Sustainable expansion of irrigated agriculture and horticulture in Northern Adelaide Corridor: Task 2 ‐ Modelling nutrient and chemical fate to support the long‐term sustainability of the use of recycled water APPENDICES 1 to 4 Dirk Mallants, Vinod Phogat, Danni Oliver, Jackie Ouzman, Yousef Beiraghdar, Jim Cox Goyder Institute for Water Research Technical Report Series No. 19/15 www.goyderinstitute.org
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Sustainable expansion of irrigated agriculture and horticulture
in Northern Adelaide Corridor: Task 2 ‐ Modelling nutrient and
chemical fate to support the long‐term sustainability of the use
2.2 Data ...........................................................................................................................125
2.3 Pedotransfer function predictions ............................................................................132 2.3.1 Methodology ................................................................................................132 2.3.2 Input data from site specific soil cores ........................................................132 2.3.3 Input data from regional database ..............................................................136
3 Validation of PTF .......................................................................................................138
Table 2 Soil water retention parameters fitted with RECT based on data measured with suction plates. Note: pressure data from Table 1 have units of kPa (negative pressure or suction), which were converted into cm of water column for fitting purposes, with 100 kPa = 1 atmosphere = 10 m of water column. When pressure (i.e. suction when negative) units used in RETC and Hydrus are cm, the water retention parameter α has units (cm-1).
Soil group Sample code, depth
van Genuchten parameters
α (cm-1)
n (-)
θr
(cm3/cm3) θs
(cm3/cm3)
Deep uniform to gradational
NAP-8, 0-10cm
0.0018 1.580 0.041 0.394
NAP-8, 10-30cm
0.0014 1.329 0.126 0.473
Hard red brown
NAP-10, 0-10cm
0.0138 1.2671 0.067 0.447
NAP-10, 10-30cm
0.008 1.2675 0.0645 0.374
NAP-12, 0-10cm
0.0143 1.2238 0.0665 0.512
NAP-12, 10-30cm
0.0067 1.1958 0.0725 0.367
NAP-13, 0-10cm
0.0106 1.2244 0.0013 0.422
NAP-13, 10-30cm
0.0263 1.2092 0.0705 0.36
NAP-13, 30-60cm
0.2816 1.1327 0.1095 0.465
NAP-15, 0-10cm
0.0361 1.168 0.123 0.53
NAP-15, 10-30cm
0.0157 1.1703 0.161 0.567
NAP-18, 0-10cm
0.0147 1.2237 0.091 0.424
NAP-18, 10-30cm Rep1
0.037 1.1357 0.1315 0.436
NAP-20, 0-10cm
0.0502 1.1498 0.113 0.465
NAP-20, 10-30cm
0.2304 1.0925 0.131 0.543
Sand over clay NAP-9, 0-10cm 0.0116 1.8195 0.034 0.436
Appendix 1 Soil hydraulic properties | 103
NAP-9, 10-30cm 0.0285 1.3294 0.056 0.481
NAP-11, 0-10cm 0.0169 1.478 0.052 0.399
NAP-11, 10-30cm
0.0222 1.5753 0.0825 0.435
NAP-11, 30-60cm Rep1
0.0207 1.2217 0.086 0.402
NAP-11, 60-90cm Rep1
0.0435 1.2675 0.0811 0.4615
NAP-14, 0-10cm 0.018 3.7681 0.0531 0.4008
NAP-14, 10-30cm
0.0231 2.0793 0.0125 0.3963
NAP-14, 30-60cm
0.0248 1.619 0.0320 0.3713
NAP-14, 60-90cm
0.0167 6.3259 0.0305 0.3620
Calcareous NAP-16, 0-10 cm
0.036 1.2628 0.0525 0.485
NAP-16, 10-30 cm
0.086 1.2365 0.075 0.476
NAP-17, 0-10cm 0.0216 1.1943 0.098 0.452
NAP-17, 10-30cm Rep1
0.1076 1.1692 0.1075 0.484
NAP-19, 0-10cm 0.0465 1.2593 0.0825 0.504
NAP-19, 10-30cm Rep1
0.06 1.2178 0.1065 0.487
Appendix 1 Soil hydraulic properties | 104
Table 3 Mean soil water retention parameters fitted with RECT (from Table 2) based on data measured with suction plates.
Soil group Sample code, depth
Mean van Genuchten parameters
α (cm-1)
n (-)
θr
(cm3/cm3) θs
(cm3/cm3)
Deep uniform to gradational
0-10 cm 0.0018 1.580 0.041 0.394
10-30 cm 0.0014 1.329 0.126 0.473
Hard red brown
0- 10 cm 0.025 1.217 0.073 0.469
10 -30 cm 0.059 1.187 0.101 0.446
30 – 60 cm 0.282 1.133 0.109 0.465
Sand over clay 0- 10 cm 0.016 2.355 0.046 0.412
10 -30 cm 0.025 1.661 0.050 0.437
30 – 60 cm 0.023 1.420 0.059 0.387
60 – 90 cm 0.030 3.797 0.056 0.412
Calcareous 0- 10 cm 0.035 1.239 0.078 0.480
10 -30 cm 0.085 1.208 0.096 0.482
Appendix 1 Soil hydraulic properties | 105
Table 4 Measured saturated hydraulic conductivitiy. Soil group Soil sample Mean Ksat
(m/s) Std dev Ksat
(m/s)
Deep uniform to gradational
NAP-8, 0-10 cm 4.52E-06 4.14E-06
NAP-8, 10-30 cm 3.20E-06 4.27E-06
Hard red brown
NAP-10, 0-10 cm 3.49E-06 9.17E-07
NAP-10, 10-30 cm 1.75E-05 2.42E-05
NAP-12, 0-10 cm 7.30E-07 2.31E-07
NAP-12, 10-30 cm 5.51E-07 1.13E-07
NAP-13, 0-10 cm 1.25E-05 1.65E-05
NAP-13, 10-30 cm 8.66E-06 1.02E-05
NAP-13, 30-60 cm 4.97E-05 6.89E-05
NAP-15, 0-10 cm 1.76E-06 2.04E-06
NAP-15, 10-30 cm 3.53E-07 3.21E-08
NAP-18, 0-10 cm 1.63E-05 2.20E-05
NAP-18, 10-30 cm Rep1 2.07E-07 NC
NAP-20, 0-10 cm 2.21E-07 2.49E-08
NAP-20, 10-30 cm 7.62E-07 8.05E-07
Sand over clay
NAP-9, 0-10 cm 2.63E-05 6.26E-06
NAP-9, 10-30 cm 1.24E-05 6.29E-06
NAP-11, 0-10 cm 1.08E-05 5.48E-07
NAP-11, 10-30 cm 1.04E-05 6.26E-07
NAP-11, 30-60 Rep1 1.74E-6 NC
NAP-11, 60-90 cm Rep1 2.19E-05 NC
NAP-14, 0-10 cm 7.07E-05 4.61E-06
NAP-14, 10-30 cm 1.23E-05 1.52E-06
NAP-14, 30-60 cm 1.48E-05 4.54E-06
NAP-14, 60-90 cm 2.29E-05 2.45E-05
Calcareous NAP-16, 0-10 cm 1.71E-05 1.15E-05
NAP-16, 10-30 cm 3.54E-05 2.35E-05
Appendix 1 Soil hydraulic properties | 106
NAP-17, 0-10 cm 2.75E-05 3.69E-05
NAP-17, 10-30 cm Rep1 1.16E-06 NC
NAP-19, 0-10 cm 2.66E-05 1.00E-05
NAP-19, 10-30 cm Rep1 2.54E-05 NC
Table 5 Mean measured saturated hydraulic conductivitiy (based on data from Table 4). Soil Group Depth (cm) Average Ks (m/s)
Deep uniform to gradational 0-10 4.52E-06
10-30 3.20E-06
Hard red brown 0-10 5.8E-06
10-30 4.7E-06
30-60 5.0E-05
Sand over clay 0-10 3.6E-05
10-30 1.2E-05
30-60 8.3E-06
60-90 2.2E-05
Calcareous 0-10 2.4E-05
10-30 2.1E-05
Appendix 1 Soil hydraulic properties | 107
Figure 1 Fitted retention curve using the van Genuchten model (soil profile NAP8 – deep uniform to gradational). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Values for θr were fixed to 50% of the measured water content at 1500 kpa. Top: soil depth 10-30 cm; bottom: soil depth 0-10 cm.
0 0.1 0.2 0.3 0.4Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (0-10 cm)Theta_r = 0.041
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.1 0.2 0.3 0.4 0.5
Data (10-30 cm)Theta_r = 0.126
NAP8
Appendix 1 Soil hydraulic properties | 108
Figure 2 Fitted retention curve using the van Genuchten model (soil profile NAP10 – hard red brown). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Values for θr were fixed to either 50% of the measured water content at 1500 kpa (orange curve) or fixed to a value > 0.001 (black line) (each time θr reaches 0.001 forces RECT to put θr = 0, which is to be avoided). Top: soil depth 10-30 cm; bottom: soil depth 0-10 cm.
0 0.1 0.2 0.3 0.4 0.5Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (0-10 cm)Theta_r = 0.0023Theta_r = 0.067
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.1 0.2 0.3 0.4 0.5
Data (10-30 cm)Theta_r = 0.0012Theta_r = 0.0645
NAP10
Appendix 1 Soil hydraulic properties | 109
Figure 3 Fitted retention curve using the van Genuchten model (soil profile NAP12 – hard red brown). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Values for θr were fixed to either 50% of the measured water content at 1500 kpa (orange curve) or fixed to a value > 0.001 (black line) (each time θr reaches 0.001 forces RECT to put θr = 0, which is to be avoided). Top: soil depth 10-30 cm; bottom: soil depth 0-10 cm.
0 0.2 0.4 0.6Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (0-10 cm)Theta_r = 0.0039Theta_r = 0.0665
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.1 0.2 0.3 0.4 0.5
Data (10-30 cm)Theta_r = 0.0011Theta_r = 0.0725
NAP12
Appendix 1 Soil hydraulic properties | 110
Figure 4 Fitted retention curve using the van Genuchten model (soil profile NAP13 – hard red brown). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Values for θr were fixed to either 50% of the measured water content at 1500 kpa (orange curve) or fixed to a value > 0.001 (black line) (each time θr reaches 0.001 forces RECT to put θr = 0, which is to be avoided). Top: soil depth 10-30 cm; bottom: soil depth 0-10 cm.
0 0.1 0.2 0.3 0.4 0.5Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (0-10 cm)Theta_r = 0.0013Theta_r = 0.06
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.1 0.2 0.3 0.4 0.5
Data (10-30 cm)Theta_r = 0.0013Theta_r = 0.0705
NAP13
Appendix 1 Soil hydraulic properties | 111
Figure 5 Fitted retention curve using the van Genuchten model (soil profile NAP13 – hard red brown). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Values for θr were fixed to either 50% of the measured water content at 1500 kpa (orange curve) or fixed to a value > 0.001 (black line) (each time θr reaches 0.001 forces RECT to put θr = 0, which is to be avoided). Soil depth 30-60 cm.
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.1 0.2 0.3 0.4 0.5Soil water content (cm3/cm3)
Data (30-60 cm)Theta_r = 0.0052Theta_r = 0.1095
NAP13
Appendix 1 Soil hydraulic properties | 112
Figure 6 Fitted retention curve using the van Genuchten model (soil profile NAP15 – hard red brown). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Values for θr were fixed to either 50% of the measured water content at 1500 kpa (orange curve) or fixed to a value > 0.001 (black line) (each time θr reaches 0.001 forces RECT to put θr = 0, which is to be avoided). Top: soil depth 10-30 cm; bottom: soil depth 0-10 cm.
0 0.2 0.4 0.6Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (0-10 cm)Theta_r = 0.0016Theta_r = 0.123
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.2 0.4 0.6
Data (10-30 cm)Theta_r = 0.208Theta_r = 0.161
NAP15
Appendix 1 Soil hydraulic properties | 113
Figure 7 Fitted retention curve using the van Genuchten model (soil profile NAP16 – hard red brown). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Values for θr were fixed to 50% of the measured water content at 1500 kpa. Top: soil depth 10-30 cm; bottom: soil depth 0-10 cm.
0 0.1 0.2 0.3 0.4 0.5Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (0-10 cm)Theta_r = 0.0525
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.1 0.2 0.3 0.4 0.5
Data (10-30 cm)Theta_r = 0.075
NAP16
Appendix 1 Soil hydraulic properties | 114
Figure 8 Fitted retention curve using the van Genuchten model (soil profile NAP18 – hard red brown). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Values for θr were fixed to either 50% of the measured water content at 1500 kpa (orange curve) or fixed to a value > 0.001 (black line) (each time θr reaches 0.001 forces RECT to put θr = 0, which is to be avoided). Top: soil depth 10-30 cm; bottom: soil depth 0-10 cm.
0 0.1 0.2 0.3 0.4 0.5Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (0-10 cm)Theta_r = 0.0041Theta_r = 0.091
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.2 0.4 0.6
Data (10-30 cm)Theta_r = 0.180Theta_r = 0.131
NAP18
Appendix 1 Soil hydraulic properties | 115
Figure 9 Fitted retention curve using the van Genuchten model (soil profile NAP20 – hard red brown). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Values for θr were fixed to either 50% of the measured water content at 1500 kpa (orange curve) or fixed to a value > 0.001 (black line) (each time θr reaches 0.001 forces RECT to put θr = 0, which is to be avoided). Top: soil depth 10-30 cm; bottom: soil depth 0-10 cm.
0 0.1 0.2 0.3 0.4 0.5Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (0-10 cm)Theta_r = 0.007Theta_r = 0.113
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.2 0.4 0.6
Data (10-30 cm)Theta_r = 0.0012Theta_r = 0.131
NAP20
Appendix 1 Soil hydraulic properties | 116
Figure 10 Fitted retention curve using the van Genuchten model (soil profile NAP9 – sand over clay). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Value for θr was fixed to 50% of the measured water content at 1500 kpa. Top: soil depth 10-30 cm; bottom: soil depth 0-10 cm.
0 0.1 0.2 0.3 0.4 0.5Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (0-10 cm)Theta_r = 0.034
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.1 0.2 0.3 0.4 0.5
Data (10-30 cm)Theta_r = 0.056
NAP9
Appendix 1 Soil hydraulic properties | 117
Figure 11 Fitted retention curve using the van Genuchten model (soil profile NAP11 – sand over clay). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Value for θr was fixed to 50% of the measured water content at 1500 kpa (except for 0-10 data where θr was fitted). Top: soil depth 10-30 cm; bottom: soil depth 0-10 cm.
0 0.1 0.2 0.3 0.4 0.5Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (0-10 cm)Theta_r = 0.052
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.1 0.2 0.3 0.4 0.5
Data (10-30 cm)Theta_r = 0.0825
NAP11
Appendix 1 Soil hydraulic properties | 118
Figure 12 Fitted retention curve using the van Genuchten model (soil profile NAP11 – sand over clay). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Value for θr was fixed to 50% of the measured water content at 1500 kpa (except for 0-10 data). Top: soil depth 60-90 cm; bottom: soil depth 30-60 cm.
0 0.1 0.2 0.3 0.4 0.5Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (30-60 cm)Theta_r = 0.086
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.1 0.2 0.3 0.4 0.5
Data (60-90 cm)Theta_r = 0.081
NAP11
Appendix 1 Soil hydraulic properties | 119
Figure 13 Fitted retention curve using the van Genuchten model (soil profile NAP14 – sand over clay). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Value for θr was fixed to 50% of the measured water content at 1500 kpa (except for 0-10 data where θr was fitted). Top: soil depth 10-30 cm; bottom: soil depth 0-10 cm.
0 0.1 0.2 0.3 0.4 0.5Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (0-10 cm)Theta_r = 0.0531
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.1 0.2 0.3 0.4 0.5
Data (10-30 cm)Theta_r = 0.0125
NAP14
Appendix 1 Soil hydraulic properties | 120
Figure 14 Fitted retention curve using the van Genuchten model (soil profile NAP14 – sand over clay). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Value for θr was fixed to 50% of the measured water content at 1500 kpa (except for 60-90 data where θr was fitted). Top: soil depth 60-90 cm; bottom: soil depth 30-60 cm.
0 0.1 0.2 0.3 0.4 0.5Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (30-60 cm)Theta_r = 0.032
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.1 0.2 0.3 0.4 0.5
Data (60-90 cm)Theta_r = 0.0305
NAP14
Appendix 1 Soil hydraulic properties | 121
Figure 15 Fitted retention curve using the van Genuchten model (soil profile NAP17 – calcareous). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Value for θr was fixed to 50% of the measured water content at 1500 kpa. Top: soil depth 10-30 cm; bottom: soil depth 0-10 cm.
0 0.1 0.2 0.3 0.4 0.5Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (0-10 cm)Theta_r = 0.098
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.1 0.2 0.3 0.4 0.5
Data (10-30 cm)Theta_r = 0.1075
NAP17
Appendix 1 Soil hydraulic properties | 122
Figure 16 Fitted retention curve using the van Genuchten model (soil profile NAP19 – calcareous). Saturated and residual water content were fixed during the optimisation with RETC (van Genuchten et al. 1991). Value for θr was fixed to 50% of the measured water content at 1500 kpa. Top: soil depth 10-30 cm; bottom: soil depth 0-10 cm.
0 0.2 0.4 0.6Soil water content (cm3/cm3)
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
Data (0-10 cm)Theta_r = 0.0825
0.1
1
10
100
1000
10000
100000
Soil
suct
ion
(cm
)
0 0.1 0.2 0.3 0.4 0.5
Data (10-30 cm)Theta_r = 0.1065
NAP19
Appendix 1 Soil hydraulic properties | 123
2 Mid infrared predictions
2.1 Methodology
Mid-infrared (MIR) spectroscopy was used as an alternative to conventional soil analysis
methods to generate relationships that allow the prediction of hydraulic properties at locations
where soil samples were collected but direct estimation of the hydraulic properties was not
carried out (see Section 1). MIR analysis is rapid and inexpensive compared to conventional
wet chemistry and soil physical methods, especially because it can provide us with simultaneous
prediction of various chemical and physical properties using only soil IR spectra.
Soil samples were obtained from field soils and glass house soils. For field soils, the collected
soil material was available to depths of 1.2 m, air-dried and passed through a 2mm sieve in
preparation for MIR spectral analysis (for details, see Task 1 Report). The calibration models
for predicting soil properties were developed between IR spectra (i.e. predictor variables) and
reference soil property values (i.e. response variables). The response variables were available
from shallow soils depths as discussed in Section 1. The MIR method was used to predict water
content at different soil suctions (0.01, 4, 8, 33, 60, 100, and 1500 kpa) and saturated hydraulic
conductivity. The reliability of the MIR predictions can be asserted from the cross plot in Figure
17; water contents are very well predicted for soil suction of 8 KPa and higher, while the water
contents at low suction are somewhat less good predicted. This is not a surprise: at the 0.01 and
4 kPa soil suction the soil structure is the dominant factor determining soil water content.
Because soil structure is relatively difficult to measure with MIR, the soil water content
predictions are somewhat less reliable. At the higher suctions (8 kPa and higher), soil texture is
the dominant factor in determining soil water content. Because soil texture is relatively easily
predicted with MIR, the water content is too. The predicted saturated hydraulic conductivity
compares reasonably well with the measured values, especially in the wetter range (Figure 18).
The resulting predicted soil water retention data are discussed in Section 2.2.
For glasshouse soils, two soils were samples at three locations and two depths (0-10, 20-30 cm).
Core analysis was the same as for the field soils.
Appendix 1 Soil hydraulic properties | 124
Figure 17 Comparison between measured and MIR predicted soil water content.
Water retention at 0.01 kPaWater content at 4 kPaWater content at 8 kPaWater content at 33 kPaWater content at 60 kPaWater content at 100 kPaWater content at 1500 kPa
0-10 cm 0.483 0.355 0.384 0.281 0.271 0.262 0.199 5.1E-06
Farm2_S2,
20-30 cm 0.436 0.351 0.359 0.308 0.292 0.276 0.168 5.1E-06
Farm2_S3,
0-10 cm 0.443 0.349 0.348 0.267 0.260 0.244 0.165 7.6E-06
Farm2_S3,
20-30 cm 0.406 0.346 0.334 0.310 0.286 0.272 0.168 7.6E-06
Lot13PGR_S1,
0-10 cm 0.482 0.421 0.392 0.268 0.248 0.234 0.111 8.8E-06
Lot13PGR_S1,
20-30 cm 0.435 0.402 0.347 0.290 0.258 0.241 0.094 1.2E-05
Lot13PGR_S2,
0-10 cm 0.484 0.385 0.380 0.247 0.238 0.222 0.113 6.0E-06
Lot13PGR_S2,
20-30 cm 0.417 0.361 0.312 0.238 0.222 0.202 0.084 9.6E-06
Lot13PGR_S3,
0-10 cm 0.503 0.441 0.406 0.334 0.324 0.303 0.198 7.4E-06
Lot13PGR_S3,
20-30 cm 0.461 0.416 0.365 0.329 0.313 0.292 0.188 1.1E-05
Appendix 1 Soil hydraulic properties | 131
Table 12 Soil water retention parameters fitted with RECT based on MIR data for glasshouse soils.
Sample code, depth
van Genuchten parameters
α
(cm-1)
η
(-)
θr
(cm3/cm3)
θs
(cm3/cm3)
R2 SSE
Farm2_S1,
0-10 cm
0.05750 1.13448 0.1809 0.4488 0.991 0.00042
Farm2_S1,
20-30 cm
0.05693 1.15322 0.2110 0.4249 0.950 0.00161
Farm2_S2,
0-10 cm
0.13456 1.17825 0.1983 0.4826 0.962 0.00200
Farm2_S2,
20-30 cm
0.05233 1.17232 0.1956 0.4359 0.950 0.00205
Farm2_S3,
0-10 cm
0.07233 1.19682 0.1736 0.4428 0.986 0.00065
Farm2_S3,
20-30 cm
0.03580 1.17112 0.1938 0.4059 0.947 0.00174
Lot13PGR_S1,
0-10 cm
0.02015 1.32277 0.1230 0.4820 0.992 0.00076
Lot13PGR_S1,
20-30 cm
0.01389 1.30350 0.1237 0.4350 0.973 0.00206
Lot13PGR_S2,
0-10 cm
0.03399 1.29368 0.1250 0.4839 0.983 0.00153
Lot13PGR_S2,
20-30 cm
0.02593 1.29149 0.1079 0.4170 0.985 0.00110
Lot13PGR_S3,
0-10 cm
0.03658 1.20409 0.2105 0.5029 0.992 0.00045
Lot13PGR_S3,
20-30 cm
0.03358 1.19106 0.2058 0.4609 0.977 0.00105
Appendix 1 Soil hydraulic properties | 132
2.3 Pedotransfer function predictions
2.3.1 Methodology
To generate hydraulic properties for the Northern Adelaide Plains irrigation project in a cost-
effective manner where direct measurements or MIR predictions are not available, pedotransfer
functions (PTF) that utilise either existing gridded basic soil properties (such as particle size)
or measured particle size data were used. Pedotransfer functions typically use relatively easy to
measure soil properties (particle size, bulk density, etc.) to predict either the water content at a
specific soil pressure head or moisture retention parameters of a specific model. The predictive
capacity of PTF generally increases when more input data is provided. Therefore, this study
will also explore different approaches that use different data types when generating soil
hydraulic properties through PTFs. The predictive capacity of the approaches will be tested
using a limited set of independent soil hydraulic data (water retention curve and saturated
hydraulic conductivity, Ks).
