Investigating the impacts of groundwater on soil ... · Nonetheless, the geochemical model WEB-PHREEQ suggests the precipitation of carbonate, (hydr)oxide and phosphate (apatite)

INVESTIGATING THE IMPACTS OF GROUNDWATER

ON SOIL PROPERTIES AND PASTURE NUTRITION

IN IRRIGATED AGRICULTURE, PILBARA REGION

OF WESTERN AUSTRALIA

Simon Guo Hong Yeap

Bachelor of Science in Environmental Science and Environmental Technology

School of Veterinary and Life Sciences

Murdoch University

Murdoch, Western Australia, 6150

Australia

June 2014

Investigating the impacts of groundwater on soil properties and pasture

nutrition

ii

Acknowledgements

To my supervisors, Professors Richard Bell and Richard Harper, and to my family and

friends whose constant guidance and encouragement has enabled me to successfully

accomplish this research. To Rio Tinto Iron Ore for providing financial assistance and

staff – especially Dr Sunil Samaraweera for his invaluable insights and commitment to

the project, and the Hamersley Agricultural Project team, Simon Mathwin and Nicholas

Collins. Thanks are also due to Stuart Anstee (Rio Tinto), and Dr Andrew Storey and

Sarah Emery from Wetland Research and Management (WRM) for technical assistance

during the planning and reconnaissance phase. Subsequent work by Dr Sunil

Samaraweera on the Exchangeable Sodium Percentage and Sodicity of Hamersley

Agricultural Project Soils (Samaraweera, 2015) are gratefully acknowledged.

iii

DECLARATION

I declare that this thesis is my own account of my research and contains as its

main content work which has not previously been submitted for a degree at any tertiary

education institution.

Simon Guo Hong Yeap

iv

ABSTRACT

Dewatering of groundwater systems has become a common practice for iron ore

mining in the Pilbara region of Western Australia. While the discharge of surplus water

to local tributaries and re-injection into the aquifer are widely practiced, the re-use of

this water for irrigated forages is an innovative solution. However, the chemistry of the

groundwater and the impacts on soil properties from long-term application of

groundwater need to be assessed.

Surplus water from the Marandoo iron ore mine is utilised to irrigate Rhodes

grass (Chloris gayana) for hay production at the Hamersley Agricultural Project (HAP).

After amendment with nutrients, the irrigation water was slightly alkaline (pH 8.0) and

slightly brackish-sodic (total dissolved solids, TDS, of 580 mg/L) with Ca (61 mg/L), Mg

(50 mg/L) and Na (43 mg/L) as the dominant cations and bicarbonate (270 mg/L) as the

dominant anion. This study aims to identify the implications of irrigation with this water

for pasture production and soil management.

Following the commencement of irrigation in October 2012, significant changes

and trends in soil properties and leaf nutrient composition of C. gayana were examined

over a 15 month period, based on a quarterly sampling program across 10 centre-pivot

irrigation systems. Analysis initially showed that the continuation of current trends

could result in: (1) increases in soil sodicity, since ESP levels had exceeded 5% at 0-10

cm and 7% at 20-30 cm, and (2) alkalinisation, such that the soil pH is predicted to reach

~8.2. However, subsequent analysis with pre-washed soil samples to remove soluble

salts indicated that irrigation had not caused a measureable change in the ESP and hence

no change in the sodicity of HAP soils.

Nonetheless, the geochemical model WEB-PHREEQ suggests the precipitation of

carbonate, (hydr)oxide and phosphate (apatite) minerals of Ca, Mg, Fe and Mn could also

impose a risk for immobilising nutrients applied from irrigation water, given suitable

conditions for nucleation and crystal growth. Moreover, changes in the relative

abundance of soil exchangeable cations may also adversely affect plant nutritional

balance whereby exchangeable Mg2+ as a percentage of cation exchange capacity has

significantly increased while the percentages of exchangeable Ca2+ and K+ have

significantly decreased.

In the next 20 years, based on the estimated duration of the HAP, soil

alkalinisation could emerge as a problem by suppressing the availability of various


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nutrients. Future monitoring and research, in conjunction with effective irrigation and

soil management practice, will hence be imperative to ensure long-term sustainability of

pasture production at the HAP, as well as for rehabilitation of soils after

decommissioning.


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TABLE OF CONTENTS

DECLARATION ...................................................................................................................................... III

ABSTRACT ............................................................................................................................................ IV

TABLE OF CONTENTS ........................................................................................................................... VI

LIST OF FIGURES .................................................................................................................................. IX

LIST OF TABLES .................................................................................................................................. XIII

1. INTRODUCTION ............................................................................................................................. 1

1.1. SALINITY AND SODICITY IN IRRIGATED AGRICULTURE ........................................................... 1

1.2. SALT AFFECTED SOILS AND IMPLICATIONS FOR PLANT GROWTH ........................................... 2

1.2.1. SALINITY AND SALT STRESS 2

1.2.2. SODICITY AND ALKALI STRESS 3

1.2.3. DETERIORATION OF SOIL PHYSICAL CONDITION 5

1.3. PROJECT SCOPE .......................................................................................................................... 5

1.3.1. MINE DEWATERING IN THE PILBARA 5

1.3.2. THE HAMERSLEY AGRICULTURAL PROJECT 6

1.3.3. RESEARCH OBJECTIVES 6

2. MATERIALS AND METHODS .......................................................................................................... 8

2.1. STUDY AREA ............................................................................................................................... 8

2.1.1. IRRIGATION PIVOTS 10

2.2. SAMPLING AND MONITORING SOIL, LEAF TISSUE, AND WATER QUALITY ............................ 12

2.3. GEOCHEMICAL MODELLING FOR MINERAL PRECIPITATION ................................................. 13

2.4. ALKALINITY MASS BALANCE AND ASH ALKALINITY DETERMINATION ................................ 14

2.5. EXCHANGEABLE SODIUM PERCENTAGE ................................................................................. 15

2.6. DATA ANALYSIS ...................................................................................................................... 15

3. RESULTS...................................................................................................................................... 17

3.1. SIGNIFICANT DIFFERENCES BETWEEN MONITORING SPANS................................................. 17

3.2. BASELINE SOIL DATA .............................................................................................................. 18

3.3. SIGNIFICANT CHANGES AND TRENDS ..................................................................................... 20

3.3.1. SOIL PROPERTIES 20

3.3.2. LEAF NUTRIENT COMPOSITION 35

3.4. CORRELATION AND LINEAR REGRESSION ANALYSIS ............................................................. 41


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3.4.1. SOIL PROPERTIES 41

3.4.2. PARTICLE SIZE AND SOIL CHEMICAL PROPERTIES 47

3.4.3. LEAF NUTRIENT COMPOSITION AND SOIL PROPERTIES 48

3.5. WATER QUALITY AND GEOCHEMICAL MODELLING ............................................................... 49

3.6. ASH ALKALINITY DETERMINATION AND MASS BALANCE ...................................................... 51

4. DISCUSSION................................................................................................................................. 54

4.1. OVERVIEW ............................................................................................................................... 54

4.2. MAJOR FINDINGS ..................................................................................................................... 55

4.2.1. EXCHANGEABLE SODIUM AND SODICITY 55

4.2.2. SOIL PH AND ALKALINISATION 57

4.2.3. MINERAL PRECIPITATION 59

4.3. MINOR FINDINGS ..................................................................................................................... 63

4.3.1. EFFECT ON EXCHANGEABLE BASE CATIONS 63

4.3.2. HEAVY METALS AND METALLOIDS 64

4.3.3. VOLATILISATION OF NITROGEN FERTILISERS 67

4.4. MANAGEMENT IMPLICATIONS ................................................................................................ 67

4.4.1. OTHER IRRIGATION PROJECTS IN THE REGION 68

4.4.2. REHABILITATION AFTER DECOMMISSIONING 69

5. CONCLUSION ............................................................................................................................... 70

6. LITERATURE CITED .................................................................................................................... 72

APPENDIX A: CORRELATION ANALYSIS ............................................................................................ 90

SOIL PROPERTIES AND LEAF NUTRIENT COMPOSITION ................................................................... 90

LEAF NUTRIENT COMPOSITION ......................................................................................................... 92

APPENDIX B: WEB-PHREEQ OUTPUT DATA ................................................................................ 93

DEWATERING SURPLUS ..................................................................................................................... 93

SENSITIVITY ANALYSIS 98

FERTIGATION MIXTURE ................................................................................................................... 103

SENSITIVITY ANALYSIS 108

APPENDIX C: ASH ALKALINITY ....................................................................................................... 114

STANDARDISATION OF STRONG ACID WITH WEAK BASE .............................................................. 114

COMPARISON OF FINELY MILLED AND NON-MILLED SAMPLES ...................................................... 114

NEUTRALISING EXCESS ALKALINITY TO PREVENT SOIL ALKALINISATION ................................... 114


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APPENDIX D: CLUSTER ANALYSIS – STRATIFYING IRRIGATION PIVOTS ...................................... 117

RESULTS ........................................................................................................................................... 117

TEST 1: ELECTRICAL CONDUCTIVITY AND EXCHANGEABLE ALUMINIUM PERCENTAGE 124

TEST 2: CALCIUM CARBONATE EQUIVALENT AND CARBON/NITROGEN RATIO 125

TEST 3: CLAY CONTENT AND ARSENIC CONCENTRATION 127

APPENDIX E: SOIL CARBONATE DETERMINATION – A METHODOLOGY DEVELOPMENT EXERCISE

.......................................................................................................................................................... 130

METHODS AND MATERIALS ............................................................................................................. 130

METHOD 1 130

METHOD 2 130

PRECISION AND ACCURACY OF METHODS 1 AND 2 132

RESULTS ........................................................................................................................................... 133

DISCUSSION ...................................................................................................................................... 136

APPENDIX F: SOIL TEXTURE ........................................................................................................... 138

IRRIGATION WATER QUALITY AND RISK FOR CLAY DISPERSION .................................................. 139

CALCULATING THE SODIUM ADSORPTION RATIO 139

APPENDIX G: FUTURE SOIL AND LEAF MONITORING RECOMMENDATIONS ................................. 141

SAMPLING FREQUENCY – TEMPORAL VARIABILITY ....................................................................... 141

SAMPLE SIZE – SPATIAL VARIABILITY ............................................................................................ 143

SOIL SAMPLING DEPTH 144

APPENDIX H: CHANGES WITH TIME OF EXCHANGEABLE SODIUM PERCENTAGE (ESP) AND

SODICITY OF HAMERSLEY AGRICULTURE PROJECT SOILS ............................................................ 145


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LIST OF FIGURES

Figure 1. Hypoxia and salinity interact to decrease the growth of wheat plants (Barrett-

Lennard, 2003). Pots on the left were hypoxic (N2-bubbled for 33 days); pots on

the right were aerated: (a) Zero salt in the solutions; (b) 20 mol m-3 (or 0.02 M)

NaCl in solutions; (c) 120 mol m-3 (or 0.12 M) NaCl in the solutions. ....................... 4

Figure 2. Regional location of Marandoo and Hope Downs iron ore mine. Image adapted

from Rio Tinto Iron Ore (2008). ................................................................................................ 8

Figure 3. Cross-sectional schematic of the Southern Fortescue geology (Rio Tinto Iron

Ore, 2008). .......................................................................................................................................... 9

Figure 4. Location of 17 irrigation pivots at the Hamersley Agricultural Project (HAP).

