Two PhD positions “Elevated Low Relief Landscapes in Mountain Belts: Active Tectonics or Glacial Reshaping? A Case Study in the Eastern Alps”
Two PhD positions within the FWFproject “Elevated Low Relief Landscapes in Mountain Belts: Active Tectonics or Glacial Reshaping? A Case Study in the Eastern Alps”
This project will focus on the evolution of elevated low relief landscapes (plateaus) in active mountain ranges. The project is funded by the Austrian Science Fund (FWF) and the government of Salzburg for a period of three years and will commence in March 2019. Details of the research project are available under: www.geodynamics.at.
Duration of the employment
The two PhD positions will be fully financed for 36 months. In accordance with the Collective Labour Agreement for Austrian Universities in Austrian (§ 26 “Kollektivvertrag für die ArbeitnehmerInnen der Universitäten“ Verwendungsgruppe B1), a salary of € 2,096,00 gross per month (14 x) for a 30-h / week employment.
Desired skills and experience
The successful candidate should have:
- Master’s degree (or equivalent) in Geology, Geomorphology, Geophysics, Geochemistry, Computational Science
Excellent skills and practical experience in one or more of the following research areas:
- experience in numerical simulationtools and programming skills (e.g. C++, Fortran, Python, R, Matlab…)
- ability to work in rugged alpine terrain and caves
- experience with lab-work and chemical preparation of rock samples
- knowledge of the principles of earthsurface dynamics (in particular the interaction of processes driven by climate and tectonics)
- autonomous and proactive working
- written and spoken English proficiency
- skills in dissemination of scientific results (e.g. writing scientific publications)
- flexibility and the ability to workin a team
Specification of the main focus of the two PhD positions:
- PhD-candidate A will work at the University of Salzburg under the supervision of Jörg Robl.She/He will focus on morphometry and landscape evolution modelling (glacialerosion). A stay abroad at Aarhus University (David Egholm) is planned. For this position we seek for an ambitious young scientist with a strong affinity to numerical modeling. Experience with field work in alpine environments is an advantage.
- PhD-candidate B is based in Graz and will work under the supervision of Kurt Stüwe. She/He willfocus on cosmogenic nuclide dating of cave sediments. A stay abroad at the SUERC Glasgow (Derek Fabel, Fin Stuart) is planned. For this position we seek for a motivated researcher with a strong affinity to lab work and caves. The ability to work in rugged alpine terrain and caves is a prerequisite.
A tight cooperation between all team members is expected. Amongst others this will include joint field work in the Eastern Alps, meetings in Salzburg and Graz, GIS and modelling workshops, conference visits, and paper writing.
The Application should include:
- letter of motivation for the desired position (PhD-A: Salzburg or PhD-B: Graz)
- CV (academic career, scientific publications, research interests, skills)
The applications can be submitted until December 31 to the following Email address: firstname.lastname@example.org
Here is an advertisement for an open PhD position at the University of Roma for a project led by Paolo Ballato and Claudio Faccenna. I am collaborating in the project.
Ph.D. position at the Department of Science (Section Geology) of the University of Roma
Deciphering the Mantle Contribution on Surface uplift in the Atlas-Meseta system (Morocco).
The idea that mantle flow dynamics may contribute to the topographic development of orogens has changed our vision on mountain building processes and inspired an increasing number of modelling studies. Isolating and documenting such a contribution however, has been proved to be difficult, especially in continental settings where the paleontological record is not as determinant as in marine systems. This research proposal aims to decipher the influence of mantle flow on the topographic growth of the Atlas-Meseta system of Morocco. There, the occurrence of several hundred of meters of mantle driven uplift, offers the possibility to investigate magnitude, timing and rates of surface uplift, by means of a multidisciplinary approach involving recent advancements on stratigraphy, geomorphology, geochronology, and low-temperature thermochronology. The outcome of this field- and laboratory-based approach will be finally integrated for developing an analogue geodynamic model and gain more insights into the mechanisms of mantle flow. Specifically, the candidate student will quantify longitudinal and latitudinal spatio-temporal patterns of surface uplift and regional tilting induced by mantle flow along two transects across the Atlas-Meseta system. In addition, the expected results will provide geological information that will be used for calibrating a final geodynamic analogue model, which will be of general interest for unravelling the evolution of mountain belts that are not supported by orogenic roots.
The successful candidate must have high motivation, a MSc degree in Geology, Earth Sciences or equivalent, solid basic knowledge in field geology, geomorphology, stratigraphy and tectonics. Basic knowledge in ArcGIS and MATLAB are also required. Applicants must be also proficient in spoken and written English and have teamwork skills.
