TY - JOUR A1 - Melnick, Daniel A1 - Moreno, Marcos A1 - Quinteros, Javier A1 - Carlos Baez, Juan A1 - Deng, Zhiguo A1 - Li, Shaoyang A1 - Oncken, Onno T1 - The super-interseismic phase of the megathrust earthquake cycle in Chile JF - Geophysical research letters N2 - Along a subduction zone, great megathrust earthquakes recur either after long seismic gaps lasting several decades to centuries or over much shorter periods lasting hours to a few years when cascading successions of earthquakes rupture nearby segments of the fault. We analyze a decade of continuous Global Positioning System observations along the South American continent to estimate changes in deformation rates between the 2010 Maule (M8.8) and 2015 Illapel (M8.3) Chilean earthquakes. We find that surface velocities increased after the 2010 earthquake, in response to continental-scale viscoelastic mantle relaxation and to regional-scale increased degree of interplate locking. We propose that increased locking occurs transiently during a super-interseismic phase in segments adjacent to a megathrust rupture, responding to bending of both plates caused by coseismic slip and subsequent afterslip. Enhanced strain rates during a super-interseismic phase may therefore bring a megathrust segment closer to failure and possibly triggered the 2015 event. KW - megathrust KW - earthquake KW - cycle KW - Chile Y1 - 2017 U6 - https://doi.org/10.1002/2016GL071845 SN - 0094-8276 SN - 1944-8007 VL - 44 IS - 2 SP - 784 EP - 791 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Bricker, Jeremy D. A1 - Schwanghart, Wolfgang A1 - Adhikari, Basanta Raj A1 - Moriguchi, Shuji A1 - Roeber, Volker A1 - Giri, Sanjay T1 - Performance of Models for Flash Flood Warning and Hazard Assessment BT - the 2015 Kali Gandaki Landslide Dam Breach in Nepal JF - Mountain research and development N2 - The 2015 magnitude 7.8 Gorkha earthquake and its aftershocks weakened mountain slopes in Nepal. Co- and postseismic landsliding and the formation of landslide-dammed lakes along steeply dissected valleys were widespread, among them a landslide that dammed the Kali Gandaki River. Overtopping of the landslide dam resulted in a flash flood downstream, though casualties were prevented because of timely evacuation of low-lying areas. We hindcast the flood using the BREACH physically based dam-break model for upstream hydrograph generation, and compared the resulting maximum flow rate with those resulting from various empirical formulas and a simplified hydrograph based on published observations. Subsequent modeling of downstream flood propagation was compromised by a coarse-resolution digital elevation model with several artifacts. Thus, we used a digital-elevation-model preprocessing technique that combined carving and smoothing to derive topographic data. We then applied the 1-dimensional HEC-RAS model for downstream flood routing, and compared it to the 2-dimensional Delft-FLOW model. Simulations were validated using rectified frames of a video recorded by a resident during the flood in the village of Beni, allowing estimation of maximum flow depth and speed. Results show that hydrological smoothing is necessary when using coarse topographic data (such as SRTM or ASTER), as using raw topography underestimates flow depth and speed and overestimates flood wave arrival lag time. Results also show that the 2-dimensional model produces more accurate results than the 1-dimensional model but the 1-dimensional model generates a more conservative result and can be run in a much shorter time. Therefore, a 2-dimensional model is recommended for hazard assessment and planning, whereas a 1-dimensional model would facilitate real-time warning declaration. KW - Nepal KW - earthquake KW - landslide dam breach KW - flood KW - HEC-RAS KW - Delft-FLOW KW - steep mountain stream Y1 - 2017 U6 - https://doi.org/10.1659/MRD-JOURNAL-D-16-00043.1 SN - 0276-4741 SN - 1994-7151 VL - 37 IS - 1 SP - 5 EP - 15 PB - International Mountain Society CY - Lawrence ER - TY - JOUR A1 - Jara-Munoz, Julius A1 - Melnick, Daniel A1 - Zambrano, Patricio A1 - Rietbrock, Andreas A1 - Gonzalez, Javiera A1 - Argandona, Boris A1 - Strecker, Manfred T1 - Quantifying offshore fore-arc deformation and splay-fault slip using drowned Pleistocene shorelines, Arauco Bay, Chile JF - Journal of geophysical research : Solid earth N2 - Most of the deformation associated with the seismic cycle in subduction zones occurs offshore and has been therefore difficult to quantify with direct observations at millennial timescales. Here we study millennial deformation associated with an active splay-fault system in the Arauco Bay area off south central Chile. We describe hitherto unrecognized drowned shorelines using high-resolution multibeam bathymetry, geomorphic, sedimentologic, and paleontologic observations and quantify uplift rates using a Landscape Evolution Model. Along a margin-normal profile, uplift rates are 1.3m/ka near the edge of the continental shelf, 1.5m/ka at the emerged Santa Maria Island, -0.1m/ka at the center of the Arauco Bay, and 0.3m/ka in the mainland. The bathymetry images a complex pattern of folds and faults representing the surface expression of the crustal-scale Santa Maria splay-fault system. We modeled surface deformation using two different structural scenarios: deep-reaching normal faults and deep-reaching reverse faults with shallow extensional structures. Our preferred model comprises a blind reverse fault extending from 3km depth down to the plate interface at 16km that slips at a rate between 3.0 and 3.7m/ka. If all the splay-fault slip occurs during every great megathrust earthquake, with a recurrence of similar to 150-200years, the fault would slip similar to 0.5m per event, equivalent to a magnitude similar to 6.4 earthquake. However, if the splay-fault slips