Geological Hazards - Science topic

You should firs consider basic details pertaining to all three basic types of rocks i.e. Igneous, Metamorphic and Sedimentary Rocks.

Subsequently, basics about site selection/ geological investigation studies for various civil structures, esp. Hydro Power Projects (Dams/ Reservoirs etc.), Underground Excavations (Tunnels, Caverns etc.), Bridges etc.

Rock Mass Characterization including various empirical approaches like Rock Mass Rating (RMR), Q-Syste, Geological Strength Index (GSI) etc. preferably with some case studies.

Basic aspects of Structural Geology including dip strike calculations, plans and sections preparations etc.

Engineering Geological Properties of Rocks and Soils, with procedures/ codes for their determination with in laboratory as well as in field.

Basic/ Advanced Hydrological Properties/ Tests/ Investigation Procedures with examples/ case studies.

Best Wishes

Hello Gerald, Ulli, Volker,

There quite a few nice examples I'm aware of where accretionary lapilli were sampled soon after fallout. One is the 2002 study by Bonadonna et al. on the 1995-1999 eruption at Montserrat (Geol. Soc. London Memoirs). Another is the 2009 eruption of Redoubt, Alaska, described by Kristi Wallace et al. in JVGR, 2013. The latter samples provided the basis of my study of 'volcanic hail' using radar observations and plume modeling with ATHAM in Nature Communications. As suggested by Gerald, these samples were indeed frozen upon landing, though that's not too surprising for an Alaskan eruption. It is clear from lab experiments that neither ice nor salt precipitates are required to grow aggregates >1cm diameter. I do not think aggregates need to undergo freezing, however, it does seem to be very common and does affect their growth rates and internal structure. 

There are also some gorgeous, layered accretionary lapilli from the 18 May 1980 eruption of Mount St. Helens, which have been archived for the past 35 years. I've recently thin-sectioned these samples and am currently working on comparing their internal structures to the eruptive stratigraphy and photographic record of the eruption dynamics. Hopefully I'll be presenting this work at the Cities on Volcanoes meeting in Chile this year. Ulli and I were talking about organizing a workshop on ash aggregation there if there's enough interest. 

All the best

Alexa

I do not work with social modelling, but I would use old data and analyse them against the predictor variables (environmental and others). And based on this statistic I would create a predictive models and then used a second old dataset to validate, or rather evaluate, the predictive model. But that requires that the data used for happening is within the range of the data used for creating the model, if not you can not trust the predictive model if you  do not fully trust the interpolation that is made.

Dear Ananta,

There are many ways to assess rainfall induced landslides susceptibility. In general the available techniques are divided in physical and probabilistic approaches. Both need morphological data (DEM) and a database of past events to be calibrated for a specific region considered geologically and morphologically homogeneous. In particular physical models need IDF curves and a certain amount of geotechnical parameters of soils that are in some cases difficult to obtain. But their major advantage is that they can easily include the return period without having information on timing and rainfall amount that have triggered the landslide, which are hardly available in remote areas (i.e. mountainous areas). While statistical models can avoid the use of geotechnical parameters, but they need an extended database with information on time and rainfall of previous events (not easily available) to build, for instance, rainfall thresholds.

The reference given by Hamid is really interesting. Many authors, including my research group, have been investigating on these topics. I leave you some more references hoping that will be of your interest.

Fell R, Corominas J, Bonnard C, Cascini L, Leroi E, Savage WZ (2008) Guidelines for landslide susceptibility, hazard and risk zoning for land use planning. Eng Geol 102:85–98

J. Corominas and J. Moya, “A review of assessing landslide frequency for hazard zoning purposes,” Engineering Geology, vol. 102, no. 3-4, pp. 193–213, 2008

Chevalier G, Medina V, Hürlimann M, Bateman A (2013) Debris-flow susceptibility analysis using fluvio-morphological parameters and data mining: application to the Central-Eastern Pyrenees. Natural Hazards. Springer, Netherlands, pp 1–26

Bregoli, F., Medina, V., Chevalier, G., Hürlimann, M., & Bateman, A. (2014). Debris-flow susceptibility assessment at regional scale: Validation on an alpine environment. Landslides, 1-18.

Good luck,

Francesco

Demonstrations of different wave phenomena at five stations.Students work with the five hand-on demos in small groups

Dear Sandip,

The relevant part of the distribution in natural hazard analysis is the tail, especially in distributions with hard tails (ie, with extreme values). Mean values are not so relevant. We quantify natural hazard using the concept of Average Recurrence Interval (ARI) which can be calculated by fitting an Extreme Value Distribution to the tail of your data. This ARI gives you the magnitude of extreme values of an event and their recurrence, it is more commonly known as 'Return Period'.

Cheers,

Augusto