{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/84005"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/84005","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Tool Development for Studies on Tephra Fall Deposits and their Stratigraphic Characterization","abstract":"Ph.D.","abstract_html":"Ph.D.","abstract_has_math":false,"creators":["Yang, Qingyuan; 0000-0002-5631-889X"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Bursik, Marcus","Geology"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-06-21T15:46:57Z","date_published":"2022-06-21T15:46:57Z","updated_at":"2026-07-27T19:05:28Z","subjects":["geology"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/84005","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Bursik, Marcus","Geology"]},{"key":"dc:creator","label":"Author","values":["Yang, Qingyuan; 0000-0002-5631-889X"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-06-21T15:46:57Z","2020"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["geology"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/84005"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ph.D.","This thesis focuses on different aspects of studies on tephra fall deposits, and is composed of three projects. The first one investigates physical properties of tephra fall deposits preserved within the Wilson Creek Formation, eastern central California. The other two focus on proposing and testing new methods to identify the vent location of tephra fall deposits, and to estimate the output of volcanic ash transport model Ash3d with Gaussian Process statistical emulator, respectively. Numerous tephra layers occur within the late Pleistocene Wilson Creek Formation, where they are interbedded with lacustrine deposits of Lake Russell, the ancestor of present-day Mono Lake. Most of the tephra layers are rhyolitic in composition, and were produced from the Mono Craters. I present detailed stratigraphy and sedimentology of the tephra layers, sampled at twelve outcrops near the shoreline of Mono Lake and the Mono Craters, and implement grain size, componentry, and surface morphology analyses to characterize their physical properties. Sub-unit correlation is proposed for certain tephra units. Noticeable features are highlighted, and interpretations are made for tephra layers within the Wilson Creek Formation. Knowing the vent location is fundamental to studies on tephra fall deposits. The presented method to identify the vent location uses thickness or maximum clast size measurements as input. The method couples a first-order gradient descent method with either one of two commonly-used semi-empirical models of tephra thickness distribution. It is validated against datasets of varying sizes and qualities and tephra deposits with distinct thickness or maximum clast size distributions. The results suggest the utility of the method, and show that estimating the dispersal axis is a more robust way to constrain the vent location compared to directly estimating the vent coordinates, given sparse observations. Bootstrap aggregation and visualizing the surface of the cost function are used to characterize the uncertainty of the method. How different features of tephra deposits and technical aspects of the method would affect the performance of the method are pointed out. Suggestions on how to use the method given limited observations are listed, which are demonstrated with three small datasets. I also apply the method to well-correlated tephra sub-units within the Wilson Creek Formation to estimate their vent locations and volumes.Probabilistic ash fall hazard assessment provides inferences on regional planning and decision making for areas potentially exposed to volcanic hazards. Conventionally, its implementation requires a large number of numerical simulations, which could become impractical if the adopted numerical model is computationally expensive. The developed algorithm can be used to predict the output of volcanic ash transport model Ash3d for unrun initial conditions based on the machine learning technique Gaussian Process statistical emulator. This algorithm only requires a limited number of Ash3d runs to generate the training data, and the prediction process is fast and efficient. It hence avoids the difficulty in using conventional methods, and enables probabilistic ash fall hazard assessment with computationally expensive models. I illustrate how the algorithm is designed, and test its performance with cross-validation. Novelties of the algorithm are consistent with the physics of tephra transport, and have the potential to benefit the emulator design of other advection-diffusion based numerical models. Advantages, limitations, and simplifications of the algorithm as well as potential measures to optimize it are listed and discussed.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Tool Development for Studies on Tephra Fall Deposits and their Stratigraphic Characterization"]}]}],"canonical_facts":{"dc:contributor":["Bursik, Marcus","Geology"],"dc:creator":["Yang, Qingyuan; 0000-0002-5631-889X"],"dc:date":["2022-06-21T15:46:57Z","2020"],"dc:description":["Ph.D.","This thesis focuses on different aspects of studies on tephra fall deposits, and is composed of three projects. The first one investigates physical properties of tephra fall deposits preserved within the Wilson Creek Formation, eastern central California. The other two focus on proposing and testing new methods to identify the vent location of tephra fall deposits, and to estimate the output of volcanic ash transport model Ash3d with Gaussian Process statistical emulator, respectively. Numerous tephra layers occur within the late Pleistocene Wilson Creek Formation, where they are interbedded with lacustrine deposits of Lake Russell, the ancestor of present-day Mono Lake. Most of the tephra layers are rhyolitic in composition, and were produced from the Mono Craters. I present detailed stratigraphy and sedimentology of the tephra layers, sampled at twelve outcrops near the shoreline of Mono Lake and the Mono Craters, and implement grain size, componentry, and surface morphology analyses to characterize their physical properties. Sub-unit correlation is proposed for certain tephra units. Noticeable features are highlighted, and interpretations are made for tephra layers within the Wilson Creek Formation. Knowing the vent location is fundamental to studies on tephra fall deposits. The presented method to identify the vent location uses thickness or maximum clast size measurements as input. The method couples a first-order gradient descent method with either one of two commonly-used semi-empirical models of tephra thickness distribution. It is validated against datasets of varying sizes and qualities and tephra deposits with distinct thickness or maximum clast size distributions. The results suggest the utility of the method, and show that estimating the dispersal axis is a more robust way to constrain the vent location compared to directly estimating the vent coordinates, given sparse observations. Bootstrap aggregation and visualizing the surface of the cost function are used to characterize the uncertainty of the method. How different features of tephra deposits and technical aspects of the method would affect the performance of the method are pointed out. Suggestions on how to use the method given limited observations are listed, which are demonstrated with three small datasets. I also apply the method to well-correlated tephra sub-units within the Wilson Creek Formation to estimate their vent locations and volumes.Probabilistic ash fall hazard assessment provides inferences on regional planning and decision making for areas potentially exposed to volcanic hazards. Conventionally, its implementation requires a large number of numerical simulations, which could become impractical if the adopted numerical model is computationally expensive. The developed algorithm can be used to predict the output of volcanic ash transport model Ash3d for unrun initial conditions based on the machine learning technique Gaussian Process statistical emulator. This algorithm only requires a limited number of Ash3d runs to generate the training data, and the prediction process is fast and efficient. It hence avoids the difficulty in using conventional methods, and enables probabilistic ash fall hazard assessment with computationally expensive models. I illustrate how the algorithm is designed, and test its performance with cross-validation. Novelties of the algorithm are consistent with the physics of tephra transport, and have the potential to benefit the emulator design of other advection-diffusion based numerical models. Advantages, limitations, and simplifications of the algorithm as well as potential measures to optimize it are listed and discussed.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/84005"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["geology"],"dc:title":["Tool Development for Studies on Tephra Fall Deposits and their Stratigraphic Characterization"],"dc:type":["Text","Dissertation"]},"updated_at":"2026-07-27T19:05:28Z"}