2.3.2 Input data from site specific soil cores
Soil water retention parameters were predicted with the Rosetta software (Schaap et al., 2001)
using input data (%sand, %silt, %clay, bulk density) from soil cores collected from 10 sites
during this project. Soil profiles were distributed across four Soil Groups: calcareous soils (3),
hard red brown soils (6), sand over clay soils (3), and deep uniform to gradational soils (1). Soil
cores could generally be collected only at shallow depths, usually down to 30 or 60 cm and
exceptionally to 90 cm. Because soil hydraulic properties have been obtained through direct
measurements on the same soil material, use of pedotransfer functions would likely yield soil
hydraulic properties that are inferior to the ones measured directly. The value of the
pedotransfer function predictions is more in providing estimates that can be tested versus the
direct measurements, and hence allow to validate the pedotransfer functions. This is important
as the pedotransfer function predictions will be used for i) soil depths were no direct
measurements are available (usually the deepest part of the soil profile), and ii) for the cracking
soils that were not sampled during this project. Predicted van Genuchten soil moisture
parameters and saturated hydraulic conductivity are shown in Table 13 to Table 16.
Appendix 1 Soil hydraulic properties | 133
Table 13 Soil water retention parameters for deep uniform to gradational predicted with Rosetta (Schaap et al., 2001) using input parameters from site specific soil cores.
Soil sample Input parameters for PTFs van Genuchten parameters
Table 14 Soil water retention parameters for hard red brown predicted with Rosetta (Schaap et al. 2001) using input parameters from site specific soil cores.
Soil sample Input parameters for PTFs van Genuchten parameters
Table 15 Soil water retention parameters for sand over clay soil predicted with Rosetta (Schaap et al. 2001) using input parameters from site specific soil cores.
Soil sample Input parameters for PTFs van Genuchten parameters
Table 16 Soil water retention parameters for calcareous soil predicted with Rosetta (Schaap et al. 2001) using input parameters from site specific soil cores.
Soil sample Input parameters for PTFs van Genuchten parameters
Nathan (2014): Soil and Landscape Grid Digital Soil Property Maps for South Australia (3" resolution). v3. CSIRO. Data Collection.http://doi.org/10.4225/08/5472DCCD081D2
The ability of the PTFs of Schaap et al. (2001) to reliably predict soil water retention parameters
was tested by comparing the predicted values with direct measurements. For this purpose we
used cores for which both input parameters for the pedotransfer function were known (particle
size and bulk density) and direct measurements of hydraulic properties were available.
3.2 Laboratory moisture retention data
Two data sets were used for this purpose: i) a database from Green (2010) involving two Soil
Groups (sand over clay soils and hard red brown soils) (Table 22), and ii) the database obtained
Appendix 1 Soil hydraulic properties | 139
in the current project encompassing four Soil Groups (sand over clay soils, hard red brown
soils, deep uniform to gradational soils, and calcareous soils) (Table 13 to Table 16). Cross plots
for the four van Genuchten parameters are shown in Figure 19 while Figure 20 shows the cross
plot for saturated hydraulic conductivity. Pearson correlation coefficients for all parameters are
listed in Table 23. The general trend is that the α parameter has the poorest predictions while the
remaining parameters are reasonably well predicted.
Table 22 van Genuchten soil hydraulic parameters estimated with the RETC (Van Genuchten et al. 1991) program utilizing measured θ-h and K at -10kPa values. Soil group D (hard red brown texture contrast): site HX, SR, TR. Soil group G (sand over clay soils): site PGR (data source: Green, 2010).
θr
(cm3/cm3) θs
(cm3/cm3) α
(cm-1) n (-)
Ks (cm/day)
l (-)
Soil Group G – Sand over clay soils PGR1 0-10 0.0213 0.48562 0.0726 1.387 26.42 0.5
Figure 19 Validation of PTF using CSIRO’s laboratory data (this study) and Green’s field data (Green, 2010). Soil group A = calcareous soils; soil group D = hard red brown soils; soil group G = sand over clay soils; soil group M = deep gradational soils.
Table 23 Pearson correlation coefficient between estimated (pedotransfer function - PTF) and measured (laboratory) van Genuchten parameters.
Parameter Pearson correlation coefficient
All soil groups combined
Hard red brown soils
Sand over clay soils Calcareous soils
α (PTF) - α (lab) 0.324 0.411 0.429 0.270
n (PTF) - n (lab) 0.705 0.416 0.597 0.358
θr (PTF) - θr (lab) 0.738 0.822 0.910 0.707
θs (PTF) - θs (lab) 0.516 0.010 0.909 0.715
0 0.04 0.08 0.12α - PTF
0
0.04
0.08
0.12
α -
lab
1
1.25
1.5
1.75
2
2.25
2.5n
- lab
1 1.25 1.5 1.75 2 2.25 2.5n - PTF
0
0.05
0.1
0.15
0.2
0.25
θ r -
Lab
0 0.05 0.1 0.15 0.2 0.25θr - PTF
0.2
0.3
0.4
0.5
0.6
θ s -
lab
0.2 0.3 0.4 0.5 0.6θs - PTF
Green (CL031-soil Group D)Green (CL036-soil Group D)Green (CL035-soil Group D)Green (CL012-soil Group G)CSIRO (soil Group D)CSIRO (soil Group G) CSIRO (soil Group A)CSIRO (soil Group M)
1 2 3 4 5 6
1
2
3
4
5
6
Appendix 1 Soil hydraulic properties | 141
Figure 20 Validation of PTF for KS using CSIRO’s laboratory data.
