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Geotalk: The mantle and models and measurements, oh my! Talking geophysics with Juan Carlos Afonso

27 Mar

This week in Geotalk, we’re talking to Juan Carlos Afonso, a geophysicist from Macquarie University, Sydney. He explains how a holistic approach is crucial to understanding tectonic processes and how a little “LitMod philosophy” can go a long way to achieving this…

First, could you introduce yourself and tell us a little about what you are currently working on?

My name is Juan Carlos Afonso and I’m a geophysicist currently working at Macquarie University in Sydney, Australia.  My research interests lie in the fields of geophysics and geodynamics, and span many different geophysical and geological processes. My current research integrates a lot of different disciplines, such as mineral physics, petrology, geodynamics, lithospheric modelling, nonlinear inversion, and physics of the mantle, to explore and improve our understanding of lithospheric evolution and plate tectonics.

More specifically, I am interested in the thermochemical structure and evolution of the lithospheric mantle, the mechanical and geochemical interactions between tectonic plates and the sublithospheric upper mantle, and their effects on small- and large-scale tectonic processes. The lithosphere is critical to humans because it is the reservoir of most of the natural resources on which modern society depends, as well as the locus of important geological and biological process such as seismic activity, CO2-recycling, mineralisation events, and volcanism!

Juan Carlos out in the field! (Credit: Juan Carlos Afonso)

Juan Carlos out in the field! (Credit: Juan Carlos Afonso)

During EGU 2012, you received a Division Outstanding Young Scientists Award for your research into the lithosphere and its properties. Could you tell us a bit more about your work in this area?

First of all, it was such a humbling experience to receive this award. I really admire the previous awardees and it is a real honour to have received this award.

I was selected for this award based mainly on the work I did on combining different geophysical and geochemical datasets into a single conceptual framework that has become known as the “LitMod approach”. This theoretical and computational framework fully integrates geochemistry, mineral physics, thermodynamics, and geophysics in an internally-consistent manner*. And allows researchers from different disciplines – seismology, geodynamics, petrology, mineral physics, etc. – to construct models of the Earth that not only satisfy one particular set of observations, but a multitude of observations. This is of primary importance because it guarantees consistency between theories and models (i.e. you can’t cheat!), and results in better and more robust data interrogation and interpretation. This approach is being applied to a wide range of geodynamic and geophysical problems, from studying the water content of the mantle to inferring the thermal structure of Venus.

More recently, my colleagues and I presented the idea of multi-observable probabilistic inversion, a technique that is similar to CAT-scanning in medicine, but that we used to study the thermochemical (or thermo-chemical-mechanical) structure of the lithosphere and upper mantle. We showed that it is a feasible, powerful and general method that makes the most out of available datasets and helps reconcile disparate observations and interpretations. This unifying framework brings researchers from diverse disciplines together under a unique holistic platform where everything is connected to everything else and it will hopefully help understand the workings of the Earth in a more complete manner. But there is a lot of work yet to be done to achieve this!!

…and off duty! (Credit: Juan Carlos Afonso)

…and off duty! (Credit: Juan Carlos Afonso)

How can programmes like LitMod help improve our understanding of plate tectonics?

A great scientist recently said “Each single discipline within the geosciences has progressed tremendously over the 20th century; the problems now lie at the interfaces between the sub-disciplines and ensuring that all geoscientific data are honoured in integrated models. We are well beyond the time when scientists can present their interpretations based on mono-discipline thinking. We absolutely must think of the Earth as a single physico-chemical system that we are all observing with different tools.”  These sentences capture very well the spirit of the LitMod approach, which forces you to think about and interpret geoscientific data in a manner that ensures consistency (as much as possible!). I think one of the reasons for the interest in such an approach is the need for robust and easy-to-use tools that researchers from different disciplines can apply to their individual datasets (seismic, gravity, magnetotelluric, etc.) and explore the connections to other related datasets and disciplines  it helps researchers have a better understanding of the broader implications of their own models. It is also useful to petrologists interested in testing the geophysical and geodynamic implications of their petrological and geochemical models.

