Articles | Volume 14, issue 3
https://doi.org/10.5194/esurf-14-443-2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
From XRD signal to erosion rate maps
Download
- Final revised paper (published on 10 Jun 2026)
- Preprint (discussion started on 06 Oct 2025)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
-
RC1: 'Comment on egusphere-2025-4695', Anonymous Referee #1, 15 Nov 2025
- AC1: 'Reply on RC1', Fien De Doncker, 11 Mar 2026
-
RC2: 'Comment on egusphere-2025-4695', Mikaël Attal, 12 Feb 2026
- AC2: 'Reply on RC2', Fien De Doncker, 11 Mar 2026
Peer review completion
AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Fien De Doncker on behalf of the Authors (20 Mar 2026)
Author's response
Author's tracked changes
Manuscript
ED: Publish subject to technical corrections (11 May 2026) by Simon Mudd
ED: Publish subject to technical corrections (18 May 2026) by Tom Coulthard (Editor)
AR by Fien De Doncker on behalf of the Authors (18 May 2026)
Author's response
Manuscript
DeDonker et al. present a novel and ambitious inverse methodology to infer maps of erosion rates from mineralogical data derived from XRD analysis of suspended sediments. Their method defines a model matrix, which uses bedrock mineralogy data also from XRD analysis and a geological map to characterise the catchment, and then uses a non-linear inversion to infer erosion rates based on the mineralogical data of the suspended sediments. They provide a thorough analysis of the inversion method, including testing two different inverse schemes, as well as testing a wide range of various parameter values to explore their limitations. Having done this, they then apply their method to the Gornergletscher catchment, presenting an erosion rate map for the area. Generally I found the manuscript to be well written, and will likely be suitable for publication following some further exploration/explanation of the limitations of the inversion.
Firstly, I think the authors do an excellent job of acknowledging and testing many of the limitations of the inversion, and so I commend them for this. However, I found some of the presentation of the scatter plots in figures 7-10 to be slightly unintuitive. It would be really helpful, perhaps in a supplement, or alongside these figures, that the resulting erosion rate maps of the synthetic tests are shown. Of course, it would be nice to see all of them, but perhaps 3 for each parameter tested would aid the reader in understanding how different the inversion result can be. For example, what do the three erosion rate maps look like for the three different geological map inputs? Perhaps the results are very similar, but at the moment, it is difficult to infer how much variation is possible for the model results based on different inversion parameters being changed.
On this note, I perhaps would also like to see a more complex synthetic test set up than the one presented. Something akin to a checkerboard test might be ideal, or a scenario where there are more than one peak in erosion rate. From what I can tell, the present synthetic test has high erosion rates across two similar lithologies (Stockhorn-Turftgrat-Gornergrat and ZSF ophiolites?), and low rates elsewhere. This is quite a simple set up. Would the inversion scheme be able to identify two different peaks of erosion that are spatially discrete within these two units? What about three peaks spread out across the catchment? Hence, I would like to see a slightly more complex synthetic erosion rate map tested. Having said this, I did like the testing of two different inversion schemes on the synthetic data to decide which one is more suitable – nice analysis.
Finally, I felt that the XRD data needed explaining a little better and perhaps slightly more exploration of the associated errors. For instance, the number of bedrock XRD analyses is not stated. I wondered whether if only one per lithology were analysed, how different two samples from the same lithology could be, and how much error this could introduce? If only one is used per lithology, is the assumption that each mapped lithology is homogenous fair? From what I can tell from the unit descriptions they can be quite variable. How is this variability accounted for? Hence, I would like to firstly see greater detail given for the acquisition of XRD data and mineralogy data, and perhaps some exploration of inversion results akin the analysis presented in figure 8 for an error introduced when the measured bedrock mineralogy is different from the true bedrock mineralogy. Here you could synthesise a sediment mineralogy based on one set of bedrock mineralogies, and then randomly change each mineralogy in the A matrix by some value of the ‘error’. I am not sure whether this is reasonable or not however, as I am not an expert in XRD, and I am not sure how the bedrock XRD data was collected.
One final comment, the introduction is duplicated. One needs to be removed, and the section numbers redone.
I hope the authors find these help to improve the manuscript. I also outline a few line comments below.
Line 61 – Should be an in-text citation.
Line 270ish Gorner-gletscher then gornergletcher, needs to be consistent throughout the manuscript.
Figure 7. Originial geology – should be original.