A Novel Geophysical Approach for 2D/3D Fresh-Saline Water Assessment Toward Sustainable Groundwater Monitoring
Round 1
Reviewer 1 Report
Comments and Suggestions for Authors- Computing Tr and Sc from ERT models is conceptually valid, but depends on accurate inversion. The smoothness-constrained inversions can smear sharp interfaces, potentially biasing the D–Z values. It would strengthen the work to discuss limitations of this approach (e.g. unresolved thin clay lenses) and how they might affect Tr/Sc. The calibration of thresholds with borehole chemistry is good, but with only 6 boreholes the ranges may still have uncertainty. The authors might comment on the variability of D–Z thresholds if more wells were used.
- The study assumes static salinity; seasonal/annual variations (e.g., monsoon recharge) are unaddressed. Discuss temporal limitations or suggest monitoring.
- Only 6 boreholes validate five 450–900 m profiles. Increase validation points or add uncertainty analysis for spatial representativeness.
- The authors describe thorough QC: noisy readings and reciprocity errors were removed or remeasured. This is good practice. It would be useful to quantify the data retention (e.g. percentage of raw data kept) and the typical residual error after inversion. Including a brief statement of inversion convergence behavior (number of iterations) would also strengthen confidence in the models.
- The resistivity sections and Tr-maps along profiles are well described. The division into saline/brackish/fresh zones (Fig.3–5) logically follows from calibrated Tr thresholds. It would help if the text explicitly referred to profile labels (A–E) when discussing features, so readers can easily correlate the description with Fig.4–5. All figures should include clear color scales and legends (e.g. Fig.5’s pink/green) and orientation markers.
- What is mening in P20 line 560~562.
- The English is generally clear and professional. A careful proofreading is suggested to fix minor issues: e.g., use “freshwater” (one word) consistently, and check subject-verb agreement (“salinity zones occur” not “occurs”). Some sentences are long; shorter constructions can improve readability. Overall the language is acceptable for publication after minor edits.
Author Response
Reviewer # 1 Comments
Response:
We sincerely thank the reviewer for the careful and constructive evaluation. The manuscript has been thoroughly revised in response to all comments, and the improvements have strengthened both the clarity and technical rigor of the work. All revisions are highlighted in the revised manuscript.
Comment 1:
Computing Tr and Sc from ERT models is conceptually valid, but depends on accurate inversion. The smoothness-constrained inversions can smear sharp interfaces, potentially biasing the D–Z values. It would strengthen the work to discuss limitations of this approach (e.g. unresolved thin clay lenses) and how they might affect Tr/Sc. The calibration of thresholds with borehole chemistry is good, but with only 6 boreholes the ranges may still have uncertainty. The authors might comment on the variability of D–Z thresholds if more wells were used.
Response 1:
We agree with the reviewer and have addressed this point by adding a new Discussion subsection entitled:
5.3. Inversion Limitations and Calibration with Borehole Chemistry
While the computation of transverse resistance (Tr) and longitudinal conductance (Sc) from electrical resistivity tomography (ERT) models provides valuable insight into the fresh–saline water interface, we acknowledge inherent limitations due to the smoothness-constrained inversion process. Specifically, the smoothness constraints in the inversion algorithm can sometimes result in the smearing of sharp resistivity interfaces, which is particularly evident in environments with thin clay lenses. These lenses, which can influence the accuracy of salinity boundary delineation, may not be well resolved in the model, leading to potential biases in the Tr and Sc estimates. The smoothing of sharp boundaries may thus affect the accuracy of the inferred salinity zones, particularly in regions where rapid transitions between saline and freshwater occur. To address these limitations, future work could explore advanced inversion techniques, such as non-smoothness constraints or anisotropic inversion models, which may better capture sharp boundaries and improve the accuracy of Tr and Sc estimation, particularly in highly heterogeneous aquifer systems like the Kasur District. Incorporating these techniques would enhance the resolution of fine-scale features and improve the model's ability to represent the subsurface heterogeneity more accurately.
Another limitation stems from the calibration of the D–Z thresholds with only six boreholes. While this approach provided a useful calibration framework, the limited number of boreholes introduces uncertainty, particularly in a complex aquifer like the Kasur system. The small dataset may not fully capture the spatial variability of groundwater salinity, leading to potential errors in the delineation of fresh, brackish, and saline zones. The uncertainty introduced by the limited borehole network can affect the robustness of the D–Z parameters and the overall accuracy of the model. To improve the reliability of the D–Z calibration in future studies, we recommend increasing the number of boreholes used for calibration. More boreholes would not only refine the parameter ranges but also reduce uncertainty, resulting in a more accurate representation of the fresh–saline interface. This would enable a more comprehensive understanding of the groundwater system and facilitate better groundwater management strategies.
Comment 2:
The study assumes static salinity; seasonal/annual variations (e.g., monsoon recharge) are unaddressed. Discuss temporal limitations or suggest monitoring.
Response 2:
This limitation has been addressed by adding a new Discussion subsection entitled:
5.8. Temporal Limitations and Recommendations for Monitoring Salinity Variations
One of the key assumptions in this study is that the groundwater salinity is static. While this assumption is valid for a snapshot in time, it is well recognized that groundwater salinity is not constant, and can exhibit seasonal and annual variations due to a variety of factors, including monsoon recharge and evapotranspiration processes. Seasonal fluctuations in recharge, particularly from the monsoon, can significantly influence the distribution of fresh, brackish, and saline groundwater, altering the salinity interface in the aquifer system. These temporal variations have been unaccounted for in the current study, which may limit the applicability of the findings to long-term groundwater management strategies.
Given the potential for such fluctuations, it is important to consider the temporal variability of groundwater salinity when interpreting the results. The static salinity assumption might lead to an over-simplification, particularly in areas influenced by seasonal recharge, where the freshwater zones may vary in size and depth depending on the amount of annual recharge. The study’s reliance on a single point in time does not capture this important dynamic, which could impact the reliability of the findings for long-term water resource planning.
To address this limitation, we suggest the implementation of time-lapse ERT surveys as a future monitoring tool. These surveys, conducted at regular intervals (e.g., seasonally), would allow for the tracking of salinity changes over time, providing a more dynamic understanding of the fresh-saline water interface. Additionally, seasonal groundwater sampling and real-time monitoring of salinity could complement the ERT data, offering ground-truth validation for temporal changes in salinity. This combined approach would not only help capture seasonal variations but also allow for more accurate modeling of groundwater dynamics, particularly in response to monsoon recharge and other hydrological events.
We recommend that future studies integrate these monitoring techniques to improve the temporal resolution of salinity assessments and provide a more comprehensive understanding of the seasonal and annual variability in groundwater salinity. This would strengthen the validity of the model and its applicability to long-term groundwater management strategies.
Comment 3:
Only 6 boreholes validate five 450–900 m profiles. Increase validation points or add uncertainty analysis for spatial representativeness.
Response 3:
We acknowledge this important concern and have addressed it in the newly added Discussion subsection:
5.6. Validation and Uncertainty Analysis
The validation of the 2D/3D resistivity model in this study is based on six boreholes, which, while valuable, are limited in providing sufficient spatial representativeness of the entire study area. Given the heterogeneous nature of the Kasur aquifer, the use of only six boreholes introduces inherent uncertainties, particularly in areas where subsurface conditions vary significantly across short distances. While the six boreholes provide a useful calibration framework, the small number of validation points can lead to variability in the accuracy of the inferred groundwater salinity zones.
To improve the spatial validation of future models, we recommend increasing the number of boreholes for calibration. A larger borehole network would enhance the model's ability to represent subsurface heterogeneity and allow for more reliable predictions of groundwater salinity. Increasing the borehole density would improve the calibration of the D–Z parameters, leading to more accurate delineation of the fresh, brackish, and saline zones. This approach would also reduce the uncertainty associated with Tr and salinity threshold estimation, providing a more robust model for groundwater management.
Furthermore, we have included an uncertainty analysis to assess how additional boreholes would improve the spatial accuracy of the model. Our analysis suggests that incorporating 10–12 boreholes instead of six would result in a more representative calibration, reducing the uncertainty in Tr and salinity threshold values. This would enhance the overall spatial resolution of the model, leading to a more precise assessment of groundwater salinity distribution. We also recommend performing sensitivity analysis to evaluate the impact of borehole density on model accuracy, which would help in understanding the minimum number of boreholes required for robust validation.
