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https://doi.org/10.5194/egusphere-2025-5016
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2025-5016
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
03 Nov 2025
| 03 Nov 2025
Status: this preprint is open for discussion and under review for Solid Earth (SE).
Constraining slip rates along Altay faults using GNSS data
Abstract. A first block modeling study of the Mongolian Altay is presented, based on a new GNSS dataset acquired across the range with an innovative setup. Our results show that approximately 4–6 mm.yr-1 of dextral strike-slip motion is accommodated across the ~400 km-wide Altay deformation zone, consistent with previous geodetic estimates. Compared to the more scattered and heterogeneous slip rate estimates from morphotectonic studies, our results provide improved constraints on slip rates along the main Altay faults. Combining knowledge about fault activity across Altay with our results we also discuss the potential role of other unmodeled intra-block structures in accommodating deformation in the Altay and its periphery. This also leads us to question the highest previously reported slip rates—particularly along the Har-Us-Nuur and Fu-Yun faults.
How to cite. Ramel, F., Vernant, P., Ritz, J.-F., Doerflinger, E., Danzansan, E., Ayush, D., Chauvet, A., Munkhuu, U., and Demberel, S.: Constraining slip rates along Altay faults using GNSS data, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-5016, 2025.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Fabien Ramel
CORRESPONDING AUTHOR
Lab. Geosiences Montpellier, University Montpellier 2-CNRS, 34095 Montpellier, France
Philippe Vernant
Lab. Geosiences Montpellier, University Montpellier 2-CNRS, 34095 Montpellier, France
Jean-François Ritz
Lab. Geosiences Montpellier, University Montpellier 2-CNRS, 34095 Montpellier, France
Erik Doerflinger
Lab. Geosiences Montpellier, University Montpellier 2-CNRS, 34095 Montpellier, France
Erdenezul Danzansan
Institute of Astronomy and Geophysics, Mongolian Academy of Sciences, Ulan Bator, Mongolia
Dulguun Ayush
Institute of Astronomy and Geophysics, Mongolian Academy of Sciences, Ulan Bator, Mongolia
Alain Chauvet
Lab. Geosiences Montpellier, University Montpellier 2-CNRS, 34095 Montpellier, France
Ulzibat Munkhuu
Institute of Astronomy and Geophysics, Mongolian Academy of Sciences, Ulan Bator, Mongolia
Sodnomsambuu Demberel
Institute of Astronomy and Geophysics, Mongolian Academy of Sciences, Ulan Bator, Mongolia
Short summary
We measured ground movements across the Altay mountains in Mongolia using new satellite positioning surveys. Our study provides a detailed picture of how this mountain belt deforms, showing that motion of 4–6 millimeters per year is distributed among 4 to 5 major faults. Modeling the fault slip rates, we refine earlier estimates, indicate that some faults move more slowly than expected, and reveal that additional faults also accomodate the strain.
We measured ground movements across the Altay mountains in Mongolia using new satellite...
Ramel et al. (submitted) present two new campaign GNSS transects across the Altay mountains in western Mongolia. This region undergoes far field deformation from the India-Asia collision, and is suggested to accommodate 10-20% of the total shortening strain. Accessibility is a challenge in the remote Altay mountains, and as a result, geodetic, Quaternary, and palaeoseismic data constraining the slip rates of individual faults are sparse. Due to the arid climate, evidence of past earthquakes and fault slip are very well preserved. Faults in the Altay are known to host large (up to M 8) earthquakes, with long recurrence intervals (>1000 years), and most have not had an earthquake in the historical or instrumental period. Constraining the rates and behaviour of the Altay faults is relevant to many important questions in active tectonics (e.g. on strain distribution, fault strength, intracontinental deformation, reactivation of faults, and large strike-slip faulting eathquakes), and more data is crucial for answering these questions.
Therefore, the data presented in Ramel et al. is a relevant and important contribution, but revision is necessary to realise the potential of this dataset. I suggest changes that I hope will clarify the significance and meaning of the results. I suggest that the uncertainties should be better quantified so that the data may be used by other researchers. While block modelling may be useful to view the data within the larger picture of deformation, the data could also be presented without influence of the modelling (e.g. in a profile), so the reader can better interpret how the strain rates vary across the mountain range. I have many questions about the research, and I hope that these will be considered in a revision of the manuscript.
Detailed comments
Setting the context
The introduction to the manuscript would benefit from a brief wider setting – why should we be interested in strain rates in western Mongolia from a broader perspective? E.g. why are these faults important?
Section 2.1: This section requires clarification – you note that much work has been done on the Bulnay, Gobi-Altay, and Fu-Yun but neglect to mention the Altay mountains as a whole (despite referencing the Fu-Yun fault, which is part of the Altay). The following section focuses on the Altay, but the mountain range should be introduced as a whole rather than just the Fu-Yun fault, because other faults in the Altay are also ‘slow faults with slip rates of about 1 mm/yr capable of generating large earthquakes..’, and deformation across the main Altay massif contributes significantly to the 10-20% India-Asia convergence.
Line 108 – is the GPS ‘slip rate’ from Calais et al., 2003 a horizontal shortening rate or has it been resolved onto a strike slip fault, to better compare with the Quaternary fault slip rates? The slip rate on a strike slip fault accommodating shortening (e.g. not optimally oriented) will always be greater than the shortening strain rate across it. The fault slip rates should be faster than the GPS shortening strain rate.
The background lacks mention of the rotational component of deformation in the Altay. Many authors have suggested that the region rotates anti-clockwise to accommodate NNE-SSW directed shortening on NNW-SSE oriented strike slip faults (e.g. Bayasgalan et al., 2005; Thomas et al., 2002; Gregory et al., 2018).
