the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 12 Jun 2025
Introducing a new normalized cryospheric index (NCI) to categorize sub-watersheds on arid environments
Abstract. This study examines sub-watersheds in the arid northern region of Chile (26°41’–28°24’S), situated within the broader Copiapo watershed. The primary water source for this watershed originates from cryospheric reservoirs. The region exhibits pronounced physiographic and climatic diversity, with its northern sector situated within the South American Arid Diagonal (SAAD), where cryospheric features exhibit greater spatial isolation. The aim of this study is to quantify the water volume contributed by distinct cryoforms to regional watersheds. This study employs a classification methodology to categorize cryospheric reservoirs within sub-watersheds, integrating an inventory of cryoforms, historical snow cover data derived from satellite imagery, and published ice content and depth measurements. The Normalized Cryospheric Index (NCI) is calculated under varying hydrological conditions to assess and compare potential water volumes across sub-watersheds. The analysis reveals significant spatial variability in cryospheric reserves and their strategic hydrological significance. Under average and low-precipitation conditions, the southern sub-watersheds of the Copiapo river Basin exhibit the greatest water storage potential. The Montosa river (NCI = 0.82), Manflas river (NCI = 0.62), Estero Come Caballo (NCI = 0.57), and Del Potro river (NCI = 0.51) sub-watersheds have been identified as strategic priority areas within the region for sustaining surface runoff and safeguarding water availability. During high-snowfall periods, northern sub-watersheds in the Copiapo river Basin, such as Estero Come Caballos, exhibit elevated NCI values despite their limited cryospheric reserves. In contrast, the Montosa, Manflas, and Pulido sub-watersheds contain the most extensive cryospheric reserves and rank among the top four sub-watersheds with the highest NCI scores.
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- RC1: 'Comment on egusphere-2025-1198', Anonymous Referee #1, 19 Sep 2025
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RC2: 'Comment on egusphere-2025-1198', Anonymous Referee #2, 20 Sep 2025
Review: Introducing a new normalized cryospheric index (NCI) to categorize sub-watersheds on arid environments by Ulloa et al., (2025)
General comments
This article presents an analysis of the cryospheric components of the Copiapó watershed. This watershed is located in arid region of Chile, this region is considered one of the richest in ice-rich features, hence understanding the spatial distribution of cryo-landforms and their potential significance for local communities relying on water resources is very relevant. However, the overall aim of the study is not clearly articulated. In the abstract, the authors state that their goal is to quantify the water volume contributed by distinct cryoforms to the regional watershed. At the same time, they propose to categorize cryospheric reservoirs within sub-watersheds, while also introducing the concept of a Normalized Cryospheric Index (NCI) as a novel framework for “cryospheric watershed classification.” Given these multiple objectives, the authors should more explicitly define the central purpose of the study or better articulate how these components are connected.
In general, the manuscript presents some interesting and potentially valuable ideas; however, it lacks organization and important clarifications, and some of the applied methodologies require re-evaluation. in order to strengthen the coherence and focus of the manuscript. For these reasons, I recommend that the paper be considered for publication only after major revisions. I provide further details in my specific comments below.
Methodology and results
In general, the use of the terms “reserve” and “resources” is not always straightforward, and at times the distinction is difficult to follow. Nevertheless, I find the introduction of the NCI to be a very interesting and innovative contribution. The manuscript applies several techniques and methodologies to estimate water volumes; however, these approaches require more careful evaluation and justification, as many of them rely on assumptions and overlook relevant previous work.
The periglacial and glacial landform inventory is primarily based on the work of García et al. (2017). However, this earlier inventory could be improved by incorporating more recent guidelines, such as those developed by the IPA Action Group on Rock Glacier Inventories and Kinematics. Re-evaluating García’s inventory using the updated techniques and methods proposed by this initiative would be highly desirable. Furthermore, regarding the debris-covered glacier inventory, it is not entirely clear which conceptual framework was applied to define this glacier type. Was Kirkbride’s definition adopted, or another classification scheme? In addition, the uncertainty of the inventories has not been addressed. There are well-recognized studies that provide methodologies for estimating such uncertainties (e.g., Paul et al., 2013; Braun et al., 2019).