only with a megathrust earthquake every similar to 1000years, the fault would slip similar to 3.7m per event, equivalent to a magnitude similar to 7.5 earthquake. KW - splay fault KW - marine terraces KW - Arauco Bay KW - TerraceM KW - fore arc KW - earthquake Y1 - 2017 U6 - https://doi.org/10.1002/2016JB013339 SN - 2169-9313 SN - 2169-9356 VL - 122 SP - 4529 EP - 4558 PB - American Geophysical Union CY - Washington ER - TY - THES A1 - Lehmann, Lukas T1 - Performance Test von Phasenpickern T1 - Performance test of phase pickers N2 - Die genauen Einsatzzeiten seismischer P-Phasen von Erdbeben werden in SeisComP3 und anderen Auswerteprogrammen standardmäßig und in Echtzeit automatisch bestimmt. S-Phasen stellen dagegen eine weit größere Herausforderung dar. Nur mit genauen Picks der P- bzw. S-Phasen können die Erdbebenlokationen korrekt und stabil bestimmt werden. Darum besteht erhebliches Interesse, diese mit hoher Genauigkeit zu bestimmen. Das Ziel der vorliegenden Bachelorarbeit war es, vier verschiedene, bereits vorhandene S-Phasenpicker auf ausgewählte Parameter optimal zu konfigurieren, auf Testdaten anzuwenden und deren Leistungsfähigkeit objektiv zu bewerten. Dazu wurden ein S-Picker (S-L2) aus dem OpenSource SeisComp3-Programmpaket, zwei S-Picker (S-AIC, S-AIC-V) als kommerzielles Modul der Firma gempa GmbH für SeisComP3 und ein S-Picker (Frequenzband) aus dem OpenSource PhasePaPy-Paket ausgewählt. Die Bewertung erfolgte durch Vergleich automatischer Picks mit manuell bestimmten Einsatzzeiten. Alle vier Picker wurden separat konfiguriert und auf drei verschiedene Datensätze von Erdbeben in N-Chile und im Vogtland, Deutschland, angewandt. Dazu wurden regional bzw. lokal typische Erdbeben zufällig ausgewählt und die P- und S-Phasen manuell bestimmt. Mit den zu testenden S-Pickeralgorithmen wurden dieselben Daten durchsucht und die Picks automatisch bestimmt. Die Konfigurationen der Picker wurden gleichzeitig automatisch und objektiv durch iterative Anpassung optimiert. Ein neu erstelltes Bewertungssystem vergleicht die manuellen und die automatisch gefundenen S-Picks anhand von definierten Qualitätsfaktoren. Die Qualitätsfaktoren sind: der Mittelwert und die Standardabweichung der zeitlichen Differenzen zwischen den S-Picks, die Anzahl an übereinstimmenden S-Picks, die Prozentangaben über mögliche S-Picks und die benötigt Rechenzeit. Die objektive Bewertung erfolgte anhand eines Scores. Der Scorewert ergibt sich aus der gewichteten Summe folgender normierter Qualitätsfaktoren: Standardabweichung (20%), Mittelwert (20%) und Prozentangabe über mögliche S-Picks (60%). Konfigurationen mit hohem Score werden bevorzugt. Die bevorzugten Konfigurationen der verschiedenen Picker wurden miteinander verglichen, um den am besten geeigneten S-Pickeralgorithmus zu bestimmen. Allgemein zeigt sich, dass der S-AIC Picker für jeden der drei Datensätze die höchsten Scores und damit die besten Ergebnisse liefert. Dabei wurde für jeden Datensatz ein andere Konfiguration der Parameter des S-AIC Pickers als die am besten geeignete bezeichnet. Daher ist für jede Erdbebenregion eine andere Konfigurationen erforderlich, um optimale Ergebnisse mit diesem S-Picker zu bekommen. N2 - The exact onset times of seismic P phases are automatically determined in analysis programs like SeisComP3 by default and in real-time. However the S phases are more challenging. To get an exact and stable result for earthquake location determination both, the P and the S phases, have to be picked accurate. The aim of this bachelor thesis was to optimize four different existing S phase pickers for different parameters, to apply these to data and to evaluate the results objectively. The chosen pickers were one S picker (S-L2) from the OpenSource SeisComp3 program package, two S pickers (S-AIC, S-AIC-V) as commercial module of the company gempa GmbH for SeisComp3 and one S picker (Frequency Band) from the OpenSource PhasePaPy package. The evaluation was based on the comparison between automatic and manually determined onset times. All those four pickers were configured separately and applied to three different records of earthquakes from northern Chile and Vogtland, Germany. The data sets consist of regional and/or local typical randomly chosen earthquakes for which both P and S phases were manually picked. The tested S pick algorithms determined the automatic picks for the exact same records. A newly created evaluation system compares the manual and the automatic S picks for predefined quality factors. These factors are: the mean and the standard deviation of the pick time differences, the number of corresponding S picks, the rates of possible S picks and the needed calculation time. The objectively rating was based on a score value. This value is calculated by a weighted sum of the following normalized quality factors: standard deviation (20%), mean (20%) and the rate of possible S picks (60%). The higher the score the better the configuration. The best configurations of the tested S pickers were compared to find the best algorithm, dataset wise. In general it is shown that the S-AIC picker has for each data set the highest score value and as a result it is named the best picker algorithm. But for each data set the picker has a different set of parameters which were determined as the best ones. For that reason there is a need to change the configuration for every earthquake location and field of application to find the best results with the S-AIC picker algorithm. KW - Geophysik KW - Seismologie KW - Erdbeben KW - Phasenpicker KW - S-Phase KW - SeisComP3 KW - PhasePaPy KW - geophysics KW - seismology KW - earthquake KW - phasepicker KW - S Phase KW - SeisComP3 KW - PhasePaPy KW - Picker KW - picker KW - Einsatzzeiten KW - onset times Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-401993 ER -