Monitoring changes in soil salinity and sodicity to depth, at a decadal scale, in a semiarid irrigated region of Australia
Patrick Filippi
A C , Stephen R. Cattle A , Thomas F. A. Bishop A , Matthew J. Pringle B and Edward J. Jones A
+ Author Affiliations
- Author Affiliations
A The University of Sydney, School of Life and Environmental Sciences, Sydney Institute of Agriculture, Sydney, New South Wales, Australia.
B Department of Science, Information Technology and Innovation, Queensland Government, Australia.
C Corresponding author. Email: patrick.filippi@sydney.edu.au
Soil Research 56(7) 696-711 https://doi.org/10.1071/SR18083
Submitted: 26 March 2018 Accepted: 31 July 2018 Published: 2 October 2018
Abstract
Soil salinity and sodicity are two of the most limiting constraints for agriculture in arid and semiarid landscapes, but long-term studies are scarce, and most solely focus on the topsoil. This study monitors the change in soil electrical conductivity (EC) and exchangeable sodium percentage (ESP) to 1.2 m depth with bivariate linear mixed models between 2002 and 2015 in a semiarid, irrigated cotton-growing region of south-west New South Wales, Australia. In this work, the impacts of shifts in rainfall, variability of irrigation water quantity and quality, and agricultural land uses, on soil salinity and sodicity are analysed. The study area possessed generally low levels of soil salinity, and shifts in EC were detected over time, but only isolated areas of the various sampling depths experienced statistically significant changes in EC. Some areas under irrigated cotton production experienced a desalination trend, whereas soil EC under irrigated perennial horticulture increased over time. This increase was attributed to the use of fertilisers that contain salts, and the varying quantity and quality of applied irrigation water. Sodicity was low to moderate in the upper 0.5 m of the soil profile but high in deeper layers, with a trend of increasing soil sodicity through time. Most of the statistically significant increases in ESP occurred in areas under irrigated cotton and horticulture, with this likely due to the continued addition of sodium to the soil system. This study also demonstrates that visible near infrared spectroscopy can be used in to predict soil ESP values to reasonable accuracy.
Additional keywords: digital soil monitoring, irrigation, salinity, sodicity, soil change, subsoil.
References
Bishop TFA, McBratney AB, Laslett GM (1999) Modelling soil attribute depth functions with equal-area quadratic smoothing splines. Geoderma 91, 27–45.| Modelling soil attribute depth functions with equal-area quadratic smoothing splines.Crossref | GoogleScholarGoogle Scholar |
Bureau of Meteorology (BOM) (2017) Monthly rainfall – Hillston airport. Available from: <http://www.bom.gov.au/jsp/ncc/cdio/weatherData/av?p_nccObsCode=139&p_display_type=dataFile&p_startYear=&p_c=&p_stn_num=075032> [25 April 2017]
Cattle SR, Field DJ (2013) A review of the soil science research legacy of the triumvirate of cotton CRC. Crop & Pasture Science 64, 1076–1094.
Cetin M, Kirda C (2003) Spatial and temporal changes of soil salinity in a cotton field irrigated with low-quality water. Journal of Hydrology 272, 238–249.
| Spatial and temporal changes of soil salinity in a cotton field irrigated with low-quality water.Crossref | GoogleScholarGoogle Scholar |
Corwin DL, Kaffka SR, Hopmans JW, Mori Y, van Groenigen JW, van Kessel C, Lesch SM, Oster JD (2003) Assessment and field-scale mapping of soil quality properties of a saline-sodic soil. Geoderma 114, 231–259.
| Assessment and field-scale mapping of soil quality properties of a saline-sodic soil.Crossref | GoogleScholarGoogle Scholar |
Darwish T, Atallah T, El Moujabber M, Khatib N (2005) Salinity evolution and crop response to secondary soil salinity in two agro-climatic zones in Lebanon. Agricultural Water Management 78, 152–164.
| Salinity evolution and crop response to secondary soil salinity in two agro-climatic zones in Lebanon.Crossref | GoogleScholarGoogle Scholar |
Filippi P, Minasny B, Cattle SR, Bishop TFA (2016) Monitoring and modeling soil change: the influence of human activity and climatic shifts on aspects of soil spatiotemporally. Advances in Agronomy 139, 153–214.
| Monitoring and modeling soil change: the influence of human activity and climatic shifts on aspects of soil spatiotemporally.Crossref | GoogleScholarGoogle Scholar |
Filippi P, Cattle SR, Bishop TFA, Odeh IOA, Pringle MJ (2018) Digital soil monitoring of top- and sub-soil pH with bivariate linear mixed models. Geoderma 322, 149–162.
| Digital soil monitoring of top- and sub-soil pH with bivariate linear mixed models.Crossref | GoogleScholarGoogle Scholar |
Ford G, Martin J, Rengasamy P, Boucher S, Ellington A (1993) Soil sodicity in Victoria. Soil Research 31, 869–909.
| Soil sodicity in Victoria.Crossref | GoogleScholarGoogle Scholar |
Hatton TJ, Ruprecht J, George RJ (2003) Preclearing hydrology of the Western Australia wheatbelt: target for the future. Plant and Soil 257, 341–356.
| Preclearing hydrology of the Western Australia wheatbelt: target for the future.Crossref | GoogleScholarGoogle Scholar |
Hazelton P, Murphy B (2007) ‘Interpreting soil test results - What do all the numbers mean?’ (CSIRO Publishing: Collingwood, Australia)
Herrero J, Pérez-Coveta O (2005) Soil salinity changes over 24 years in a Mediterranean irrigated district. Geoderma 125, 287–308.
| Soil salinity changes over 24 years in a Mediterranean irrigated district.Crossref | GoogleScholarGoogle Scholar |
Holland J, Eastwood C (2014) An evaluation of the current understanding of cotton-growing soils and soil management practice issues in Southern NSW. NSW Department of Primary Industries. Available at <http://www.insidecotton.com/xmlui/bitstream/handle/1/4259/DAN1408%20Final%20Report.pdf?sequence=1&isAllowed=y> [Verified 13 March 2018]
Hulugalle NR, Entwistle PC, Weaver TB, Scott F, Finlay LA (2002) Cotton-based rotation systems on a sodic Vertosol under irrigation: effects on soil quality and profitability. Australian Journal of Experimental Agriculture 42, 341–349.
Hulugalle NR, Weaver TB, Finlay LA (2013) Soil water storage, drainage, and leaching in four irrigated cotton-based cropping systems sown in a Vertosol with subsoil sodicity. Soil Research 50, 652–663.
| Soil water storage, drainage, and leaching in four irrigated cotton-based cropping systems sown in a Vertosol with subsoil sodicity.Crossref | GoogleScholarGoogle Scholar |
Isbell RF, National Committee on Soil and Terrain (NCST) (2016) ‘The Australian Soil Classification’, 2nd edn. (CSIRO Publishing: Melbourne)
Jalali M, Merikhpour H, Kaledhonkar MJ, Van Der Zee SEATM (2008) 95, 143–153.
Lark RM (2000) A comparison of some robust estimators of the variogram for use in soil survey. European Journal of Soil Science 51, 137–157.
| A comparison of some robust estimators of the variogram for use in soil survey.Crossref | GoogleScholarGoogle Scholar |
Lark RM (2009) Estimating the regional mean status and change of soil properties: two distinct objectives for soil survey. European Journal of Soil Science 60, 748–756.
| Estimating the regional mean status and change of soil properties: two distinct objectives for soil survey.Crossref | GoogleScholarGoogle Scholar |
Lark RM, Papritz A (2003) Fitting a linear model of coregionalization for soil properties using simulated annealing. Geoderma 115, 245–260.
| Fitting a linear model of coregionalization for soil properties using simulated annealing.Crossref | GoogleScholarGoogle Scholar |
Lin LIK (1989) A concordance correlation coefficient to evaluate reproducibility. Biometrics 45, 255–268.
| A concordance correlation coefficient to evaluate reproducibility.Crossref | GoogleScholarGoogle Scholar |
Marchant BP, Lark RM (2007) Estimation of linear models of coregionalization by residual maximum likelihood. European Journal of Soil Science 58, 1506–1513.
| Estimation of linear models of coregionalization by residual maximum likelihood.Crossref | GoogleScholarGoogle Scholar |
McKenzie D, Orange PLM (2003) Salinity and sodicity – what’s the difference. The Australian Cottongrower 24, 28
McNeal BL (1968) Prediction of the effect of mixed-salt solutions on soil hydraulic conductivity. Soil Science Society of America Journal 32, 190–193.
| Prediction of the effect of mixed-salt solutions on soil hydraulic conductivity.Crossref | GoogleScholarGoogle Scholar |
Melland A, Biggs A, Silburn M, Shaw R (2016) Changes in soil salinity, sodicity and nitrate under irrigated cotton. The Australian Cottongrower 37, 26–31.
Minasny B, McBratney AB (2006) A conditioned Latin hypercube method for sampling in the presence of ancillary information. Computers & Geosciences 32, 1378–1388.
| A conditioned Latin hypercube method for sampling in the presence of ancillary information.Crossref | GoogleScholarGoogle Scholar |
Mora JL, Herrero J, Weindorf DC (2017) Multivariate analysis of soil salination-desalination in a semi-arid irrigated district of Spain. Geoderma 291, 1–10.
| Multivariate analysis of soil salination-desalination in a semi-arid irrigated district of Spain.Crossref | GoogleScholarGoogle Scholar |
Northcote KH, Skene JKM (1972) Australian soils with saline and sodic properties. CSIRO Soil Publication No. 27, CSIRO Division of Soils, Melbourne, Victoria.
O’Rourke SM, Stockmann U, Holden NM, McBratney AB, Minasny B (2016) An assessment of model averaging to improve predictive power of portable vis-NIR and XRF for the determination of agronomic soil properties. Geoderma 279, 31–44.
| An assessment of model averaging to improve predictive power of portable vis-NIR and XRF for the determination of agronomic soil properties.Crossref | GoogleScholarGoogle Scholar |
Office of Environment and Heritage (OEH) (2017) NSW Landuse 2007. NSW Government, Australia. Available at https://datasets.seed.nsw.gov.au/dataset/nsw-landuseac11c [verified 20 Septemer 2018].
Orton TG, Pringle MJ, Page KL, Dalal RC, Bishop TFA (2014) Spatial prediction of soil organic carbon stock using a linear model of coregionalisation. Geoderma 230–231, 119–130.
| Spatial prediction of soil organic carbon stock using a linear model of coregionalisation.Crossref | GoogleScholarGoogle Scholar |
Orton TG, Mallawaarchchi T, Pringle MJ, Menzies NW, Dalal RC, Kopittke PM, Searle R, Hochman Z, Dang YP (2018) Quantifying the economic impact of soil constraints on Australian agriculture: a case study of wheat. Land Degradation & Development
| Quantifying the economic impact of soil constraints on Australian agriculture: a case study of wheat.Crossref | GoogleScholarGoogle Scholar |
Papritz A, Flühler H (1994) Temporal change of spatially autocorrelated soil properties: optimal estimation by cokriging. Geoderma 62, 29–43.
| Temporal change of spatially autocorrelated soil properties: optimal estimation by cokriging.Crossref | GoogleScholarGoogle Scholar |
Quinlan JR (1986) Induction of decision trees. Machine Learning 1, 81–106.
| Induction of decision trees.Crossref | GoogleScholarGoogle Scholar |
R Development Core Team (2017) ‘R: A language and environment for statistical computing, R version 3.2.1.’ (R Foundation for Statistical Computing: Vienna)
Rayment GE, Lyons DJ (2011). ‘Soil chemical methods: Australasia, 3.’ (CSIRO Publishing: Collingwood, Vic.)