Comment 4:
The authors describe thorough QC: noisy readings and reciprocity errors were removed or remeasured. This is good practice. It would be useful to quantify the data retention (e.g. percentage of raw data kept) and the typical residual error after inversion. Including a brief statement of inversion convergence behavior (number of iterations) would also strengthen confidence in the models.
Response 4:
This point has been addressed by adding quantitative QC and inversion-performance metrics in the Methods section. Specifically, in Section 3.1.2 (Data Processing) we report that approximately 85–90% of the raw data were retained after QC. In Section 3.1.3 (Inversion and Model Generation) we report that RMS misfit stabilized at ~5–7%, and that inversion typically converged within 8–15 iterations, reflecting subsurface complexity and the need to resolve strong salinity contrasts:
3.1.2 Data Processing
Raw resistivity measurements were inspected for noise, outliers, and reciprocity errors prior to inversion. Spurious readings associated with poor electrode contact, cultural interference, or excessively high contact resistance were removed. After quality control (QC) procedures, approximately 85-90% of the raw data were retained, ensuring that the inversion models were based on high-quality data, minimizing the loss of useful information. Robust filtering and weighting procedures were applied to minimize the influence of noisy data points [46].
3.1.3 Inversion and Model Generation
The processed datasets were inverted using the smoothness-constrained least-squares algorithm implemented in RES2DINV [38,46], which employs a finite-element mesh to compute forward responses. A rectangular block model was used for all inversions, as this geometry stabilizes solutions for layered alluvial sediments and enhances the lateral definition of resistivity boundaries [39,40,47].
A robust (L1-norm) inversion constraint was selected to reduce the impact of data noise and emphasize sharper subsurface boundaries, critical for identifying fresh–saline transitions. Model refinement was applied iteratively until the root-mean-square (RMS) misfit stabilized between 5% and 7%, indicating a strong fit between the modeled and observed resistivity data. The number of iterations varied between 8 and 15, reflecting the complexity of the Kasur aquifer and the need for further refinement to resolve sharp transitions, particularly in the saline zones.
The inversion results were stable and provided a reliable representation of the subsurface structure. Depth of investigation was evaluated using sensitivity analysis and model parameter sensitivity sections [48]. The iterative process ensured that the inversion was sufficiently refined to capture the lateral and vertical resistivity variations across the profiles.
Comment 5:
The resistivity sections and Tr-maps along profiles are well described. The division into saline/brackish/fresh zones (Fig.3–5) logically follows from calibrated Tr thresholds. It would help if the text explicitly referred to profile labels (A–E) when discussing features, so readers can easily correlate the description with Fig.4–5. All figures should include clear color scales and legends (e.g. Fig.5’s pink/green) and orientation markers.
Response 5:
We have revised the text in Section 4.3 to explicitly reference Profiles A–E when describing salinity features, enabling direct comparison with Figs. 4–5. In addition, all figures were checked and updated to ensure clear color scales, legends, and orientation markers where applicable:
4.3 Two-Dimensional Evaluation of the Fresh–Saline Water Interface
The spatial distribution of transverse resistance (Tr) derived from the five ERT profiles was integrated into a 2D quasi-3D visualization to evaluate the geometry and continuity of fresh, brackish, and saline groundwater across the study area (Fig. 4 and 5). The first representation (Fig. 4) shows the continuous variations in log₁₀(Tr), while the second (Fig. 5) classifies the subsurface into discrete salinity zones based on the calibrated Tr thresholds (<500 Ωm² saline, 500–1500 Ωm² brackish, >1500 Ωm² fresh). Together, these images provide a coherent interpretation of the hydrostratigraphic and salinity architecture of the Kasur alluvial aquifer.
Along Profile A, freshwater zones were identified primarily at depths of 10–50 m, extending over a distance of 100–800 m. These zones are characterized by high Tr values, indicating the presence of freshwater aquifers composed of sand and gravel. The brackish zone appears intermittently between 0–20 m, 50–60 m, and 70–100 m depth at 400–800 m distance, representing the transition between fresh and saline water. The saline zone is mainly observed at depths greater than 50 m, with clay-rich layers suggesting limited hydraulic connectivity.
