the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 Sep 2023
An underground drip water monitoring network to characterize rainfall recharge of groundwater at different geologies, environments, and climates across Australia
Abstract. Understanding when and why groundwater recharge occurs is of fundamental importance for the sustainable use of this essential freshwater resource for humans and ecosystems. However, accurately capturing this component of the water balance is widely acknowledged to be a major challenge. Direct physical measurement identifying when groundwater recharge is occurring is possible by utilizing a sensor network of hydrological loggers deployed in underground spaces located in the vadose zone. Through measurements of water percolating into these spaces from above, we can record the potential groundwater recharge process in action. By using automated sensors, it is possible to precisely determine when recharge occurs (which event, month, or season, and for which climate condition). Combined with daily rainfall data, it is possible to quantify the ‘rainfall recharge threshold’, the amount of rainfall needed to generate groundwater recharge, and its temporal and spatial variability. Australia’s National Groundwater Recharge Observing System (NGROS) provides the first dedicated sensor network for observing groundwater recharge at an event-scale across a wide range of geologies, environments, and climate types representing a wide range of Australian hydroclimates. Utilizing tunnels, mines, caves, and other subsurface spaces located in the vadose zone, the sensors effectively record ‘deep drainage’, water that can move beyond the shallow subsurface and root zone to generate groundwater recharge. The NGROS has the temporal resolution to capture individual recharge events, with multiple sensors deployed at each site to constrain the heterogeneity of recharge between different flow paths, and to quantify (including uncertainty bounds) rainfall recharge thresholds. Established in 2022, the network is described here together with examples of data being generated.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-2053', Anonymous Referee #1, 03 Oct 2023
General comment:
The paper presents the Australia’s National Groundwater Recharge Observing System (NGROS) which is the first dedicated sensor network for observing the recharge of groundwater at the event-scale across a wide range of geologies, environments, and climate types that represent a wide range of Australian hydroclimates.
Though simple the monitoring concept for NGROS is quite original as it provides data on the timing of recharge at the event timescale and allows estimating the amount of precipitation needed to generate recharge at an event scale. According to the authors, the NGROS observing system is deployed into specific sites to cover a range of geologies, environmental and climate types, to simply capture some evidence connecting these factors with the number of recharge events and the amount of precipitation needed to generate such events. Nevertheless, the acquisition system and the methodology adopted for the data analysis seems not suitable for a quantitative evaluation of the recharge events as this would ask for a deeper understanding of the hydrogeological features of every adopted monitoring site. The lack of a quantitative derivation based on the drip counting thus limited the data processing to the frequency domain.
Another drawback related to the presentation of the NGROS system is that the dataset recorded at the observation sites is not available despite the authors claimed its availability from a specified website.
In conclusion, the NGROS monitoring system though being based on the direct observation of groundwater recharge phenomena, does not provide systematic characterization of the hydrologic response of the fractured rocks to the rainfall input. Some examples of in-depth system characterization and for more robust hydrological analysis can be found in the recent literature published on HESS referring to some caves in Australia (e.g. Mahmud et al. 2016; Mahmud et al. 2018).
Specific comment:
Section 2.1: The site description is not homogeneous from one site to the other. The details concerning the geological settings should be standardized so that the cave dripping can be related to specific features of the site. The sub-sections in section 2.1 are hard to read given the large number of monitoring sites (14!). A summarizing table with all climatic, geological and landcover features far all sites will be useful for a better clarity.
Section 3: Similarly, the results section could be more clear to the reader through a summarizing table where the relationship between rainfall events and recharge response become more evident in all sites (and not only in the sub-set of sites reported in the Figures 4-6). Moreover, it seems that the comments regarding Figure 5 and 6 are not complete, compared to those regarding Figure 4 (lines 306-312).
The results section should deal with all monitoring sites, particularly given the unavailability of observation records.
Citation: https://doi.org/10.5194/egusphere-2023-2053-RC1 -
AC2: 'Reply on RC1', Andy Baker, 24 Jan 2024
We thank the reviewer for their review and comments on this pre-print. Our response is made in the context that the pre-print has been submitted to Geoscientific Instrumentation, Methods and Data Systems, where our understanding is that the journal aims and scope are on advances in concepts, design and description of instrumentation and data systems, and that the preprint, therefore, focuses on what we believe is an advance, using instrumentation situated in human-made and natural spaces in the vadose zone to quantify the timing of groundwater recharge events.
As stated on lines 74-75 of the pre-print, the monitoring concept for NGROS is to (1) provide data on the timing of recharge at the event timescale and (2) determine the amount of precipitation needed to generate recharge at an event scale. We agree with the reviewer that this concept focuses on the temporal aspects of groundwater recharge. We agree that the focus is on the frequency domain, and the approach precludes the determination of recharge volume or amount of recharge, which would require further analyses that are outside the scope of this pre-print. We propose that we add some new text to the manuscript that addresses the fact that the NGROS network does not address recharge volume. We agree that the approaches of Mahmud et al (2016, 2018) could be used by future research to generate recharge volume estimations at cave sites by combining the data produced by NGROS and techniques such as in-cave lidar. The methods of Mahmud et al (2016, 2018) would not work at the mine sites, as the approaches required the counting of stalactites to quantify the number of water flow pathways into the cave.
The groundwater.unsw.edu.au website provides access to the NGROS data. It went live in mid-October and unfortunately was not available at the time of review.
We agree that a summary table will be helpful given the large number of initial sites described in this pre-print. We will add this to Section 2.1, and at the same time check that everything is standardised between sub-sections.We appreciate the request to provide results from all 14 initial NGROS sites. We believe that level of data analysis and interpretation would be outside the scope of the Geoscientific Instrumentation, Methods and Data Systems (see https://www.geoscientific-instrumentation-methods-and-data-systems.net/about/aims_and_scope.html). We would like to note that the pre-print focuses on the initial fourteen sites and is intended to present the monitoring concept and research platform that is NGROS, including three examples illustrating the type of data collected. We expect to expand the number of sites over time as more partners join to collaborate with the project.
We checked whether the text relating to Figures 4, 5 and 6 was complete, and at this time would not propose to add any further text about these three examples.
Finally, we would like to take this opportunity to correct the description for Capricorn Caves (section 2.1.10) which incorrectly duplicates text from section 2.1.12. We apologise for that mistake. The correct text is:
“This natural cave site is in an isolated c. 50 m high limestone hill with 390M yr old Devonian reef limestone geology. It has a native dry rainforest vegetation cover. The local climate has a mean annual temperature of 23.4 °C, mean annual rainfall of 815 mm, and modelled pan evaporation of 2525 mm. The climate is on the boundary of Cfa (temperate, no dry season, hot summer) and tropical savanna climate classifications (Aw). Loggers have been placed in the lowest cave passages, closest to the groundwater. The site is privately owned and managed.”References
Mahmud, K., Mariethoz, G., Treble, P.C. and Baker, A., 2016. Terrestrial LiDAR survey and morphological analysis to identify infiltration properties in the Tamala Limestone, Western Australia. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 8, 4871-4881.Mahmud, K., Mariethoz, G., Baker, A. and Treble, P.C., 2018. Hydrological characterization of cave drip waters in a porous limestone: Golgotha Cave, Western Australia. Hydrology and Earth System Sciences, 22, 977-988
Citation: https://doi.org/10.5194/egusphere-2023-2053-AC2
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AC2: 'Reply on RC1', Andy Baker, 24 Jan 2024
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CC1: 'Comment on egusphere-2023-2053', Sarah Bourke, 20 Dec 2023
This manuscript presents a novel approach for understanding groundwater recharge using drip loggers in underground cavities. This manuscript seems to be a technical note summarizing the monitoring infrastructure, data analysis approach and preliminary data collected. It is evident from Section 4 that further data collection and interpretation is anticipated. This will make a worthwhile contribution to the literature as a description of a novel method for improving our understanding of groundwater recharge, which is vital as climates change and world population grows. It would be good if the authors can further clarify whether or not this approach can give quantitative estimates of recharge rates or volumes (as flagged by the referee), and if the maximum value of the data lies in combining the drips with other data from instrumentation at CZO sites. The aspirational statements in Section 4 are admirable, but seem somewhat out of place in what seems intended to be a relatively brief technical note. More discussion in this section of how this application of drip loggers extends their use from what has been done before, and how this new data source will add to our current literature-based understanding would be welcome.
Citation: https://doi.org/10.5194/egusphere-2023-2053-CC1 -
AC3: 'Reply on CC1', Andy Baker, 24 Jan 2024
Thank you very much for taking the time to make a community comment.
We confirm, as in our response to Reviewer Comment 1, that we will clarify that this methodology focuses on the temporal occurrence of recharge, and the approach precludes the direct determination of recharge volume or amount of recharge, which would require further analyses. This data generated is predominantly of the timing of recharge at the event timescale and the determination of rainfall recharge thresholds. This can then be combined with other data e.g. of recharge volumes using techniques such as the soil moisture water balance, water table fluctuation, chloride mass balance or isotopic techniques, or comparison with other vadose zone monitoring approaches such as co-location with Critical Zone Observatories.
We will also expand the emphasis in Section 4 to include the novelty of this approach. Namely (1) to provide data on the timing of recharge at the event timescale at sites where the source of the recharge water is known e.g. direct and focused recharge from precipitation and (2) determine the amount of precipitation needed to generate recharge at an event scale. We will include our statements provided above, that the network would complement and add value to other methods of recharge estimation and vadose zone monitoring, and that this would be suitable for applications globally (a comment made by RC2).
Citation: https://doi.org/10.5194/egusphere-2023-2053-AC3
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AC3: 'Reply on CC1', Andy Baker, 24 Jan 2024
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RC2: 'Comment on egusphere-2023-2053', Anonymous Referee #2, 09 Jan 2024
The paper, "An underground drip water monitoring network to characterize rainfall recharge of groundwater at different geologies, environments, and climates across Australia" by Baker et al., introduces a sensor network for monitoring groundwater recharge at a subregion of Australia. This network, the National Groundwater Recharge Observing System (NGROS), uses sensors in "underground spaces" to measure when and how groundwater recharge occurs. By combining these observations with rainfall data, the system is meant to support understanding about groundwater renewal rates.
Groundwater recharge is hard to measure and the new network intriduced here allows to some extent its quantification. For that reaosn I am convinced that it will be a valuable contribution for the readers of this journal after some minor revisions:
Figure 1: describe the dark brown layer in which the drip sensor are located.
L79: “The sites focus on fractured-rock lithologies;”. That means the drip sensors should be located at the intersects with the major fractures that transport the water downwards. How can this be ensured/tested?
L83-84: “At each site, between three and twelve sensors are deployed …” How to make sure the number is large enough to provide representative information?
Figure 3: the caption is really long. Could you at least provide a legend and explain the climate zones directly in the map?
L121 onwards: is there any information on the precision of the AWRA-L precipitation data (some RMSE or std)? Alternatively, are there some local stations at some of the sites to give an idea about the strengths/weaknesses of the product?
L137/2.1.1 to 2.1.14: The site summaries are written systematically and short. It’s still a bit tricky to understand which od them are similar or where they differ. Could you come up with a summary table?
In Fig 6, it seems that the drip sensor resolution is coarser than 1 drip/hour. Can you comment on the precision of these devices and or the data processing (would suit into 2.2)
Chapter 4 (Summary and Conclusions): The network is located within Australia so it makes sense highlighting its importance for Australian water research and education. However, similar networks could also be of great benefit for other regions where groundwater (and its recharge dynamics) are important. Could you add some words about why such networks would benefit other regions, too?
