc.date.available 2021-02-24T19:25:22Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2017
dc.date.issued 2017-08-01
dc.description.abstract <p>In the gradient method, soil heat flux density at a known depth <em>G</em> is determined as the product of soil thermal conductivity <em>λ</em> and temperature <em>T</em> gradient. While measuring <em>λ</em> in situ is difficult, many field studies readily support continuous, long-term monitoring of soil <em>T</em> and water content <em>θ</em> in the vadose zone. In this study, the performance of the gradient method is evaluated for estimating near-surface <em>G</em> using modeled <em>λ</em> and measured <em>T</em>. Hourly <em>λ</em> was estimated using a model that related <em>λ</em> to <em>θ</em>, soil bulk density <em>ρ</em><sub><em>b</em></sub>, and texture at 2-, 6-, and 10-cm depths. Soil heat flux <em>G</em><sub><em>m</em></sub> was estimated from modeled <em>λ</em> and measured <em>T</em> gradient (from thermocouples). The <em>G</em><sub><em>m</em></sub> results were evaluated with heat flux data <em>G</em><sub>HP</sub> determined using independent measured <em>λ</em> and <em>T</em> gradient from heat-pulse probes. The <em>λ</em> model performed well at the three depths with 3.3%–7.4% errors. The <em>G</em><sub><em>m</em></sub> estimates were similar to <em>G</em><sub>HP</sub> (agreed to within 15.1%), with the poorest agreement at the 2-cm soil depth, which was caused mainly by the relatively greater variability in <em>ρ</em><sub><em>b</em></sub>. Accounting for temporal variations in <em>ρ</em><sub><em>b</em></sub> (with core method) improved the accuracies of <em>λ</em> and <em>G</em><sub><em>m</em></sub> at the 2-cm depth. Automated <em>θ</em> monitoring approaches (e.g., time domain reflectometry), rather than gravimetric sampling, captured the temporal dynamics of near-surface <em>λ</em> and <em>G</em> well. It is concluded that with continuous <em>θ</em> and <em>T</em> measurements, the <em>λ</em> model–based gradient method can provide reliable near-surface <em>G</em>. Under conditions of soil disturbance or deformation, including temporally variable <em>ρ</em><sub><em>b</em></sub>, data improves the accuracy of <em>G</em> data.</p>
dc.description.comments <p>This article is published as Peng, Xiaoyang, Joshua Heitman, Robert Horton, and Tusheng Ren. "Determining near-surface soil heat flux density using the gradient method: A thermal conductivity model–based approach." <em>Journal of Hydrometeorology</em> 18, no. 8 (2017): 2285-2295. doi: <a href="https://doi.org/10.1175/JHM-D-16-0290.1" target="_blank">10.1175/JHM-D-16-0290.1</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/agron_pubs/677/
dc.identifier.articleid 1725
dc.identifier.contextkey 19346454
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath agron_pubs/677
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/93076
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/agron_pubs/677/2017_Horton_DeterminingNear.pdf|||Sat Jan 15 01:28:06 UTC 2022
dc.source.uri 10.1175/JHM-D-16-0290.1
dc.subject.disciplines Agriculture
dc.subject.disciplines Soil Science
dc.subject.disciplines Statistical Models
dc.title Determining Near-Surface Soil Heat Flux Density Using the Gradient Method: A Thermal Conductivity Model–Based Approach
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication d3fb0917-6868-417e-9695-a010896cfafa
relation.isOrgUnitOfPublication fdd5c06c-bdbe-469c-a38e-51e664fece7a
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