The quantification of ice volume (reserves) is somewhat unclear. On the one hand, in Section 3.2 (Survey of cryospheric water reserves), the authors state that ice thickness for debris-covered glaciers was estimated following Farinotti et al. (2019). However, in Section 3.5.2 they indicate that area–volume scaling was applied, while in Section 3.5.1 you mention the use of the physically based model proposed by Farinotti et al. (2017). It is therefore not evident which method was ultimately employed in your analysis. In any case, I would strongly recommend relying on the physically based model, or even using existing outputs from that approach, rather than area–volume scaling, which has been shown to systematically over- or underestimate ice volume.
Why did you not use the airborne GPR measurements collected over glaciers in the study area, specifically Del Potro and Tronquitos glaciers? These data were obtained during a joint Chile–Germany field campaign funded by the Dirección General de Aguas in 2013, where ice thickness measurements were acquired (DGA, 2014). Incorporating these observations would significantly strengthen your analysis, as they could be used either to constrain the model parameters or to validate the modeled ice thickness and volume estimates.
Estimating rock glacier ice volumes is highly challenging, as values can vary between 10% and 90%. Accurate estimates generally require the use of geophysical inversion models (e.g., 4Phase or similar; Halla et al., 2021). This important consideration should be discussed in detail, which is currently missing from the manuscript. Similarly, the assumed ice thickness in gelifluction and protalus lobes (5–10 m) may be over- or underestimated if not supported by prior evidence; in fact, the results presented suggest higher ice content (up to 15 m). Ice-rich mountain permafrost can also occur in other, less typical cryospheric landforms, such as block and talus slopes or terraces, which may likewise be underestimated in the current analysis (Köhler et al., 2025).
Regarding snow (resource): If the authors aim to evaluate the water volume of the cryospheric components, a key aspect to consider is snow depth. Without estimates of snow depth and its spatial distribution, the assessment of total water reserves remains incomplete. There are two initiatives currently working with similar datasets in the Andes, and previous work has already addressed this topic (e.g., Saavedra et al., 2018). Please review these initiatives and earlier studies for comparison, as they also include methodologies for estimating uncertainties. Moreover, previous glacier mass balance estimates should be considered, as they provide insights into potential contributions to runoff. This addition would strengthen the manuscript analysis and discussion, especially since earlier studies have reported neutral or slightly negative rates (e.g., Braun et al., 2019; Dussaillant et al., 2019).
Another important aspect missing from the manuscript is the inclusion of runoff data to validate the assumptions presented. Again, if the stated goal is to quantify the water volume contributed by distinct cryospheric landforms to regional watersheds (lines 11–12), a more comprehensive description of the hydrology is necessary. Some of the sub-watersheds are well equipped with gauging instruments (Water directorate of Chile), which could help assess potential contributions. But, without including groundwater analysis, the link between cryospheric components and their contribution remains incomplete. Once more, the manuscript leaves many open questions and unresolved aspects because the overall purpose of the article is not clearly defined.
Line-specific comments:
- 106: The concept of Cryospheric reserves and resources is interesting. However, sometimes less is more. My original suggestion was to retain the term cryospheric components and avoid introducing additional terminologies. After reading the manuscript, I notice these definitions are used throughout the text, and while generally acceptable, some instances may be unnecessary. For example, on line 129, I would simply use cryospheric components.
- 133: It is unclear what you mean by “in this review.” Please clarify.
- 139: Be aware that Peña and Nazarala (1987) observed the driest year on record, which explains why 67% of the total discharge was reported.
- 142-143: There are several more recent studies relevant to the Alps that should be cited (e.g., Ciccoria et al., 2019; 2020).