LitMod provides a platform wherein chemistry and physics are married such that models of lithosphere and sub-lithospheric mantle must be consistent with petrology, heat flow, topography, gravity, geoid, and seismic and electromagnetic observations. Too often we see models of the Earth, derived from a single dataset, that are incompatible with other observations. Some are better, some are worse. To have a model that explains all observations does not imply that the model is correct, but it does minimise the chances of being wrong! Plate tectonics and science in general use this concept to advance our knowledge of the Earth.

An important (if not the most important!) factor to mention here is that, as with any other project of this magnitude, LitMod would not be possible without the contribution of many scientists who unselfishly helped me to put things together. I’d like to thank Javier Fullea, James Connolly, Nick Rawlinson, Yingjie Yang, Alan Jones, Bill Griffin, Sue O’Reilly and Manel Fernandez for all their help and crucial input to the “LitMod philosophy”.

Sussing out an outcrop. (Credit: Juan Carlos Afonso)

Sussing out an outcrop. (Credit: Juan Carlos Afonso)

And importantly, how does it work?

The main idea is actually quite simple:  a valid physicochemical model of the Earth has to explain all available data in a consistent manner. In essence, this is one of the main steps of the scientific method, right? The LitMod approach is simply a way of constructing Earth models (either by forward or inverse modelling) that satisfy basic physical principles and observations. In a nutshell, LitMod says “you cannot try to fit an observation by changing one parameter of your model without having to change all other parameters in a physically and thermodynamically consistent way, which in turn will affect the prediction of all the other observations”. This is a nice idea, and it should provide robust results as long as what one thinks is consistent, is actually correct. At this stage, we are confident with most of our choices, but there still is much work to do to get a complete understanding of how to model all available datasets simultaneously and how much we can believe our results.

The problem lies in the details, of course, because it is not easy to explain all data consistently when our understanding of each individual dataset is incomplete to different degrees. Moreover, the resolution and sensitivities of different datasets are markedly different too. This problem has a potential solution though. We just need to study the individual problems more carefully (e.g. more laboratory experiments, field case studies, etc.) until we obtain an understanding of them that is similar to the others. In practise this is not straightforward, and many gaps still exist in the description of some problems. A current example, but not the only one, is the discrepancy between results obtained by the magnetotelluric and seismic methods. But even in this case, an integrated modelling approach helps us to isolate the root causes of these discrepancies and to propose new studies to remediate them; something that could not be done by analysing the data separately.

And don’t forget the computational problems, which I find particularly fascinating and frustrating at the same time. Surprisingly, there is not much written about formal joint inversions of multiple datasets; we are learning as we go, but that is what keeps it entertaining!

Lastly, what are your research plans for the future?

I cannot know for sure what I’ll be doing in 10 years (probably geochemistry!), but I can tell you what I’m going to be doing in the next 5-6. Besides continuing working on regional scale inversions with LitMod, I am currently starting to work on two fronts that may appear disconnected at a first glance, but are actually intimately related. The first front is the construction of whole-Earth thermo-chemical-mechanical models, similar to what we are doing with LitMod, but at planetary scale. The other is modelling multiphase reactive flow in the Earth’s mantle with some new numerical techniques. In the end, 5-6 years from now, I think these two fronts will coalesce into a single thick wall… but noone knows whether the wall will stand solid or collapse like a castle of cards… we have to try though!

Want to know more about LitMod? Check out these resources:

Afonso, J. C. , Fullea, J., Griffin, W. L. , Yang, Y., Jones, A. G. , Connolly, J. A. D., O’Reilly, S. Y.: 3D multi-observable probabilistic inversion for the compositional and thermal structure of the lithosphere and upper mantle. I: a priori petrological information and geophysical observables. J. Geophys. Res., 118, 2586–2617, 2013.

Afonso, J. C., Fullea, J., Yang, Y., Connolly, J. A. D., Jones, A. G.: 3D multi-observable probabilistic inversion for the compositional and thermal structure of the lithosphere and upper mantle. II: General methodology and resolution analysis. J. Geophys. Res., 118, 1650–1676, 2013.

