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Exploring the contribution of crop water use to remotely sensed estimates of soil salinity in irrigated agriculture

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dc.contributor.authorCraig, Brian D., author
dc.contributor.authorChávez, José L., advisor
dc.contributor.authorGates, Timothy K., advisor
dc.contributor.authorButters, Gregory L., committee member
dc.date.accessioned2024-01-01T11:23:56Z
dc.date.available2024-01-01T11:23:56Z
dc.date.issued2023
dc.description.abstractGlobally, 72% of the world's water withdrawals are used for agriculture. As the world's population continues to grow and increase its caloric intake, agricultural producers must provide more food and fiber with the same amount of water and soil, or less, due to expanding urbanization and climate change. In Colorado (CO, U.S.A.), agricultural producers in the South Platte and Arkansas River Basins, for instance, have been offered water transfer programs to temporarily or permanently transfer their water shares to municipalities and industry. Another challenge agricultural growers face is soil salinization, which needs to be monitored. In the Arkansas River basin, upflux from saline shallow groundwater tables consistently contributes to crop evapotranspiration (ET), leaving salts in the vadose zone. These salts accumulate over decades to the point where crop yields decline, threatening agricultural sustainability. Remote sensing is an economical tool to monitor salinity (e.g., soil electrical conductivity; EC, dS m-1) at large spatial scales. Existing remote sensing models that predict EC mostly utilize vegetation indices (VIs), which are arithmetic combinations of vegetation reflectances captured by discrete spectral bands. In this study, two additional explanatory variables were investigated: 1) the actual crop ET (ETa, mm d-1), and 2) the crop water stress index (CWSI). Calculations of ETa were performed using Landsat satellite multispectral imagery and a surface energy balance approach. This research was conducted over two growing seasons in commercial maize fields located within the Fairmont Drainage District near Swink, CO. Results indicate that models including ETa or CWSI with existing VIs improve the accuracy of soil EC mapping over models including VIs alone. The developed EC models are accurate within ±1 dS m-1 (Root Mean Squared Error), which is considered well within the precision required to make pragmatic field and ditch company-level management decisions.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.identifierCraig_colostate_0053N_18067.pdf
dc.identifier.urihttps://hdl.handle.net/10217/237347
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2020-
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectremote sensing
dc.subjectevapotranspiration
dc.subjectsalinity
dc.titleExploring the contribution of crop water use to remotely sensed estimates of soil salinity in irrigated agriculture
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineCivil and Environmental Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.S.)

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