.............................................................................................................................................................. 11

Figure 5. Schematic diagram of a 50 ha irrigation pivot and soil and leaf sampling

locations in each pivot at the Hamersley Agricultural Project (HAP)..................... 12

Figure 6. Mean (± SE) soil particle size distribution – sand (red), silt (green) and clay

(blue) content at 0-10 cm and 20-30 cm for samples collected in March 2014,

based on Pivots 1-8, 10 and 11. .............................................................................................. 20

Figure 7. Changes (left) and trends (right) in electrical conductivity (EC, dS/m) at 0-10

cm and 20-30 cm between baseline (blue) and December 2013 (red) periods. 22

Figure 8. Changes (left) and trends (right) in pHCa at 0-10 cm and 20-30 cm between

baseline (blue) and December 2013 (red) periods. ....................................................... 23

Figure 9. Changes (left) and trends (right) in CaCO3 equivalent (CCE, %) at 0-10 cm and

20-30 cm between baseline (blue) and December 2013 (red) periods. ................ 23

Figure 10. Changes (left) and trends (right) in soil organic carbon (OC, %) at 0-10 cm

and 20-30 cm between baseline (blue) and December 2013 (red) periods. ....... 24

Figure 11. Changes (left) and trends (right) in nitrate-nitrogen (NO3-N, mg/kg) at 0-10


Figure 12. Changes (left) and trends (right) in total N content (%) at 0-10 cm and 20-30

cm between baseline (blue) and December 2013 (red) periods. ............................. 25

Figure 13. Changes (left) and trends (right) in carbon/nitrogen (C/N) ratio at 0-10 cm


Figure 14. Changes (left) and trends (right) in Colwell P concentration (mg/kg) at 0-10


Figure 15. Changes (left) and trends (right) in total P concentration (mg/kg) at 0-10 cm


Figure 16. Changes (left) and trends (right) in phosphorus retention index (PRI) at 0-10


Figure 17. Changes (left) and trends (right) in the effective cation exchange capacity

(ECEC, cmol(+)/kg) at 0-10 cm and 20-30 cm between baseline (blue) and

December 2013 (red) periods. ................................................................................................ 28

Figure 18. Changes (left) and trends (right) in exchangeable Ca concentration

(cmol(+)/kg) at 0-10 cm and 20-30 cm between baseline (blue) and December

2013 (red) periods. ...................................................................................................................... 29

Figure 19. Changes (left) and trends (right) in exchangeable Ca percentage (%) at 0-10



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Figure 20. Changes (left) and trends (right) in exchangeable Mg concentration


2013 (red) periods. ..................................................................................................................... 30

Figure 21. Changes (left) and trends (right) in exchangeable Mg percentage (%) at 0-10


Figure 22. Changes (left) and trends (right) in exchangeable Na concentration


2013 (red) periods. ..................................................................................................................... 31

Figure 23. Changes (left) and trends (right) in exchangeable Na percentage (ESP, %) at

0-10 cm and 20-30 cm between baseline (blue) and December 2013 (red)

periods. ............................................................................................................................................. 32

Figure 24. Changes (left) and trends (right) in exchangeable K concentration

(cmol(+)/kg) at 0-10 cm between baseline (blue) and December 2013 (red)

periods. ............................................................................................................................................. 33

Figure 25. Changes (left) and trends (right) in exchangeable K percentage (%) at 0-10


Figure 26. Changes (left) and trends (right) in exchangeable Al percentage (%) at 0-10

cm between baseline (blue) and December 2013 (red) periods. ............................. 34

Figure 27. Changes (left) and trends (right) in chromium levels (mg/kg) at 0-10 cm and

20-30 cm between baseline (blue) and December 2013 (red) periods. ............... 34

Figure 28. Significant changes (left) and trends (right) in the overall mean phosphorus

concentration (P, %) in leaf tissue between March (blue) and December 2013

(red). .................................................................................................................................................. 36

Figure 29. Significant changes (left) and trends (right) in the overall mean calcium

concentration (Ca, %) in leaf tissue between March (blue) and December 2013

(red). .................................................................................................................................................. 36

Figure 30. Significant changes (left) and trends (right) in the overall mean magnesium

concentration (Mg, %) in leaf tissue between March (blue) and December 2013

(red). .................................................................................................................................................. 37

Figure 31. Significant changes (left) and trends (right) in the overall mean sulphur

concentration (S, %) in leaf tissue between March (blue) and December 2013

(red). .................................................................................................................................................. 37

Figure 32. Significant changes (left) and trends (right) in the overall mean zinc

concentration (Zn, mg/kg) in leaf tissue between March (blue) and December

2013 (red). ...................................................................................................................................... 38

Figure 33. Significant changes (left) and trends (right) in the overall mean boron

concentration (B, mg/kg) in leaf tissue between March (blue) and December

2013 (red). ...................................................................................................................................... 38

Figure 34. Significant changes (left) and trends (right) in the overall mean nitrate-

nitrogen concentration (NO3-N, mg/kg) in leaf tissue between March (blue) and

December 2013 (red). ................................................................................................................ 39

Figure 35. Significant changes (left) and trends (right) in the overall mean cadmium

concentration (Cd, ug/kg) in leaf tissue between March (blue) and December

2013 (red). ...................................................................................................................................... 39


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Figure 36. Significant changes (left) and trends (right) in the overall mean chromium

concentration (Cr, mg/kg) in leaf tissue between March (blue) and December

2013 (red)........................................................................................................................................ 40

Figure 37. Significant changes (left) and trends (right) in the overall mean lead

concentration (Pb, ug/kg) in leaf tissue between March (blue) and December

2013 (red)........................................................................................................................................ 40

Figure 38. Significant changes (left) and trends (right) in the overall mean nickel

concentration (Ni, mg/kg) in leaf tissue between March (blue) and December

2013 (red)........................................................................................................................................ 41

Figure 39. Linear relationship between pHCa and exchangeable Mg concentration

(cmol(+)/kg) at 0-10 cm. ........................................................................................................... 42

Figure 40. Linear relationship between pHCa and exchangeable Mg percentage (%)at 0-

10 cm. ................................................................................................................................................ 42

Figure 41. Linear relationship between exchangeable Mg percentage (%) and Ca

percentage (%) at 0-10 cm (left) and 20-30 cm (right)................................................ 42

Figure 42. Linear relationship between pH (CaCl2) and exchangeable K percentage (%)

at 0-10 cm. ....................................................................................................................................... 42

Figure 43. Linear relationship between exchangeable Mg percentage (%) and K

percentage (%) at 0-10 cm. ...................................................................................................... 42

Figure 44. Linear relationship between exchangeable Na percentage (ESP, %) and Ca

percentage (%) at 0-10 cm (left) and 20-30 cm (right)................................................ 43

Figure 45. Linear relationship between electrical conductivity (EC, dS/m) and

exchangeable Na concentration (cmol(+)/kg) at 0-10 cm (left) and 20-30 cm

(right). ............................................................................................................................................... 43

Figure 46. Linear relationship between exchangeable Na concentration (cmol(+)/kg)

and Na percentage (ESP, %) at 0-10 cm (left) and 20-30 cm (right). ..................... 44

Figure 47. Linear relationship between exchangeable Al concentration (cmol(+)/kg)

and Al percentage (%) at 0-10 cm (left) and 20-30 cm (right). ................................ 44

Figure 48. Linear relationship between chromium concentrations (Cr, mg/kg) in leaf

tissue and soil at 0-10 cm (left) and 20-30 cm (right), based on Span 3 results

from March to December 2013 with December 2013 outliers included (top) and

removed (bottom). ....................................................................................................................... 48

Figure 49. Comparing a good combination (left) and a bad combination (right) of three

variables used in two-step cluster analysis .................................................................... 118

Figure 50. Test 1 clustering of 10 active irrigation pivots at the HAP, based on electrical

conductivity (EC, dS/m) and exchangeable Al percentage (%) and colour coded:

Cluster 1 (red), Cluster 2 (blue), Cluster 3 (purple) and Cluster 4 (green). ...... 119

Figure 51. Test 2 clustering of 10 active irrigation pivots at the HAP, based on CaCO3

equivalent (CCE, %) and carbon/nitrogen (C/N) ratio and colour coded: Cluster

1 (red), Cluster 2 (blue), Cluster 3 (purple) and Cluster 4 (green)....................... 119

Figure 52. Test 3 clustering of 10 active irrigation pivots at the HAP, based on clay

content (%) and arsenic concentration (mg As/kg) and colour coded: Cluster 1

(red), Cluster 2 (blue), Cluster 3 (purple) and Cluster 4 (green). ......................... 120

Figure 53. Gross irrigation volumes used at each irrigation pivot at the Hamersley

Agricultural Project (HAP) for the baseline (blue) period, and periods between


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baseline and December 2013 (red), and baseline and February 2014 (green),

based on unpublished data (Rio Tinto Iron Ore, 2014). ............................................ 123

Figure 54. Level of importance of variables (EC and exchangeable Al %) used in test 1

............................................................................................................................................................ 124

Figure 55. Description of cluster size and mean values for variables (EC and

exchangeable Al %) in test 1.................................................................................................. 124

Figure 56. Comparing the distribution of individual clusters in test 1 (EC and

exchangeable Al %) with the overall distribution of the December 2013 soil

(20-30 cm layer, Span 3) data set ........................................................................................ 125

Figure 57. Level of importance of variables (CCE and C/N ratio) used in test 2 ............. 126

Figure 58. Description of cluster size and mean values for variables (CCE and C/N ratio)

in test 2 ........................................................................................................................................... 126

Figure 59. Comparing the distribution of individual clusters in test 2 (CCE and C/N

ratio) with the overall distribution of the December 2013 soil (20-30 cm layer,

Span 3) data set ........................................................................................................................... 127

Figure 60. Level of importance of variables (clay % and As concentration) used in test 3

............................................................................................................................................................ 128

Figure 61. Description of cluster size and mean values for variables (clay % and As

concentration) in test 3 ........................................................................................................... 128

Figure 62. Comparing the distribution of individual clusters in test 3 (clay % and As

concentration) with the overall distribution of the December 2013 soil (20-30

cm layer, Span 3) data set ....................................................................................................... 129

Figure 63. Standard curve for Method 2 using 0.4 M CH3COOH and CaCO3 weights of 10,

30, 50, 70, 90, 110 and 130 mg (linear relationship: y = 0.767x + 4.409 and R2 =

0.996) .............................................................................................................................................. 132

Figure 64. Standard curve for Method 2 using 0.4 M CH3COOH and CaCO3 weights of 10,

30, 50, 70, 90, 110 and 130 mg (linear relationship: y = 0.772x + 4.435 and R2 =

0.999) .............................................................................................................................................. 133

Figure 65. Calcium carbonate equivalent (CCE, %) of eight September 2013 and

December 2013 soil samples determined by Methods 1 and 2 .............................. 135

Figure 66. Correlation between pH (CaCl2) and calcium carbonate equivalent (CCE, %)

of eight September and December 2013 soil samples determined using Method

1 (left) and Method 2 (right) ................................................................................................. 135

Figure 67. Comparing expected and reported CCE (%) values from Method 1 (blue) and

Method 2 (red) from standard additions of 0, 2, 4, 6, 8 and 10 mg CaCO3/g .... 136

Figure 68. Mean monthly rainfall and temperature at Wittenoom in the Pilbara region,

Western Australia ...................................................................................................................... 142

Figure 69. Trends in mean exchangeable sodium percentage (ESP,% ± SEM) at two

depths (0-10 cm and 20-30 cm)of the soil profile of the HAP area. ...................... 145

Figure 70. Mean (± SEM) of exchangeable Na (meq/100g of soil) of a total of 28 soil

samples taken at two depths, 0-10 cm (14 samples) and 20-30 cm (14 samples).

............................................................................................................................................................ 146

Figure 71. Mean (± SEM) of exchangeable sodium percentage (ESP) of a total of 28 soil

samples taken at 0-10 cm (14 samples) and 20-30 cm (14 samples). ................. 146


nutrition

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LIST OF TABLES

Table 1. One-way ANOVA between Spans 1, 2 and 3 for soil properties at 0-10 cm and

20-30 cm in December 2013. ................................................................................................... 17

Table 2. One-way ANOVA between Spans 1, 2 and 3 for leaf nutrient composition in

December 2013. ............................................................................................................................ 18

Table 3. Overall mean baseline values and standard errors of soil properties in the 0-10

cm and 20-30 cm soil layers. .................................................................................................... 19

Table 4. Overall mean values and standard errors for soil properties at the 0-10 cm and

20-30 cm soil layer between baseline (October 2012 to February 2013) and

December 2013. ............................................................................................................................ 21

Table 5. Mean values and standard errors of 20 leaf nutrient concentrations between

March and December 2013, based on 10 irrigation pivots and 3 monitoring

spans per pivot. ............................................................................................................................. 35

Table 6. Correlation (R2) between soil properties at 0-10 cm, using only Span 3 data

from baseline to December 2013 based on Pivots 1-8, 10 and 11. .......................... 45

Table 7. Correlation (R2) between soil properties at 20-30 cm, using only Span 3 data

from baseline to December 2013 based on Pivots 1-8, 10 and 11. .......................... 46

Table 8. Correlation (R2) between soil particle size and soil chemical properties at 0-10

cm and 20-30 cm, using Span 3 results based on Pivots 1-8, 10 and 11. .............. 47

Table 9. Composition of dewatering surplus and fertigation mixture sampled in

December 2013. ............................................................................................................................ 49

