Articles | Volume 17, issue 11
https://doi.org/10.5194/essd-17-6113-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-6113-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A detailed streamflow and groundwater salinity dataset for Muttama Creek Catchment, NSW, Australia
R. Willem Vervoort
Sydney Institute of Agriculture, The University of Sydney, Sydney, NSW 2006, Australia
Floris F. van Ogtrop
CORRESPONDING AUTHOR
Sydney Institute of Agriculture, The University of Sydney, Sydney, NSW 2006, Australia
Mina Tambrchi
Sydney Institute of Agriculture, The University of Sydney, Sydney, NSW 2006, Australia
Farzina Akter
Sydney Institute of Agriculture, The University of Sydney, Sydney, NSW 2006, Australia
Alexander J. V. Buzacott
Sydney Institute of Agriculture, The University of Sydney, Sydney, NSW 2006, Australia
Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki, Finland
Jason S. Lessels
Sydney Institute of Agriculture, The University of Sydney, Sydney, NSW 2006, Australia
James P. Moloney
Sydney Institute of Agriculture, The University of Sydney, Sydney, NSW 2006, Australia
Dipangkar Kundu
Sydney Institute of Agriculture, The University of Sydney, Sydney, NSW 2006, Australia
Feike A. Dijkstra
Sydney Institute of Agriculture, The University of Sydney, Sydney, NSW 2006, Australia
Thomas F. A. Bishop
Sydney Institute of Agriculture, The University of Sydney, Sydney, NSW 2006, Australia
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Cited articles
Akter, F., Bishop, T. F. A., and Vervoort, R. W.: Space-time modelling of groundwater level and salinity, Science of the Total Environment, 776, 145865, https://doi.org/10.1016/j.scitotenv.2021.145865, 2021. a
Breuer, L., Hiery, N., Kraft, P., Bach, M., Aubert, A. H., and Frede, H.-G.: HydroCrowd: a citizen science snapshot to assess the spatial control of nitrogen solutes in surface waters, Scientific Reports, 5, 16503, https://doi.org/10.1038/srep16503, 2015. a
Canedo-Arguelles, M., Hawkins, C. P., Kefford, B. J., Schäfer, R. B., Dyack, B. J., Brucet, S., Buchwalter, D., Dunlop, J., Frör, O., Lazorchak, J., Coring, E., Fernandez, H. R., Goodfellow, W., Achem, A. L. G., Hatfield-Dodds, S., Karimov, B. K., Mensah, P., Olson, J. R., Piscart, C., Prat, N., Ponsá, S., Schulz, C.-J., and Timpano, A. J.: Saving freshwater from salts, Science, 351, 914–916, https://doi.org/10.1126/science.aad3488, 2016. a, b
Cartwright, I., Weaver, T. R., Simmons, C. T., Fifield, L. K., Lawrence, C. R., Chisari, R., and Varley, S.: Physical hydrogeology and environmental isotopes to constrain the age, origins, and stability of a low-salinity groundwater lens formed by periodic river recharge: Murray Basin, Australia, Journal of Hydrology, 380, 203–221, https://doi.org/10.1016/j.jhydrol.2009.11.001, 2010. a, b
Conyers, M. K., Hume, I., Summerell, G., Slinger, D., Mitchell, M., and Cawley, R.: The ionic composition of the streams of the mid-Murrumbidgee River: Implications for the management of downstream salinity, Agricultural Water Management, 95, 598–606, https://doi.org/10.1016/j.agwat.2008.01.007, 2008. a, b, c, d, e, f
Crosbie, R. S., Hughes, J. D., Friend, J., and Baldwin, B. J.: Monitoring the hydrological impact of land use change in a small agricultural catchment affected by dryland salinity in central NSW, Australia, Agricultural Water Management, 88, 43–53, https://doi.org/10.1016/j.agwat.2006.08.009, 2007. a, b, c
Dahlhaus, P., Evans, T., Nathan, E., Cox, J., and Simmons, C.: Groundwater-level response to land-use change and the implications for salinity management in the West Moorabool River catchment, Victoria, Australia, Hydrogeology Journal, https://doi.org/10.1007/s10040-010-0616-y, 2010. a, b
Deb, P., Kiem, A. S., and Willgoose, G.: Mechanisms influencing non-stationarity in rainfall-runoff relationships in southeast Australia, Journal of Hydrology, 571, 749–764, https://doi.org/10.1016/j.jhydrol.2019.02.025, 2019. a
Department of Environment and Climate Change NSW: Salinity Audit Upland catchments of the New South Wales Murray–Darling Basin, Report, Department of Environment and Climate Change NSW, 2009. a
Finlayson, J., Bathgate, A., Nordblom, T., Theiveyanathan, T., Farquharson, B., Crosbie, R., Mitchell, D., and Hoque, Z.: Balancing land use to manage river volume and salinity: Economic and hydrological consequences for the Little River catchment in Central West, New South Wales, Australia, Agricultural Systems, 103, 161–170, https://doi.org/10.1016/j.agsy.2009.12.003, 2010. a
