Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Defining an Earthquake Intensity Based Method for a Rapid Earthquake Classification System
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 30 credits / 45 HE creditsStudent thesisAlternative title
Definiera en intensitets-baserad metod för snabb klassificering av jordbävningar och förutsägelse av skador (Swedish)
Abstract [en]

Ground motions caused by earthquakes may be strong enough to cause destruction of infrastructure and possibly casualties. If such past destructive earthquakes are analysed, the gained information could be used to develop earthquake warning systems that predicts and possibly reduce the damage potential of further earthquakes. The Swedish National Seismic Network (SNSN) runs an automated early warning system that attempts to predict the damage of an earthquake that just got recorded, and forward the predictions to relevant government agencies. The predictions are based on, e.g. earthquake magnitude, source depth and an estimate of the size of affected human population. The purpose of this thesis is to introduce an additional parameter: earthquake intensity, which is a measure of the intensity with which the ground shakes. Based on this, a new earthquake hazard scheme, the Intensity Based Earthquake Classification (IBEC) scheme, is created. This scheme suggests alternate methods, relative to SNSN, of how earthquake classifications can be made. These methods will use an intensity database established by modelling scenario earthquakes in the open-source software ShakeMap by the U.S. Geological Survey. The database consists of scenarios on the intervals: 4.0 ≤ Mw ≤ 9.0 and 10 ≤ depth ≤ 150 kilometre, and covers the whole intensity scale, Modified Mercalli Intensity, 1.0 ≤ Imm ≤ 10.0. The IBEC classification scheme also enabled the creation of the 'Population-to-Area' criterion. It improves prediction of earthquakes that struck isolated cities, located in e.g. valleys in large mountainous areas and deserts. Even though such earthquakes are relatively uncommon, once they occur, they may cause great damage as many cities in such regions around the world often are less developed regarding resistance to ground motions.

Abstract [sv]

Markrörelser orsakade av jordbävningar kan va starka nog att skada vår infrastruktur och orsaka dödsoffer. Genom att analysera forna destruktiva jordbävningar och utveckla program som försöker att förutsäga deras inverkan så kan den potentiella skada minskas. Svenska Nationella Seismiska Nätet (SNSN) driver ett automatiserat tidigt varningssystem som försöker förutsäga skadorna som följer en jordbävning som precis spelats in, och vidarebefodra denna information till relevanta myndigheter. Förutsägelserna är baserade på, t.ex. jordbävnings-magnitud och djup samt uppskattning av mänsklig population i det påverkade området. Syftet med denna avhandlingen är att introducera ytterligare en parameter: jordbävnings-intensitet, som är ett mått av intensiteten i markrörelserna. Baserat på detta skapas ett jordbävnings-schema kallat Intensity Based Earthquake Classification (IBEC). Detta schema föreslår alternativa metoder, relativt SNSN, för hur jordbävnings-klassificering kan göras. Dessa metoder använder sig av en intensitets-databas etablerad genom modellering av jordbävning-scenarios i open source-\linebreak programmet ShakeMap, skapat av U.S. Geological Survey. Databasen består av scenarior över intervallen 4.0 ≤ Mw ≤ 9.0 och 10 ≤ djup ≤ 150 kilometer, vilka täcker hela intensitetsskalan, Modified Mercalli Intensity, 1.0 ≤ Imm ≤ 10.0. IBECs klassificeringsschema har även möjliggjort skapandet av "Population-mot-Area"-kriteriet. Detta förbättrar förutsägelsen av jordbävningar som träffar isolerade städer, placerade i t.ex. dalgångar i stora bergskjedjor och öknar. Även om denna typ av jordbävningar är relativt ovanliga så orsakar dom ofta enorm skada då sådana här städer ofta är mindre utvecklade rörande byggnaders motstånd mot markrörelser.

Place, publisher, year, edition, pages
2017. , p. 59
Series
Examensarbete vid Institutionen för geovetenskaper, ISSN 1650-6553 ; 393
Keywords [en]
Ground motions, earthquake intensity, earthquake warning systems, damage prediction, classification
Keywords [sv]
Markrörelser, jordbävnings-intensitet, jordbävnings-varningssystem, skadeförutsägelse, klassificering
National Category
Geophysics
Identifiers
URN: urn:nbn:se:uu:diva-317406OAI: oai:DiVA.org:uu-317406DiVA, id: diva2:1081482
Subject / course
Geophysics
Educational program
Master Programme in Physics
Supervisors
Examiners
Available from: 2017-03-20 Created: 2017-03-14 Last updated: 2017-03-20Bibliographically approved

Open Access in DiVA

Defining an Earthquake Intensity Based Method for a Rapid Earthquake Classification System(4220 kB)134 downloads
File information
File name FULLTEXT01.pdfFile size 4220 kBChecksum SHA-512
5c744180756201a887d1c645627dbb4b5fc94c11560c4d0e2a89bce565c19badbfca9f5c5ddd537d9a4a399c0685df1d737492e8ceeaa750de1c1b52bdb361b7
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Bäckman, Erik
By organisation
Department of Earth Sciences
Geophysics

Search outside of DiVA

GoogleGoogle Scholar
Total: 134 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 981 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf