2-Dimensional soil and vadose-zone representation using an EM38 and EM34 and a laterally constrained inversion model
J. Triantafilis A C and F. A. Monteiro Santos BA School of Biological, Earth and Environmental Sciences, The University of New South Wales, NSW 2006, Australia.
B Universidade de Lisboa, Instituto Don Luís Laboratório Associado, C8, 1749-016 Lisboa, Portugal.
C Corresponding author. Email: j.triantafilis@unsw.edu.au
Australian Journal of Soil Research 47(8) 809-820 https://doi.org/10.1071/SR09013
Submitted: 13 January 2009 Accepted: 17 August 2009 Published: 11 December 2009
Abstract
The network of prior streams and palaeochannels common across the Riverine Plains of the Murray–Darling Basin act as conduits for the redistribution of water and soluble salts beneath the root-zone. To improve scientific understanding of these hydrological processes there is the need to better represent and map the connectivity and spatial extent of these physiographic and stratigraphic features. Groundbased electromagnetic (EM) instruments, which measure bulk soil electrical conductivity (σa), have been used widely to map their areal distribution across the landscape. However, methods to resolve their location with depth have rarely been attempted. In this paper we employ a 1-D inversion algorithm with 2-D smoothness constraints to predict the true electrical conductivity (σ) at discrete depth increments using EM data. The EM data we use include the root-zone measuring EM38 and the deeper sensing EM34. We collected EM38 data in the vertical (EM38v) and horizontal (EM38h) dipole modes and EM34 data in the horizontal mode and coil spacing of 10, 20, and 40 m (respectively, EM34-10, EM34-20, and EM34-40). In order to compare and contrast the value of the various EM data we carried out multiple inversions using different combinations, which include: independent inversions of (i) EM38 (root-zone) and (ii) EM34 data (vadose-zone), and in combination using (iii) EM38v, EM38h, and EM34-10 (near-surface), and (iv) all 5 EM datasets (regolith) available. The general patterns of σ are shown to compare favourably with the known pedoderms, physiographic, and stratigraphic features and soil particle size fractions collected from calibration cores drilled across the lower Macquarie Valley study area. In general we find that the EM38 assists in resolving root-zone variability, specifically duplex soil profiles and physiographic features such as prior streams, while the use of the EM34 assists in resolving the stratigraphic nature of the vadose-zone and specifically the likely location of palaeochannels and subsurface anomalies that may indicate the location of good quality groundwater and/or clay aquitards. In this case, our potential to use σ to predict clay content is limited by the non-linearity of the cumulative functions. In order to improve on the non-linearity of our inversion we need to develop a full solution of the forward problem.
Additional keywords: EM38, EM34, clay content, prior stream channel, palaeochannel, EM inversion.
Acknowledgments
The Australian Federal Governments Australian Cotton Research and Development Corporation in association with the Australian Cotton Cooperative Research Centre (CRC-11C) provided funding for the collection of the EM34 and EM38 surveys, soil sampling, and laboratory analysis. Additional funds were obtained from the Natural Heritage Trust (NHT-CW0369.99). We thank the landholders who allowed access to their farms; in particular, Mr Mal Carpenter (General Manager, Agriland Pty Ltd). We acknowledge Mr Michael Short, Mathew McRrae, Andrew Huckel, Esta Kokkoris, and Dr Ranjith Subasinghe who carried out the EM survey and Esta Kokkoris and Dr Ranjith Subasinghe for determination of the particle size fractions. F. A. Monteiro Santos acknowledges the financial support of Fundação para a Ciência e Tecnologia (Grant: SFRH/BSAB/902/2009).
Buchanan SM, Triantafilis J
(2009) Mapping water table depth using geophysical and environmental variables. Ground Water 47, 80–96.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
PubMed |
Butler BE
(1950) A theory of prior streams as a causal factor of soil occurrence in the Riverine Plain of south-eastern Australia. Australian Journal of Agricultural Research 1, 231–252.
| Crossref | GoogleScholarGoogle Scholar |
Cook PG, Walker GR
(1992) Depth profiles of electrical conductivity from linear combinations of electromagnetic induction measurements. Soil Science Society of America Journal 56, 1015–1022.