Fullea, J., Afonso, J. C., Connolly, J. A. D., Fernàndez, M., García-Castellanos, D., Zeyen, H.: LitMod3D: an interactive 3D software to model the thermal, compositional, density, rheological, and seismological structure of the lithosphere and sublithospheric mantle. Geochem. Geophys. Geosyst., 10, 2009.

*What is an internally consistent model?

By “internal consistency” I mean that all calculated parameters (e.g. thermal conductivity, bulk modulus, etc.) and observables (e.g. dispersion curves, travel times, et.c) are only and ultimately dependent on temperature, pressure, and composition (the fundamental independent variables), while being linked together by robust and sound (typically nonlinear) physical theories. This guarantees that a local change in properties (like density), which may be required to improve the fitting of a particular observable, will also be reflected in all other observables in a thermodynamically and physically consistent manner. It also implies that no linearity between observables needs to be assumed; each observable responds according to its own governing physical theory (e.g. sound propagation).

If you’d like to suggest a scientist for an interview, please contact Sara Mynott.


Imaggeo on Mondays: Friends in the field

24 Feb

Out in the field you encounter all sorts of wildlife and while mosquitos are the most frequent (and most unwelcome), they generally don’t interfere with your equipment or your data. The same can’t be said for all animals though, and many scientists have to strap their equipment out of reach, barricade it with barbed fences or place it in a relatively indestructible black box. It’s a particular problem when you need to head back to the lab or lecture theatre, and leave your equipment alone to collect precious scientific data remotely.

Animals can also cause a ruckus when you’re on site – after all, what’s more exciting than a geoscientist and their portable laboratory? This is surely the question that played on the minds of these bovine beasties before interfering with a geoelectrical survey, a method used to monitor CO2 storage and map groundwater.

Does it work? (Credit: Robert Supper, distributed via

Does it work? (Credit: Robert Supper, distributed via

While surveying groundwater in Salzburg, Austria, Robert Supper caught a crowd of curious cows taking a closer look at his equipment. “During the measurements on a meadow, we were inspected by a drove of cows, which immediately started to taste electrodes and cables,” he explains.

“On geoelectrical surveys in rural areas, we often encounter an interesting phenomenon: cows or sheep completely ignore us until we finish the installation of cables and electrodes. As soon as we are ready and want to start the measurements, they start to inspect everything, sniff on the equipment, nibble on the cables, stumble over the profile or (worst case) shit on it. If everything was tested correctly by them, they disappear,” Supper adds. Take care when you’re working in a rural area, you might just get some company.

By Sara Mynott, EGU Communications Officer

If you are pre-registered for the 2014 General Assembly (Vienna, 27 April – 2 May), you can take part in our annual photo competition! Up until 1 March, every participant pre-registered for the General Assembly can submit up three original photos and one moving image related to the Earth, planetary, and space sciences in competition for free registration to next year’s General Assembly!  These can include fantastic field photos, a stunning shot of your favourite thin section, what you’ve captured out on holiday or under the electron microscope – if it’s geoscientific, it fits the bill. Find out more about how to take part at

Geosciences column: Getting a handle on glacial lakes

21 Nov

Glacial lake outburst floods (GLOFs) are caused when masses of meltwater are released from behind a glacier moraine. Moraines are piles of unconsolidated debris that have either eroded from the glacier valley or have been deposited by melting glaciers. When they fail, a huge volume of water can be released, threatening populations further down the valley. Moraine failure can be caused by avalanches, earthquakes, erosion or an immense build-up of water pressure, but until recently there has been little in the way of a broadly applicable indicator of GLOF risk.

This is because, as far as field trips go, getting to a glacier is one of the hardest feats. So, if you can’t send a scientist to scope out the site, how can you rate the risk of flooding and assess its potential impact?

Recent research, published in Natural Hazards and Earth System Sciences suggests taking to the skies. Remote sensing is becoming an increasingly important part of Earth systems monitoring and provides great insight into the risks of a variety of natural hazards occurring, including tsunamis and volcanic eruptions.

