dc.contributor.advisor | Ochsner, Tyson | |
dc.contributor.author | Brown, William Gerald, Jr. | |
dc.date.accessioned | 2022-01-21T19:33:58Z | |
dc.date.available | 2022-01-21T19:33:58Z | |
dc.date.issued | 2021-07 | |
dc.identifier.uri | https://hdl.handle.net/11244/333834 | |
dc.description.abstract | Accurate, field-scale soil moisture information is needed to match the spatial scale of land and water management decisions related to agricultural production and environmental protection. Soil moisture measurements at the field-scale are limited because the resolution of most satellite-based soil moisture products is too coarse, while most in situ monitoring networks can provide only point-scale, not field-scale, data. This research attempts to develop a broadly applicable upscaling approach for observations from in situ soil moisture sensors using data from the Marena, Oklahoma, In Situ Sensor Testbed (MOISST) and a cosmic-ray neutron rover. The landscape at the MOISST site is predominantly grassland with some deciduous trees and eastern redcedar intermixed. Cosmic-ray neutron rover survey data were used to measure average soil moisture for the ~64 ha site on 12 dates in 2019-2020. The relationships between the point-scale in situ data and the field-scale rover data were examined using data from six in situ stations. Statistical modeling was used to identify the soil, terrain, and vegetation properties that influence these relationships. Site-specific linear upscaling models estimated the field average soil moisture with root mean squared error (RMSE) values ranging from 0.014 - 0.022 cm3 cm-3, but these models are not transferable to other sites. A general upscaling model using soil texture data was developed and achieved RMSE values ranging from 0.017 - 0.038 cm3 cm-3 for four calibration sites and values ranging from 0.015 - 0.021 cm3 cm-3 for two validation sites. The general upscaling model demonstrated accuracy better than the commonly used threshold of 0.04 cm3 cm-3 and should be further tested to evaluate its suitability as a broadly applicable upscaling approach for point-scale in situ monitoring stations. | |
dc.format | application/pdf | |
dc.language | en_US | |
dc.rights | Copyright is held by the author who has granted the Oklahoma State University Library the non-exclusive right to share this material in its institutional repository. Contact Digital Library Services at lib-dls@okstate.edu or 405-744-9161 for the permission policy on the use, reproduction or distribution of this material. | |
dc.title | Upscaling soil moisture measurements from in situ sensors | |
dc.contributor.committeeMember | Zou, Chris | |
dc.contributor.committeeMember | Abit, Sergio | |
osu.filename | Brown_okstate_0664M_17382.pdf | |
osu.accesstype | Open Access | |
dc.type.genre | Thesis | |
dc.type.material | Text | |
dc.subject.keywords | moisture | |
dc.subject.keywords | rover | |
dc.subject.keywords | upscaling | |
thesis.degree.discipline | Plant and Soil Sciences | |
thesis.degree.grantor | Oklahoma State University | |