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Michigan Technological University – College of Engineering

Michigan Technological University – College of Engineering. Historic Activity Records of Galeras Volcano, Nari ñ o , Colombia. A time series analysis example. Federica Lanza. Volcano Galeras, southwestern Colombia. What kind of Volcano?.

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Michigan Technological University – College of Engineering

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  1. Michigan TechnologicalUniversity – College ofEngineering HistoricActivityRecordsof Galeras Volcano, Nariño, Colombia A timeseriesanalysisexample Federica Lanza Master of Science in Geological & Mining & Sciences

  2. Volcano Galeras, southwestern Colombia What kind of Volcano? • Mostactivevolcano in Colombia, near the city of Pasto • Stratovolcano (complexvolcano) • Andesitic in composition • Long-term extensive hydrothermal alteration • Two major sectorcollapses(late Pleistocene) • Strike-slipcontext(Romeral-Buesaco fault system) Master of Science in Geological & Mining & Sciences

  3. Main features of eruptions From Google Images • Main central crater and smaller craters (i.e El Pinta Vent, El Viejo, Baston etc.) • Eruptions (mostlyvulcaniantype) consistof: • - centralventeruptions • explosiveeruptions (VEI 2 – 3) • phreaticexplosions • lava dome extrusions • radialfissureeruption (1993) From Smithsonian – GVN web source Pyroclastic flows Widespread tephra deposits Lava flows (rare) Lahars Master of Science in Geological & Mining & Sciences

  4. Eruptive History Spreadsheet: database • 34 data points (eruptiveevents) • Long spanoftimeinvestigated: from 7050 BC tillnow (2010) • High dispersionaround the meanvalue • Great uncertainty Data sources: Smithsonian Institution - GVN Master of Science in Geological & Mining & Sciences

  5. Dataset criteria • Assumptions • start date whenneither the daynor the monthisreported: 15th June or approximately in the middle of the year • stop date whenitisunknown: year, month and dayhavebeeninferredfromdataset • start date and/or stop date when no day (or month) is reported: 1st of the month in which the eruption has occurred or according to data trend Master of Science in Geological & Mining & Sciences

  6. Time series analysis (I) - Size • Frequency of size or “magnitude” of each eruption • Volcanic Explosivity Index (VEI) • Moderate to moderate-large eruptions Ordereddates Master of Science in Geological & Mining & Sciences

  7. Time series analysis (II) – Duration of eruptions • Short durationeruptions • Consistencyof data exceptforoneevent (1670 peak) Master of Science in Geological & Mining & Sciences

  8. Time series analysis (III) – Repose time • BC events included/not included • Decreasing pattern of repose time with time, why? Sampling resolution? Master of Science in Geological & Mining & Sciences

  9. Time series analysis (IV) – Repose time • Linear relationshipbetweenyears and intervaltimebetweenperiodsoferuption (BC data are notconsidered) • Changesin the volcanobehavior? • Wide rangeofvalues • Reliability? Master of Science in Geological & Mining & Sciences

  10. Time series analysis (V) – Volume of material emitted • Linear relationshipbetween the volume of material and the durationofactivity • - short and weakeruptions • - short but strong eruptions • - very long and vigorouseruptions Master of Science in Geological & Mining & Sciences

  11. Problems regarding the data criteria of eruptions • Whatdo wemeanby“eruption” • Datingmethods • Stochasticprocess (randomness) • Assumptions • Uncertainty: caution and evaluationofrepresentativeness Photo courtesy of Marta Calvache, August 27,1936 (INGEOMINAS-Observatorio Vulcanológico del Sur). Master of Science in Geological & Mining & Sciences

  12. Conclusions Forecasting based on historical and prehistoric activity • Caveatsforlong-termhazardsassessment • Obliterationbysubsequenteventsofolderrecords • Unreliableaveragereposeinterval due to the wide rangeoftimeintervalsbetweeneruptions • Changesin eruptionhabits • Unprecedentedevents • Changeofhazardousarea locations due tochanges in the size and shapeofvolcanoeswithtime Master of Science in Geological & Mining & Sciences

  13. Randompattern in the timing ofhistoricaleruptions • No evidenceofcyclicalbehavior • Wide variation in the reposetimesbetweeneruptions Can the Galeras dataset be used for forecasting purposes? Combine different tools to reduce uncertainty: Monitoring approach & Basic Research From Seidl (2003) Thermal radiation Seismicity Electromagnetic, magnetic data Master of Science in Geological & Mining & Sciences

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