1E-007 1E-006 1E-005 1E-004 1E-003K
S (lab, m/s)
1E-007
1E-006
1E-005
1E-004
1E-003K S (P
TF, m
/s)
Hard red brown soilsDeep gradational soilsSand over clay soilsCalcareous soils1:1
Pearson correlation = 0.58 (all data)
Appendix 1 Soil hydraulic properties | 142
4 Summary of hydraulic properties
Soil hydraulic parameters used in HYDRUS-1D simulations are summarised in Table 24 to Table
28. Three datasets were combined to have the best available information across the different
Soil Groups and soil depths. For the shallowest depths the directly measured values were used:
these provide the highest reliability as they do not depend on some prediction method using
related prediction variables. Where such data were not available, the MIR predictions were used
as they provide site specific data using auxiliary data. Finally, if neither direct measurements
nor MIR predictions were available, the pedotransfer function predictions based on the regional
data set were used.
Table 24 summary of van Genuchten soil hydraulic parameters. Orange colour = direct measurements on site specific soil cores; blue colour = predicted with MIR using site specific core material; grey colour = PTF predictions.
Soil depth (cm)
Soil Group 1: Calcareous soils
ϴr (cm3/cm3)
ϴs (cm3/cm3)
Alpha (cm-1)
n (-)
Ks (cm/day)
l (-)
0-15 0.078 0.480 0.035 1.239 207.36 0.5
15-30 0.096 0.482 0.085 1.208 181.44 0.5
30-60 0.0758 0.485 0.2781 1.1639 146 0.5
60-100 0.0001 0.4810 0.2305 1.1382 267.79 0.5
100-200 0.0735 0.4087 0.0242 1.298 22.91 0.5
Appendix 1 Soil hydraulic properties | 143
Table 25 Summary of van Genuchten soil hydraulic parameters. Orange colour = direct measurements on site specific soil cores; blue colour = RETC fitted to retention data predicted with MIR using site specific core material; grey colour = PTF predictions.
Soil depth (cm)
Soil Group 2: Hard red brown soils
ϴr (cm3/cm3)
ϴs (cm3/cm3)
Alpha (cm-1)
n
(-)
Ks (cm/day)
l (-)
0-15 0.073 0.469 0.025 1.217 50.11 0.5
15-30 0.101 0.446 0.059 1.187 13.98 0.5
30-60 0.109 0.465 0.282 1.133 13.33* 0.5
60-100 0.1365 0.4588 0.0891 1.1216 269* 0.5
100-200 0.0807 0.4112 0.0255 1.2196 12.82 0.5
*Measured and MIR predicted Ksat is too high for these layers (432 and 269 respectively for 30-60 and 60-90 cm depths). Therefore, Ksat was estimated from average particle size and bulk density data using ROSETTA.
Table 26 Summary of van Genuchten soil hydraulic parameters. Grey colour = PTF predictions.
Soil depth (cm)
Soil Group 3: Cracking soils
ϴr (cm3/cm3)
ϴs (cm3/cm3)
Alpha (1/cm)
n (-)
Ks (cm/day)
l (-)
0-15 0.0875 0.4782 0.021 1.3448 32.06 0.5
15-30 0.0944 0.4721 0.0225 1.281 22.41 0.5
30-60 0.0962 0.4671 0.0226 1.2588 18.2 0.5
60-100 0.0962 0.4671 0.0226 1.2588 18.2 0.5
100-200 0.0896 0.4271 0.024 1.2155 11.48 0.5
Table 27 summary of van Genuchten soil hydraulic parameters. Orange colour = direct measurements on site specific soil cores; grey colour = PTF predictions.
Soil depth (cm)
Soil Group 4: Sand over clay soils
ϴr (cm3/cm3)
ϴs (cm3/cm3)
Alpha (cm-1)
n (-)
Ks (cm/day)
l (-)
0-15 0.0587 0.4127 0.0171 1.7878 311.04 0.5
15-30 0.0820 0.4434 0.0371 1.4397 103.68 0.5
30-60 0.1008 0.3866 0.0243 1.4745 71.71 0.5
60-100 0.1097 0.4117 0.0250 1.7920 190.08 0.5
100-200 0.0695 0.3812 0.0259 1.2511 16.02 0.5
Appendix 1 Soil hydraulic properties | 144
Table 28 summary of van Genuchten soil hydraulic parameters. Orange colour = direct measurements on site specific soil cores; blue colour = RETC fitted to retention data predicted with MIR using site specific core material; grey colour = PTF predictions.
Soil depth (cm)
Soil Group 5: Deep uniform to gradational soils
ϴr (cm3/cm3) ϴs (cm3/cm3)
Alpha (cm-1)
n (-)
Ks (cm/day)
l (-)
0-15 0.041 0.394 0.0018 1.580 39.05 0.5
15-30 0.126 0.473 0.0014 1.329 27.65 0.5
30-60 0.102 0.442 0.0219 1.1886 171 0.5
60-100 0.1139 0.4545 0.0184 1.1781 233 0.5
100-200 0.0735 0.4007 0.0254 1.2477 17.21 0.5
Appendix 1 Soil hydraulic properties | 145
References
Green, G. 2010. Point and regional scale modelling of vadose zone water and salt fluxes in an
area of intensive horticulture. PhD Thesis. Flinders University: 187 pp.