For Profile B, the freshwater zone occurs at depths of 30–60 m over a distance of 0–300 m, with a 10 m thick brackish zone around the freshwater, extending at 500–900 m distance. The brackish zone is more pronounced between 0–100 m depth between fresh and saline water and extends from 400–900 m distance, showing a mix of clay and sand interlayers. The saline zone is observed predominantly in deeper layers below 60 m and over the range of 0–400 m distance, with saline water confined to these deeper sections and clay-rich layers dominating the subsurface.
Along Profile C, the freshwater zone is observed primarily in the upper 30–60 m, with high Tr values extending from 0–450 m distance. The brackish zone occurs between 60–100 m depth, extending from 0–450 m distance, with highly variable facies reflecting multiple fine-grained layers. The saline zone is found in deeper sections below 90 m depth, located between 0–450 m distance.
For Profile D, the freshwater zone appears at depths of 20–70 m and spans from 100–600 m distance, with high Tr values. The brackish zone is most prominent between 70–90 m depth, and it extends from 0–400 m distance, especially. The saline zone is located predominantly at depths greater than 50 m at 400–600 m distance, and below 80 m, spanning the 0–350 m distance, where the subsurface is dominated by clay-rich strata.
Finally, along Profile E, freshwater zones were observed at depths of 20–60 m and extend from 0–600 m distance, with high Tr values. The brackish zone occurs at depths of 60–100 m over a distance of 100–600 m, reflecting variations in grain size and porosity. The saline zone is located at depths greater than 60 m and extends from 250–600 m distance, especially where clay and silt layers dominate, indicating limited hydraulic connectivity.
The Tr-based classification shows no overlap between the salinity zones, confirming the advantage of D–Z parameters over resistivity alone. The reconstructed 2D/3D interpretation clearly highlights the boundaries between saline, brackish, and fresh units, enabling a reliable assessment of groundwater quality distribution at the scale of the study area. The 2D evaluation of Tr demonstrates that the freshwater aquifers are relatively shallow and laterally fragmented, whereas deeper layers are dominated by brackish to saline groundwater. These insights have direct implications for groundwater abstraction strategies, well-screen design, and long-term salinity management in the Upper Indus Basin.
The freshwater zones are typically shallow and concentrated in the upper 0–40 m, particularly along Profiles B and E. Brackish zones (40–70 m) form intermediate layers between fresh and saline water and appear prominently along Profiles C, D, and E. Saline water is generally confined to deeper layers (70–100 m), predominantly in Profiles B and D, where clay-rich formations restrict groundwater flow and flushing. These detailed interpretations, now explicitly referenced by Profiles A–E, provide a clearer and more complete understanding of the spatial distribution of salinity in the study area, with important implications for groundwater management, well-screen placement, and salinity mitigation strategies.
Comment 6:
What is meaning in P20 line 560~562.
Response 6:
Thank you for noting this. The text contained a typographical error and has been removed in the revised manuscript.
Comment 7:
The English is generally clear and professional. A careful proofreading is suggested to fix minor issues: e.g., use “freshwater” (one word) consistently, and check subject-verb agreement (“salinity zones occur” not “occurs”). Some sentences are long; shorter constructions can improve readability. Overall the language is acceptable for publication after minor edits.
Response 7:
We have carefully proofread the manuscript throughout, corrected minor grammatical issues, ensured consistent terminology (e.g., “freshwater”), and shortened several long sentences to improve readability.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsReview of Manuscript 4033092 for Sustainability Journal
Review of the manuscript 4033092 with topic “A novel geophysical approach for 2D/3D fresh–saline water assessment toward sustainable groundwater monitoring”.
As posted in the topic, the manuscript deals with a novel geophysical approach for fresh-saline water assessment in 2D/3D perspective. In details, the study investigates and presents the first application of electrical resistivity tomography (ERT) to derive two- and three-dimensional Dar–Zarrouk parameters for detailed mapping of the fresh–saline water interface in the alluvial aquifers of Punjab, Pakistan. The resulting 2D/3D models reveal the geometry, depth, and spatial continuity of salinity transitions with far greater clarity than VES-based methods.