- 146 / Table 2: The table caption is not correct. I suggest including an additional column indicating which cryospheric component(s) or landform were evaluated in each study. Also, note that Ayala et al. (2016) was conducted during the Megadrought (Garreaud et al., 2017), and Ayala et al. (2020) provides a long-term estimation, offering a more comprehensive glacio-hydrological perspective. Peña and Nazarala (1987) focused on a single extremely dry year, so be cautious when presenting numbers without climate context.
- 151-156: This paragraph is somewhat confusing, as the different cryospheric components appear mixed. Consider reorganizing for clarity.
- 156: Please provide the reference for the study mentioned; it is not clear which work you are citing.
- 161: Standardize the punctuation between periods and commas for consistency.
- 166-170: Use debris instead of detritus for clarity and consistency with cryospheric terminology.
- 211: It is unclear which cryoform was measured here. Were only gelifluction slopes measured, or were rock glaciers also included? Please clarify.
- 368-398: Why is this section titled Glacier and Periglacial Environment Inventory Results if these results were obtained previously? Were they already published? Please clarify. If this is a new presentation, justify it.
References:
Braun, M. H., Malz, P., Sommer, C., Farías-Barahona, D., Sauter, T., Casassa, G., Soruco, A., Skvarca, P., and Seehaus, T. C.: Constraining glacier elevation and mass changes in South America, Nat. Clim. Change, 9, 130–136, https://doi.org/10.1038/s41558-018-0375-7, 2019
DGA (2014). Estimación de volumenes de hielo mediante sondajes de radar en zonas Norte, Central y Sur.
Dussaillant, I., Berthier, E., Brun, F., Masiokas, M., Hugonnet, R., Favier, V., Rabatel, A., Pitte, P., and Ruiz, L.: Two decades of glacier mass loss along the Andes, Nat. Geosci., 12, 802–808, https://doi.org/10.1038/s41561-019-0432-5, 2019.
Farinotti, D., Huss, M., Fürst, J. J., Landmann, J., Machguth, H., Maussion, F., and Pandit, A.: A consensus estimate for the ice thickness distribution of all glaciers on Earth, Nat. Geosci., 12, 168–173, https://doi.org/10.1038/s41561-019-0300-3, 2019.
Köhler T, Schoch-Baumann A, Bell R, Buckel J, Ortiz DA, Liaudat DT and Schrott L (2025) Expanding cryospheric landform inventories – quantitative approaches for underestimated periglacial block- and talus slopes in the Dry Andes of Argentina. Front. Earth Sci. 13:1534410. doi: 10.3389/feart.2025.1534410
Paul, F. et al. On the accuracy of glacier outlines derived from remote-sensing data. Ann. Glaciol. 54, 171–182 (2013).
Saavedra, F. A., Kampf, S. K., Fassnacht, S. R., and Sibold, J. S.: Changes in Andes snow cover from MODIS data, 2000–2016, The Cryosphere, 12, 1027–1046, https://doi.org/10.5194/tc-12-1027-2018, 2018.
Citation: https://doi.org/10.5194/egusphere-2025-1198-RC2 -
EC1: 'Editor's comment on egusphere-2025-1198', Tobias Bolch, 06 Oct 2025
Dear authors,
As you have noted the reviewers recognise the value of the contribution, but also raise substantial concerns.These are in particular:
- The inventory of the landforms
- The analysis of the runoff
- The quantification of the ice volumes
- The structure and organisation of the manuscript.
I ask you to provide a point-to-point reply to these and the other raised major comments of the reviewers. I will then decide whether I invite you to submit a revised version of the manuscript.