Schaap, M., Leij, F. and van Genuchten M.Th. 2001. rosetta: a computer program for estimating
soil hydraulic parameters with hierarchical pedotransfer functions. Journal of Hydrology
251: 163-176.
van Genuchten, M.T.h, Leij F.J., and Yates S.R. 1991. The RETC code for quantifying the
hydraulic functions of unsaturated soils. Report No. EPA/600/2-91/065. R. S. Kerr
Environmental Research Laboratory, U. S. Environmental Protection Agency, Ada, OK.
85 pp.
Youngs E.G. 2001. Hydraulic conductivity of saturated soils. Chapter 4. In Soil and
Environmental Analysis. Physical methods, revised and expanded. CRC Press.
Where [Na], [K], [Mg], and [Ca] are molal activities in solution (dimensionless), and [Na-X],
[K-X], [Mg-X], and [Ca-X] are adsorbed concentrations (mmolc/kg soil).
The molal activity [i] is related to the molal concentration mi by an activity coefficient which
corrects for non-ideal behaviour. For aqueous solutes, the relation is (Simunek et al., 1996):
[𝑖𝑖] = 𝛾𝛾𝑖𝑖𝑚𝑚𝑖𝑖/𝑚𝑚𝑖𝑖0 ≡ 𝛾𝛾𝑖𝑖𝑚𝑚𝑖𝑖 (7)
where [i] is the activity of ion i (dimensionless), γi is the activity coefficient (dimensionless),
mi is the molality (mol/kgH2O), mi0 is the standard state, i.e. 1 mol/kg H2O. The factor 1/mi
0 is
unity for all species and cancels in the practical enumeration of Equation (7) but causes the
activity to become dimensionless.
Activity coefficients γi for solutes were calculated using the Debye-Hückel theory. In this
theory, first the ionic strength, I, is defined which describes the number of electrical charges in
the solution (Appelo and Postma, 2005):
𝐼𝐼 = 12� ∑𝑚𝑚𝑖𝑖 𝑚𝑚𝑖𝑖,0� 𝑧𝑧𝑖𝑖2 (8)
Appendix 2 Soil chemical properties | 148
where zi is the charge number of ion i, and mi is the molality of i (mol/kg H2O). Similarly to
the definition of activity, the ionic strength becomes dimensionless by division with the
standard state mi0 i.e. 1 mol/kg H2O. The ionic strength of freshwater is typically smaller than
0.02 while seawater has an ionic strength of about 0.7 (Appelo and Postma, 2005).
For an ionic strength I of up to about 0.5, the Davies equation is used to calculate activity
coefficients (Appelo and Postma, 2005):
𝑙𝑙𝑙𝑙𝑀𝑀10𝛾𝛾𝑖𝑖 = −𝐴𝐴𝑧𝑧𝑖𝑖2 �√𝐼𝐼
1+√𝐼𝐼− 0.3𝐼𝐼� (9)
where A is a temperature dependent coefficient equal to 0.5085 at 25 °C.
1.2 Calculation of ionic strength
First, ionic strength I was calculated for 9 soil samples across four soil groups using Eq. (8).
For nine analytes (K+, Na+, Ca2+, Mg2+, Br-, Cl-, F-, NO3-, SO4
2-) pore-water composition (for
details see Task 1 Report, Oliver et al., 2018) was obtained by extraction of soil solution from
soil samples at maximum water holding capacity, where the latter is defined as the water
content at -5 kPa (Jenkinson and Powlson, 1976; McLaughin et al., 1997). The extraction
solution had 4 mg/L chloride which is equal to the amount of chloride in rain water near
Adelaide (Crosbie et al., 2012). Table 2 provides measured solution composition in mmol/L and
the corresponding ionic strength based on Eq. (8). Because all ionic strength values were
sufficiently smaller than 0.5, the Davies equation (Eq. 9) was used to calculate the ion activity
coefficients.
1.3 Calculation of activity coefficients
Activity coefficients calculated with Eq. 7 are listed in Table 2. As shown in Figure 1, activity
coefficients decrease with increasing ionic strength and the rate of decrease is strongest for
divalent ions.
Appendix 2 Soil chemical properties | 149
Figure 1 Activity coefficients as function of ionic strength.
1.4 Calculation of selectivity coefficients
Gapon selectivity or exchange coefficients were calculated using Eq. (4-6), with adsorbed
concentrations from Table 3. All calculated Gapon coefficients are shown in Table 3, with mean
values listed in Table 1. Green (2010) also derived Gapon coefficients for Sand over clay and
Hard red brown soil from the NAP. For Sand over clay, Gapon coefficients were in the range
1-20 for KCa/Na, 0.3-1.7 for KMg/Ca, and 0.03 – 1.5 for KCa/K. For Hard red brown, values were
in the range 1.8-12 for KCa/Na, 0.09-1.65 for KMg/Ca, and 0.14-2 for KCa/K.
Table 1 Mean values of Gapon selectivity or exchange coefficients Soil Group KCa/Na KCa/K KMg/Ca
Hard red brown 0.753 0.065 0.033
Deep uniform to gradational 1.313 0.025 0.013
Sand over clay 1.880 0.014 0.020
Calcareous 0.957 0.009 0.038
0 0.01 0.02 0.03Ionic Strength (-)
0.5
0.6
0.7
0.8
0.9
1
Activ
ity c
oeffi
cien
ts (-
)Ca, MgNa, KDavies model (divalent ion)Davies model (monovalent ion)
Appendix 2 Soil chemical properties | 150
Table 2 Soil chemical solution composition, ionic strength (I), and activity coefficients (γi) (based on data from Task 1 Report, Oliver et al., 2018). Soil Code Major Soil Group Field
Root water uptake parameters for use in Hydrus-1D were compiled from the literature. Crops
were then grouped into five categories: vegetative crops, root crops, fruit crops, grain crops,
and other vegetation. Simulations with HYDRUS-1D were carried out for wine grapes,
almonds, pistachios, pasture/legumes, onions, carrots, and potatoes. Greenhouse crops were
also simulated: tomato, cucumber, capsicum, and eggplant. Results from these crops may be
extrapolated to similar crops provided the root water uptake parameters and rooting depths are
similar.