Jardani A,
Revil A,
Santos F,
Fauchard C, Dupont JP
(2007) Detection of preferential infiltration pathways in sinkholes using joint inversion of self-potential and EM-34 conductivity data. Geophysical Prospecting 55, 749–760.
| Crossref | GoogleScholarGoogle Scholar |
Kuras O,
Meldrum PI,
Beamish D, Ogilvy D
(2007) Capacitive resistivity imaging with towed arrays. Journal of Environmental & Engineering Geophysics 12, 267–279.
| Crossref | GoogleScholarGoogle Scholar |
Monteiro Santos FA
(2004) 1-D laterally constrained inversion of EM34 profilling data. Journal of Applied Geophysics 56, 123–134.
| Crossref | GoogleScholarGoogle Scholar |
Odeh IOA,
Todd AJ,
Triantafilis J, McBratney AB
(1998) Status and trends of soil salinity at different scales: the case of the irrigated cotton growing region of eastern Australia. Nutrient Cycling in Agroecosystems 50, 99–107.
| Crossref | GoogleScholarGoogle Scholar |
Pels S
(1964) The present and ancestral Murray River System. Australian Geographical Studies 2, 111–119.
| Crossref | GoogleScholarGoogle Scholar |
Potts IW
(1990) Use of the EM-34 instrument in groundwater exploration in the Shepparton region. Australian Journal of Soil Research 28, 433–442.
| Crossref | GoogleScholarGoogle Scholar |
Sasaki Y
(1989) Two-dimensional joint inversion of magnetotelluric and dipole–dipole resistivity data. Geophysics 54, 254–262.
| Crossref | GoogleScholarGoogle Scholar |
Triantafilis J,
Ahmed MF, Odeh IOA
(2002) Application of a mobile electromagnetic sensing system (MESS) to assess cause and management of soil salinization in an irrigated cotton-growing field. Soil Use and Management 18, 330–339.
| Crossref | GoogleScholarGoogle Scholar |
Triantafilis J, Buchanan SM
(2009a) Mapping the spatial distribution of subsurface saline material in the Darling River valley. Journal of Applied Geophysics (in press). ,
Triantafilis J, Buchanan SM
(2009b) Identifying common near-surface and subsurface strtigraphic units using EM34 signal data and fuzzy k-means analysis in the Darling River valley. Australian Journal of Earth Sciences 56, 535–558.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
Triantafilis J,
Huckel AI, Odeh IOA
(2001) Comparison of statistical prediction methods for estimating field-scale clay content using different combinations of ancillary variables. Soil Science 166, 415–427.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
Triantafilis J,
Huckel AI, Odeh IOA
(2003a) Field-scale assessment of deep drainage risk. Irrigation Science 21, 183–192.
Triantafilis J,
Kerridge B, Buchanan SM
(2009b) Digital soil-class mapping from proximal and remotely sensed data at the field level. Agronomy Journal 101, 841–853.
| Crossref | GoogleScholarGoogle Scholar |
Triantafilis J, Lesch SM
(2005) Mapping clay content variation using electromagnetic induction techniques. Computers and Electronics in Agriculture 46, 203–237.
| Crossref | GoogleScholarGoogle Scholar |
Triantafilis J,
Lesch SM,
Lau KL, Buchanan SM
(2009a) Field level digital soil mapping of cation exchange capacity using electromagnetic induction and a hierarchical spatial regression model. Australian Journal of Soil Research 47, 651–663.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
Triantafilis J,
Odeh IOA,
Minasny B, McBratney AB
(2003b) Elucidation of physiographic and hydrogeological features of the lower Namoi valley using fuzzy k-means classification of EM34 data. Environmental Modelling & Software 18, 667–680.
| Crossref | GoogleScholarGoogle Scholar |
Triantafilis J,
Odeh IOA,
Jarman AL,
Short MG, Kokkoris E
(2004) Estimating and mapping deep drainage risk at the district level in the lower Gwydir and Macquarie valleys, Australia. Australian Journal of Experimental Agriculture 44, 893–912.
| Crossref | GoogleScholarGoogle Scholar |
Vervoort RW, Annen YL
(2006) Palaeochannels in Northern New South Wales: Inversion of electromagnetic induction data to infer hydrologically relevant stratigraphy. Australian Journal of Soil Research 44, 35–45.
| Crossref | GoogleScholarGoogle Scholar |
Williams BG, Baker GC
(1982) An electromagnetic induction technique for reconnaissance surveys of soil salinity hazards. Australian Journal of Soil Research 20, 107–118.
| Crossref | GoogleScholarGoogle Scholar |
Willis TM, Black AS
(1996) Irrigation increases groundwater recharge in the Macquarie valley. Australian Journal of Soil Research 34, 837–847.
| Crossref | GoogleScholarGoogle Scholar |
Willis TM,
Black AS, Meyer WS
(1997) Estimates of deep percolation beneath cotton in the Macquarie valley. Irrigation Science 17, 141–150.
| Crossref | GoogleScholarGoogle Scholar |
