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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

Michigan TechnologicalUniversity – College ofEngineering

HistoricActivityRecordsof Galeras Volcano, Nariño, Colombia

A timeseriesanalysisexample

Federica Lanza

Master of Science in Geological & Mining & Sciences


Michigan technological university college of engineering

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


Michigan technological university college of engineering

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


Michigan technological university college of engineering

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


Michigan technological university college of engineering

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


Michigan technological university college of engineering

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


Michigan technological university college of engineering

Time series analysis (II) – Duration of eruptions

  • Short durationeruptions

  • Consistencyof data exceptforoneevent (1670 peak)

Master of Science in Geological & Mining & Sciences


Michigan technological university college of engineering

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


Michigan technological university college of engineering

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


Michigan technological university college of engineering

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


Michigan technological university college of engineering

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


Michigan technological university college of engineering

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


Michigan technological university college of engineering

  • 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