Table 10. Saturation indices of solid phases in source water (pH 8.2) and fertigation

mixture (pH 8.0) sampled in December 2013, calculated from WEB-PHREEQ

using input values in Table 9 – Al, Cd, Pb and Fe concentrations are half their

detection limit. ............................................................................................................................... 50

Table 11. Saturation indices of carbonates, (hydr)oxides and apatite in source water

and fertigation mixture, modelled at pH 7. ........................................................................ 50

Table 12. Ash content (%) and ash alkalinity (eq/g) of duplicate hay subsamples from

Pivots 1-5 collected in February 2014 for the growth cycle between November

2013 and January 2014 - titration of 50 ml of 0.0494 M HCl and hay ash with

0.05 M Na2CO3. ............................................................................................................................... 51

Table 13. Mean net alkalinity values determined from a mass balance of alkalinity

added from irrigation and removed by hay production for Pivots 1-5 between

November 2013 and January 2014 – based on the total alkalinity of irrigation

water measured in November 2013, using unpublished hay yield and irrigation

data (Rio Tinto Iron Ore, 2014). ............................................................................................. 53

Table 14. Total net alkalinity gained from irrigated pastures for Pivots 1-5 throughout

the study period from October 2012 to January 2014 – assuming relatively

constant total alkalinity of irrigation water, using unpublished hay yield and

irrigation data (Rio Tinto Iron Ore, 2014). ........................................................................ 53

Table 15. Comparing mean leaf nutrient concentrations of C. gayana in December 2013

with "normal"/adequate nutrient concentration ranges for C. gayana and

Phalaris aquatica. ......................................................................................................................... 64


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Table 16. Comparing December 2013 concentrations in leaf tissue of C. gayana with

maximum tolerable levels (National Research Council, 2000) and overall

toxicity limits (Underwood and Suttle, 1999) for ruminant livestock (e.g., such

as cattle and sheep). .................................................................................................................... 66

Table 17. Correlation (R2) between leaf nutrient composition and soil properties at 0-

10 cm, using only Span 3 data from March to December 2013................................. 90

Table 18. Correlation (R2) between leaf nutrient composition and soil properties at 20-

30 cm, using only Span 3 data from March to December 2013................................. 91

Table 19. Correlation (R2) between leaf composition, using only Span 3 data from

March to December 2013 ......................................................................................................... 92

Table 20. Standardisation of ~0.05 M HCl with 0.05 M Na2CO3 ............................................. 114

Table 21. Comparing ash alkalinity and net alkalinity results for finely milled and non-

milled duplicate hay subsamples for Pivots 1-5 between November 2013 and

January 2014 ................................................................................................................................ 115

Table 22. Calculated excess total alkalinity (mg CaCO3/L) in irrigation water to be

neutralised by sulphuric acid (H2SO4) to cease soil alkalinisation, based on

results in Table 17 ..................................................................................................................... 115

Table 23. Designated cluster memberships for irrigation pivots using a specified 4-

cluster solution, based on Span 3 soil properties from December 2013 and

particle size from March 2014 at the 20-30 cm layer. Colour coding is

independent for each test. ...................................................................................................... 118

Table 24. One-way ANOVA between clusters for soil properties at 20-30 cm, using Span

3 December 2013 results ........................................................................................................ 121

Table 25. Preliminary CaCO3 content (mg) and calculated CaCO3 equivalent (CCE, %) of

unknown samples using Method 2 ..................................................................................... 133

Table 26. Comparing calcium carbonate equivalent (CCE, %) assessed by Method 1 and

2 for eight September 2013 and December 2013 soil samples and their

respective soil pHCa values – pivot and span denoted as ‘P’ and ‘S’, respectively

............................................................................................................................................................ 134

Table 27. Comparing expected soil calcium carbonate equivalent (CCE, %) and reported

values from Methods 1 and 2 using standard additions of 0, 2, 4, 6, 8, 10 and

100 mg CaCO3/g .......................................................................................................................... 135

Table 28. Texture classifications from physical observations of texture and particle size

analysis using mid-infrared reflectance (MIR) spectroscopy (Rayment and

Lyons, 2011, p. 80) ..................................................................................................................... 138

Table 29. Water quality guidelines for risk of dispersion, crusting and swelling of soils

with > 30 % swelling clay (California Fertilizer Association, 1995). The location

of the HAP in this framework is indicated by the highlighted row. ...................... 139

1

1. INTRODUCTION

1.1. SALINITY AND SODICITY IN IRRIGATED AGRICULTURE

Groundwater constitutes an important water source for irrigated agriculture in

arid and semi-arid regions where rainfall is often low, unreliable, and frequently

exceeded manifold by annual evapotranspiration (Scanlon et al., 2006). However, due to

population growth and increased demand for water, pronounced water scarcity,

particularly in developing countries, has led to an increasing trend of poor irrigation

practice (e.g., overuse of saline-sodic groundwater, over-pumping of coastal aquifers,

insufficient subsoil drainage) and the continual degradation of irrigated land (Ondrasek

et al., 2011).

According to the Food and Agriculture Organization (FAO) and the United

Nations Educational, Scientific, and Cultural Organization (UNESCO), secondary

salinisation, alkalinisation (sodification) and waterlogging has affected more than 50%

of existing irrigated land worldwide (Pessarakli and Szabolcs, 1999, Martinez-Beltran

and Manzur, 2005, Sundquist, 2007). In total, about 6.5% of the global land area (or more

than 830 million hectares) is salt-affected (Shahid et al., 2011, Hasanuzzaman et al.,

2013), with many millions of hectares abandoned annually as a consequence (Szabolcs,

1988). Indeed, virtually all irrigated land in semi-arid and arid lands will, to some degree,

be susceptible to problems with salinity and sodicity (alkalinity) as salts accumulate

through time (Pessarakli and Szabolcs, 1999).

The secondary formation of salt-affected soils substantially affects the growth

and productivity of irrigated crops and pastures worldwide (Bernstein, 1975, Pessarakli

and Szabolcs, 1999, Pitman and Läuchli, 2002, Rengasamy, 2002, Wang et al., 2011, Javid

et al., 2012). In Australia, sodicity is most prevalent (Rengasamy and Olsson, 1991),

affecting over 80% of irrigated soils, with about 72% alkaline-sodic and 11% non-

alkaline sodic (Northcote and Skene, 1972). Consequently, the poor physical and

chemical conditions induced by sodicity may partly explain why the productivity of

Australian crops is generally low (Rengasamy and Olsson, 1993).

To gain a better understanding, the various implications of salinity, sodicity and

alkalinity for plant growth will be discussed in some detail. This is followed by a section

on the scope and objectives of this research.


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1.2. SALT AFFECTED SOILS AND IMPLICATIONS FOR PLANT GROWTH

Salt-affected soils comprise several groups, including saline, saline-sodic, and

sodic soils (Pessarakli and Szabolcs, 1999, Ondrasek et al., 2011):

i. saline soils develop under high concentrations of soluble salts (electrical

conductivity in saturated extract (ECe) > 4 dS/m) and low exchangeable Na

percentage (ESP < 15);

ii. saline-sodic soils develop under high electrolyte concentrations (> 4 dS/m) and

high ESP (> 15); and,

iii. sodic soils develop under low electrolyte concentrations (< 4 dS/m) and high ESP

(> 15%) which may, or may not, be alkaline (pH > 8.5) depending on the

predominant type of Na salt – e.g., Na2CO3 and NaHCO3 are capable of alkaline

hydrolysis, while Na2SO4 and NaCl are neutral.

Alkalinisation and sodification are distinct processes where alkalinisation per se

is generally defined by an increase in pH and pH buffering capacity (see Section 1.2.2).

However, due to the presence of Na2CO3 and NaHCO3, alkalinisation and sodification

often co-occur, resulting in alkaline-sodic soils. Therefore, salinisation, sodification and

alkalinisation are three serious sources of soil degradation in irrigated agriculture and

their various effects on plant growth are discussed.

1.2.1. SALINITY AND SALT STRESS

Salt-affected soils usually have low biological activity (Pessarakli and Szabolcs,

1999). Salinity suppresses the growth of all plants, but the degree to which they are

affected by salinity varies widely among species (Parida and Das, 2005) and with the

degree of waterlogging in the root zone (Barrett-Lennard and Shabala, 2013). The

injurious effect of salt on plants directly involves both osmotic and ionic stresses (Yang

et al., 2009), including: (1) increased osmotic potential of the soil solution which

decreases water availability to plants (i.e., low water potential) and thus causes

physiological drought (Pessarakli and Szabolcs, 1999); (2) nutrient imbalance and

disruption of intracellular ion homeostasis in plants by ion displacement and deficiency

(Parida and Das, 2005); and (3) toxicity from the uptake of excessive Na+ and Cl- ions

which damages plant cells and tissues (Bernstein, 1975, Warrence and Bauder, 2001,

Munns, 2002, Phocaides, 2007, Saqib et al., 2008, Yang et al., 2008a, Evelin et al., 2009,

Yang et al., 2009). Excessive levels of salinity may eventually cause death as


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photosynthesis, protein synthesis, and energy and lipid metabolism become severely

impaired (Sudhir and Murthy, 2004, Parida and Das, 2005). Seed germination also

becomes constrained (Vicente et al., 2007).

When coinciding with waterlogged soils, salinity can have serious implications

for plants (Cramer and Hobbs, 2002). Waterlogging often occurs in areas of shallow

watertable or in sodic soils that are poorly drained (Barrett-Lennard and Shabala, 2013)

– this is a common feature in many irrigated agricultural landscapes of arid and semi-

arid Australia (Grieve et al., 1986, McFarlane et al., 1989, Cramer and Hobbs, 2002,

McFarlane and Williamson, 2002, Shaw et al., 2013). Waterlogging induces soil hypoxia

which causes: (1) a rapid decline in root and shoot growth, and subsequent senescence

of roots; (2) impaired solute movement and nutrient uptake; and, (3) decreased stomatal

conductance and/or leaf water potentials (Barrett-Lennard, 2003). Under both saline

and waterlogged conditions, plant growth and survival may also greatly diminish from

increased ion toxicity (i.e., Na+ and Cl-, Figure 1; Barrett-Lennard and Shabala, 2013).

1.2.2. SODICITY AND ALKALI STRESS

Sodic (alkali) stress may similarly exert both osmotic stress and ion injury, but

with the added effect of high pH (Yang et al., 2008a, Yang et al., 2009, Davis et al., 2012).

Additionally, the presence of high Na+ may severely damage soil structure and reduce

permeability (see Section 1.2.3; Warrence and Bauder, 2001, Bethune and Batey, 2002).

It is understood that sodicity and alkalinity could inflict greater damage to crop and

pasture production than salinity alone (Javid et al., 2012).

Many authors recognise that it is the high pH (> 8.5) and buffer capacity in

alkaline-sodic soils that causes injurious effects on plants (Pessarakli and Szabolcs, 1999,

Wang et al., 2008, Yang et al., 2008a, Yang et al., 2008b, Wang et al., 2011, Li et al., 2012).

Severely alkaline-sodic conditions may inhibit plant growth by disrupting

photosynthetic activities (Yang et al., 2008b) and anti-oxidative metabolism (Kukavica

et al., 2013), and also interfere with ion uptake and mineral nutrition (Peng et al., 2008).

Alkalinity may suppress the solubility and hence the bioavailability of various macro-

(e.g., Ca, N and P) and micro-nutrients (e.g., Cu, Fe, Mg, Ni, and Zn; Umali, 1993) which

becomes a principle limiting factor to plant productivity (Marlet et al., 1998). High levels

of alkalinity may also constrain seed germination (Guan et al., 2009, Li et al., 2010) and

seedling survival (Liu et al., 2010, Patil et al., 2012).


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Moreover, elevated bicarbonate concentrations could significantly depress root

growth by pH-buffering in the root apoplast and direct interference on root metabolism

(Peiter et al., 2001, Javid et al., 2012). The presence of substantial amounts of bicarbonate

may also cause Ca to precipitate and this effectively increases the ESP or SAR which may

exacerbate soil structural problems (ANZECC/ARMCANZ, 2000).

