{"id":{"repo_id":"central-wash","oai_identifier":"oai:digitalcommons.cwu.edu:etd-1989"},"canonical_url":"https://search.dev.ndltd.org/etd/central-wash/oai:digitalcommons.cwu.edu:etd-1989","repository":{"repo_id":"central-wash","name":"Central Washington University","base_url":"https://digitalcommons.cwu.edu/do/oai/"},"display":{"title":"Slip Estimation from Real-Time GPS in Cascadia","abstract":"Current systems for rapidly characterizing earthquakes are based on seismic, teleseismic, and Deep-ocean Assessment and Reporting of Tsunami (DART) buoy data. These systems have significant limitations that hinder them from making rapid and accurate assessments of large earthquakes used for local tsunami warnings where run-up can occur minutes after the earthquake. Seismic and teleseismic networks saturate around M<sub>w</sub> 7.0. Tsunami waves take tens of minutes to reach the buoys, so rapid assessment is impossible. GPS overcomes these limitations for large earthquakes. GPS does not saturate, and the offsets being detected occur very quickly after an earthquake. This thesis develops the algorithms necessary for detecting and characterizing large earthquakes from GPS measurements. Point positioned GPS solutions are acquired from the CWU Geodesy Lab and filtered to detect offsets. Any detected offsets are then inverted to determine slip along the relevant faults. The moment and moment magnitude are calculated based on the estimated slip. The final solutions, detected offsets, calculated offsets and other relevant data are continuously pushed out to a database even when no earthquake is detected. The produced solutions can be used with existing methods to better inform tsunami estimates immediately following a large earthquake.","abstract_html":"Current systems for rapidly characterizing earthquakes are based on seismic, teleseismic, and Deep-ocean Assessment and Reporting of Tsunami (DART) buoy data. These systems have significant limitations that hinder them from making rapid and accurate assessments of large earthquakes used for local tsunami warnings where run-up can occur minutes after the earthquake. Seismic and teleseismic networks saturate around M&lt;sub&gt;w&lt;/sub&gt; 7.0. Tsunami waves take tens of minutes to reach the buoys, so rapid assessment is impossible. GPS overcomes these limitations for large earthquakes. GPS does not saturate, and the offsets being detected occur very quickly after an earthquake. This thesis develops the algorithms necessary for detecting and characterizing large earthquakes from GPS measurements. Point positioned GPS solutions are acquired from the CWU Geodesy Lab and filtered to detect offsets. Any detected offsets are then inverted to determine slip along the relevant faults. The moment and moment magnitude are calculated based on the estimated slip. The final solutions, detected offsets, calculated offsets and other relevant data are continuously pushed out to a database even when no earthquake is detected. The produced solutions can be used with existing methods to better inform tsunami estimates immediately following a large earthquake.","abstract_has_math":false,"creators":["Senko, Jesse"],"institution":null,"degree_name":"Master of Science (MS)","degree_level":null,"degree_discipline":"Geological Sciences","degree_department":null,"school":null,"contributors":["Tim Melbourne","Breanyn MacInnes","Walter Szeliga"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-01-01T08:00:00Z","date_published":"2018-01-01T08:00:00Z","updated_at":"2026-07-24T01:37:23Z","subjects":["earthquake; GNSS; tsunami","Earth Sciences","Geophysics and Seismology","Physical Sciences and Mathematics"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.cwu.edu/etd/1014","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Tim Melbourne","Breanyn MacInnes","Walter Szeliga"]},{"key":"dc:creator","label":"Author","values":["Senko, Jesse"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-08-20T07:00:00Z"]},{"key":"dc:type","label":"Dc Type","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Geological Sciences"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["earthquake; GNSS; tsunami","Earth Sciences","Geophysics and Seismology","Physical Sciences and Mathematics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.cwu.edu/etd/1014"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Current systems for rapidly characterizing earthquakes are based on seismic, teleseismic, and Deep-ocean Assessment and Reporting of Tsunami (DART) buoy data. These systems have significant limitations that hinder them from making rapid and accurate assessments of large earthquakes used for local tsunami warnings where run-up can occur minutes after the earthquake. Seismic and teleseismic networks saturate around M<sub>w</sub> 7.0. Tsunami waves take tens of minutes to reach the buoys, so rapid assessment is impossible. GPS overcomes these limitations for large earthquakes. GPS does not saturate, and the offsets being detected occur very quickly after an earthquake. This thesis develops the algorithms necessary for detecting and characterizing large earthquakes from GPS measurements. Point positioned GPS solutions are acquired from the CWU Geodesy Lab and filtered to detect offsets. Any detected offsets are then inverted to determine slip along the relevant faults. The moment and moment magnitude are calculated based on the estimated slip. The final solutions, detected offsets, calculated offsets and other relevant data are continuously pushed out to a database even when no earthquake is detected. The produced solutions can be used with existing methods to better inform tsunami estimates immediately following a large earthquake."]},{"key":"dc:title","label":"Title","values":["Slip Estimation from Real-Time GPS in Cascadia"]}]}],"canonical_facts":{"dc:contributor":["Tim Melbourne","Breanyn MacInnes","Walter Szeliga"],"dc:creator":["Senko, Jesse"],"dc:date.available":["2018-08-20T07:00:00Z"],"dc:description.abstract":["Current systems for rapidly characterizing earthquakes are based on seismic, teleseismic, and Deep-ocean Assessment and Reporting of Tsunami (DART) buoy data. These systems have significant limitations that hinder them from making rapid and accurate assessments of large earthquakes used for local tsunami warnings where run-up can occur minutes after the earthquake. Seismic and teleseismic networks saturate around M<sub>w</sub> 7.0. Tsunami waves take tens of minutes to reach the buoys, so rapid assessment is impossible. GPS overcomes these limitations for large earthquakes. GPS does not saturate, and the offsets being detected occur very quickly after an earthquake. This thesis develops the algorithms necessary for detecting and characterizing large earthquakes from GPS measurements. Point positioned GPS solutions are acquired from the CWU Geodesy Lab and filtered to detect offsets. Any detected offsets are then inverted to determine slip along the relevant faults. The moment and moment magnitude are calculated based on the estimated slip. The final solutions, detected offsets, calculated offsets and other relevant data are continuously pushed out to a database even when no earthquake is detected. The produced solutions can be used with existing methods to better inform tsunami estimates immediately following a large earthquake."],"dc:identifier":["https://digitalcommons.cwu.edu/etd/1014"],"dc:language":["English"],"dc:subject":["earthquake; GNSS; tsunami","Earth Sciences","Geophysics and Seismology","Physical Sciences and Mathematics"],"dc:title":["Slip Estimation from Real-Time GPS in Cascadia"],"dc:type":["Text"],"thesis:degree_discipline":["Geological Sciences"],"thesis:degree_name":["Master of Science (MS)"]},"updated_at":"2026-07-24T01:37:23Z"}