2 Data
Root water uptake parameters are summarised into groups: vegetative crops, root crops, fruit
crops, grain crops, and other vegetation (Table 1). Bold faced crops are the ones for which
HYDRUS-1D simulations were carried out. Parameters for other crops are included to allow
extrapolation of simulation results. Rooting depths for crops used in the HYDRUS-1D
simulations are given in Table 2. Parameters describing salinity stress are provided in Table 3.
Table 1 Root water uptake parameters for common crops. h1: no water extraction at higher pressure heads; h2: h below which optimum water uptake starts; h3: h below which water uptake reduction starts at high Tpot; h4: h below which water uptake reduction starts at low Tpot; h5: wilting point, no water uptake at lower pressure heads. Crops simulated in this study are in bold face.
Soil attribute maps of particular interest were obtained from the GIS-based database Land and Soil Spatial Data for Southern Australia developed by the DWLBC’s, Soil and Land Program (Liddicoat et al., 2014). The sampling points from the NatureMaps were overlain onto the mapping data to generate the soil attribute maps and to extract the soil type classification of the sampling points. The soil attribute maps generated through this process include the toxicity of Aluminium and Boron, Salinity, depth to water table, deep drainage, and potential root zone depths for different crop types (Table 1 and Section 2). These maps provide useful background information for the further planning of expansion of irrigated agriculture in the Northern Adelaide Plains, and in the area north of the current study area between Gawler and Light River.
Table 1 Overview of soil property maps. Map #
Soil property map Features displayed Property at soil profile sites
1 Aluminium toxicity Proportion of land with potentially high or moderate aluminium toxicity. Moderate toxicity is 2-4 mg/kg extractable aluminium and high toxicity is more than 4 mg/kg extractable aluminium.
All 12 soil profile sites within the Goyder project focus area have negligible to minor toxicity.
2 Deep drainage Depth to impeding layer determines the deep drainage characteristics of the soils.
None of the 12 soil profile sites within the Goyder project focus area have an impeding layer within 100 cm of the surface.
3 Depth to toxic layer - Boron
Depth to boron concentrations exceeding 15 mg/kg. Boron concentrations exceeding 15 mg/kg are considered toxic.
Only 2 out of 12 soil sampling sites exceed the 15 mg/kg threshold within 25-50 cm of the surface. For all other sites the distance to this layer is at least 50 cm.
4 Depth to water table Maximum groundwater level maintained for at least two weeks per year.
For all 12 soil profiles the depth to groundwater is at least 200 cm for 70% of the landscape.
5 Dry saline land Indicative ECe (dS/m) in surface and subsurface soil. Compare with salinity threshold values (Table 3, Appendix 3)
Two out of 12 soil sampling sites have a moderately high ECe (ECe 2-4 dS/m at surface), all other sites have a moderately low ECe (ECe 4-8 dS/m at surface).
6 Potential root zone depth for crops
Potential rooting zone depth for sensitive perennial horticultural crops such as citrus and avocadoes (CA)
Ten out of 12 soil sampling sites have a potential rooting zone depth of 30-40cm; the remaining soil sites have a rooting zone depth of 20-30 cm.
7 Potential root zone depth for crops
Potential rooting zone depth for medium sensitive perennial horticultural crops (CB) including stone fruits, pome fruits and almonds
Eight out of 12 soil sampling sites have a potential rooting zone depth of 40-50cm; the remaining four soil sites have a rooting zone depth of 30-40 cm.
8 Potential root zone depth for crops
Potential rooting zone depth for hardy perennial horticultural
Nine out of 12 soil sampling sites have a potential rooting zone depth of 50-60cm; the remaining
Appendix 4 Soil property maps | 164
crops (CC) such as grape vines and olives
three soil sites have a rooting zone depth of 30-40 cm
9 Potential root zone depth for crops
Potential rooting zone depth for root crops including potatoes, carrots and onions (CD)
Ten out of 12 soil sampling sites have a potential rooting zone depth of 30-40cm; the remaining two soil sites have a rooting zone depth of 20-30 cm
10 Potential root zone depth for crops
Potential rooting zone depth for above ground annual horticultural crops such as brassicas (CD)
Ten out of 12 soil sampling sites have a potential rooting zone depth of 30-40cm; the remaining two soil sites have a rooting zone depth of 20-30 cm
Appendix 4 Soil property maps | 165
2 Data
Soil property maps for the focus are shown in Figure 1 to Figure 10.
Figure 1 Aluminium toxicity.
Figure 2 Deep drainage.
Appendix 4 Soil property maps | 166
Figure 3 Depth to toxic layer - Boron.
Figure 4 Depth to water table.
Appendix 4 Soil property maps | 167
Figure 5 Dry saline land.
Figure 6 Potential root zone depth for crops (CA: sensitive perennial horticultural crops).
Appendix 4 Soil property maps | 168
Figure 7 Potential root zone depth for crops (CB: medium sensitive perennial horticultural crops).
Figure 8 Potential root zone depth for crops (CC: hardy perennial horticultural crops).
Appendix 4 Soil property maps | 169
Figure 9 Potential root zone depth for crops (CD: root crops).
Figure 10 Potential root zone depth for different crops (CE: above ground annual horticultural crops).
Appendix 4 Soil property maps | 170
References
Liddicoat, C., Holmes, K., Maschmedt, D., Rowland, J., Searle, R., Odgers, N. 2014. Soil and Landscape Grid Digital Soil Property Maps for South Australia (3" resolution). v3. CSIRO. Data Collection.http://doi.org/10.4225/08/5472DCCD081D2