Figure 1. Hypoxia and salinity interact to decrease the growth of wheat plants (Barrett-Lennard,

2003). Pots on the left were hypoxic (N2-bubbled for 33 days); pots on the right were aerated:

(a) Zero salt in the solutions; (b) 20 mol m-3 (or 0.02 M) NaCl in solutions; (c) 120 mol m-3 (or

0.12 M) NaCl in the solutions.


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1.2.3. DETERIORATION OF SOIL PHYSICAL CONDITION

Both salinisation and sodification frequently co-occur, however the destructive

effects of sodicity only become evident after rainfall or irrigation when soluble salts are

leached (Rengasamy and Olsson, 1991). Elevated concentrations of Na+ causes soil

particles to deflocculate and colloidal particles to clog pores, resulting in reduced

permeability to air and water (Bernstein, 1975, Marlet et al., 1998). Once sodic soils dry

after wetting, surface crusting and hard-setting occurs (Condom et al., 1999), further

reducing infiltration and hydraulic conductivity, and increasing soil erodibility

(Pessarakli and Szabolcs, 1999). Such poor physical conditions impair plant

development by restricting root growth, making it difficult to obtain water and nutrients

(Stearns et al., 2005, Saqib et al., 2008). Seedling emergence and establishment also

become severely inhibited (Warrence and Bauder, 2001). As mentioned, poor drainage

may also cause temporary flooding or waterlogging which further impairs root function

and ultimately inhibits plant growth and survival (Marlet et al., 1998, Alam, 1999,

Warrence and Bauder, 2001, Barrett-Lennard, 2003).

1.3. PROJECT SCOPE

1.3.1. MINE DEWATERING IN THE PILBARA

In the Pilbara region of Western Australia, iron ore production has rapidly

developed due to growing markets in the major East Asian steel-producing countries,

China, Japan, South Korea and Taiwan (Economic Consulting Services, 2007, Department

of Water, 2010b). However, as iron ore operations continue to expand, the cumulative

impacts of mining on the environment need to be assessed.

Many iron ore mines in the region now extract ore from below the watertable

(Barber and Jackson, 2011) and, to maintain dry working conditions, an array of deep

wells surrounding the mine are pumped at high rates to locally depress the groundwater

level and this is referred to as ‘mine dewatering’ (Woldai and Taranik, 2008). Mine

dewatering consequently generates significant volumes of water that frequently exceed

mine use requirements and thus require disposal. This may involve aquifer reinjection,

transfer to other industrial locations, utilisation as irrigation water for agriculture, and

contingency discharges to nearby environments, such as rivers and streams


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(Department of Water, 2013). However, as below-watertable mining continues to

develop, dewatering will present major environmental and socio-economic challenges in

the region, particularly if in-stream discharge becomes increasingly practiced in the

future.

1.3.2. THE HAMERSLEY AGRICULTURAL PROJECT

The Hamersley Agricultural Project (HAP) is an irrigated forage scheme that

commenced operation in October 2012 as a mitigation strategy for Rio Tinto, in the

central Pilbara region of Western Australia. The HAP utilises surplus water generated

from the Marandoo Mine Phase 2 (MMP2) project as the source water for irrigating

Rhodes grass (Chloris gayana) for hay production (Hamersley Iron Pty Ltd, 2011) and

provides an exceptional opportunity for drought-proofing pastoral stations in the region

(The Chamber of Minerals and Energy of Western Australia, 2012). Accordingly,

contingency discharges from Marandoo mine to the Southern Fortescue River that began

in July 2012 have reduced from continuous to intermittent flow in favour of water use in

the HAP.

While contingency discharges may be substantially reduced, in-stream discharge

at Rio Tinto’s Hope Downs iron ore mine is required for flow supplementation in Weeli

Wolli Creek (Environmental Protection Authority, 2001). There is consequently

significant attention towards the potential cumulative impacts of in-stream discharge on

the ecosystem (e.g., Wetland Research & Management, 2010, Crisalis International Pty

Ltd, 2012), particularly for creek-bed and sediment properties and hence for stream and

riparian vegetation. Thus, as part of on-going research, the present study explores the

effects of source water from Marandoo mine on irrigated soils and pasture growth at the

HAP.

1.3.3. RESEARCH OBJECTIVES

The study explores the implications of irrigation of water derived from mine

dewatering at Marandoo for soil condition and pasture growth and nutrition at the HAP.

Soil and leaf tissue data were examined for key changes and trends between baseline

(October 2012 to February 2013) and December 2013 sampling periods. This research

also aims to identify factors that need to be considered to develop sustainable irrigation

and soil management practices for long-term pasture productivity (20 years).


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The main objectives of this study are to:

I. identify how irrigation water has altered (a) soil properties and, (b) leaf

composition of pasture species at the HAP – based on time trends for data from

baseline to December 2013 sampling periods;

II. examine the composition of irrigation water (with added nutrients) to determine

possible precipitate formation; and,

III. based on Objectives (I) and (II), identify any potential for adverse changes in

long-term pasture productivity and soil management.

Recommendations on future soil and leaf monitoring were also developed and

are provided in Appendix G.


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2. MATERIALS AND METHODS

2.1. STUDY AREA

The HAP area is located below the plains of the Karijini National Park and is

approximately 6 km west of the Marandoo mine (22o34’12.45” S, 118o00’32.99” E) in the

central Pilbara region of Western Australia (Figure 2). The study area falls within a 570

km2 upper catchment of the Southern Fortescue River Valley, bounded to the east and

west by rugged hills of outcropping Brockman Iron and Marra Mamba Iron Formations

(Figure 3). Proterozoic rocks of the Hamersley Province constitute the geology of this

catchment, with the Marra Mamba Iron Formation as the basal stratigraphic unit and ore

deposit at Marandoo. Beyond this unit are widely distributed Cainozoic rocks and soils,

including erosional remnants of the Wittenoom Formation and sequences of tertiary

sediments (Rio Tinto Iron Ore, 2008).

Figure 2. Regional location of Marandoo and Hope Downs iron ore mine. Image adapted from

Rio Tinto Iron Ore (2008).


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The climate is arid tropical, with distinct summer wet and winter dry seasons

(Gentilli, 1972, Rio Tinto Iron Ore, 2008). Summer extends from October to April, with

highest monthly mean temperatures of 36-43oC, while winter extends from May to

September, with highest monthly mean temperatures of 26-34oC (Bureau of

Meteorology, 2014a). During summer, maximum daily temperatures can exceed 47oC

(Rio Tinto Iron Ore, 2008). Rainfall mainly occurs between December and March, but is

generally low, erratic and unreliable. The average annual rainfall recorded from the

Bureau of Meteorology weather stations in the vicinity are approximately 363 mm at

Tom Price, 394 mm at Marandoo and 461 mm at Wittenoom.

Figure 3. Cross-sectional schematic of the Southern Fortescue geology (Rio Tinto Iron Ore,

2008).

However, as the Pilbara coastline is prone to cyclonic activity (averaging five

tropical cyclones annually; Department of Parks and Wildlife, 2013), cyclones passing

inland may generate localised heavy rain with over 100-200 mm falling within 24 hours

(Mattiske Consulting Pty Ltd, 2008, Rio Tinto Iron Ore, 2008). This consequently causes

major flooding and considerable erosion. In contrast, drought is common throughout the

region as evaporation rates exceed average annual rainfall by about 7.5 fold (Van

Vreeswyk et al., 2004). The average annual pan evaporation rate in the study region

ranges from approximately 2800 mm to 3200 mm, based on at least 10 years of records

from 1975 to 2005 (Bureau of Meteorology, 2014a).

In response to climatic regimes, most rivers and tributaries in the region are

ephemeral and tend to associate with shallow alluvial aquifers or sub-surface

groundwater storages (Department of Water, 2010a). Vegetation communities along the

local tributaries are consequently adapted to these conditions, comprising woodlands of

Acacia citrinoviridis interspersed with occasional patches of Eucalyptus victrix and E.

xerothermica (Mattiske Consulting Pty Ltd, 2008). In the valley, the vegetation varies


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from open woodlands of E. victrix and A. citrinoviridis to shrublands of A. pyrifolia and A.

bivenosa on alluvial flats.

2.1.1. IRRIGATION PIVOTS

The HAP comprises 17 centre-pivot irrigation systems that cover approximately

850 ha, including a 7 ha pivot for native seeds, within an area of 2800 ha (Figure 4). The

pasture chosen (C. gayana) is a subtropical (C4) perennial that is grown throughout the

year for stock feed. Water is supplied at approximately 60-80 ML/d – i.e., 80 ML/d

between October and March and 60 ML/d between April and September for an estimated

duration of approximately 20 years, based on the life of MMP2 and supply of dewatering

surplus (Hamersley Iron Pty Ltd, 2011). Low concentrations of liquid fertilisers are also

applied with irrigation water to meet daily crop requirements.

Figure 4. Location of 17 irrigation pivots at the Hamersley Agricultural Project (HAP).

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2.2. SAMPLING AND MONITORING SOIL, LEAF TISSUE, AND WATER QUALITY

The period between October 2012 and February 2013 is defined as the baseline.

During this period, each irrigation pivot was seeded and irrigation commenced, but at

different times for each pivot. Soil and leaf tissue were subsequently sampled on a

quarterly basis in March, July, September/October and December 2013 in the early

stages of the pasture growth cycle. Baseline leaf compositions of the pasture were not

available; therefore the sampling will represent different durations of continuous

irrigation for each pivot.

All sampling was planned and conducted by site personnel and hence a 2-day site

visit was undertaken by the author on the 17th to 18th December, 2013, as a

reconnaissance to understand the site, the monitoring program and sampling protocols.

Soil and leaf tissue samples were collected quarterly from the same marked location with

Figure 5 illustrating the general sampling area. Soils were sampled from depths of 0-10

cm and 20-30 cm, while leaf tissue was taken as random grab samples of whole tops (i.e.,

the whole plant above cutting height). Leaf samples were collected at the beginning

stages of seed head emergence. Soil and leaf tissue samples were bulked from five

locations within the three innermost spans along a transect route (Figure 5). These three

spans (to be referred as 'Span 1, 2, and 3') are ‘Help Lines’ which monitor the varying

rates of irrigation for crop production and soil moisture levels. The rate of irrigation at

Span 1, 2, and 3 was 2X, ½X, and X respectively, where X is the expected (or normal) rate

required for daily crop requirements. Soil and leaf tissue samples were then bulked from

each span for analysis by the CSBP Soil and Plant Analysis Laboratory, Western Australia.

Figure 5. Schematic diagram of a 50 ha irrigation pivot and soil and leaf sampling locations in

each pivot at the Hamersley Agricultural Project (HAP).


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In addition to examining soil chemical properties, mid-infrared reflectance (MIR)

for soil particle size (Rayment and Lyons, 2011, p. 80) was conducted by CSBP for March

2014 samples only. Since weathering is a relatively slow process, soil texture should

remain fairly constant (McCauley et al., 2005). No other data from March 2014 were

included in this study due to limited time.

Irrigation water samples were collected on a monthly basis, from: (1) the

Reduced Pressure Zone (RPZ), representing the quality of source water from the

Marandoo dewatering operations; and, (2) the fertigation mixture. Samples were

retained in an iced cooler for immediate delivery to SGS Australia for water quality

analysis. In this study only November and December 2013 data were used.

2.3. GEOCHEMICAL MODELLING FOR MINERAL PRECIPITATION

To determine possible mineral precipitation from irrigation water, the

saturation index (SI) of solid phases in solution were computed using the aqueous

geochemical model WEB-PHREEQ (Saini-Eidukat, 1999, Saini-Eidukat and Yahin, 1999).

This is a WWW-based version of PHREEQC by Parkhurst and Appelo (1999) for

performing a variety of low-temperature aqueous geochemical calculations. In this

study, quick speciation calculations of single solutions were performed using the quality

of source water and fertigation mixture in December 2013. The saturation index can be

defined as:

SI = logIAP

Ksp [1]

where, IAP and Ksp are the ion activity product (the activities of all the ions) and

the solubility product, respectively. Interpretations for insoluble mineral formation are

as follows:

a. IAP = Ksp, SI = 0 (or -0.2 < SI < 0.2), the solution is saturated with the

mineral (equilibrium);

b. IAP < Ksp, SI < 0, the solution is undersaturated with the mineral

(dissolution); or,

c. IAP > Ksp, SI > 0, the solution is oversaturated with the mineral

(precipitation).


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2.4. ALKALINITY MASS BALANCE AND ASH ALKALINITY DETERMINATION

The amount of alkalinity added in irrigation water and removed in hay yield was

determined to confirm the net change in soil alkalinity. As plants absorb exchangeable

base cations from solution a hydrogen ion is released to maintain electrical balance and

the resulting loss of bases and build-up of hydrogen ions causes acidity in the

rhizosphere (Plaster, 2013). Therefore, it was hypothesised that the soil pH will increase

as long as the rate of alkalinity applied from irrigation water exceeds that removed by

plants. A simple mass balance can be used to describe this relationship:

Net soil alkalinity = water(alkalinity × 𝑣) − hay(alkalinity × 𝑚) [2]

where, v and m are the volume of irrigation water and dry weight of hay yield,

respectively.

