Understanding and modeling the relationship between solar-induced chlorophyll fluorescence, carbon, water, and vegetation

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dc.contributor.advisorYang, Zong-liang
dc.contributor.committeeMemberDickinson, Robert E
dc.contributor.committeeMemberScanlon, Bridget R
dc.contributor.committeeMemberJoiner, Joanna
dc.contributor.committeeMemberBanner, Jay L
dc.creatorHalubok, Maryia
dc.creator.orcid0000-0002-6498-9570
dc.date.accessioned2018-10-12T19:51:36Z
dc.date.available2018-10-12T19:51:36Z
dc.date.created2018-08
dc.date.issued2018-08-16
dc.date.submittedAugust 2018
dc.date.updated2018-10-12T19:51:36Z
dc.description.abstractOur ability to understand how global vegetation uptakes atmospheric CO2 is crucial for closing the Earth’s carbon budget and predicting feedbacks under a changing climate, but this understanding has been poor primarily due to limited observations and analyses. Recently, satellite retrievals of solar-induced chlorophyll fluorescence (SIF) have provided a highly credible opportunity to estimate gross primary production (GPP) and for monitoring droughts. Despite this exciting progress, there are limited studies on how SIF is related to precipitation, soil moisture and GPP. Ultimately, it remains unknown how SIF is emitted from vegetation canopies before it can be detected by satellites from space. This dissertation aims to address the following questions: (1) How can SIF in conjunction with other environmental variables be used to estimate plant production? (2) What are possible implications of SIF-based GPP for drought detecting and monitoring? How effective is SIF in capturing the onset and demise of a drought event? (3) How can simulations of solar-induced chlorophyll fluorescence radiative transfer be improved with the use of Monte Carlo ray tracing approach and what are the advantages and limitations of this method? Is it feasible to employ this approach in addressing issues with satellite-based SIF related to the configuration of satellites? The main scientific findings are as follows: (1) Multiple linear regression estimates of GPP using SIF, precipitation and soil moisture and accounting for the lead–lag relationship between SIF, precipitation and soil moisture, are produced and agree well with FLUXNET flux tower data; (2) SIF is unlikely to be useful as an early meteorological drought indicator; in addition, SIF apparently does not respond to the stress conditions faster than common remotely-sensed vegetation indices (VIs); (3) The Monte Carlo ray tracing model can successfully simulate fluorescence emitted from the top of a canopy and provides useful insights into how global scale SIF satellite retrievals can be clarified.
dc.description.departmentEarth and Planetary Sciences
dc.format.mimetypeapplication/pdf
dc.identifierdoi:10.15781/T24747981
dc.identifier.urihttp://hdl.handle.net/2152/68886
dc.language.isoen
dc.subjectSolar-induced chlorophyll fluorescence
dc.subjectPlant productivity
dc.subjectDrought events
dc.titleUnderstanding and modeling the relationship between solar-induced chlorophyll fluorescence, carbon, water, and vegetation
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentGeological Sciences
thesis.degree.disciplineGeological sciences
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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