Citation: https://doi.org/10.5194/egusphere-2023-2053-RC2 -
AC1: 'Reply on RC2', Andy Baker, 24 Jan 2024
We thank the reviewer for their comments. We confirm that we will add to the Figure 1 caption to clarify that the dark brown layer represents an underground void (e.g. tunnel, cave or mine).
The drip sensors are located where water movement into the tunnel, mine or cave is identified (L82) and we agree that this is likely to relate to the overlying fracture network. Our existing text on L79 that states there is a focus on fractured-rock lithologies is misleading, and we thank the reviewer for alerting us to the fact. We propose that a better description to clarify that our focus is to monitor where there is observed water ingress in varied lithologies. This is likely due to the presence of fractures; however the precise nature of the overlying fracture network is unknown. Inferences might be possible from the drip hydrology time series obtained from individual loggers and through additional analyses such as lidar surveys (see related reviewer comment at https://doi.org/10.5194/egusphere-2023-2053-RC1). We propose to add some text at L79 to clarify this.
The number of sensors at each site necessary to identify recharge events is guided by our previous experience monitoring in caves and karst where we have successfully interpreted recharge data using nine loggers in one cave system (Baker et al 2021) and 14 loggers distributed across six caves in a regional analysis (Baker et al 2020). We will add further text to explain this at L84.
We agree that the Figure 3 caption is very long, and we will modify Figure 3 to shorten the caption as suggested.
Jones et al (2009) provide analysis of the quality of the gridded precipitation data available for Australia and report a mean absolute error (MAE) for daily precipitation of 1.2 mm for Australia as a whole, with highest uncertainties in the tropical north where rainfall extremes are highest and the monitoring network sparsest. This is outside of the NGROS monitoring region. The gridded precipitation product has the lowest error in the southern half of Australia, and we would anticipate the MAE to be lower for our sites. Where local stations are available, the gridded and observational data can be compared, noting that the local station is likely to be included in the gridding process.
Both reviewers have asked for an additional Summary Table for the sites, and we will include this in the revised manuscript.
We will clarify that the loggers used count drips over a user specified period that could range from seconds to days. We have chosen to count the number of drips over one hour, as this provides sufficient temporal resolution to identify recharge events and allows logger deployment for several years before the logger memory is full. Data output is in the form of a .csv or .xls files and data processing only involves data screening in the case that the logger is moved. Detailed analysis of logger precision is provided in Collister and Mattey (2009). We will add more detail about all of these aspects in section 2.2.
We agree that the Australian network could be replicated elsewhere in the world and that it could benefit any country where a greater understanding of the timing of groundwater recharge is of importance. We will add this to the summary and conclusions.
Citation: https://doi.org/10.5194/egusphere-2023-2053-AC1
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AC1: 'Reply on RC2', Andy Baker, 24 Jan 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2053', Anonymous Referee #1, 03 Oct 2023
General comment:
The paper presents the Australia’s National Groundwater Recharge Observing System (NGROS) which is the first dedicated sensor network for observing the recharge of groundwater at the event-scale across a wide range of geologies, environments, and climate types that represent a wide range of Australian hydroclimates.
Though simple the monitoring concept for NGROS is quite original as it provides data on the timing of recharge at the event timescale and allows estimating the amount of precipitation needed to generate recharge at an event scale. According to the authors, the NGROS observing system is deployed into specific sites to cover a range of geologies, environmental and climate types, to simply capture some evidence connecting these factors with the number of recharge events and the amount of precipitation needed to generate such events. Nevertheless, the acquisition system and the methodology adopted for the data analysis seems not suitable for a quantitative evaluation of the recharge events as this would ask for a deeper understanding of the hydrogeological features of every adopted monitoring site. The lack of a quantitative derivation based on the drip counting thus limited the data processing to the frequency domain.
Another drawback related to the presentation of the NGROS system is that the dataset recorded at the observation sites is not available despite the authors claimed its availability from a specified website.