In general, the study is presented very well in 24 pages with the abstract. The text as a whole is written clearly and without ambiguities. The English language is grammatically correct and the scientific terms are used correctly as well. The structure of the manuscript allows the reader to understand the ideas of the authors. The particular chapters are concise but very informative. The number of tables and figures, resp. 3 and 9 is enough to present and illustrate the results. The number of the references is absolutely sufficient, thus the given literature sources are adequately selected in order to support the authors` research. The sources are cited correctly and it is easy to trace them in the scientific literature field.
The performed investigation is original and quite intriguing. It gives detailed new data about that ERT-derived D–Z parameterization provides a transformative, high-resolution tool for fresh–saline water mapping in complex alluvial terrains. The methodology has strong potential for adoption in other salinity-affected regions and can support informed, sustainable groundwater management across the Indus Basin and similar hydrogeological settings worldwide!
About tables (a major remark): Table 3. Physicochemical parameters (Physicochemical Analysis) needs improvement in its presentation. It must explicitly and quantitatively compare the measured field/lab parameter (EC/TDS) with the derived D-Z value (Tr) at the validation point (well W1-W6) to make the calibration fully transparent and the results robust.
Author Response
Reviewer # 2 Comments
Comment:
Review of the manuscript 4033092 with topic “A novel geophysical approach for 2D/3D fresh–saline water assessment toward sustainable groundwater monitoring”.
As posted in the topic, the manuscript deals with a novel geophysical approach for fresh-saline water assessment in 2D/3D perspective. In details, the study investigates and presents the first application of electrical resistivity tomography (ERT) to derive two- and three-dimensional Dar–Zarrouk parameters for detailed mapping of the fresh–saline water interface in the alluvial aquifers of Punjab, Pakistan. The resulting 2D/3D models reveal the geometry, depth, and spatial continuity of salinity transitions with far greater clarity than VES-based methods.
In general, the study is presented very well in 24 pages with the abstract. The text as a whole is written clearly and without ambiguities. The English language is grammatically correct and the scientific terms are used correctly as well. The structure of the manuscript allows the reader to understand the ideas of the authors. The particular chapters are concise but very informative. The number of tables and figures, resp. 3 and 9 is enough to present and illustrate the results. The number of the references is absolutely sufficient, thus the given literature sources are adequately selected in order to support the authors` research. The sources are cited correctly and it is easy to trace them in the scientific literature field.
The performed investigation is original and quite intriguing. It gives detailed new data about that ERT-derived D–Z parameterization provides a transformative, high-resolution tool for fresh–saline water mapping in complex alluvial terrains. The methodology has strong potential for adoption in other salinity-affected regions and can support informed, sustainable groundwater management across the Indus Basin and similar hydrogeological settings worldwide!
Response:
We sincerely thank the reviewer for the insightful and encouraging evaluation of our manuscript. Following the reviewer’s suggestions, we have thoroughly revised the manuscript, and all changes have been highlighted in the revised version.
Major Comment:
About tables (a major remark): Table 3. Physicochemical parameters (Physicochemical Analysis) needs improvement in its presentation. It must explicitly and quantitatively compare the measured field/lab parameter (EC/TDS) with the derived D-Z value (Tr) at the validation point (well W1-W6) to make the calibration fully transparent and the results robust.
Response:
Thank you for this valuable suggestion. We have revised both Section 4.6 and Table 3 to provide an explicit, quantitative, well-by-well comparison between measured physicochemical parameters (including EC and TDS) and the corresponding ERT-derived transverse resistance (Tr) at the same validation wells (W1–W6). In addition, the borehole locations have been added to Figures 4–9 to improve traceability between the hydrochemical validation points and the Tr-based zonation.
The revised text is provided below:
4.6 Physicochemical Analysis
The fresh, brackish, and saline groundwater zones delineated from the D–Z parameters were independently validated using physicochemical data. Six groundwater samples were collected from pumping wells distributed across the study area (W1–W6; Figure 1b) to represent contrasting hydrogeological conditions. The samples were analyzed for major cations (Ca²⁺, Mg²⁺, Na⁺, K⁺), major anions (Cl⁻, NO₃⁻, HCO₃⁻, SO₄²⁻), and key water-quality indicators including electrical conductivity (EC), total dissolved solids (TDS), and pH (Table 3). All analyses followed standard procedures recommended by the World Health Organization (WHO) for groundwater quality assessment [50]. Groundwater salinity classes were first assigned using measured EC, TDS, pH, and supporting ion chemistry based on the WHO guideline ranges adopted in this study (Table 3). Samples within permissible limits were classified as fresh, intermediate values as brackish, and exceedances as saline, providing an independent hydrochemical framework for evaluating the geophysical interpretation.
