the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 03 Nov 2025
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.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-5016', Laura Gregory, 02 Dec 2025
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RC2: 'Comment on egusphere-2025-5016', Edwin Nissen, 05 Jan 2026
This paper presents an important new GNSS velocity dataset from a relatively understudied sector of the India–Eurasia collision zone in the Altai mountains of western Mongolia. The dataset itself is clearly valuable and, in my view, well worth publication. The spatial coverage and density of GNSS observations represent a significant contribution that will be of broad interest to researchers working on continental deformation, fault kinematics, and the mechanics of intracontinental mountain belts. However, while the dataset is strong, I have more substantial concerns about the block modelling and the way its results are interpreted and contextualized.
Before invoking a block model, the authors could extract more insight directly from the GNSS velocities themselves. For example, plotting profiles of shortening and strike-slip components along the closely spaced northern and southern transects would allow direct comparison with nearby geological slip-rate estimates and would provide an observational benchmark for later modelling.
With respect to the block model, the authors state that “Block boundaries are designed from mapped faults, seismicity, historic earthquakes, and the GPS velocities,” and that all blocks must be closed. This immediately raises several issues. It is unclear whether all block boundaries are assumed to be vertical, and if so, how the sometimes large compressional and extensional components resolved along them should be interpreted. Along steep or vertical faults, such components would imply very fast dip-slip rates, for which there is little geological or seismological evidence. The assumed 15 km locking depth is also not fully justified. While this depth is broadly consistent with regional waveform modelling (e.g. Bayasgalan et al., 2005), deeper earthquakes at ~30–40 km are observed within the northern Junggar Basin in the Wimpenny & Watson (2021) Global Waveform Catalog, suggesting that fault bottom depths may vary significantly across the region.
More generally, there is little discussion of the limitations inherent in the block modelling approach. The requirement that all blocks be closed necessarily introduces artificial boundaries where no real faults exist, or produces boundaries with implausible kinematics. A clear example is the E–W trending, supposedly left-lateral block boundaries along the northern edges of the HOVD and FYUN blocks. To my knowledge, there is no evidence for left-lateral faulting along these trends. On the contrary, the 2003 Chuya earthquake sequence, which provides one of the best-constrained kinematic observations in this part of the NW Altai, involved E–W right-lateral and reverse faulting (Nissen et al., 2007). Although the inconsistency between the block model and the Chuya earthquakes is correctly noted, the modelled ~0.5 mm/yr left-lateral slip along this E–W trend is dismissed as a “minor discrepancy” (line 298). This is difficult to reconcile with the treatment of similar-magnitude discrepancies between geodetic and geological slip-rate estimates elsewhere in the Altai, which are highlighted as major results of the study. A more even-handed discussion of these inconsistencies would be appropriate.
A related issue is the widespread appearance of normal components along many block boundaries, including along what are clearly restraining not releasing bends (e.g. the northernmost Har Us Nuur fault—see Walker et al., 2006). The authors note that longer GNSS time series are required to determine whether this extension is significant, which is reasonable. However, this inference could also be evaluated against independent constraints. There is, to my knowledge, no geomorphological evidence for normal faulting in the Altai, whereas there is plenty of such evidence for reverse/thrust faulting (both distinct from and as dip-slip components of the main strike-slip faults). Nor are normal-faulting focal mechanisms observed; where dip-slip mechanisms do exist, they are uniformly thrust (Bayasgalan et al., 2005). These geological and seismological observations integrate deformation over longer timescales than the GNSS dataset and should be discussed in relation to the model results.
At the same time, the block model appears to oversimplify areas where internal deformation is well documented. A good example is the southern part of the HUSN block, which contains the Baatar Hyarhan massif. This massif is bounded by clearly-expressed thrust faults on both margins and, based on OSL dating, may accommodate ~1–2 mm/yr of shortening according to Nissen et al., (2009, GJI). Although this paper is cited, it is not actually discussed (perhaps it is muddled with another paper by the same lead author in the same year?), and the southern GNSS velocity transect actually crosses the Baatar Hyarhan massif without any mention of its tectonic significance. Internal deformation is only explicitly considered for the large MONG block in the east, despite clear evidence that other blocks are not rigid.
The robustness of the block model also depends critically on the number and distribution of GNSS sites within each block, yet this is not discussed. While at least three sites per block are required to determine Euler poles and thus block boundary slip-rates, many more well-distributed sites are presumably needed to do so reliably. The “lever arm” effect is mentioned (line 286) but not adequately explored, and a discussion of site numbers per block and their spatial distribution would strengthen confidence in the modelling results. This issue is further exacerbated when additional effects of vertical-axis rotational deformation are also considered, as discussed next.
Counterclockwise vertical-axis block rotations are likely an important component of regional deformation (e.g. Bayasgalan et al., 2005; Nissen et al., 2007; Gregory et al., 2018), and are indeed are required in order for NNW-trending right-lateral faults to be able to accommodate NNE-directed shortening. Not discussing rotational deformation at all is a major oversight of this paper, refuting the somewhat grandiose statement that “Our block model provides the first detailed GNSS kinematic description of Altay deformation” (line 279). Presumably the block model resolves vertical-axis rotation rates as well as slip rates, so these need to be discussed. Are these results consistent with independent paleomagnetic data (Thomas et al., 2002; Gregory et al., 2018)? It would be worth considering whether small errors in rotation rate might resolve into large errors in block boundary slip-rate; perhaps this could help explain discrepancies with some geological slip-rate data, which are not impacted by uncertainties in rotation rates in the same way?