In conclusion, the NGROS monitoring system though being based on the direct observation of groundwater recharge phenomena, does not provide systematic characterization of the hydrologic response of the fractured rocks to the rainfall input. Some examples of in-depth system characterization and for more robust hydrological analysis can be found in the recent literature published on HESS referring to some caves in Australia (e.g. Mahmud et al. 2016; Mahmud et al. 2018).
Specific comment:
Section 2.1: The site description is not homogeneous from one site to the other. The details concerning the geological settings should be standardized so that the cave dripping can be related to specific features of the site. The sub-sections in section 2.1 are hard to read given the large number of monitoring sites (14!). A summarizing table with all climatic, geological and landcover features far all sites will be useful for a better clarity.
Section 3: Similarly, the results section could be more clear to the reader through a summarizing table where the relationship between rainfall events and recharge response become more evident in all sites (and not only in the sub-set of sites reported in the Figures 4-6). Moreover, it seems that the comments regarding Figure 5 and 6 are not complete, compared to those regarding Figure 4 (lines 306-312).
The results section should deal with all monitoring sites, particularly given the unavailability of observation records.
Citation: https://doi.org/10.5194/egusphere-2023-2053-RC1 -
AC2: 'Reply on RC1', Andy Baker, 24 Jan 2024
We thank the reviewer for their review and comments on this pre-print. Our response is made in the context that the pre-print has been submitted to Geoscientific Instrumentation, Methods and Data Systems, where our understanding is that the journal aims and scope are on advances in concepts, design and description of instrumentation and data systems, and that the preprint, therefore, focuses on what we believe is an advance, using instrumentation situated in human-made and natural spaces in the vadose zone to quantify the timing of groundwater recharge events.
As stated on lines 74-75 of the pre-print, the monitoring concept for NGROS is to (1) provide data on the timing of recharge at the event timescale and (2) determine the amount of precipitation needed to generate recharge at an event scale. We agree with the reviewer that this concept focuses on the temporal aspects of groundwater recharge. We agree that the focus is on the frequency domain, and the approach precludes the determination of recharge volume or amount of recharge, which would require further analyses that are outside the scope of this pre-print. We propose that we add some new text to the manuscript that addresses the fact that the NGROS network does not address recharge volume. We agree that the approaches of Mahmud et al (2016, 2018) could be used by future research to generate recharge volume estimations at cave sites by combining the data produced by NGROS and techniques such as in-cave lidar. The methods of Mahmud et al (2016, 2018) would not work at the mine sites, as the approaches required the counting of stalactites to quantify the number of water flow pathways into the cave.
The groundwater.unsw.edu.au website provides access to the NGROS data. It went live in mid-October and unfortunately was not available at the time of review.
We agree that a summary table will be helpful given the large number of initial sites described in this pre-print. We will add this to Section 2.1, and at the same time check that everything is standardised between sub-sections.We appreciate the request to provide results from all 14 initial NGROS sites. We believe that level of data analysis and interpretation would be outside the scope of the Geoscientific Instrumentation, Methods and Data Systems (see https://www.geoscientific-instrumentation-methods-and-data-systems.net/about/aims_and_scope.html). We would like to note that the pre-print focuses on the initial fourteen sites and is intended to present the monitoring concept and research platform that is NGROS, including three examples illustrating the type of data collected. We expect to expand the number of sites over time as more partners join to collaborate with the project.
We checked whether the text relating to Figures 4, 5 and 6 was complete, and at this time would not propose to add any further text about these three examples.