The ash alkalinity of hay was determined from duplicate subsamples of dry hay

from Pivots 1 (cut 8), 2 (cut 7), 3 (cut 6), 4 (cut 7) and 5 (cut 7). Samples were collected

in late January 2014 and represent the growth cycle from mid November 2013 to early

January 2014. Dry hay samples were finely milled and weighed to approximately 500 mg

in porcelain crucibles. Samples were then heated to approximately 550oC in a muffle

furnace for 6 hours. Crucibles were left to cool in desiccators and subsequently weighed

to determine the ash content (Poorter et al., 2011):

Ash content = dry weight of ash (g)

dry weight of plant sample (g)× 100 [3]

The ash was treated with 50 ml of 0.05 M hydrochloric acid, HCl, and boiled for a

maximum of 30 seconds to remove the carbonate (Poorter et al., 2011). Once cooled to

room temperature, this was then titrated against 0.05 M sodium carbonate, Na2CO3, with

3 drops of methyl orange as the endpoint indicator. Ash alkalinity was determined from

equation [4]:

Ash alkalinity = 𝑐[HCl]𝑣[HCl]− 𝑐[Na2CO3]𝑣[Na2CO3]

dry weight of plant sample (g) [4]

where, c and v are the concentration and volume of the reagent used,

respectively.


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The acid was prepared by adding 4.9 ml HCl (32%, 10.18 M) to 100 ml deionised

water and diluted to 1 L. The base was prepared by dissolving 5.3 g of Na2CO3

(anhydrous) in 100 ml deionised water and diluting to 1 L. Methyl orange was prepared

by dissolving 0.1 g of the solid in 100 ml deionised water. Prior to determining ash

alkalinity, HCl was standardised against 0.05 M Na2CO3 and the volume of Na2CO3 used

to reach endpoint is summarised in Appendix C.

2.5. EXCHANGEABLE SODIUM PERCENTAGE

In this study, soil ESP was determined by the CSBP Soil and Plant Analysis

Laboratory employing method 15A1 (Rayment and Lyons, 2011). This method however

does not include the removal of soluble salts prior to determination of the exchangeable

cations (Samaraweera, 2015). Therefore, a follow up study on the impact of irrigation on

soil sodicity was undertaken (Samaraweera, 2015; see Appendix H) by determining

exchangeable Na concentrations via two methods: (1) 15A1, that does not include pre-

treatment of soluble salts; and, (2) 15C1, that includes pre-treatment for soluble salts (by

washing with 60% aqueous ethanol and 20% aqueous glycerol). A total of 28 samples

collected from 7 locations at 2 depths from HAP area were analysed.

2.6. DATA ANALYSIS

To determine the effect(s) of irrigation with slightly alkaline and slightly

brackish-sodic water on soil condition, various soil properties and leaf nutrient

concentrations were examined using a series of parametric statistics from the IBM SPSS

Statistics 21 (2012) and Microsoft Excel (2007) software packages. Significant changes

over 15 months between baseline (October 2012 to February 2013) and December 2013

sampling periods were identified using t-Tests and one-way analysis of variance

(ANOVA), and available time series data evaluated for systematic pattern. Bivariate

correlation and linear regression analyses were also performed concurrently to study

possible cause-and-effect relationships amongst: (1) soil chemical properties, (2) soil

particle size and soil chemical properties, (3) soil chemical properties and leaf nutrient

concentrations, and (4) leaf nutrient concentrations (see Appendix A). The calculated

Pearson Correlation Coefficient (r) was converted to the Coefficient of Determination

(R2), with interpretations on correlation strength based on crude estimates – e.g., very


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strong (0.80-0.99), strong (0.60-0.79), moderate (0.40-0.59), weak (0.20-0.39) and very

weak to no correlation (0.00-0.19).


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3. RESULTS

3.1. SIGNIFICANT DIFFERENCES BETWEEN MONITORING SPANS

In general, soil properties and leaf nutrient composition in December 2013 were

not significantly different between Spans 1, 2 and 3 despite varying irrigation rates. Only

soil nitrate-nitrogen (NO3-N) concentrations were significantly different at both 0-10 cm

(P < 0.05) and 20-30 cm soil layers (P < 0.01; Table 1). In leaf tissue, zinc concentrations

were significantly different (P < 0.05; Table 2).

Table 1. One-way ANOVA between Spans 1, 2 and 3 for soil properties at 0-10 cm and 20-30 cm

in December 2013.

Parameters 0-10 cm 20-30 cm

F P F P

Electrical conductivity, EC 0.85 0.44 1.19 0.32

pHCa 2.06 0.15 2.85 0.08 CaCO3 equivalent, CCE 0.10 0.90 0.21 0.81

Organic C, OC 0.30 0.75 1.42 0.26

NO3-N* 5.07 0.01 6.93 0.00

NH4-N 1.24 0.30 2.21 0.13 Total N 0.72 0.49 3.16 0.06

C/N ratio 0.09 0.92 1.23 0.31

Colwell P 1.02 0.37 0.90 0.42

Total P 0.08 0.92 1.75 0.19 Phosphorus retention index, PRI 0.22 0.80 2.42 0.11

Colwell K 0.89 0.42 0.69 0.51

Total K 0.08 0.93 0.02 0.98

Ex. Ca 0.33 0.72 1.25 0.30 Ex. Mg 0.88 0.43 0.61 0.55

Ex. Na 0.10 0.90 0.78 0.47

Ex. K 0.74 0.49 0.30 0.74

Ex. Al 0.18 0.84 0.24 0.79 Effective cation exchange capacity, ECEC 0.48 0.63 1.21 0.31

Ex. Ca percentage 0.67 0.52 0.72 0.50

Ex. Mg percentage 2.49 0.10 0.58 0.56

Ex. Na percentage (ESP) 0.20 0.82 0.06 0.94 Ex. K percentage 0.05 0.95 1.06 0.36

Ex. Al percentage 0.11 0.90 0.17 0.85

As 0.02 0.98 0.04 0.96

Cd 0.25 0.78 1.04 0.37 Cr 0.36 0.70 0.37 0.69

Pb 0.07 0.94 0.03 0.97

*statistical significance (P ≤ 0.01)


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Table 2. One-way ANOVA between Spans 1, 2 and 3 for leaf nutrient composition in December

2013.

Parameter F P Total N 0.83 0.44 P 2.35 0.11 K 0.02 0.98 Ca 0.88 0.42 Mg 2.12 0.14 Na 0.33 0.72 Cl 0.12 0.89 S 1.86 0.18 Cu 2.40 0.11 Fe 1.01 0.38 Mn 0.13 0.88 Zn* 4.00 0.03 B 0.10 0.91 NO3-N 0.55 0.58 Al 0.22 0.81 As 0.04 0.96 Cd 0.69 0.51 Cr 0.16 0.85 Pb 1.91 0.17 Ni 0.01 1.00 *statistical significance (P ≤ 0.05)

3.2. BASELINE SOIL DATA

Soil samples collected from October 2012 to February 2013 constitute the

baseline data, based on 10 irrigation pivots which currently operate (i.e., Pivots 1-8, 10

and 11). Table 3 summarises the overall mean and standard errors across the site, and

determines the statistical significance due to soil depth.

Baseline results showed 10 soil properties were significantly different with soil

depth. Electrical conductivity (EC) at 0-10 cm ranged from 0.05-0.15 dS/m with an

overall mean double that at 20-30 cm (P < 0.01). Soil pHCa (1:5 soil/0.01 M CaCl2 extract)

at 0-10 cm ranged from 4.6-5.1 with an overall mean pHCa of 4.9. Though statistically

significant between depths (P < 0.05), values at 20-30 cm were similar with an overall

mean pHCa of 5.0. Soil organic carbon (OC) content at 0-10 cm was significantly higher

than at 20-30 cm (P < 0.01), with an overall mean of 0.51%, while at 20-30 cm, the overall

mean was 0.30%. The mean carbon/nitrogen (C/N) ratio was significantly higher at 0-

10 cm (P < 0.01) than at 20-30 cm (10.5 versus 6.7).


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Colwell P concentrations at 0-10 cm were more than double (P < 0.01) that at 20-

30 cm (5.5 versus 2.4 mg/kg). Phosphorus retention index (PRI) was 34% lower at 0-10

cm (P < 0.01) than at 20-30 cm.

Table 3. Overall mean baseline values and standard errors of soil properties in the 0-10 cm and

20-30 cm soil layers.

Parameter Units Soil depth

P* 0-10 cm 20-30 cm

Electrical conductivity, EC dS/m 0.08 (± 0.01) 0.04 (± 0.01) < 0.01 pHCa pH units 4.9 (± 0.1) 5.0 (± 0.0) < 0.05 CaCO3 equivalent, CCE % 0.25 (± 0.02) 0.26 (± 0.01) - Organic carbon, OC % 0.51 (± 0.03) 0.30 (± 0.01) < 0.01 NO3-N mg/kg 5.93 (± 0.9) 6.70 (± 1.1) - NH4-N mg/kg 2.53 (± 1.5) 1.20 (± 0.2) - Total N % 0.05 (± 0.00) 0.05 (± 0.00) - C/N ratio 10.5 (± 0.4) 6.7 (± 0.3) < 0.01 Colwell P mg/kg 5.5 (± 0.4) 2.4 (± 0.2) < 0.01 Total P mg/kg 161 (± 10) 136 (± 8) - Phosphorus retention index, PRI

39.8 (± 3.4) 60.4 (± 4.6) < 0.01

Colwell K mg/kg 294 (± 17) 257 (± 11) - Total K mg/kg 2138 (± 147) 2370 (± 154) - Ex. Ca cmol(+)/kg 2.95 (± 0.16) 3.03 (± 0.15) - Ex. Mg cmol(+)/kg 1.15 (± 0.09) 1.07 (± 0.08) - Ex. Na cmol(+)/kg 0.16 (± 0.02) 0.05 (± 0.01) < 0.01 Ex. K cmol(+)/kg 0.71 (± 0.04) 0.63 (± 0.02) - Ex. Al cmol(+)/kg 0.10 (± 0.01) 0.09 (± 0.01) - Effective cation exchange capacity, ECEC

cmol(+)/kg 5.06 (± 0.27) 4.87 (± 0.23) -

Ex. Ca percentage % 58.0 (± 1.3) 62.1 (± 0.9) < 0.05 Ex. Mg percentage % 22.6 (± 1.0) 22.0 (± 0.9) - Ex. Na percentage (ESP) % 3.2 (± 0.4) 1.0 (± 0.1) < 0.01 Ex. K percentage % 14.1 (± 0.4) 13.0 (± 0.4) - Ex. Al percentage % 2.1 (± 0.3) 2.0 (± 0.2) - As mg/kg 15.8 (± 0.5) 15.5 (± 0.5) - Cd ug/kg 63.7 (± 5.7) 52.8 (± 5.7) - Cr mg/kg 230 (± 26) 219 (± 23) - Pb mg/kg 19.1 (± 1.1) 19.6 (± 1.2) - Sand % 63.1 (± 1.0) 62.5 (± 1.2) - Silt % 10.5 (±0.4) 7.6 (± 0.3) < 0.01 Clay % 26.4 (± 1.2) 30.0 (± 1.4) - *statistical significance (2-tail) of differences due to depth based on t-Test assuming unequal variances.

The effective cation exchange capacity (ECEC) was not significantly different

between 0-10 cm and 20-30 cm, with an overall mean of about 5 cmol(+)/kg. The

exchangeable Mg, K, and Al percentages were not significantly different between soil

depths and ranged from 15.6-26.0 %, 11.2-15.9 %, and 1.0-4.1 %, respectively.

Exchangeable Ca concentrations were not significantly different between depths,

but exchangeable Ca percentage was significantly higher at 20-30 cm (P < 0.05), ranging

from 53.8-68.9 % at 0-10 cm, while values at 20-30 cm ranged from 58.9-68.5 %.

Exchangeable Na concentration (0.16 versus 0.05 cmol(+)/kg) and ESP (3.2 versus 1.0

%) were about three times higher at 0-10 cm than at 20-30 cm (P < 0.01).


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20

Trace elements such as Cr, Pb, As, and Cd were not significantly different between

0-10 cm and 20-30 cm, ranging from 45-322 mg Cr/kg, 11.7-24.8 mg Pb/kg, 12.5-17.3

mg As/kg, and 13.3-89.3 ug Cd/kg, respectively. Note that Cr concentrations were

comparatively lower in Pivot 4 (see Figure 27).