Another use is investigating the risk of GLOFs, which present a serious hazard in the Himalayas. But detailed ground-based studies of them are rarely undertaken in here because they are so difficult to access.

A series of glacial lakes in Bhutan. (Credit: NASA)

A series of glacial lakes in Bhutan. (Credit: NASA)

The remote location of glacial lakes ensures the trigger of GLOFs remains a mystery, but the effect of the outburst of the damming moraine can give us clues. GLOFs leave in their wake a v-shaped channel that slices through the moraine, suggesting that moraine failure is a key factor in the onset of a GLOF.

Given the difficulty of getting to glaciers in high Himalayan locations, there is a pressing need to effectively assess risk using remote sensing techniques. Koji Fujita and his team have developed means of using satellite data and digital elevation models to do just that.

The steep lakefront area lies ahead of the lake and much of the moraine, and the steeper it is, the more likely the lake is to flood. Fujita identified a critical angle beyond which there is a significant risk of a GLOF occurring – that angle is 10 degrees. GLOFs are also more likely to occur when the moraine dam is narrow, as this makes it weaker and more susceptible to failure.

All these parameters can be calculated with some satellite data and a digital elevation model. The depression angle of the steep lakefront area, together with the minimum distance tell us how likely a moraine dam is to fail and the other parameters help calculate the potential flood volume. Since we know how area relates to lake depth, we can use satellite data to estimate lake depth without making any measurements on site. (Credit: Fujita et al, 2013)

All these parameters can be calculated with some satellite data and a digital elevation model. The depression angle of the steep lakefront area, together with the minimum distance tell us how likely a moraine dam is to fail, and the other parameters help calculate the potential flood volume. Since we know how area relates to lake depth, scientists can use satellite data to estimate lake depth without making any measurements on site. (Credit: Fujita et al, 2013)

In addition to monitoring the risk of moraine failure remotely, satellite data can be used to estimate the amount of water dammed behind it. Combining these approaches allows not just the risk of an event occurring to be estimated, but also its magnitude – fundamental factors in hazard assessment. The potential flood volume can be calculated from the lake area (which can also be used to infer how deep the lake is) and the level the lake surface is likely to drop by. Knowing the potential flood volume can help assess risk to populations downstream of the glacier.

The potential flood volume of glacial lakes in the Himalayas. (Credit: Fujita et al, 2013)

The potential flood volume of glacial lakes in the Himalayas. (Credit: Fujita et al, 2013)

GLOFs are a serious natural hazard in Himalayan countries, but when armed with the knowledge of which lakes have the greatest potential flood volume, scientists can prioritise areas for more detailed study. There are thousands of glacial lakes in the Himalayas, making the ability to screen them remotely and hone in on those that are most hazardous a very important development.

By Sara Mynott, EGU Communications Officer


Fujita, K., Sakai, A., Takenaka, S., Nuimura, T., Surazakov, A. B., Sawagaki, T., and Yamanokuchi, T.: Potential flood volume of Himalayan glacial lakes, Nat. Hazards Earth Syst. Sci., 13, 1827-1839, 2013.

Hoechner, A., Ge, M., Babeyko, A. Y., and Sobolev, S. V.: Instant tsunami early warning based on real-time GPS – Tohoku 2011 case study, Nat. Hazards Earth Syst. Sci., 13, 1285-129, 2013.

Strozzi, T., Wiesmann, A., Kääb, A., Joshi, S., and Mool, P.: Glacial lake mapping with very high resolution satellite SAR data, Nat. Hazards Earth Syst. Sci., 12, 2487-2498, 2012.

Geotalk: Yagmur Derin on posters and precipitation

13 Nov

This week in Geotalk, we’re talking to Yagmur Derin, a masters student from Middle East Technical University, Turkey. She tells us about the intersecting fields of hydrology, climate science and remote sensing, and what it’s like to take the plunge and present your first poster at an international conference.

Firstly, can you introduce yourself and what you’ve been investigating as part of your MSc course?