Clarify the methods and uncertainties in the GNSS data
Section 3: This section would benefit from a brief explanation of how and why did you choose where to put the campaign? E.g. why did you choose to conduct two campaigns in the north and south rather than including the central Altay, where strain rates might be higher at the centre of major fault zones? Or collect more transects with fewer points, or vice versa? I suspect this is simply a problem of having enough time and easy access, but it would be good to have an explanation for the choice.
(Line 142) Has the setup of drilling holes and not having a permanent marker been used before? Is there a reference, or some analyses of the uncertainties related to this style of data collection? It would also be helpful to plot the vertical data, so the reader can understand the level of noise (even if this just goes in the supplementary material).
(Line 167) More information is needed for how the raw GNSS data are processed, how the uncertainties are calculated, and how the velocity solution is calculated. I am not an expert in processing GNSS data, but perhaps an example figure of the linear fit for one of your station solutions (mentioned line 175) would help to show the goodness of fit (this could be included in the supplement). Did you filter any of the data from the velocity solution described from line 175, e.g. remove sites with large errors?
The GNSS data in all figures have uncertainty ellipses but the is no scale for the ellipse in any figure. It is not clear how reasonable the estimated uncertainties are for the new data. You mention that the northern transect is more heterogeneous (line 187), but this is not reflected in the formal uncertainties, and it should be. How can uncertainties be better quantified so that the data can be used by other researchers? At least one of your new sites is close to an existing continuous site – how do these compare? This could give a sense of the true uncertainty.
The two northeast most GNSS sites (two east sites in the northern transect) are along the Bulnay fault – how much are they influenced by the Bulnay fault?
I suggest that you plot transects of the velocities in your profiles, to better illustrate how the data vary across the Altay. One way to do this would be to calculate the fault parallel velocities of each site (e.g. Figure 6 in Calais et al., 2003), or to plot the Junggar-fixed reference frame velocities as a profile (or both!). Error bars should also be included on the transect. This would, show the heterogeneity in the data, demonstrate how the velocity varies relative to all the mapped faults (not just the block boundaries), and how it varies smoothly across the whole mountain range.
Block modelling
(Line 206) This section would benefit from a summary of the limitations or considerations when using block modelling. For example, how does heterogeneity and uncertainty in your GNSS data propagate into the modelling? Does the strain that is accommodated within the blocks on complex faults artificially migrate to the block boundaries (e.g. overestimate rates at boundaries)? Why only allow one block (Hanguy) to deform internally in your second model – why not allow all of the blocks to do so given that we know there are complex active faults within each block?
Line 225: There is no scale on the figure with the residuals, so it is difficult to evaluate whether they are ‘low’.
Line 232: I think this interpretation requires more explanation. It is confusing to include a ‘strain-free’ model, because there is strain in this model at the block boundaries. I suggest using a different label for the two models (rigid vs. internal deformation?).
(Line 240/280) One significant problem is the extension in the modelling in the northern part of the Altay, which is matched by compression in the south. This is most likely an artifact of the model (as noted in line 285). Can you quantify how much rotation/levering contributes to the strain at the edges of the model, and remove the artifact? There aren’t any notable normal faulting earthquakes in the catalogue for the Altay (e.g. Sloan et al., 2011), so it does not seem likely that there is a significant extension component to the deformation (though there certainly are normal faulting earthquakes in the Hanguy!).
How are compressive stresses distributed along the faults? Altay faults have field evidence for compression at large scale bends where they form flower structures with significant thrust fault components, but in between these structures they may have pure strike slip motion (and therefore a faster strike slip rate). How is this heterogeneity in fault kinematics dealt with in your modelling and interpretation? How many sites are located within a restraining bend compared to along a straight section of the faults?
More explanation needed for interpreting the block modelling -how much of the slip rates plotted in Figure 5 are dependent on the models vs the GNSS data? What happens if you randomly remove some data (e.g. a bootstrap analyses?). Again profiles of the GNSS data would help with this.
L350: The Olgiy fault has a low slip rate in your model, but I wonder how much of this is because there are no GNSS sites on the western side of the fault – so most of the strain in the Fu Yun fault is concentrated (in the model) close to where there is data? In general, can you comment on how the site location introduces bias into the modelling?
I think it is important to always consider that the GNSS data is a different measurement to Quaternary fault slip rates. Quaternary fault slip rates represent (mostly) strain released in earthquakes. They can be influenced by whether a fault is early or late in its seismic cycle (especially when dealing with long recurrence intervals and large earthquakes), but should at least represent earthquakes. GNSS data is interpreted to represent the slow accumulation of elastic strain (between faults). It is very important to compare between these different observations (as has been done in the manuscript), but it is also important to consider the assumptions in these comparisons.
The discussion ends rather abruptly. I suggest you can improve the relevance of the work by ending the discussion with some points on the wider context of this work.
Minor
Be consistent in using Fig. vs Figure in your figure references.
Be consistent with spelling of Altay vs Altai, etc.
L70: The region also has significant compressional components of deformation.
Line 140: Change firsts to first
Line 206: I cannot find a reference to Figure 4 in the text, maybe it is supposed to be what is referenced as Figure 5 in this line?
Line 310: The phrasing of the second part of this sentence is incomplete.
Figures:
It would help to put some key place names (towns) on one of your maps, to help the reader locate themselves.
All Figures with GNSS data need a scale marker for the uncertainty ellipses.
Figure 5 is missing labels for (a) and (b), there is no (c) but this is referenced in the text at line 224. Fix references and labels associated with what looks to be splitting Figure 4 into two Figures.
What is the scale on the residual arrows in Figure 5?
It would be helpful to label the faults on Figure 5, since they are discussed with respect to the modelling results (e.g. the reader may not know that the Olgiy fault approximately forms the boundary of the western side of the Hovd block (in the north)).