the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 01 Apr 2025
A detailed streamflow and groundwater salinity dataset for Muttama Creek Catchment, NSW, Australia
Abstract. Dryland salinity remains a major global natural resource management concern, and which is amplified in Australia. However, limited detailed space-time data sets with observations of stream and groundwater salinity has constrained a deep understanding of the range of processes that can lead to dryland salinity problems in landscapes. The aim of this study is to report on the open dataset resulting from a 14-year data collection effort in a subcatchment of the Murrumbidgee catchment in New South Wales, Australia. Over a 14-year period a series of different sampling campaigns has resulted in a large dataset with hydrogeochemical data which includes both in-situ (field) data and post laboratory analysis of major anions and cations. This data is augmented with observed groundwater levels and publicly available streamflow and climate data. The data set covers 23 groundwater sample sites and 39 surface water sites. Because the data was collected by four distinct groups and over many years, we analyse to see if this has caused a bias in the dataset. In addition, we show the major spatial and temporal trends to provide an overview of the dataset. The dataset is made open access to encourage further research and the current paper shows the richness of the collected data and opportunities for further research.
- Preprint
(4065 KB) - Metadata XML
-
Supplement
(312 KB) - BibTeX
- EndNote
Status: open (until 19 Jul 2025)
-
RC1: 'Comment on essd-2025-105', Justin Hughes, 13 Jun 2025
reply
I am pleased to see such a data set being made public. As the authors state, at many of the experimental catchments involving salinity and hydrology, data have not been made public, for various reasons. I do note that while there are many standard methods available for surface water gauging and groundwater sampling, nothing appears available regarding the conjunctive use of manual and logger based groundwater depth measurements, particularly correction, so this paper, while using reasonably common methods, does document these which is pleasing. On a minor technical point, bicarbonate in surface water sourced from groundwater, particularly in the concentrations common in that part of the world, tends to 'gas off' in equilibrium to the atmosphere quite quickly and therefore making bicarbonate concentrations a little more difficult to interpret.Â
-
RC2: 'Comment on essd-2025-105', Anonymous Referee #2, 14 Jun 2025
reply
This study presents a comprehensive dataset for a catchment with significant ground salinity issue. This data contains long term observation of water flow, ground water and salinity levels, which is very useful for further research. Therefore, I recommend a major revision of the manuscript before it can be accepted for publication.
General comments:
There are so many figures in the main-text. Some of the figures need to be moved to supplementary information.
The authors need to state something about the representativeness of the watershed in the discussion. Otherwise, this is a local dataset. Can you write something about how this dataset can be useful for the study for other regions of the world with similarity in hydrological or geological conditions.
Line-to-line comments:
Figure 4 are not very important; can you move it to supplementary information. I think you only need to present the figures relate to the results.
Figure 5 and 6 can be put together.
Page 8: can you move the Pseudo code to supplementary information
Can you compile figure 10 and 12 together? Also, for Figure 11 and 13.
Â
Line 240: can you compare the items in other national datasets?
Citation: https://doi.org/10.5194/essd-2025-105-RC2 -
RC3: 'Comment on essd-2025-105', Anonymous Referee #3, 22 Jun 2025
reply
General Comments
This article offers a brief yet intriguing description of a hydrogeochemical dataset. This dataset comprises 1,160 water samples gathered over a span of 14 years at 62 different sites. Both the dataset and this article hold important value for the community interested in dryland and irrigation salinity. Nevertheless, the article may require substantial revisions prior to publication.
My primary concern lies in the further value of this dataset, considering that the data were collected through inconsistent methods. The authors do provide a comprehensive description of the dataset regarding its collection process, quality, and known and unknown biases. However, the potential of the data set for further use is not adequately emphasized. A concrete example of this critique is Section 3.3. In this section, Table 2 and Figures 8 - 13 present some instances of what this dataset can reveal, but the analysis is rather weak. If six figures and one table only warrant two general paragraphs of explanation, then the necessity of presenting these items might be called into question. Moreover, Figures 10 and 11 are not mentioned at all throughout the article, and Figures 7, 8, and 9 are in different sections from their corresponding references/explanations, indicating that the organization of the content needs considerable improvement.
For a data - description paper, it is preferable to offer readers information beyond just the appearance of the dataset. More importantly, it should inspire others regarding its greater potential. Specific scientific questions that the dataset can contribute to may be helpful.
Details
Line 98 mentions "62 sample locations," which does not align with the sites marked and numbered in Figure 2. Additionally, as the authors have clarified that "not all sites were sampled at all times," I suggest incorporating an extra color bar in Figure 2 for location markers to denote the specific number of samples through different colors. In this case, the previous "GW/SW" color bar could be removed, and the information it conveys could instead be represented by varying shapes of the location markers. Regarding the caption of Figure 2, the mention of "Brown/Orange" seems inaccurate. Isn't the color for "GW" coral red?
Line 109 – 112: The description of Table 1 as well as Table 1 itself is not very clear. Readers cannot tell from Table 1 which locations consist of 6/5/4… variables or at least the numbers of locations that include specific numbers of variables.
L119-L120: The exact instrument information with the data is crucial for others to do research based on data sets not collected by themselves. Could the authors make more effort to supplement the instruments and their configuration information?
L146: ‘pseudocode below’, The comparison operator in the conditional statement of the pseudocode is missing.
L151: ‘due to the a lack of…’
Figures
Some captions of tables/figures, have a comma at the end while others do not, please unify them.
Figure 4: This figure is poorly presented. I cannot distinguish thicker lines from these sparse, thin lines.
Figure 6: Why not use the same visualization method as Figure 5? (with intervals between adjacent bars)
Citation: https://doi.org/10.5194/essd-2025-105-RC3
Data sets
A detailed streamflow and groundwater salinity dataset for Muttama Creek Catchment, NSW, Australia Rutger Willem Vervoort et al. https://doi.org/10.25910/m0wp-8890
Muttama Creek Catchment Groundwater data R. Willem Vervoort and Farzina Akter https://doi.org/10.17605/OSF.IO/BEUWK
Model code and software
MuttamaDataPaper Rutger Willem Vervoort et al. https://github.com/WillemVervoort/MuttamaDataPaper
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 283 | 59 | 17 | 359 | 19 | 14 | 16 |
- HTML: 283
- PDF: 59
- XML: 17
- Total: 359
- Supplement: 19
- BibTeX: 14
- EndNote: 16
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1