Best regards,
Tobias Bolch - Editor TCCitation: https://doi.org/10.5194/egusphere-2025-1198-EC1
Data sets
MOD10A1 Fractional snow cover since 2000th in raster format. Christopher Ulloa, Ayon García https://doi.org/10.5281/zenodo.14921552
Cryosphere reserves data Christopher Ulloa, Ayon García https://doi.org/10.5281/zenodo.15633086
The glacial and periglacial inventory for the Atacama region Christopher Ulloa, Ayon García https://doi.org/10.5281/zenodo.14921499
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- 1
The article “Introducing a new normalized cryospheric index (NCI) to categorize sub-watersheds on arid environments” by Ulloa and others presents a new index aimed to characterize watershed importance in terms of cryosphere water storage and sources. The aim is to present a novel tool to aid in water management and to identify areas that are more critical as water sources or storage at the basin scale. Particularly, they stress that this new tool will help to understand better the importance of different subbasins in arid mountain environments.
The structure of the article is unbalanced and mixed. The methods are very briefly introduced, and the results present mainly a description of the landforms' distribution, without showing the ice content and ice volume estimation in detail. Figures could also be improved.
Although the idea initially appears promising, the method of computing the NCI is unclear, and the methodology is based on too many assumptions, some of which are not supported by new evidence or previous research, rendering the new index not very useful.
Considering the amount of work presented here, I will attempt to summarize my comments to the authors to clarify my point and contribute to the discussion on the importance of the cryosphere as a water source and storage in the driest part of the Andes.
General comments:
Please use the same name throughout the manuscript; it is tough to follow if the variable names are changed throughout the text without notice. After reading the manuscript, it is not clear which variable has been used to assess the snow cover in the area.
The article lacks a proper analysis of the runoff data for the Copiapó basin and its subbasins, as well as their hydrology. The study is based on the assumption that snow, glaciers, and periglacial landforms are the primary source and storage of water in dry mountain areas. Although the role of snow as a critical water source and the importance of glaciers as hydrological buffers in drought periods are well known. The role and importance of rock glaciers and other periglacial landforms are still a matter of debate. Nevertheless, the lack of an analysis of the hydrology of the basin, particularly the role of groundwater, shows that not all the components of the hydrology of the basin have been assessed before jumping straight to the conclusion that the subbasin where more glacial and periglacial landforms are, is the ones that produce or will produce more runoff. It is mandatory that they fully assess the hydrology of the basin before being pointed out or classified as dependent on the cryosphere. In this aspect, it is surprising that they do not assess the runoff data to support their classification or their assumptions.
The article lacks a proper assessment of the ice volume of the different cryosphere components. It is unclear to me whether the authors use the ice thickness data of Farinotti et al. (2019) or if they compute the ice thickness distribution for each debris-free glacier using the model of Farinotti et al. (2017). If the latter is the case, they must show their new results and compare them with the previous assessment. If they use previously published data, they need to assess the quality of this data for the region. If I understand correctly, authors use the V-A scalar approximation to assess the part of the glaciers that are covered by debris, which flawlessly matches the proposed method, which is based on the empirical relationship between extent and volume of glaciers. It is not possible to apply this relationship just to a fraction of the glacier. The assessment of ice volume for the rock glacier is underscored. This could be a highlight of this work, but it is roughly mentioned. I recommend that the authors focus more on these results. Considering the results of Hilbich et al. (2022) and Schrott (1996), and one ERT survey made by them, the authors assess the thickness and ice content for gelifluxion slopes. Considering the scarcity of data, the difficulties in mapping the boundary of the area with gelifluxion lobes, and the fact that Hilbich et al. (2022) also highly that there is a similar amount of ice thickness in sediment slopes without distinctive surface characteristics, the ice volume estimated for gelifluxion slopes is still highly speculative. To support the conclusion of the manuscript, that the gelifluxion slopes are the largest water storage in the area, more data is needed. Particularly, the range of thickness used could lead to the wrong conclusion that this slope could have a thickness similar to rock glaciers, which is nonsense. I think the authors here are confusing the estimate (there are no supporting measurements) of the permafrost thickness of Schrott with the ice-rich layer of Hilbich et al. (2022).
