the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Dec 2024
Catchment landforms predict groundwater-dependent wetland sensitivity to recharge changes
Abstract. This study investigates the influence of topography on the desaturation rates of groundwater-dependent wetlands in response to changes in recharge. We examined sixty catchments across northern Chile, which feature a wide variety of landforms. We categorized the landforms using geomorphon descriptors, identifying three distinct clusters: lowland, transition, and mountain settings. Using steady-state 3D groundwater models, we derived flow partitioning and seepage area extent for each catchment. Each cluster revealed consistent seepage areas evolution under varying wet-to-dry conditions. Our findings indicate that mountains exhibit reduced seepage area compared to lowlands at equivalent hydraulic conductivity to recharge (K/R) ratios but are less sensitive to recharge fluctuations with slower rates of seepage area variation. Statistical evidence demonstrates that geomorphons-defined landforms correlate with desaturation indicators, enabling the prediction of catchment sensitivity to climate change based solely on a topographic analysis.
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RC1: 'Comment on hess-2024-381', Anonymous Referee #1, 20 Feb 2025
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Thank you for submitting your Manuscript to HESS. Please find below the comments and suggestions made regarding the current version of the manuscript.
This manuscript aims to study the influence of topography on the desaturation rates of groundwater-dependent landscapes in response to changes in recharge. The authors achieve this objective by categorizing the catchments into lowland, transition, and mountain settings clusters, using geomorphon descriptors, and implementing 3D steady-state groundwater models to derive each catchment's flow partitioning and seepage area extent. The findings illustrate that mountains exhibit reduced seepage area compared to lowlands at equivalent hydraulic conductivity and recharge ratios but are less sensitive to fluctuations in recharge. Finally, the authors performed a correlation statistical analysis between the geomorphon-define landforms and the desaturation indicators, which, according to them, enables the prediction of sensitivity to climate change based on topographic analysis.
I have read the manuscript with great interest. My overall opinion is that the manuscript is well-written but needs some moderate revisions and clarifications. Below, I have listed comments, hoping they may help improve the manuscript’s quality.
Specific Comments
- Some clarification is needed regarding the 3D numerical model approach.
- The authors extended the model domain by 20% of the total area of the catchment to avoid boundary effects. In the extended domain, did the authors use the elevation of adjacent catchments? Have the authors considered possible interbasin flow happening among catchments, as described in Fan (2019)? If so, are there any implications for this interbasin flow in the general results for lowland settings?
- To simplify the analysis, the authors assumed an aquifer thickness of 100 meters for all catchments with a homogeneous and isotropic hydraulic conductivity. Although these assumptions ease the comparison of these systems, there are some limitations that need to be addressed. For instance, what are the values of hydraulic conductivity used for each catchment? did the authors calculate an equivalent hydraulic conductivity for each catchment using the geology of each site? Also, the depth to bedrock may vary within each catchment depending on the geology; could these changes affect the seepage calculations? Lastly, it has been suggested that meteoric water can travel to depths of kilometers in areas with high topographic relief (i.e., Frisbee et al., 2017; McIntosh & Ferguson, 2021). Have the authors considered that some of the flowpaths that contribute to seepage or that export to other catchments could come from these deep groundwater systems? I suggest including these limitations within the manuscript to aid in discussing the results.
- Similarly, the authors assumed a uniform effective recharge for all the catchments. Did the authors assume probable recharge ranges for the area of study or arbitrarily pick recharge values to explore a wide range of K/R that presented desaturation? I recommend clarifying this part in the text.
- This reviewer understands that this might be out of the scope of the study. However, the authors focused on the dimensionless ratio between hydraulic conductivity and recharge (K/R). This dimensionless quantity comes from previous studies done on 1D and 2D analysis (e.g., Bresciani et al., 2014). Have the authors considered doing a dimensional analysis of their 3D model to explore what other dimensionless quantities arise from a catchment scale system? There might be other dimensionless quantities that relate aquifer thickness and drainage length, allowing another physical approach to relating the studied catchments.
- In line 157, within the results section, the authors state: “The fit shows minimal RMSE values between 0.01 and 0.08, indicating that seepage evolution with increasing K/R can be successfully parameterized with only two parameters, λ and n.” These results come from the multiple assumptions made to the conceptual model. Have the authors considered if this conclusion will hold if the analyzed system is heterogeneous and anisotropic or if the thickness of the aquifer is variable within the system? Some of these thoughts can be addressed as possible limitations of the study.
- By the end of the results section, starting in line 216, the authors briefly explain how they fitted a Random Forest model to predict the values of λ and n in other catchments based on PCA analysis of the topographic parameters. I suggest moving and expanding this explanation to the methods section, as it will aid in understanding the reasoning behind performing such an analysis.
- This analysis shows that some predicted catchments are clustered as lowland catchments (red contours) despite being located within the Andes Cordillera (Figure 4d at the northern part of the map). Are these correctly labeled? Are these there because they are located in flatter places within the Cordillera? Or are these outliers from the analysis? I suggest adding more information about these possible outliers.
- Based on the previous comments, I suggest including an additional paragraph or section that addresses the study's potential limitations. This addition can help describe the implications of these findings and the future work needed to address some of the assumptions.
Technical Corrections
Besides the comments described above, I have a few technical recommendations for the manuscript.
- Line 27 states: “Considering steady-state groundwater flow systems, the depth of the water table, and so the distribution of flow paths…” Consider removing “so.”
- In lines 77 and 139, there is a reference to Figure 1a and Figure 1c, arguing that this figure shows the catchment colors and clusters. However, there is no reference to the colors and clusters in Figure 1. This might be missing from the figure, or the authors might reference Figure 4 instead. Please verify this inconsistency.
- I suggest changing the equation numbering to “(1)” instead of “Equation 1.”
References
Bresciani, E., Davy, P., & de Dreuzy, J.-R. (2014). Is the Dupuit assumption suitable for predicting the groundwater seepage area in hillslopes? Water Resources Research 50(3), 2394–2406. https://doi.org/10.1002/2013WR014284
Fan, Y. (2019). Are catchments leaky? Wiley Interdisciplinary Reviews: Water, 6. https://doi.org/10.1002/wat2.1386
Frisbee, M. D., Tolley, D. G., & Wilson, J. L. (2017). Field estimates of groundwater circulation depths in two mountainous watersheds in the western U.S. and the effect of deep circulation on solute concentrations in streamflow. Water Resources Research 53(4), 2693–2715. https://doi.org/10.1002/2016WR019553
McIntosh, J. C., & Ferguson, G. (2021). Deep Meteoric Water Circulation in Earth’s Crust. Geophysical Research Letters, 48(5), e2020GL090461. https://doi.org/10.1029/2020GL090461
Citation: https://doi.org/10.5194/hess-2024-381-RC1 - Some clarification is needed regarding the 3D numerical model approach.
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