Finally, we would like to take this opportunity to correct the description for Capricorn Caves (section 2.1.10) which incorrectly duplicates text from section 2.1.12. We apologise for that mistake. The correct text is:
“This natural cave site is in an isolated c. 50 m high limestone hill with 390M yr old Devonian reef limestone geology. It has a native dry rainforest vegetation cover. The local climate has a mean annual temperature of 23.4 °C, mean annual rainfall of 815 mm, and modelled pan evaporation of 2525 mm. The climate is on the boundary of Cfa (temperate, no dry season, hot summer) and tropical savanna climate classifications (Aw). Loggers have been placed in the lowest cave passages, closest to the groundwater. The site is privately owned and managed.”References
Mahmud, K., Mariethoz, G., Treble, P.C. and Baker, A., 2016. Terrestrial LiDAR survey and morphological analysis to identify infiltration properties in the Tamala Limestone, Western Australia. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 8, 4871-4881.Mahmud, K., Mariethoz, G., Baker, A. and Treble, P.C., 2018. Hydrological characterization of cave drip waters in a porous limestone: Golgotha Cave, Western Australia. Hydrology and Earth System Sciences, 22, 977-988
Citation: https://doi.org/10.5194/egusphere-2023-2053-AC2
-
AC2: 'Reply on RC1', Andy Baker, 24 Jan 2024
-
CC1: 'Comment on egusphere-2023-2053', Sarah Bourke, 20 Dec 2023
This manuscript presents a novel approach for understanding groundwater recharge using drip loggers in underground cavities. This manuscript seems to be a technical note summarizing the monitoring infrastructure, data analysis approach and preliminary data collected. It is evident from Section 4 that further data collection and interpretation is anticipated. This will make a worthwhile contribution to the literature as a description of a novel method for improving our understanding of groundwater recharge, which is vital as climates change and world population grows. It would be good if the authors can further clarify whether or not this approach can give quantitative estimates of recharge rates or volumes (as flagged by the referee), and if the maximum value of the data lies in combining the drips with other data from instrumentation at CZO sites. The aspirational statements in Section 4 are admirable, but seem somewhat out of place in what seems intended to be a relatively brief technical note. More discussion in this section of how this application of drip loggers extends their use from what has been done before, and how this new data source will add to our current literature-based understanding would be welcome.
Citation: https://doi.org/10.5194/egusphere-2023-2053-CC1 -
AC3: 'Reply on CC1', Andy Baker, 24 Jan 2024
Thank you very much for taking the time to make a community comment.
We confirm, as in our response to Reviewer Comment 1, that we will clarify that this methodology focuses on the temporal occurrence of recharge, and the approach precludes the direct determination of recharge volume or amount of recharge, which would require further analyses. This data generated is predominantly of the timing of recharge at the event timescale and the determination of rainfall recharge thresholds. This can then be combined with other data e.g. of recharge volumes using techniques such as the soil moisture water balance, water table fluctuation, chloride mass balance or isotopic techniques, or comparison with other vadose zone monitoring approaches such as co-location with Critical Zone Observatories.
We will also expand the emphasis in Section 4 to include the novelty of this approach. Namely (1) to provide data on the timing of recharge at the event timescale at sites where the source of the recharge water is known e.g. direct and focused recharge from precipitation and (2) determine the amount of precipitation needed to generate recharge at an event scale. We will include our statements provided above, that the network would complement and add value to other methods of recharge estimation and vadose zone monitoring, and that this would be suitable for applications globally (a comment made by RC2).
Citation: https://doi.org/10.5194/egusphere-2023-2053-AC3
-
AC3: 'Reply on CC1', Andy Baker, 24 Jan 2024
-
RC2: 'Comment on egusphere-2023-2053', Anonymous Referee #2, 09 Jan 2024
The paper, "An underground drip water monitoring network to characterize rainfall recharge of groundwater at different geologies, environments, and climates across Australia" by Baker et al., introduces a sensor network for monitoring groundwater recharge at a subregion of Australia. This network, the National Groundwater Recharge Observing System (NGROS), uses sensors in "underground spaces" to measure when and how groundwater recharge occurs. By combining these observations with rainfall data, the system is meant to support understanding about groundwater renewal rates.
Groundwater recharge is hard to measure and the new network intriduced here allows to some extent its quantification. For that reaosn I am convinced that it will be a valuable contribution for the readers of this journal after some minor revisions:
Figure 1: describe the dark brown layer in which the drip sensor are located.