Soil particle size ranged from 57.1-68.4 % sand, 6.5-13.2 % silt and 19.2-35.7 %

clay (Figure 6). The proportion of sand and clay did not differ between depths. However,

silt content was significantly higher at 0-10 cm (P < 0.01) than at 20-30 cm (10.5 versus

7.6 %). Further details on soil texture are provided in Table 28, Appendix F.

Figure 6. Mean (± SE) soil particle size distribution – sand (red), silt (green) and clay (blue)

content at 0-10 cm and 20-30 cm for samples collected in March 2014, based on Pivots 1-8,

10 and 11.

3.3. SIGNIFICANT CHANGES AND TRENDS

3.3.1. SOIL PROPERTIES

December 2013 results were benchmarked against baseline data to determine

the overall change in soil properties. This analysis was limited to irrigation pivots

currently in operation, viz Pivots 1-8, 10 and 11. Several soil properties did not

significantly change between the baseline and December 2013 (Table 4), including CCE,

NH4-N, Colwell K, total K, exchangeable Al, As, Cd and Pb concentrations. Figures 7-27

illustrate the mean of each pivot (± SE values of 3 monitoring spans) and the overall mean

of the site for key soil properties, across the time series examined (March, July,

September and December). Trends were based on only Span 3 data to reflect the normal

irrigation rate, representative of the larger HAP irrigation area.

0

10

20

30

40

50

60

70

80

1 2 3 4 5 6 7 8 9 10 11

Par

ticl

e s

ize

dis

trib

uti

on

(%

)

Irrigation pivot

0-10 cm

0

10

20

30

40

50

60

70

80

1 2 3 4 5 6 7 8 9 10 11

Par

ticl

e s

ize

dis

trib

uti

on

(%

)

Irrigation pivot

20-30 cm


nutrition

21

Table 4. Overall mean values and standard errors for soil properties at the 0-10 cm and 20-30

cm soil layer between baseline (October 2012 to February 2013) and December 2013.

Parameter Units Depth (cm) Baseline Dec-13 P*

Electrical conductivity, EC

dS/m 0-10 0.08 (± 0.01) 0.15 (± 0.02) < 0.01

20-30 0.04 (± 0.01) 0.18 (± 0.01) < 0.01 pHCa pH units 0-10 4.9 (± 0.1) 6.9 (± 0.1) < 0.01 20-30 5.0 (± 0.0) 5.5 (± 0.1) < 0.01 CaCO3 equivalent, CCE % 0-10 0.25 (± 0.02) 0.28 (± 0.02) - 20-30 0.26 (± 0.01) 0.26 (± 0.02) - Organic carbon, OC % 0-10 0.51 (± 0.03) 0.66 (± 0.04) < 0.01 20-30 0.30 (± 0.01) 0.34 (± 0.01) - NO3-N mg/kg 0-10 5.93 (± 0.90) 4.57 (± 0.81) - 20-30 6.70 (± 1.10) 0.60 (± 0.10) < 0.01 NH4-N mg/kg 0-10 2.53 (± 1.5) 1.50 (± 0.13) - 20-30 1.20 (± 0.2) 1.17 (± 0.07) - Total N % 0-10 0.05 (± 0.00) 0.07 (± 0.00) < 0.01 20-30 0.05 (± 0.00) 0.06 (± 0.00) < 0.01 C/N ratio 0-10 10.5 (± 0.5) 8.9 (± 0.4) < 0.05 20-30 6.7 (± 0.3) 5.8 (± 0.2) < 0.05 Colwell P mg/kg 0-10 5.5 (± 0.4) 5.8 (± 0.4) - 20-30 2.4 (± 0.2) 1.1 (± 0.1) < 0.01 Total P mg/kg 0-10 161 (± 10) 197 (± 8) < 0.05 20-30 136 (± 8) 172 (± 6) < 0.01 Phosphorus retention index, PRI

0-10 39.8 (± 3.4) 50.4 (± 3.2) < 0.05

20-30 60.4 (± 4.6) 87.8 (±5.8) < 0.01 Colwell K mg/kg 0-10 294 (± 17) 332 (± 14) - 20-30 257 (± 11) 267 (± 13) - Total K mg/kg 0-10 2138 (± 147) 1889 (± 66) - 20-30 2370 (± 154) 2044 (± 67) - Ex. Ca cmol(+)/kg 0-10 2.95 (± 0.16) 4.18 (± 0.24) < 0.01 20-30 3.03 (± 0.15) 3.56 (± 0.18) < 0.05 Ex. Mg cmol(+)/kg 0-10 1.15 (± 0.09) 3.19 (± 0.16) < 0.01 20-30 1.07 (± 0.08) 1.66 (± 0.07) < 0.01 Ex. Na cmol(+)/kg 0-10 0.16 (± 0.02) 0.46 (± 0.04) < 0.01 20-30 0.05 (± 0.01) 0.48 (± 0.03) < 0.01 Ex. K cmol(+)/kg 0-10 0.71 (± 0.04) 0.83 (± 0.04) < 0.05 20-30 0.63 (± 0.02) 0.64 (± 0.03) - Ex. Al cmol(+)/kg 0-10 0.10 (± 0.01) 0.08 (± 0.01) - 20-30 0.09 (± 0.01) 0.10 (± 0.01) - Effective cation exchange capacity, ECEC

cmol(+)/kg 0-10 5.06 (± 0.27) 8.73 (± 0.45) < 0.01

20-30 4.87 (± 0.23) 6.44 (± 0.28) < 0.01 Ex. Ca percentage % 0-10 58.0 (± 1.3) 47.6 (± 0.6) < 0.01 20-30 62.1 (± 0.9) 55.0 (± 0.7) < 0.01 Ex. Mg percentage % 0-10 22.6 (± 1.0) 36.6 (± 0.5) < 0.01 20-30 22.0 (± 0.9) 25.9 (± 0.5) < 0.01 Ex. Na percentage (ESP) % 0-10 3.2 (± 0.4) 5.2 (± 0.3) < 0.01 20-30 1.0 (± 0.1) 7.4 (± 0.2) < 0.01 Ex. K percentage % 0-10 14.1 (± 0.4) 9.6 (± 0.1) < 0.01 20-30 13.0 (± 0.4) 10.0 (± 0.2) < 0.01 Ex. Al percentage % 0-10 2.1 (± 0.3) 0.9 (± 0.2) < 0.01 20-30 2.0 (± 0.2) 1.7 (± 0.2) - As mg/kg 0-10 15.8 (± 0.5) 16.2 (± 0.5) - 20-30 15.5 (± 0.5) 15.3 (± 0.4) - Cd ug/kg 0-10 63.7 (± 5.7) 72.8 (± 2.2) - 20-30 52.8 (± 5.7) 58.7 (± 1.2) - Cr mg/kg 0-10 230 (± 26) 351 (± 22) < 0.01 20-30 219 (± 23) 305 (± 15) < 0.01 Pb mg/kg 0-10 19.1 (± 1.1) 20.2 (± 0.8) - 20-30 19.6 (± 1.2) 19.3 (± 0.5) - *statistical significance (1-tail) based on t-Test assuming unequal variances.

Soil EC significantly increased from 0.08 to 0.15 dS/m at 0-10 cm (P < 0.01) and

from 0.04 to 0.18 dS/m at 20-30 cm (P < 0.01; Figure 7). Relative to the baseline, there


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22

was a consistent increase in the overall mean EC at both 0-10 cm and 20-30 cm, except

in July 2013 at 0-10 cm which appears to have significantly dropped back to baseline

values.

Figure 7. Changes (left) and trends (right) in electrical conductivity (EC, dS/m) at 0-10 cm

and 20-30 cm between baseline (blue) and December 2013 (red) periods.

Soil pHCa significantly increased by 2 pH units at 0-10 cm (P < 0.01), but only by

0.5 pH units at 20-30 cm (P < 0.01; Figure 8). Mean pHCa values in December were circum-

neutral in the 0-10 cm surface layer, while remaining slightly acidic in the subsoil. Trends

were consistent although increases in pHCa at 20-30 cm were only gradual. Nonetheless,

at 0-10 cm, the overall mean pHCa significantly increased within 4 months of irrigation

between baseline and March (P < 0.01).

Soil CCE did not significantly change between baseline and December (Figure 9).

However, time trends indicated CCE to have peaked in July at both depths (P < 0.01).

Soil OC significantly increased at 0-10 cm from 0.51 to 0.66 % (P < 0.051; Figure

10), but did not significantly change at 20-30 cm. However, trends at 20-30 cm showed

an increase in the overall mean between baseline and July, but then a subsequent decline.

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

1 2 3 4 5 6 7 8 9 10 11

EC (

dS/

m)

Irrigation pivot

0-10 cm

0.00

0.05

0.10

0.15

0.20

Baseline Mar Jul Sep Dec

EC (

dS/

m)

0-10 cm

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

1 2 3 4 5 6 7 8 9 10 11

EC (

dS/

m)

Irrigation pivot

20-30 cm

0.00

0.05

0.10

0.15

0.20

0.25


EC (

dS/

m)

20-30 cm


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23

Figure 8. Changes (left) and trends (right) in pHCa at 0-10 cm and 20-30 cm between baseline

(blue) and December 2013 (red) periods.

Figure 9. Changes (left) and trends (right) in CaCO3 equivalent (CCE, %) at 0-10 cm and 20-30

cm between baseline (blue) and December 2013 (red) periods.

4

5

6

7

8

1 2 3 4 5 6 7 8 9 10 11

pH

Ca

Irrigation pivot

0-10 cm

4

5

6

7

8


pH

Ca

0-10 cm

4.0

4.5

5.0

5.5

6.0

6.5

1 2 3 4 5 6 7 8 9 10 11

pH

Ca

Irrigation pivot

20-30 cm

4.4

4.6

4.8

5.0

5.2

5.4

5.6


pH

Ca

20-30 cm

0.1

0.2

0.3

0.4

0.5

1 2 3 4 5 6 7 8 9 10 11

CC

E (%

)

Irrigation pivot

0-10 cm

0.0

0.1

0.2

0.3

0.4


CC

E (%

)

0-10 cm

0.1

0.2

0.3

0.4

0.5

1 2 3 4 5 6 7 8 9 10 11

CC

E (%

)

Irrigation pivot

20-30 cm

0.0

0.1

0.2

0.3

0.4


CC

E (%

)

20-30 cm


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24

Figure 10. Changes (left) and trends (right) in soil organic carbon (OC, %) at 0-10 cm and 20-

30 cm between baseline (blue) and December 2013 (red) periods.

Figure 11. Changes (left) and trends (right) in nitrate-nitrogen (NO3-N, mg/kg) at 0-10 cm


0.0

0.2

0.4

0.6

0.8

1.0

1.2

1 2 3 4 5 6 7 8 9 10 11

OC

(%

)

Irrigation pivot

0-10 cm

0.0

0.2

0.4

0.6

0.8

1.0


OC

(%

)

0-10 cm

0.15

0.20

0.25

0.30

0.35

0.40

0.45

1 2 3 4 5 6 7 8 9 10 11

OC

(%

)

Irrigation pivot

20-30 cm

0.0

0.1

0.2

0.3

0.4

0.5

0.6


OC

(%

)

20-30 cm

0

4

8

12

16

20

1 2 3 4 5 6 7 8 9 10 11

NO

3-N

(m

g/kg

)

Irrigation pivot

0-10 cm

0

2

4

6

8

10


NO

3-N

(m

g/kg

)

0-10 cm

0

4

8

12

16

20

24

1 2 3 4 5 6 7 8 9 10 11

NO

3-N

(m

g/kg

)

Irrigation pivot

20-30 cm

0

1

2

3

4

5


NO

3-N

(m

g/kg

)

20-30 cm


nutrition

25

The overall mean NO3-N concentration significantly decreased from 6.70 to 0.60

mg/kg at 20-30cm (P < 0.01; Figure 11) between baseline and December, but was not

significantly different at 0-10 cm. Mean concentrations were variable at 0-10 cm, but had

decreased consistently at 20-30 cm.

Total N significantly increased from an overall mean of 0.05 to 0.07 % at 0-10 cm

(P < 0.01) and to 0.06% at 20-30 cm (P < 0.01; Figure 12). Trends showed little

consistency over time, but patterns were similar at depth – values significantly dropped

in July 2013 before increasing to December.

Figure 12. Changes (left) and trends (right) in total N content (%) at 0-10 cm and 20-30 cm

between baseline (blue) and December 2013 (red) periods.