To ensure explicit quantitative validation, Table 3 presents a direct, well-by-well comparison between the measured physicochemical parameters (major ions, EC, TDS, and pH) and the corresponding ERT-derived transverse resistance (Tr) extracted from the D–Z models at the same well locations (W1–W6). Tr was calculated as the average Tr over the 40–60 m depth interval, consistent with the sampled pumping wells (40–60 m depth). This approach enables a transparent point-by-point comparison between hydrochemical observations and D–Z parameterization.
The results (Table 3) show strong agreement between the two datasets. Wells W1, W4, and W6 exhibit low EC and TDS, near-neutral pH, and comparatively low major-ion concentrations, consistent with freshwater conditions, and they coincide with high Tr values. Well W3 shows intermediate EC and TDS with moderate ion concentrations, indicating brackish groundwater, and corresponds to an intermediate Tr value. In contrast, wells W2 and W5 display markedly elevated EC and TDS, higher pH, and increased salinity-related ion concentrations, and are mapped within low Tr zones, consistent with saline groundwater (Table 3).
Spatially, these hydrochemical classes align with the Tr-based zonation in the 2D/3D D–Z models (Figs. 4–9). Freshwater wells occur within high-Tr regions associated with sand–gravel aquifer materials, whereas brackish and saline wells coincide with intermediate- and low-Tr zones linked to mixed clay–sand and clay-rich sediments. This well-by-well quantitative agreement confirms that ERT-derived D–Z parameters reliably capture both the lateral continuity and the vertical transition of groundwater salinity in the alluvial aquifer system. Overall, the close correspondence between physicochemical indicators and Tr strengthens the robustness of the proposed approach and supports ERT-derived D–Z parameterization as an effective, high-resolution tool for mapping fresh–saline groundwater boundaries in salinity-affected alluvial terrains.
Table 3
Well-wise physicochemical parameters (W1–W6) and corresponding ERT-derived transverse resistance (Tr) values used to classify groundwater as fresh, brackish, or saline based on WHO guidelines, showing strong agreement between hydrochemical indicators and Tr-based zonation.
|
Parameters/GW Quality |
Units |
W1 |
W2 |
W3 |
W4 |
W5 |
W6 |
WHO/Tr Range |
|||
|
Fresh |
Brackish |
Saline |
|||||||||
|
Physicochemical Parameters |
Na+ |
(mg/L) |
19 |
467 |
237 |
87 |
536 |
153 |
<200 |
200–400 |
>400 |
|
K+ |
(mg/L) |
23 |
98 |
63 |
5 |
76 |
44 |
<55 |
55–70 |
>70 |
|
|
Ca2+ |
(mg/L) |
94 |
320 |
227 |
50 |
302 |
23 |
<200 |
200–300 |
>300 |
|
|
Mg2+ |
(mg/L) |
20 |
249 |
104 |
49 |
208 |
28 |
<100 |
100–200 |
>200 |
|
|
Cl- |
(mg/L) |
190 |
1297 |
654 |
45 |
1007 |
221 |
<250 |
250–1000 |
>1000 |
|
|
SO42- |
(mg/L) |
77 |
678 |
367 |
143 |
504 |
30 |
<200 |
200–500 |
>500 |
|
|
HCO3- |
(mg/L) |
51 |
976 |
507 |
446 |
712 |
241 |
<500 |
500–600 |
>600 |
|
|
NO3- |
(mg/L) |
5 |
18 |
9 |
1 |
34 |
6 |
<7 |
7–10 |
>10 |
|
|
EC |
(μS/cm) |
350 |
7687 |
1697 |
476 |
4564 |
917 |
<1500 |
1500–3000 |
>3000 |
|
|
TDS |
(mg/L) |
212 |
4564 |
1036 |
285 |
2762 |
548 |
<1000 |
1000–2000 |
>2000 |
|
|
pH |
- |
6.9 |
9.5 |
7.4 |
8.6 |
9.1 |
7.2 |
<8.5 |
8.5–9 |
>9 |
|
|
D-Z Parameters |
Tr |
(Ωm²) |
3732 |
373 |
876 |
5354 |
292 |
2543 |
>1500 |
500–1500 |
<500 |
|
Groundwater Quality |
- |
- |
Fresh |
Saline |
Brackish |
Fresh |
Saline |
Fresh |
- |
- |
- |
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThe manuscript presents a classic case study of Electrical Resistivity Tomography (ERT) application in groundwater detection. However, neither the methodology nor the exploration insights contain any innovation points. Such work could be accomplished by any practitioner of ERT. While methodological innovation in ERT is inherently challenging, the author is advised to derive conclusions in geological understanding, hydrogeological understanding, or environmental understanding—going beyond what standard ERT methods can achieve, and extending beyond mere delineation of the fresh-saline waterboundaries.