Rengasamy P (2006) World salinization with emphasis on Australia. Journal of Experimental Botany 57, 1017–1023.
| World salinization with emphasis on Australia.Crossref | GoogleScholarGoogle Scholar |
Rengasamy P, Olsson K (1991) Sodicity and soil structure. Soil Research 29, 935–952.
| Sodicity and soil structure.Crossref | GoogleScholarGoogle Scholar |
Rengasamy P, Walters L, Cresswell H, Abbott T, Lynch B, Shaw R, Churchman J, Doyle RB, Olsson K, Cochrane H (1994) Introduction to soil sodicity. Technical Report. CRC for Soil and Land Management, Adelaide, Australia.
Rosenzweig B (2012) Crop nutrition: it’s not just NPK. All about Almonds Fact Sheet. Almond Board of Australia, Berri, South Australia.
Roth G (2014) Australian grown cotton sustainability report. Cotton Research and Development Corporation and Cotton Australia. Available at https://www.crdc.com.au/publications/australian-grown-cotton-sustainability-report [verified 13 March 2018].
Shahid SA (2013) Developments in soil salinity assessment, modeling, mapping, and monitoring from regional to submicroscopic scales. In ‘Developments in soil salinity assessment and reclamation: innovative thinking and use of marginal soil and water resources in irrigated agriculture.’ (Eds SA Shahid, MA Abdelfattah, FK Taha) pp. 3–43. (Springer Netherlands: Dordrecht)
Shainberg I, Rhoades JD, Prather RJ (1981) Effect of low electrolyte concentration on clay dispersion and hydraulic conductivity of a sodic soil. Soil Science Society of America Journal 45, 273–277.
| Effect of low electrolyte concentration on clay dispersion and hydraulic conductivity of a sodic soil.Crossref | GoogleScholarGoogle Scholar |
Shirokova Y, Forkutsa I, Sharafutdinova N (2000) Use of electrical conductivity instead of soluble salts for soil salinity monitoring in Central Asia. Irrigation and Drainage Systems 14, 199–206.
| Use of electrical conductivity instead of soluble salts for soil salinity monitoring in Central Asia.Crossref | GoogleScholarGoogle Scholar |
Speirs SD, Cattle SR, Melville GJ (2011) Impact of sodium adsorption ratio of irrigation water on the structural form of two Vertosols used for cotton production. Soil Research 49, 481–493.
| Impact of sodium adsorption ratio of irrigation water on the structural form of two Vertosols used for cotton production.Crossref | GoogleScholarGoogle Scholar |
Stenberg B, Viscarra Rossel RA, Mouazen AM, Wetterlind J (2010) Chapter Five - Visible and near infrared spectroscopy in soil science. Advances in Agronomy 107, 163–215.
| Chapter Five - Visible and near infrared spectroscopy in soil science.Crossref | GoogleScholarGoogle Scholar |
Sumner ME (1993) Sodic soils: new perspectives. Australian Journal of Soil Research 31, 683–750.
| Sodic soils: new perspectives.Crossref | GoogleScholarGoogle Scholar |
Viscarra Rossel RA, Walvoort DJJ, McBratney AB, Janik LJ, Skjemstad JO (2006) Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties. Geoderma 131, 59–75.
| Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties.Crossref | GoogleScholarGoogle Scholar |
Viscarra Rossel RA, Cattle SR, Ortega A, Fouad Y (2009) In situ measurements of soil colour, mineral composition and clay content by vis–NIR spectroscopy. Geoderma 150, 253–266.
| In situ measurements of soil colour, mineral composition and clay content by vis–NIR spectroscopy.Crossref | GoogleScholarGoogle Scholar |
Water NSW (2017) ‘Lachlan River at Hillston Weir (Site 412039) – Daily electrical conductivity data (2002 to 2015).’ (NSW Government, Australia)
Zornoza R, Guerrero C, Mataix-Solera J, Scow KM, Arcenegui V, Mataix-Beneyto J (2008) Near infrared spectroscopy for determination of various physical, chemical and biochemical properties in Mediterranean soils. Soil Biology & Biochemistry 40, 1923–1930.
| Near infrared spectroscopy for determination of various physical, chemical and biochemical properties in Mediterranean soils.Crossref | GoogleScholarGoogle Scholar |