Soil C/N ratio significantly decreased between baseline and December at both

depths (P < 0.05; Figure 13). However, trends show mean C/N ratios peaked in July

before decreasing to December.

The overall mean Colwell P concentration at 0-10 cm was not significantly

different between baseline and December 2013, but at 20-30 cm, it significantly

decreased by more than half the mean value (P < 0.01; Figure 14). Trends showed little

consistency, but the overall mean decreased between March and September.

0.00

0.02

0.04

0.06

0.08

0.10

1 2 3 4 5 6 7 8 9 10 11

Tota

l N (

%)

Irrigation pivot

0-10 cm

0.00

0.02

0.04

0.06

0.08


Tota

l N (

%)

0-10 cm

0.00

0.02

0.04

0.06

0.08

0.10

1 2 3 4 5 6 7 8 9 10 11

Tota

l N (

%)

Irrigation pivot

20-30 cm

0.00

0.02

0.04

0.06

0.08


Tota

l N (

%)

20-30 cm


nutrition

26

Figure 13. Changes (left) and trends (right) in carbon/nitrogen (C/N) ratio at 0-10 cm and 20-

30 cm between baseline (blue) and December 2013 (red) periods.

Figure 14. Changes (left) and trends (right) in Colwell P concentration (mg/kg) at 0-10 cm


2

6

10

14

18

1 2 3 4 5 6 7 8 9 10 11

C/N

rat

io

Irrigation pivot

0-10 cm

0

5

10

15

20


C/N

rat

io

0-10 cm

4

5

6

7

8

9

1 2 3 4 5 6 7 8 9 10 11

C/N

rat

io

Irrigation pivot

20-30 cm

0

5

10

15

20


C/N

rat

io

20-30 cm

0

2

4

6

8

10

1 2 3 4 5 6 7 8 9 10 11

Co

lwe

ll P

(m

g/kg

)

Irrigation pivot

0-10 cm

0

2

4

6

8


Co

lwe

ll P

(m

g/kg

)

0-10 cm

0

1

2

3

4

1 2 3 4 5 6 7 8 9 10 11

Co

lwe

ll P

(m

g/kg

)

Irrigation pivot

20-30 cm

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5


Co

lwe

ll P

(m

g/kg

)

20-30 cm


nutrition

27

Total P concentration significantly increased by 22% of the overall mean at 0-10

cm (P < 0.05) and by 26% at 20-30 cm (P < 0.01; Figure 15). These increases in total P

were consistent at both depths, except from September to December at 20-30 cm.

Figure 15. Changes (left) and trends (right) in total P concentration (mg/kg) at 0-10 cm and

20-30 cm between baseline (blue) and December 2013 (red) periods.

Soil PRI significantly increased by about 27% at 0-10 cm (P < 0.05) and 45% at

20-30 cm (P < 0.01; Figure 16) between baseline and December. Trends at 0-10 cm

showed the overall mean to increase between March and July before stabilising to

December; at 20-30 cm this was somewhat variable.

The overall mean ECEC significantly increased by about 73% at 0-10 cm (P <

0.01) and by 32% at 20-30 cm (P < 0.01; Figure 17), with relatively consistent increases

over time between baseline and December.

Exchangeable Ca concentrations significantly increased by about 42% at 0-10 cm

(P < 0.01) and 17% at 20-30 cm (P < 0.05; Figure 18). Trends were consistent at 0-10 cm,

but less noticeable at 20-30 cm.

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11

Tota

l P (

mg/

kg)

Irrigation pivot

0-10 cm

100

140

180

220


Tota

l P (

mg/

kg)

0-10 cm

50

100

150

200

250

1 2 3 4 5 6 7 8 9 10 11

Tota

l P (

mg/

kg)

Irrigation pivot

20-30 cm

100

120

140

160

180

200


Tota

l P (

mg/

kg)

20-30 cm


nutrition

28

Figure 16. Changes (left) and trends (right) in phosphorus retention index (PRI) at 0-10 cm


Figure 17. Changes (left) and trends (right) in the effective cation exchange capacity (ECEC,

cmol(+)/kg) at 0-10 cm and 20-30 cm between baseline (blue) and December 2013 (red)

periods.

20

30

40

50

60

70

80

90

1 2 3 4 5 6 7 8 9 10 11

PR

I

Irrigation pivot

0-10 cm

0

10

20

30

40

50

60

70


PR

I

0-10 cm

20

40

60

80

100

120

140

1 2 3 4 5 6 7 8 9 10 11

PR

I

Irrigation pivot

20-30 cm

0

20

40

60

80

100


PR

I

20-30 cm

0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 11

ECEC

(cm

ol(

+)/k

g)

Irrigation pivot

0-10 cm

0

2

4

6

8

10


ECEC

(cm

ol(

+)/k

g)

0-10 cm

0

2

4

6

8

10

1 2 3 4 5 6 7 8 9 10 11

ECEC

(cm

ol(

+)/k

g)

Irrigation pivot

20-30 cm

0

2

4

6

8


ECEC

(cm

ol(

+)/k

g)

20-30 cm


nutrition

29

Figure 18. Changes (left) and trends (right) in exchangeable Ca concentration (cmol(+)/kg) at

0-10 cm and 20-30 cm between baseline (blue) and December 2013 (red) periods.

Figure 19. Changes (left) and trends (right) in exchangeable Ca percentage (%) at 0-10 cm


0

1

2

3

4

5

6

1 2 3 4 5 6 7 8 9 10 11

Ex. C

a (c

mo

l(+)

/kg)

Irrigation pivot

0-10 cm

2.0

2.5

3.0

3.5

4.0

4.5


Ex. C

a (c

mo

l(+)

/kg)

0-10 cm

0

1

2

3

4

5

6

1 2 3 4 5 6 7 8 9 10 11

Ex. C

a (c

mo

l(+)

/kg)

Irrigation pivot

20-30 cm

2.0

2.5

3.0

3.5

4.0

Baseline Mar Jul Sep DecEx

. Ca

(cm

ol(

+)/k

g)

20-30 cm

30

40

50

60

70

80

1 2 3 4 5 6 7 8 9 10 11

Ex. C

a (%

)

Irrigation pivot

0-10 cm

30

35

40

45

50

55

60

65


Ex. C

a (%

)

0-10 cm

45

50

55

60

65

70

75

1 2 3 4 5 6 7 8 9 10 11

Ex. C

a (%

)

Irrigation pivot

20-30 cm

50

52

54

56

58

60

62

64


Ex. C

a (%

)

20-30 cm


nutrition

30

However, exchangeable Ca percentage significantly decreased from 58.0 to 47.6

% at 0-10 cm (P < 0.01) and from 62.1 to 55.0 % at 20-30 cm (P < 0.01; Figure 19). At 20-

30 cm, the decrease from baseline to March was most pronounced (P < 0.01) –

subsequent decreases were then gradual.

Exchangeable Mg concentration significantly increased by nearly 3 times the

overall mean at 0-10 cm (P < 0.01), while increasing by 55% at 20-30 cm (P < 0.01; Figure

20). Trends showed a strong consistent increase in concentrations at both depths.

Figure 20. Changes (left) and trends (right) in exchangeable Mg concentration (cmol(+)/kg)

at 0-10 cm and 20-30 cm between baseline (blue) and December 2013 (red) periods.

Exchangeable Mg percentage also significantly increased from an overall mean

of 22.6 to 36.6 % at 0-10 cm (P < 0.01) and from 22.0 to 25.9 % at 20-30 cm (P < 0.01;

Figure 21). Trends were consistent, but there was greater variability among Pivots for

the 20-30 cm depth.

0

1

2

3

4

5

1 2 3 4 5 6 7 8 9 10 11

Ex. M

g (c

mo

l(+)

/kg)

Irrigation pivot

0-10 cm

0

1

2

3

4


Ex. M

g (c

mo

l(+)

/kg)

0-10 cm

0.0

0.5

1.0

1.5

2.0

2.5

1 2 3 4 5 6 7 8 9 10 11

Ex. M

g (c

mo

l(+)

/kg)

Irrigation pivot

20-30 cm

0.0

0.5

1.0

1.5

2.0


Ex. M

g (c

mo

l(+)

/kg)

20-30 cm


nutrition

31

Figure 21. Changes (left) and trends (right) in exchangeable Mg percentage (%) at 0-10 cm


Figure 22. Changes (left) and trends (right) in exchangeable Na concentration (cmol(+)/kg) at

0-10 cm and 20-30 cm between baseline (blue) and December 2013 (red) periods.

10

20

30

40

50

1 2 3 4 5 6 7 8 9 10 11

Ex. M

g (%

)

Irrigation pivot

0-10 cm

20

25

30

35

40


Ex. M

g (%

)

0-10 cm

14

18

22

26

30

1 2 3 4 5 6 7 8 9 10 11

Ex. M

g (%

)

Irrigation pivot

20-30 cm

20

22

24

26

28

30


Ex. M

g (%

)

20-30 cm

0.0

0.2

0.4

0.6

0.8

1.0

1 2 3 4 5 6 7 8 9 10 11

Ex. N

a (c

mo

l(+)

/kg)

Irrigation pivot

0-10 cm

0.0

0.1

0.2

0.3

0.4

0.5

0.6


Ex. N

a (c

mo

l(+)

/kg)

0-10 cm

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1 2 3 4 5 6 7 8 9 10 11

Ex. N

a (c

mo

l(+)

/kg)

Irrigation pivot

20-30 cm

0.0

0.1

0.2

0.3

0.4

0.5

0.6


Ex. N

a (c

mo

l(+)

/kg)

20-30 cm


nutrition

32

Overall mean exchangeable Na concentrations (determined without pre-washing

of samples) significantly increased nearly 3 times at 0-10 cm (P < 0.01) and over 9 times

at 20-30 cm (P < 0.01; Figure 22). Trends at 0-10 cm were somewhat variable, but

relatively consistent at 20-30 cm. Like many other parameters, significant increases at

both depths were already observable within 4 months of irrigation (P < 0.01) from

baseline to March. By contrast, at 20-30 cm, subsequent increases were gradual before

significantly increasing to December (P < 0.01).

Overall mean ESP levels, based on samples without pre-washing for soluble salts,

significantly increased from 3.2 to 5.2 % at 0-10 cm (P < 0.01) and 1.0 to 7.4 % at 20-30

cm (P < 0.01; Figure 23). Trends were similar to that of exchangeable Na concentration.

Figure 23. Changes (left) and trends (right) in exchangeable Na percentage (ESP, %) at 0-10

cm and 20-30 cm between baseline (blue) and December 2013 (red) periods.

Exchangeable K concentration significantly increased at only 0-10 cm from an

overall mean of 0.71 to 0.83 cmol(+)/kg (P < 0.05; Figure 24), but no distinct trend was

apparent between baseline and December.

0

2

4

6

8

1 2 3 4 5 6 7 8 9 10 11

ESP

(%

)

0-10 cm

0

2

4

6

8


ESP

(%

)

0-10 cm

0

2

4

6

8

10

1 2 3 4 5 6 7 8 9 10 11

ESP

(%

)

20-30 cm

0

2

4

6

8

10


ESP

(%

)

20-30 cm


nutrition

33

Figure 24. Changes (left) and trends (right) in exchangeable K concentration (cmol(+)/kg) at


By contrast, the overall mean exchangeable K percentage significantly decreased

from 14.1 to 9.6 % at 0-10 cm (P < 0.01) and from 13.0 to 10.0 % at 20-30 cm (P < 0.01;

Figure 25). A consistent decrease in the mean was observed at both depths.

Figure 25. Changes (left) and trends (right) in exchangeable K percentage (%) at 0-10 cm and


Exchangeable Al percentage significantly decreased at 0-10 cm (Figure 26).

Trends show mean percentages at 0-10 cm were consistently below the baseline, with

exception to values in September.

0.4

0.6

0.8

1.0

1.2

1 2 3 4 5 6 7 8 9 10 11

Ex. K

(cm

ol(

+)/k

g)

Irrigation pivot

0-10 cm

0.0

0.2

0.4

0.6

0.8

1.0


Ex. K

(cm

ol(

+)/k

g)

0-10 cm

6

8

10

12

14

16

18

1 2 3 4 5 6 7 8 9 10 11

Ex. K

(%

)

Irrigation pivot

0-10 cm

6

8

10

12

14

16


Ex. K

(%

)

0-10 cm

6

8

10

12

14

16

18

1 2 3 4 5 6 7 8 9 10 11

Ex. K

(%

)

Irrigation pivot

20-30 cm

6

8

10

12

14


Ex. K

(%

)

20-30 cm


nutrition

34

Figure 26. Changes (left) and trends (right) in exchangeable Al percentage (%) at 0-10 cm

between baseline (blue) and December 2013 (red) periods.