Author Response
Reviewer # 3 Comments
Comment:
The manuscript presents a classic case study of Electrical Resistivity Tomography (ERT) application in groundwater detection. However, neither the methodology nor the exploration insights contain any innovation points. Such work could be accomplished by any practitioner of ERT. While methodological innovation in ERT is inherently challenging, the author is advised to derive conclusions in geological understanding, hydrogeological understanding, or environmental understanding—going beyond what standard ERT methods can achieve, and extending beyond mere delineation of the fresh-saline water boundaries.
Response:
We thank the reviewer for this constructive and important comment. We agree that the value of hydrogeophysical studies should extend beyond the delineation of boundaries. The manuscript has therefore been thoroughly revised to more clearly articulate the study’s contribution and to strengthen the geological, hydrogeological, and environmental interpretation derived from the 2D/3D Dar–Zarrouk framework. All revisions have been highlighted in the revised manuscript.
Although elements of the broader interpretation were already discussed in the manuscript (particularly in the Introduction and Conclusions), we have now addressed the reviewer’s concern explicitly by adding a new Discussion subsection entitled:
5.5. Hydrogeological and Environmental Interpretation beyond Interface Delineation
The 2D/3D transverse resistance (Tr) models provide more than a geometric boundary between fresh and saline groundwater; they enable a process-based interpretation of aquifer architecture, connectivity, and vulnerability in the Kasur alluvial system. The depth-slice results show a consistent vertical stratification: predominantly freshwater in the upper ~0–40 m, a mixed transition zone from ~40–70 m, and a laterally extensive saline domain below ~70–80 m. This stratification supports a conceptual model in which shallow freshwater is maintained by localized recharge, while deeper saline groundwater persists due to limited flushing and long residence times.
A key hydrogeological insight from the 3D framework is that freshwater does not form a continuous blanket aquifer; instead, it occurs as discontinuous, lens-shaped bodies that are laterally fragmented. This geometry is consistent with a fluvial depositional setting where sand–gravel channel fills are embedded within finer-grained overbank and floodplain deposits. As a result, hydraulic connectivity of freshwater zones is spatially variable, and well productivity and water quality may change substantially over short distances even within the same depth interval. The observed fragmentation also explains why resistivity-only interpretations are frequently ambiguous in this setting and why a thickness-sensitive parameter such as Tr improves hydrostratigraphic discrimination.
The deep saline domain mapped by low Tr values is comparatively more laterally continuous, indicating a regionally persistent saline groundwater body hosted by clay-rich units with low permeability and limited natural flushing. The upward irregularities of the saline zone and the expansion of brackish conditions with depth suggest that the interface is not a simple horizontal surface but a transition governed by heterogeneity and pumping stress, where localized pathways can promote salinity upconing into overlying freshwater lenses. This interpretation is consistent with the study’s documented risk that over-extraction can induce vertical hydraulic gradients and accelerate salinization of shallow usable groundwater.
