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dc.contributor.advisorCrimmins, Michael A.en
dc.contributor.authorMcKellar, Trevor T.
dc.creatorMcKellar, Trevor T.en
dc.date.accessioned2017-03-28T16:58:50Z
dc.date.available2017-03-28T16:58:50Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/10150/622900
dc.description.abstractDrought indices based on monthly precipitation and sometimes temperature are widely used due to their simple calculation with readily available climate data. The portrayal of drought through simple precipitation anomalies or water balances when accounting for temperature may not capture the potentially complex evolution of drought events due to the timing, intensity, and frequency of precipitation events at the daily scale. In this study, we present a new drought index that incorporates a deterministic soil model, HYDRUS-1D, and daily climate data to assess how representative simple drought indices are of soil moisture status in the Southwest. Specifically, we compare our drought index with two widely used drought indices: the Standardized Precipitation Index (SPI) and the Standardized Perception-Evapotranspiration Index (SPEI). Modeled soil moisture output was summed into monthly values for direct comparison between indices. SPI and SPEI proved to be representative of soil moisture status at shallow depths, correlating best at a two-month window. SPI correlated higher with our modeled drought index than SPEI in shallow settings across all study sites. Intense drought events were controlled by the magnitude and frequency of precipitation, with large events creating water surplus and then a slow decay in soil moisture until the next large event. Furthermore, heat map correlations indicate that monitoring drought at depth is dependent upon the previous years monsoon, with the best correlating window growing with distance from monsoon onset. Modeled soil moisture showed volumetric water content increased during monsoon season and remained high through the fall and into the winter months. Higher moisture content increased hydraulic conductivity, priming the soil profile for winter recharge. We believe that the addition of a soil physics based drought index greatly improves drought monitoring conditions for the southwest.
dc.language.isoen_USen
dc.publisherThe University of Arizona.en
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en
dc.subjectHydrusen
dc.subjectIndexen
dc.subjectSouthwesten
dc.subjectSPEIen
dc.subjectSPIen
dc.subjectDroughten
dc.titleEvaluating How Representative Simple Multiscalar Drought Indices Are of Modeled Soil Moisture Across the Desert Southwest United Statesen_US
dc.typetexten
dc.typeElectronic Thesisen
thesis.degree.grantorUniversity of Arizonaen
thesis.degree.levelmastersen
dc.contributor.committeememberCrimmins, Michael A.en
dc.contributor.committeememberRasmussen, Craigen
dc.contributor.committeememberSchaap, Marcel G.en
thesis.degree.disciplineGraduate Collegeen
thesis.degree.disciplineSoil, Water and Environmental Scienceen
thesis.degree.nameM.S.en
refterms.dateFOA2018-06-18T10:20:34Z
html.description.abstractDrought indices based on monthly precipitation and sometimes temperature are widely used due to their simple calculation with readily available climate data. The portrayal of drought through simple precipitation anomalies or water balances when accounting for temperature may not capture the potentially complex evolution of drought events due to the timing, intensity, and frequency of precipitation events at the daily scale. In this study, we present a new drought index that incorporates a deterministic soil model, HYDRUS-1D, and daily climate data to assess how representative simple drought indices are of soil moisture status in the Southwest. Specifically, we compare our drought index with two widely used drought indices: the Standardized Precipitation Index (SPI) and the Standardized Perception-Evapotranspiration Index (SPEI). Modeled soil moisture output was summed into monthly values for direct comparison between indices. SPI and SPEI proved to be representative of soil moisture status at shallow depths, correlating best at a two-month window. SPI correlated higher with our modeled drought index than SPEI in shallow settings across all study sites. Intense drought events were controlled by the magnitude and frequency of precipitation, with large events creating water surplus and then a slow decay in soil moisture until the next large event. Furthermore, heat map correlations indicate that monitoring drought at depth is dependent upon the previous years monsoon, with the best correlating window growing with distance from monsoon onset. Modeled soil moisture showed volumetric water content increased during monsoon season and remained high through the fall and into the winter months. Higher moisture content increased hydraulic conductivity, priming the soil profile for winter recharge. We believe that the addition of a soil physics based drought index greatly improves drought monitoring conditions for the southwest.


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