Another important omission is any consideration of viscoelastic deformation. If most faults in the Altai are late in their earthquake cycles, as is likely except for the Fu-Yun fault, then because of visco-elasticity, interseismic deformation is expected be spatially diffuse rather than localized on faults. Modelling such deformation using a purely elastic framework can significantly underestimate true slip rates, a well-known issue in interseismic modelling (e.g. Zhu et al., 2020). This effect has been invoked to explain discrepancies between geodetic and geological slip rates in other regions, including eastern California, the Altyn Tagh fault, and NE China (Chuang & Johnson, 2011; Johnson, 2013; Wang et al., 2021), and should at least be acknowledged here as a possible explanation for similar discrepancies.
Overall, while the block model may reproduce the observed GNSS velocities quite well, its assumptions and limitations are substantial and need to be more clearly and critically discussed. The manuscript would benefit from a more cautious interpretation of model-derived slip rates and kinematics, and from placing greater emphasis on the high quality and intrinsic value of the GNSS dataset itself. This could also help clarify the broader tectonic significance of the Altai beyond slip rate estimates on individual faults.
Finally, there are a few issues with the figures. Faults are labelled on the zoomed-out Figure 1, but they are difficult to see at this scale and should also be labelled on Figure 2; for fairness, this should include faults studied in the literature but not used as block boundaries in the GNSS model (such as those bounding Baatar Hyarhan, discussed previously). Surface ruptures are essentially invisible in Figure 1 and should be shown more clearly perhaps on the more zoomed-in Figure 2; this includes those associated with the 2003 Chuya earthquake, which are well documented in Nissen et al. (2007) but not plotted here at all. In addition, Figure 5 lacks a scale for the residual GNSS velocities.
References:
Bayasgalan, A., Jackson, J. and McKenzie, D., 2005. Lithosphere rheology and active tectonics in Mongolia: relations between earthquake source parameters, gravity and GPS measurements. Geophysical Journal International, 163(3), 1151-1179.
Chuang, R.Y. and Johnson, K.M., 2011. Reconciling geologic and geodetic model fault slip-rate discrepancies in Southern California: Consideration of nonsteady mantle flow and lower crustal fault creep. Geology, 39(7), 627-630.
Gregory, L.C., Mac Niocaill, C., Walker, R.T., Bayasgalan, G. and Craig, T.J., 2018. Vertical axis rotation (or lack thereof) of the eastern Mongolian Altay Mountains: Implications for far-field transpressional mountain building. Tectonophysics, 736, 31-46.
Johnson, K.M., 2013. Slip rates and off‐fault deformation in Southern California inferred from GPS data and models. Journal of Geophysical Research: Solid Earth, 118(10), 5643-5664.
Nissen, E., Emmerson, B., Funning, G.J., Mistrukov, A., Parsons, B., Robinson, D.P., Rogozhin, E. and Wright, T.J., 2007. Combining InSAR and seismology to study the 2003 Siberian Altai earthquakes—dextral strike-slip and anticlockwise rotations in the northern India–Eurasia collision zone. Geophysical Journal International, 169(1), 216-232.
Nissen, E., Walker, R., Molor, E., Fattahi, M. and Bayasgalan, A., 2009. Late Quaternary rates of uplift and shortening at Baatar Hyarhan (Mongolian Altai) with optically stimulated luminescence. Geophysical Journal International, 177(1), 259-278.
Thomas, J.C., Lanza, R., Kazansky, A., Zykin, V., Semakov, N., Mitrokhin, D. and Delvaux, D., 2002. Paleomagnetic study of Cenozoic sediments from the Zaisan basin (SE Kazakhstan) and the Chuya depression (Siberian Altai): tectonic implications for central Asia. Tectonophysics, 351(1-2), 119-137.
Walker, R.T., Bayasgalan, A., Carson, R., Hazlett, R., McCarthy, L., Mischler, J., Molor, E., Sarantsetseg, P., Smith, L., Tsogtbadrakh, B. and Tsolmon, G., 2006. Geomorphology and structure of the Jid right-lateral strike-slip fault in the Mongolian Altay mountains. Journal of Structural Geology, 28(9), 1607-1622.
Wang, K., Zhu, Y., Nissen, E. and Shen, Z.K., 2021. On the relevance of geodetic deformation rates to earthquake potential. Geophysical Research Letters, 48(11), e2021GL093231.
Wimpenny, S. and Watson, C.S., 2021. gWFM: A global catalog of moderate‐magnitude earthquakes studied using teleseismic body waves. Seismological Society of America, 92(1), 212-226.
Zhu, Y., Wang, K. and He, J., 2020. Effects of earthquake recurrence on localization of interseismic deformation around locked strike‐slip faults. Journal of Geophysical Research: Solid Earth, 125(8), e2020JB019817.
Citation: https://doi.org/10.5194/egusphere-2025-5016-RC2
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- 1
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)).