Information and application
To apply, please send a cover letter clarifying your overall motivation together with your curriculum vitae and names, telephone numbers, and e-mail addresses of two referees to Paolo Ballato (email@example.com), before June 18th.
Conditions of employment
The project will start on November 1st as part of the University of Roma Tre Ph.D. programme (34th cycle) and will last 3 years. The scholarship has an annual amount of 13.638,47 Euro (social security fee included) and is increased (+50%) for periods of study or research abroad.
The last weeks had been quite busy to finish version 2.2 which was available as a prerelease for a long while. TopoToolbox users who keep their software constantly updated (for example by using GIT) won’t see much changes. For those that do not keep pace with the frequent commits to our repository, we encourage them to do so now. There are a lot of new functions and modifications. Benjamin Campforts added TTLEM, the TopoToolbox Landscape Evolution Model. The scope of functions for working with river networks (STREAMobj) has tremendously increased with new plotting functions, low-level chi analysis tools, and tools for geometric modifications. We added new functions to hydrologically correct and smooth river networks and values measured along them (e.g. constrained regularized smoothing (CRS)). TopoToolbox now supports multiple flow directions and there are several new functions for working with grids (GRIDobj). In addition, we consolidated the help sections in each function and increased compatibility with older MATLAB versions. Please see the readme-file for a complete overview of changes.
With version 2.2, we offer TopoToolbox as a MATLAB® toolbox file (mltbx-file). This file will make installation very easy. Simply download it, double-click, and follow the instructions.
Dirk and I met this morning in the train (here we are!) …
… and discussed possible directions for a next version. The number of functions has increased a lot which entails the threat that TopoToolbox might become confusing and even deterrent in particular for new users. Simply adding new functionalities is thus not the way forward. Instead, we decided that a new version should have a better documentation that should be integrated in MATLABs documentation browser. To quote John D’Errico, a long-time and excellent contributor of MATLAB code: Your job as a programmer does not stop when you write the last line of code. If you think so, then you should be fired. You should document your code. Provide help. Otherwise, that code is just a bunch of random bits, useful to nobody else in the world.
With this in mind, let’s go for 2.3.
Only few days left until the EGU begins, the largest European annual geoscience meeting in Vienna. In case you attend you should consider to participate the short course in geomorphometry: Getting the most out of DEMs of Difference. The course is organized by Tobias Heckmann, Paolo Tarolli and me and will be on Wednesday, 26 April, 13:30-15:00 in Room N1.
Please see here for further details on the course’s aims and scope.
Two short courses are scheduled for mid June at Potsdam University. The short courses are independent of each other; however, the topics are related and probably address a similar audience.
Geoscience investigations of point clouds, June 7-9, 2017. Instructors B. Bookhagen, R. Arrowsmith, M. Isenburg, C. Crosby.
This course will explore the acquisition, post-processing, and classification of point clouds derived from airborne and terrestrial lidar scanners and structure from motion (SfM) photogrammetry from drones. The course will take place at campus Golm (UP) and includes one day of field-data collection and two days of data post-processing and analysis.
The application is here: https://goo.gl/forms/NrRAcaASXPuseRs62. The course is sponsored by Geo-X.
Here is the flyer: PDF for more details.
Advancing understanding of geomorphology with topographic analysis emphasizing high resolution topography, June 12-15, 2017. Instructors R. Arrowsmith, W. Schwanghart, C. Crosby, B. Bookhagen.
This course will focus on advanced understanding of geomorphology with topographic analysis emphasizing high-resolution topography. The course will take place at campus Golm (UP) and includes theoretical background and analysis of digital topography using TopoToolbox in a Matlab environment. The course is sponsored by StRATEGy.
Here is the flyer: PDF for more details.
I’d be glad to see you in Potsdam!
Having prepared a stream network and equipped with a reasonable value of the m/n ratio, we are now ready to plot a chimap that visualizes the planform patterns of chi. The main interest in these maps lies in chi values near catchment divides as large differences between adjacent catchment would indicate a transient behavior of drainage basin reorganization.
Some of you might have already experimented with TopoToolbox to create chimaps. Perhaps you became exasperated with the function chiplot that is restricted to calculations with only one drainage basin and has a bewildering structure array as output. The reason for the confusing output of chiplot is that it is fairly old. At this time, I hadn’t implemented node-attribute lists that are now more common with STREAMobj methods.