L79: “The sites focus on fractured-rock lithologies;”. That means the drip sensors should be located at the intersects with the major fractures that transport the water downwards. How can this be ensured/tested?
L83-84: “At each site, between three and twelve sensors are deployed …” How to make sure the number is large enough to provide representative information?
Figure 3: the caption is really long. Could you at least provide a legend and explain the climate zones directly in the map?
L121 onwards: is there any information on the precision of the AWRA-L precipitation data (some RMSE or std)? Alternatively, are there some local stations at some of the sites to give an idea about the strengths/weaknesses of the product?
L137/2.1.1 to 2.1.14: The site summaries are written systematically and short. It’s still a bit tricky to understand which od them are similar or where they differ. Could you come up with a summary table?
In Fig 6, it seems that the drip sensor resolution is coarser than 1 drip/hour. Can you comment on the precision of these devices and or the data processing (would suit into 2.2)
Chapter 4 (Summary and Conclusions): The network is located within Australia so it makes sense highlighting its importance for Australian water research and education. However, similar networks could also be of great benefit for other regions where groundwater (and its recharge dynamics) are important. Could you add some words about why such networks would benefit other regions, too?
Citation: https://doi.org/10.5194/egusphere-2023-2053-RC2 -
AC1: 'Reply on RC2', Andy Baker, 24 Jan 2024
We thank the reviewer for their comments. We confirm that we will add to the Figure 1 caption to clarify that the dark brown layer represents an underground void (e.g. tunnel, cave or mine).
The drip sensors are located where water movement into the tunnel, mine or cave is identified (L82) and we agree that this is likely to relate to the overlying fracture network. Our existing text on L79 that states there is a focus on fractured-rock lithologies is misleading, and we thank the reviewer for alerting us to the fact. We propose that a better description to clarify that our focus is to monitor where there is observed water ingress in varied lithologies. This is likely due to the presence of fractures; however the precise nature of the overlying fracture network is unknown. Inferences might be possible from the drip hydrology time series obtained from individual loggers and through additional analyses such as lidar surveys (see related reviewer comment at https://doi.org/10.5194/egusphere-2023-2053-RC1). We propose to add some text at L79 to clarify this.
The number of sensors at each site necessary to identify recharge events is guided by our previous experience monitoring in caves and karst where we have successfully interpreted recharge data using nine loggers in one cave system (Baker et al 2021) and 14 loggers distributed across six caves in a regional analysis (Baker et al 2020). We will add further text to explain this at L84.
We agree that the Figure 3 caption is very long, and we will modify Figure 3 to shorten the caption as suggested.
Jones et al (2009) provide analysis of the quality of the gridded precipitation data available for Australia and report a mean absolute error (MAE) for daily precipitation of 1.2 mm for Australia as a whole, with highest uncertainties in the tropical north where rainfall extremes are highest and the monitoring network sparsest. This is outside of the NGROS monitoring region. The gridded precipitation product has the lowest error in the southern half of Australia, and we would anticipate the MAE to be lower for our sites. Where local stations are available, the gridded and observational data can be compared, noting that the local station is likely to be included in the gridding process.
Both reviewers have asked for an additional Summary Table for the sites, and we will include this in the revised manuscript.
We will clarify that the loggers used count drips over a user specified period that could range from seconds to days. We have chosen to count the number of drips over one hour, as this provides sufficient temporal resolution to identify recharge events and allows logger deployment for several years before the logger memory is full. Data output is in the form of a .csv or .xls files and data processing only involves data screening in the case that the logger is moved. Detailed analysis of logger precision is provided in Collister and Mattey (2009). We will add more detail about all of these aspects in section 2.2.
We agree that the Australian network could be replicated elsewhere in the world and that it could benefit any country where a greater understanding of the timing of groundwater recharge is of importance. We will add this to the summary and conclusions.
Citation: https://doi.org/10.5194/egusphere-2023-2053-AC1
-
AC1: 'Reply on RC2', Andy Baker, 24 Jan 2024
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