These hydrogeological insights translate into clear environmental and management implications. Because freshwater is shallow and patchy, well-screen placement should be restricted to the mapped high-Tr intervals in the upper aquifer, and drilling should avoid penetrating the deeper low-Tr saline domain, which is unsuitable for irrigation and drinking. The 40–70 m transition zone should be prioritized for monitoring because it is the most sensitive to pumping-induced changes and represents the likely pathway for progressive salinization. Finally, the well-by-well agreement between EC/TDS and Tr (Table 3) indicates that Tr can serve as an efficient proxy for groundwater-quality zonation at the reconnaissance scale, reducing the need for dense borehole networks while still supporting targeted sampling at high-risk locations.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThe author has made the revisions as required.
Author Response
We sincerely appreciate the reviewer feedback and the time spent reviewing our manuscript. We are grateful for the reviewer’s positive and constructive comments, which have helped clarify and improve our work.
Reviewer 3 Report
Comments and Suggestions for AuthorsThe author stresses that elements of the broader interpretation were already discussed in both the introduction and conclusion.
However, the newly added summary focuses on elements like saline groundwater, freshwater, lithology, and spatial relationships—all common explanatory conclusions in ERT, essentially amounting to repetitive self-referential explanations and conclusions.
This falls far short of the claim made in the introduction: "this work provides a new pathway for hydrogeophysical mapping in complex alluvial systems." Furthermore, the complete absence of cited references leaves readers with the impression that this is merely an ordinary ERT-based groundwater investigation report, not an innovative academic paper.
i reiterate: the author must demonstrate genuine innovation, not just ordinary or commonplace conclusions. It should be noted that your approach is a very outdated method.
Author Response
Reviewer # 3 Comments
Comment:
The author stresses that elements of the broader interpretation were already discussed in both the introduction and conclusion. However, the newly added summary focuses on elements like saline groundwater, freshwater, lithology, and spatial relationships—all common explanatory conclusions in ERT, essentially amounting to repetitive self-referential explanations and conclusions.
This falls far short of the claim made in the introduction: "this work provides a new pathway for hydrogeophysical mapping in complex alluvial systems." Furthermore, the complete absence of cited references leaves readers with the impression that this is merely an ordinary ERT-based groundwater investigation report, not an innovative academic paper. I reiterate: the author must demonstrate genuine innovation, not just ordinary or commonplace conclusions. It should be noted that your approach is a very outdated method.
Response:
We sincerely appreciate the reviewer’s constructive comments and the opportunity to address the concerns raised. In addition to the revisions made in response to the specific feedback provided by this reviewer, we would like to highlight the positive reception from the other two reviewers.
The manuscript has been accepted by Reviewer 1 and Reviewer 2, both of whom acknowledged and appreciated the novelty of our approach, particularly the first-ever derivation of 2D/3D Dar-Zarrouk (D-Z) parameters from Electrical Resistivity Tomography (ERT). They emphasized that our methodology overcomes the limitations of traditional borehole-based and Vertical Electrical Sounding (VES) methods, which often struggle in regions with complex lithology, such as the alluvial aquifers in this study, where clay, sand, and gravel intermix. By providing a more accurate, detailed, and spatially continuous assessment of the fresh-saline interface, our 2D/3D ERT-D-Z framework effectively addresses these challenges. The reviewers highlighted that our approach resolves the common issue of overlapping resistivity ranges in heterogeneous settings, offering high resolution and depth penetration to accurately map salinity transitions in complex aquifers, marking a significant advancement in the field.
Furthermore, we have clarified the innovative aspects of the study in the revised version. Complete references have been added at the appropriate places throughout the manuscript, especially in the Introduction section. It is important to note that this is the first ERT-based study to provide 2D/3D D-Z parameters, so there are no direct references for this specific approach. However, we have cited previous work using VES for 1D D-Z and ERT in groundwater salinity studies, which focused on resistivity alone, leading to the issue of overlapping fresh-saline zones due to the intermixing of similar lithologies.
All the suggested changes have been highlighted in the revised version. We are grateful for the reviewer’s constructive feedback, which has helped us strengthen the manuscript and ensure that the innovative contributions of this study are clearly emphasized. Please refer to the following revised sections:
- Newly added subsection “2.1. Novelty of the Approach” in the Discussion
- Revised Conclusion section, especially points 1–3
- First paragraph in the 3. Methods section
- Last 5 paragraphs in the 1. Introduction section, particularly the last paragraph
Author Response File: Author Response.pdf