Grayson, R. B., Gippel, C. J., Finlayson, B. L., and Hart, B. T.: Catchment-wide impacts on water quality: the use of 'snapshot' sampling during stable flow, Journal of Hydrology, 199, 121–134, https://doi.org/10.1016/S0022-1694(96)03275-1, 1997. a
Hughes, J. D., Crosbie, R. S., and van de Ven, R. J.: Salt mobilisation processes from a salinised catchment featuring a perennial stream, Journal of Hydrology, 362, 308–319, https://doi.org/10.1016/j.jhydrol.2008.09.001, 2008. a
Jolly, I., Williamson, D. R., Gilfedder, M., Walker, G., Morton, R., Robinson, G. H., Jones, H., Zhang, L., Dowling, T., Dyce, P., Nathan, R., Nandakumar, N., Clarke, R., and McNeill, V.: Historical stream salinity trends and catchment salt balances in the Murray-Darling Basin, Australia, Marine and Freshwater Research, 52, 53–63, 2001. a, b, c, d
Leblanc, M., Tweed, S., Van Dijk, A., and Timbal, B.: A review of historic and future hydrological changes in the Murray-Darling Basin, Global and Planetary Change, 80–81, 226–246, https://doi.org/10.1016/j.gloplacha.2011.10.012, 2012. a
Lessels, J. S. and Bishop, T. F. A.: A post-event stratified random sampling scheme for monitoring event-based water quality using an automatic sampler, Journal of Hydrology, 580, 123393, https://doi.org/10.1016/j.jhydrol.2018.12.063, 2020. a
Lintern, A., Webb, J. A., Ryu, D., Liu, S., Waters, D., Leahy, P., Bende-Michl, U., and Western, A. W.: What Are the Key Catchment Characteristics Affecting Spatial Differences in Riverine Water Quality?, Water Resources Research, 54, 7252–7272, https://doi.org/10.1029/2017wr022172, 2018. a, b
Lyon, S. W., Seibert, J., Lembo, A. J., Steenhuis, T. S., and Walter, M. T.: Incorporating landscape characteristics in a distance metric for interpolating between observations of stream water chemistry, Hydrol. Earth Syst. Sci., 12, 1229–1239, https://doi.org/10.5194/hess-12-1229-2008, 2008. a
McFarlane, D. J., George, R. J., Barrett-Lennard, E. G., and Gilfedder, M.: Salinity in Dryland Agricultural Systems: Challenges and Opportunities, Springer International Publishing, Cham, https://doi.org/10.1007/978-3-319-47928-6_19, pp. 521–547, 2016. a, b
R Core Team: R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (last access: 11 November 2025), 2023. a
Scanlon, B. R., Jolly, I., Sophocleous, M., and Zhang, L.: Global impacts of conversions from natural to agricultural ecosystems on water resources: Quantity versus quality, Water Resources Research, 43, W03437, https://doi.org/10.1029/2006wr005486, 2007. a
Stavi, I., Thevs, N., and Priori, S.: Soil Salinity and Sodicity in Drylands: A Review of Causes, Effects, Monitoring, and Restoration Measures, Frontiers in Environmental Science, 9, https://doi.org/10.3389/fenvs.2021.712831, 2021. a, b
van Dijk, A. I. J. M., Gilfedder, M., and Austin, J.: Influences of climate, terrain and land cover on stream salinity in southeastern Australia, and implications for management through reforestation, Hydrological Processes, 22, 3275–3284, https://doi.org/10.1002/hyp.6968, 2008. a
Vervoort, R., van Ogtrop, F., Tambrchi, M., Akter, F., Buzacott, A., Lessels, J., Moloney, J., Kundu, D., Dijkstra, F., and Bishop, T.: A detailed streamflow and groundwater salinity dataset for Muttama Creek Catchment, NSW, Australia, Sydney eScholarship Repository [data set], https://doi.org/10.25910/m0wp-8890, 2025. a, b, c
Walker, G., Zhang, L., Ellis, T., Hatton, T., and Peterham, C.: Estimating impacts of changed landuse on recharge: review of modelling and other approaches appropriate for management of dryland salinity, Hydrogeology Journal, 10, 68–90, 2002. a
Webb, L.: Hydrogeology Report for the Muttama Catchment, Report, NSW Department of Land and Water Conservation, 1999. a
White, I., Macdonald, B. C. T., Somerville, P. D., and Wasson, R.: Evaluation of salt sources and loads in the upland areas of the Murray–Darling Basin, Australia, Hydrological Processes, 23, 2485–2495, https://doi.org/10.1002/hyp.7355, 2009. a, b, c, d
Short summary
A detailed water quality dataset for a 1000 km2 catchment in New South Wales, Australia is presented. The water quality data for surface and groundwater was collected over 14 years and contains more than 1000 records. Despite missing values and different sampling methods and groups, the data provides a consistent overview of the hydrogeochemistry of the catchment. This dataset is valuable for global modelling studies as well as better understanding of local dryland salinity and water quality processes.
A detailed water quality dataset for a 1000 km2 catchment in New South Wales, Australia is...
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