Posts in the category »  Software and Applications «  ( 33 Posts )

This is a guest blog by Octavi Gómez-Novell, Universitat de Barcelona, visiting researcher at Universidad Complutense de Madrid (Spain). Contact: octgomez@ub.edu

Paleoseismic data are punctual and highly localized in defined fault strands, while earthquake surface ruptures cover much larger and complex regions in comparison. This makes the identification of paleoearthquakes in trenches strongly dependent on the slip that those particular events had at each trench site, as well as on the continuity and quality of the stratigraphy for those paleoearthquakes to be dated and well-constrained in time. For this reason, paleoseismologists always seek to increase observations by trenching several sites along fault deformation zones with the premise that more observational data might: 1) complete the paleoearthquake catalogues closer to the real event count that actually occurred, 2) reduce the event age and detection uncertainties and 3) give insight about surface rupture characteristics. While all of these premises are correct and proven successful in several cases, the truth is that in a handful of other cases increasing observations can significantly difficult the correlation of datasets between sites, making such interpretations highly subjective. For instance, in very populated paleoseismic datasets and/or those with large event date uncertainties there will be multiple correlation options; which is the right one? After all, even though based on observations, paleoseismic data are interpretations, hence models that should be treated as such. Thus, can we improve correlation using numerical modelling?

This is a guest post by Simone Bello from the Università degli Studi G. d’Annunzio Chieti e Pescara, Italy.

The QUIN project (QUaternary fault strain INdicators database) stems from the initiative of a group of researchers to make the structural-geological data of the potentially seismogenic faults cropping out along the entire Apennines in Italy available to the scientific community.

Strain and regional stress databases of active deformation patterns are largely available in the literature but are almost exclusively derived from earthquakes and geodetic data. However, in areas such as Italy, where the regional stress field has remained unchanged over the last few million years, the analysis of structural data relevant for seismogenic purposes can be extended at least to the overall Quaternary time interval. QUIN was born with this assumption. It is designed to integrate, unify, and elaborate high-detailed geologic information on potentially seismogenic faults and provides data on the location, attitude, kinematics, and deformation axes of Fault Striation Pairs (FSPs) measured along Quaternary faults.

As soon as I learned that the new iPad Pro comes with a LiDAR scanner I knew I would have to check how useful it is. Luckily, Kamil was able to buy one for our group. So we (Georg and myself) tested the 11″ version on an outcrop right next to our institute and I also scanned the way back to the office. I used the app LiDAR Scanner 3D. The full version costs 0.99 € and allows you to save and export the models as USDZ, OBJ, STL, and PLY files. I used CloudCompare to check the data.

Since I can’t go to the field right now, I am stuck with analyzing the amazing LiDAR data from Slovenia. We have 1 m resolution data covering the entire country and oh my god it’s great for active tectonics research. But how do you actually make a DEM from the data? Here’s a quick guide using free software only.

OK, this is a bit off-topic, but I was asked to write a short tutorial about how to make the flow map that I posted on Twitter. Why did I actually make it? Usually I am interested in faults and earthquakes, but sometimes secondary earthquake effects such as landslides can help us to find out about seismic activity. Since my next project will be about the Alps, I am currently looking a bit into landslides, too. The map shows a large landslide close to Jena, the Dohlenstein. This slide was activated several times in the past 300 years or so, but now seems to be stable. Behind the head scarp there is a small depression. I was wondering if this is perhaps just (paleo-)drainage, or if it could be the first hint for a new sliding plane and a larger future landslide. That’s why I made the flow map – if the depression has no outflow, it’s more likely to be related to newly forming tension cracks.

While working on my project on distributed faulting, I dig into the literature looking for additional case studies beside those contained in the SURE (SUrface Ruptures due to Earthquakes) database.

I retrieved information on 18 normal and strike-slip events occurred between 1905 and 2011, with a magnitude range of Mw 5.9 – 8.3. I digitized rupture traces from published maps at a variable scale, dependent on the resolution of the original map. Earthquakes are from Iran (7 events), Mongolia, China, Turkey, Greece (2 events for each country), Italy, Kenya and Japan (1 event).

Moderate to strong earthquakes commonly produce secondary effects (landslides, liquefaction, tsunamis), which worsen the impact of the seismic event, both during the emergency and recovery phases.

Landslides can be triggered by events of M above 5 or so, and stronger events can produce thousands of landslides. Landslide inventories were compiled for dozens of events and the relations between Mw and maximum distance or area affected by landslides have been analyzed (e.g., Keefer, 1984; Rodriguez et al., 1999). On the other hand, the total area affected by landslides is one of the metrics used to assign the ESI intensity (Environmental Seismic Intensity; Michetti et al., 2007).

The technical workshop on Internet Macroseismology will take place in beautiful Ljubljana, Slovenia, from 14-15 November, 2017. Please note that the dates have changed.

Deadline for abstract submission is 20 September. Find more information in the second circular (download, pdf, 550 kb), or visit the website for registration: https://form.jotformeu.com/72052334536350

Richard Styron has released a new, improved version of his Global CMT viewer webmap. The earthquake data are from globalcmt.org, updated every four hours, and colour-coded by depth (purple to yellow = shallow to deep). The tool also displays a number of major faults from the ATA and HimaTibetMap databases. This webmap is a fast and easy way to find interesting earthquakes and to explore global seismicity. Plus, it’s a beautiful map. Thanks Richard for that great application!