Realizing this shortcoming of chiplot, I wrote the function chitransform. chitransform is what I’d refer to as a low-level function that solves the chi-equation using upstream cumulative trapezoidal integration (see the function cumtrapz). chitransform requires a STREAMobj and a flow accumulation grid as input and optionally a mn-ratio (default is 0.45) and a reference area (default is 1 sqkm). It returns a node-attribute list, i.e., a vector with chi values for each node in the STREAMobj. Node-attribute lists are intrinsically tied to the STREAMobj from which they were derived. Yet, they can be used together with several other TopoToolbox functions to produce output.
Ok, let’s derive chi values for our stream network:
A = flowacc(FD); % calculate flow accumulation c = chitransform(S,A,'mn',0.4776);
In the next step, we will plot a color stream network on a grayscale hillshade:
imageschs(DEM,,'colormap',[1 1 1],'colorbar',false,'ticklabel','nice'); hold on plotc(S,c) colormap(jet) colorbar hold off
Interestingly, there seem to be some locations with quite some differences in chi values on either side of the divide. “Victims” seem to be rather elongated catchments draining northwest. Let’s zoom into one of these locations.
Are these significant differences? Well, it seems by just looking at the range of values. However, to my knowledge no approach exists that provides a more objective way of evaluating the significance of contrasting chi values and their implications about rates of divide migration. Still, we now have a nice map that can aid our geomorphic assessment together with the tectonic and geodynamic interpretation of the Mendocino Triple Junction.
Unfortunately, I must leave the discussion to you since I am quite unfamiliar with the region. If anyone wants to share his or her interpretation, I’d be more than happy to provide space here. So far, I hope that these few posts on chimaps were useful to you and sufficiently informative to enable you to compute chimaps by yourself. In my next post, I will give a short summary and show with another example that eventually chimaps can be derived really in a few lines of code.
My last post described the math behind chi analysis. By using the integral approach to the stream power model of incision, we derived an equation that allows us to model the longitudinal river profile as a function of chi. At the end of the last post I stated that this model is a straight line if we choose the right m/n ratio, that is the concavity index. Today, I’ll show how we can obtain this m/n ratio by means of nonlinear optimization using the function chiplot.
Ideally, we find the m/n ratio using a perfectly graded stream profile that is in steady state. I scanned through a number of streams using the GUI flowpathapp and found a nice one that might correspond to Cooskie Creek that Perron and Royden (2013) used in their analysis.
The menu Export > Export to workspace allows saving the extracted STREAMobj St to the workspace. Then, I use the function chiplot to see how different values of the m/n ratio affect the transformation of the river profile. Setting the ‘mnplot’ option makes chiplot return a figure with chi-transformed profiles for m/n ratios ranging from 0.1 to 0.9 in steps of 0.1 width.
Clearly, the chi-transformed profile varies from concave upward for low m/n values to convex for high m/n values. A value of 0.4-0.5 seems to be most appropriate but choosing a value would be somewhat hand-wavy. Thus, let’s call the function again, but this time without any additional arguments.
C = chiplot(S,DEM,A);
Calling the function this way will prompt it to find an optimal value of m/n. In addition, it will return a figure with the linearized profile. By default, the function uses the optimization function fminsearch that will vary m/n until it finds a value that maximizes the linear correlation coefficient between the chi-transformed profile and a straight line. So what is that value? Let’s look at the output variable C:
C = mn: 0.4776 mnci:  beta: 0.1565 betase: 2.2813e-04 a0: 1000000 ks: 114.8828 R2: 0.9988 x_nal: [581x1 double] y_nal: [581x1 double] chi_nal: [581x1 double] d_nal: [581x1 double] x: [582x1 double] y: [582x1 double] chi: [582x1 double] elev: [582x1 double] elevbl: [582x1 double] distance: [582x1 double] pred: [582x1 double] area: [582x1 double]
C is a structure array with a large number of fields. C.mn is the value we are interested in. It is 0.4776 and corresponds nicely to previously reported m/n ratios although it differs from the value 0.36 found by Perron and Royden (2013). Of course, this value might differ from river to river and you should repeat the analysis for other reaches to obtain an idea about the variability of m/n.
Ok, we have the m/n ratio now. In my next blog we will eventually produce the chimap that we initially set out for.
P.S.: We could have also used slope-area plots to derive the m/n ratio (see the function slopearea). However, along-river gradients are usually much more noisy than the profiles and power-law fitting a delicate matter. I’d definitely prefer chi-analysis over slope-area analysis.