Do we really need an NCI? I don’t find the answer to this question in the paper, and the authors do not discuss whether the methodology is really useful, or at least better than assessing the basin in terms of snow cover and ice volume alone. They suggest the NCI could be computed in other basins, but they don’t assess it. Furthermore, they don’t consider the fact that they optimize the critical parameter W using a Montecarlo simulation, showing that at least we could have a “best guess” of this value. Also, the NCI combines both water storage and water sources related to the cryosphere. However, since the time response of these cryosphere features is highly different, it could give the wrong impression that a basin with rock glaciers is equally critical or responds in the same way as a basin with seasonal snow. Also, I found that snow cover is, without any confirming data, assessed as the amount of snow or, even worse, as snowfall, which is not necessarily the case. Snow cover and persistence do not only depend on the amount or thickness of the snow layer, but also on the energy available for melting or sublimation. Considering that the authors assessed the ice volume at each basin, it is straightforward to rank the basins in terms of ice storage. There is no mention about the extent and hypsometry of the subbasins, which is critical, since a larger basin would have a larger snow cover than a smaller one. Another aspect that is mentioned, but not adequately assessed, is permafrost. Although rock glaciers and gelifluxion could be related to the presence of permafrost, the role of frozen ground in the hydrology of the basin is not assessed or discussed. Finally, considering Figure 14 and the discussion related to this figure, it seems more fruitful to assess the hydrological significance of each subbasin, breaking down the roles of snow, glaciers, and permafrost, as they have very different response times.
Specific comments:
Lines 8-23. Since the article presents the NCI, the abstract must clearly state what the NCI means.
Line 26. Use changes instead of shifts.
Line 27. Retreating cryoforms? What do you mean?
Line 29. There is ample evidence in Masiokas et al. (2020) indicating that glacier mass change is anything but constant.
Line 33-41. Please order the introduction, you could introduce the Copiapo basin in the study area.
Line 45-46. It is not clear what you want to express here. Do you want to say that snow transforms into ice? Considering explaining the causes behind debris-covered ice or how ice could be preserved in permafrost.
Line 47. There is a space missed before “Given”
Line 48. This sentence gives the wrong impression that debris-free, debris-covered, and rock glaciers respond in the same way. Nevertheless, there is plenty of evidence that shows that debris-covered and particularly rock glaciers contribute far less to the runoff. Please present the role of the different ice water storage. For example, Ferri et al. (2020) assess the mass change of rock glaciers in the Central Andes of Argentina, highlighting that they don’t have a loss of mass between 2000 and 2020; thus, it is feasible to assess that the melting of ice at the interior of rock glaciers was a negligible contribution to river runoff.
Line 50-52. Sublimation and melting are different processes.
Line 52. What about the ground flow? There is not even a mention about this.
Line 54-56. What do you mean by ice-rich? As far as I know, from an inventory based on satellite images, it is not possible to assess the ice content. Authors need to support why they call these landforms “ice riches”. What is the ice content on these landforms? Also, how they define a landform as ice-rich is not trivial.
Line 73-81 Move this paragraph to methodology.
Line 87-92. There is no need for “”. It is not clear how a normalized index, with values from 0 to 1, could be used to quantify the potential volume of water available. I strongly disagree with the statement that the runoff of the Copiapo basin is supported by the melting of glaciers, rock glaciers, or even the ice present at gelifluction slopes. What evidence or literature are you using to support this claim?
Figure 1 and the rest. Really, all these institutions are behind all the figures “Source map provider: National Geographic, Esri, Garmin, HERE, UNEP-WCMC, USGS, NASA, ESA, METI, NRCAN, GEBCO, NOAA, increment P Corp.” The northern part of the basin is lacking the river.
Table 1. It would be helpful to include here the extent of snow cover and the number and area of each of the glaciers and cryoforms mapped.
Figure 2. It is mandatory to include a scale on the figure. Rock glaciers look larger than debris-free glaciers.
Line 127. This section lacks new studies assessing the ice content of rock glaciers and glaciers in the Andes and other mountain areas. Like Jones et al (2018), Hu et al (2023) or Millan et al (2022), to mention a few.
Line 134. Corte (1978) highlights the importance of rock glaciers, but does not present new data to assess the ice content of rock glaciers.