I’m Yagmur Derin, MSc student, currently working as a research fellow in Department of Geological Engineering of Middle East Technical University (Ankara, Turkey). I graduated from this same department with the mind that I should get involved in academia. I took courses from different areas of undergraduate study to see what makes me feel most excited. At the end of the graduation I was sure that I should study hydrology and remote sensing in more detail. I was lucky that my current advisor had an open position in one of his projects when I graduated and was able to start working on that project immediately. The project’s focus is to see how satellite rainfall measurements can be applied to hydrologic modelling, and flood monitoring in particular.

Yagmur Derin out in the field. (Credit: Yagmur Derin)

Yagmur Derin out in the field. (Credit: Yagmur Derin)

How can we use satellite data to improve hydrological models?

The accuracy of any hydrologic study depends on the availability of good quality precipitation estimates. Precipitation estimation can be obtained from rain gauges, radar networks and satellites. The most direct physical measurement is conducted by rain gauges, but they are susceptible to certain errors due to location, spatial scale, wind, and density. Our ability to measure precipitation is limited in remote parts of the world and developing countries, where rain gauge and radar networks are either sparse or non-existent (mainly due to the high cost of establishing and maintaining the infrastructure). This situation is further worsened in regions with complex topography where rain gauges are generally located in lowland. This means that highland precipitation, which is the main interest in hydrologic studies, is underrepresented. Fully distributed hydrological models require high resolution information about the precipitation field and its variability. However, interpolating rain gauge measurements in regions with complex topography – especially over data sparse regions – gives erroneous results. Satellite-based precipitation products are perhaps the only data source to fill this important gap. 

Recent improvements in satellite-based precipitation retrieval algorithms allowed us to better represent the high variability in precipitation over space and time with near global coverage. This makes satellite data attractive for hydrologic modelling studies in data sparse regions. Satellite-based precipitation algorithms estimate precipitation rate based on remotely-sensed characteristics of clouds, such as reflectivity of clouds (visible), cloud-top temperature (infrared, IR) and scattering effects of raindrops or ice particles (passive-microwave, PMW), and these products have certain limitations too. Ongoing improvements and multiple satellite missions planned for the future make them potentially useful for hydrologic modelling studies. 

Earlier this year, you were awarded the Outstanding Student Poster Award for your poster presentation at EGU 2013, what inspired you to attend the conference and present your work?

EGU brings together geoscientists from all over the world, providing a great opportunity for scientists to present and discuss their ideas. Since my career goals lie in academia, my advisor encouraged me to attend the EGU General Assembly back 2012 so that I could meet other scientists and discuss my research.

The award-winning poster presented at EGU 2013: “Evaluation and Bias Adjustment of Multiple Satellite-based Precipitation Products over Complex Terrain” (see the credited link for a larger image). (Credit: Yagmur Derin and Koray K. Yilmaz, 2013)

The award-winning poster presented at EGU 2013: “Evaluation and Bias Adjustment of Multiple Satellite-based Precipitation Products over Complex Terrain” (see here for a larger image). (Credit: Yagmur Derin and Koray K. Yilmaz, 2013)

EGU 2012 was my first international conference with a presentation and it definitely helped broaden my perspective. It was a great experience which made me realise that I should study much more if I want to succeed with my MSc studies. Joining talks, poster sessions and communicating with fellow scientists helped me identify my shortcomings and work out how I could overcome them. After one hardworking year, I wanted to attend EGU 2013 too – the whole conference inspired me to study and participate in academia much more. This year, I benefitted from all hard work and I feel much more confident in my studies.

I suggest everyone attends as many sessions as they can during the conference, and that they meet as many scientists as they can too. Explaining present projects and getting feedback on them helps improve your research significantly. 

What do you plan to do after you have completed your masters course?

I am planning to defend my MSc thesis in June, 2014 and after that I will continue with a PhD. My area of interest has become more focused throughout my masters and I would like to continue my research in the fields of surface water hydrology, land-atmosphere interaction, rainfall-runoff modelling, hydrometeorology, remote sensing of precipitation and GIS. Currently I am applying several universities for PhDs that are related to my research interests and look forward to the possibility of starting a PhD next year.

If you’d like to suggest a scientist for a Geotalk interview, please contact Sara Mynott.


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