Table 2. Not clear what Contribution to streamflow (%) means.
Line 173. Norway? Classifying different slope cryoforms? Are you talking about Hilbich et al (2022) about the ice content in Permafrost of the Central Andes?
Line 181. The classification of this basin as cryosphere is not properly founded. See my comments on Table I.
Line 189. In this section, you need to explain how you perform the glacier and other landform inventory. It is not clear how Garcia et al 2017 and RGi 6.0 are coincidental.
Line 199. The title suggests that snow is monitoring; nevertheless, the authors only use the snow cover area. I don’t understand how snow persistence is included in the snow cover maps.
Line 218. This section shows interesting data, but a proper ground truth will also include an assessment of the ice content and or ice thickness of the rest of the cryoforms.
Line 341. See my general comment about glacier volume estimation.
Line 320, Not all are empirical equations.
Line 322. Here, snow persistence is mentioned, but in the method, snow extent is used. Thus, it is unclear whether NCI is computing snow extent, snow persistence, or a combination of both. On the other hand, I don’t see the benefit of using a Monte Carlo simulation to assess a quite simple formulation as the NCI.
Figure 4. Here it is mentioned snow permanence, but previously it was used snow cover area and snow persistence. Please clarify this and be consistent throughout the manuscript.
Line 371-374. Not clear what you mean by gap. Porto Hill? Are you sure it is not Potro? Also, why are you using Hill? They are mountains above 4000 m asl.
Line 375-376.Really, the largest? Considering the large uncertainty and all the assumptions made, I wouldn’t categorize it so categorically.
Line 377. What are elevated altitudes? Please quantify the elevation range.
Line 378. What do you mean? Talus over glaciers?
Line 380-381. It is not clear what you are comparing here.
Figure 5. Shown ice thickness data of Farinotti et al. (2019), but in the methods section, it seems that you made your own calculation.
Figure 7. What do you mean by the main axis of the Copiapo watershed? Or is the central flowline of rock glaciers?
Line 419. Snow Inventory? Please use the same names throughout the manuscript; it is tough to follow if the variable names are changed throughout the text without notice.
Line 420. Global? What do you mean?
Line 421. What do you mean by “The raster product with the calculated NCI for cryospheric resources per watershed”? Figure 8 shows a map of Fractional snow, but this variable wasn’t mentioned before. See my comment on Line 419.
Line 424. Snowfall? What do you mean? Through the manuscript, it is not clear which variables the authors are using to assess the snow. Sometimes they use snow cover, snow persistence, snow permanence, Fractional snow, and here snowfall. None of them is necessarily synonymous.
Line 443-446. Have you measured the snow accumulation or the daily thermal oscillation to support this statement? If not, I suggest using morphometric parameters like aspect or slope to describe the distribution of glaciers and other landforms.
Line 447-450. Similar to the previous sentence, too much discussion for the results presentation.
Figures 9 and 10 are lacking labels of the landforms.
Line 466-467. Which data support that they are “freezing and thawing lobulations”?
Figure 11. Include a horizontal scale.
Figure12. It would be useful to include the extent and number of each cryoform class.
Table 6 and Figure 13. Use the name of the subbasin. Considering the error or uncertainty in presenting the significant digit.
Line 551. Here it is, use snowfall. Why?
Line 558. What do you mean by small sizes?
Line 595. Cirques are glacially large-scale erosional landforms.
Line 612-615. There is no supporting evidence to classify the watershed as cryospheric.
Line 617. Snowfall frequency?
Line 619-621. It is not clear what you mean.
Line 629-631. Runoff data must support this.
Line 661-663. Are you suggesting that the glacier inventory of Chile doesn’t include debris-free glaciers?
Line 666-667. What? Are you sure? You need to explain better how you reach such a conclusion.
Line 670-671. It has not been proven; the runoff data must be assessed to confirm it.
Line 715. None of the links is working. It wasn’t possible to assess the data.