Chromium levels in the soil significantly increased by 53% at 0-10 cm (P < 0.01)

and by 39% at 20-30 cm (P < 0.01; Figure 27). However, trends showed no consistency

in these increases until an abrupt increase in the mean by 70% between September and

December at both depths (P < 0.01).

Figure 27. Changes (left) and trends (right) in chromium levels (mg/kg) at 0-10 cm and 20-30

cm between baseline (blue) and December 2013 (red) periods.

0

1

2

3

4

5

6

1 2 3 4 5 6 7 8 9 10 11

Ex. A

l (%

)

Irrigation pivot

0-10 cm

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5


Ex. A

l (%

)

0-10 cm

0

100

200

300

400

500

600

1 2 3 4 5 6 7 8 9 10 11

Cr

(mg/

kg)

Irrigation pivot

0-10 cm

0

50

100

150

200

250

300

350

400


Cr

(mg/

kg)

0-10 cm

0

100

200

300

400

500

1 2 3 4 5 6 7 8 9 10 11

Cr

(mg/

kg)

Irrigation pivot

20-30 cm

0

50

100

150

200

250

300

350


Cr

(mg/

kg)

20-30 cm


nutrition

35

3.3.2. LEAF NUTRIENT COMPOSITION

Leaf nutrient composition in December 2013 was benchmarked against those in

March, based on Pivots 1-8, 10 and 11. Statistical analyses using t-Tests show that leaf N,

K, Na, Cl, Cu, Fe, Mn, and As concentrations were not significantly different. Table 5

summarises the mean values and standard errors for leaf nutrients in March and

December 2013, with significant changes and trends illustrated in Figures 28-38.

The overall mean leaf P concentration significantly increased from 0.14 to 0.19

% (P < 0.01) between March and December (Figure 28). However, time series analysis

showed the mean P concentration failed to increase in October sampling relative to that

in July and December.

Table 5. Mean values and standard errors of 20 leaf nutrient concentrations between March and

December 2013, based on 10 irrigation pivots and 3 monitoring spans per pivot.

Parameter Units Mar-13 Dec-13 P*

Total N % 2.0 (± 0.1) 2.1 (± 0.1) -

P % 0.14 (± 0.01) 0.19 (± 0.01) < 0.01

K % 1.8 (± 0.1) 1.9 (± 0.1) -

Ca % 0.42 (± 0.02) 0.56 (± 0.01) < 0.01

Mg % 0.17 (± 0.01) 0.22 (± 0.01) < 0.01

Na % 0.38 (± 0.03) 0.47 (± 0.04) -

Cl % 1.5 (± 0.1) 1.6 (± 0.1) -

S % 0.21 (± 0.01) 0.31 (± 0.01) < 0.01

Cu mg/kg 7.0 (± 0.4) 7.3 (± 0.3) -

Fe mg/kg 100 (± 3) 113 (± 6) -

Mn mg/kg 166 (± 18) 208 (± 16) -

Zn mg/kg 22.9 (± 1.6) 32.4 (± 1.7) < 0.01

B mg/kg 4.9 (± 0.3) 8.1 (± 0.6) < 0.01 NO3-N mg/kg 137 (± 32) 47 (± 15) < 0.05 Al mg/kg 38.0 (± 2.1) 31.5 (± 2.1) < 0.05 As ug/kg 74.7 (± 5.5) 74.6 (± 5.9) - Cd ug/kg 15.6 (± 1.6) 26.4 (± 2.9) < 0.01 Cr mg/kg 0.64 (± 0.03) 4.6 (± 0.4) < 0.01 Pb ug/kg 22.6 (± 1.6) 84.0 (± 4.0) < 0.01 Ni mg/kg 4.0 (± 0.2) 2.0 (± 0.2) < 0.01 *statistical significance (2-tail) based on t-Test assuming unequal variances.


nutrition

36

Figure 28. Significant changes (left) and trends (right) in the overall mean phosphorus

concentration (P, %) in leaf tissue between March (blue) and December 2013 (red).

Leaf Ca concentration significantly increased from an overall mean of 0.42 to 0.56

% (P < 0.01) between March and December (Figure 29). Mean concentrations were

consistently higher in months following March (P < 0.01).

Leaf Mg concentration significantly increased from an overall mean of 0.17 to

0.22 % (P < 0.01) between March and December (Figure 30). Trends showed Mg

concentrations in July, October and December were consistently higher than in March (P

< 0.01).

Figure 29. Significant changes (left) and trends (right) in the overall mean calcium

concentration (Ca, %) in leaf tissue between March (blue) and December 2013 (red).

0.10

0.15

0.20

0.25

0.30

1 2 3 4 5 6 7 8 9 10 11

P (

%)

Irrigation pivot0.00

0.05

0.10

0.15

0.20

0.25

Mar Jul Oct Dec

P (

%)

0.2

0.3

0.4

0.5

0.6

0.7

1 2 3 4 5 6 7 8 9 10 11

Ca

(%)

Irrigation pivot0.0

0.2

0.4

0.6

0.8

Mar Jul Oct Dec

Ca

(%)


nutrition

37

Figure 30. Significant changes (left) and trends (right) in the overall mean magnesium

concentration (Mg, %) in leaf tissue between March (blue) and December 2013 (red).

Leaf S significantly increased from an overall mean of 0.21 to 0.31 % (P < 0.01)

between March and December (Figure 31). Trends were also consistent with those of

leaf Mg.

Figure 31. Significant changes (left) and trends (right) in the overall mean sulphur

concentration (S, %) in leaf tissue between March (blue) and December 2013 (red).

Zinc concentrations significantly increased by 41% (P < 0.01) between March

and December (Figure 32). However, mean concentrations were not different in July, but

were significantly higher in October and December (P < 0.01).

0.10

0.15

0.20

0.25

0.30

1 2 3 4 5 6 7 8 9 10 11

Mg

(%)


0.05

0.10

0.15

0.20

0.25

Mar Jul Oct Dec

Mg

(%)

0.10

0.15

0.20

0.25

0.30

0.35

0.40

1 2 3 4 5 6 7 8 9 10 11

S (%

)


0.05

0.10

0.15

0.20

0.25

0.30

0.35

Mar Jul Oct Dec

S (%

)


nutrition

38

Figure 32. Significant changes (left) and trends (right) in the overall mean zinc concentration

(Zn, mg/kg) in leaf tissue between March (blue) and December 2013 (red).

Overall mean leaf B concentrations increased significantly by 65% (P < 0.01)

between March and December (Figure 33). Trends showed a consistent increase

although concentrations in October were significantly lower than those in July and

December (P < 0.05).

Figure 33. Significant changes (left) and trends (right) in the overall mean boron

concentration (B, mg/kg) in leaf tissue between March (blue) and December 2013 (red).

Leaf NO3-N concentrations significantly decreased by about 66% (P < 0.05)

between March and December (Figure 34). Trends showed mean concentrations in

October were significantly lower than that in March (P < 0.05), but not with July and

December – March, July and December concentrations were not significantly different.

10

15

20

25

30

35

40

45

50

1 2 3 4 5 6 7 8 9 10 11

Zn (

mg/

kg)

Irrigation pivot0

10

20

30

40

50

Mar Jul Oct Dec

Zn (

mg/

kg)

0

2

4

6

8

10

12

14

1 2 3 4 5 6 7 8 9 10 11

B (

mg/

kg)

Irrigation pivot0

2

4

6

8

10

Mar Jul Oct Dec

B (

mg/

kg)


nutrition

39

Figure 34. Significant changes (left) and trends (right) in the overall mean nitrate-nitrogen

concentration (NO3-N, mg/kg) in leaf tissue between March (blue) and December 2013 (red).

Overall mean Cd concentrations in leaf tissue significantly increased by about

70% (P < 0.01) between March and December (Figure 35). However, this was not

consistent as mean concentrations in October were similar to those in March and

significantly lower relative to July and December (P < 0.05).

Figure 35. Significant changes (left) and trends (right) in the overall mean cadmium

concentration (Cd, ug/kg) in leaf tissue between March (blue) and December 2013 (red).

Leaf Cr concentrations significantly increased by over 7 times the overall mean

(P < 0.01) between March and December (Figure 36). Concentrations in March and July

were relatively similar, but significantly lower in October (P < 0.01). However, in

December, mean concentrations considerably increased (P < 0.01) by about 15 times

that in October.

0

50

100

150

200

250

300

350

400

1 2 3 4 5 6 7 8 9 10 11

NO

3-N

(m

g/kg

)

Irrigation pivot0

50

100

150

200

250

Mar Jul Oct Dec

NO

3-N

(m

g/kg

)

0

10

20

30

40

50

1 2 3 4 5 6 7 8 9 10 11

Cd

(u

g/kg

)

Irrigation pivot0

5

10

15

20

25

30

Mar Jul Oct Dec

Cd

(u

g/kg

)


nutrition

40

Figure 36. Significant changes (left) and trends (right) in the overall mean chromium

concentration (Cr, mg/kg) in leaf tissue between March (blue) and December 2013 (red).

Leaf Pb concentrations significantly increased nearly 4 times the overall mean (P

< 0.01) between March and December (Figure 37). Trends showed a significant increase

in the mean from March to July (P < 0.01), but concentrations in October and December

were not significantly different.

Figure 37. Significant changes (left) and trends (right) in the overall mean lead concentration

(Pb, ug/kg) in leaf tissue between March (blue) and December 2013 (red).

Leaf Ni concentration significantly decreased by half the overall mean (P < 0.01)

between March and December (Figure 38). Mean concentrations were consistently

lower in July, October and December (P < 0.01) but were not significantly different to one

another.

0

1

2

3

4

5

6

7

1 2 3 4 5 6 7 8 9 10 11

Cr

(mg/

kg)

Irrigation pivot0

1

2

3

4

5

6

Mar Jul Oct Dec

Cr

(mg/

kg)

0

20

40

60

80

100

120

140

1 2 3 4 5 6 7 8 9 10 11

Pb

(u

g/kg

)

Irrigation pivot0

20

40

60

80

100

120

Mar Jul Oct Dec

Pb

(u

g/kg

)


nutrition

41

Figure 38. Significant changes (left) and trends (right) in the overall mean nickel

concentration (Ni, mg/kg) in leaf tissue between March (blue) and December 2013 (red).

3.4. CORRELATION AND LINEAR REGRESSION ANALYSIS

Bivariate correlation and linear regression analyses were conducted using

results from baseline to December 2013 to determine possible cause-and-effect

relationships amongst: (1) soil chemical properties (Tables 6 and 7), (2) soil particle size

and soil chemical properties (Table 8), (3) soil chemical properties and leaf nutrient

concentrations (Table 17 and 18), and (4) leaf nutrient concentrations (Table 19, see

Appendix A). Only Span 3 data from Pivots 1-8, 10 and 11 were used. All moderate to

very strong correlations were significant at P < 0.01 level (2-tailed).

3.4.1. SOIL PROPERTIES

The soil pHCa at 0-10 cm was strongly-positively correlated with exchangeable

Mg concentration (R2 = 0.75; Figure 39) and Mg percentage (R2 = 0.70; Figure 40). There

was no correlation at 20-30 cm. Exchangeable Ca and Na had weak to no correlation with

pHCa.

Exchangeable Ca percentage was very strongly-negatively correlated with

exchangeable Mg percentage at both depths (R2 = 0.81 at 0-10 cm, R2 = 0.74 at 20-30 cm,

Figure 41). At 0-10 cm, exchangeable K percentage was moderately-negatively

correlated with soil pHCa (R2 = 0.45; Figure 42), but weakly-negatively correlated with

exchangeable Mg percentage (R2 = 0.37; Figure 43). Exchangeable K percentage was not

correlated with ESP.

0

1

2

3

4

5

6

1 2 3 4 5 6 7 8 9 10 11

Ni (

mg/

kg)

Irrigation pivot0

1

2

3

4

5

Mar Jul Oct Dec

Ni (

mg/

kg)


nutrition

42

Figure 39. Linear relationship between pHCa

and exchangeable Mg concentration

(cmol(+)/kg) at 0-10 cm.

Figure 40. Linear relationship between pHCa

and exchangeable Mg percentage (%)at 0-10

cm.

Figure 41. Linear relationship between exchangeable Mg percentage (%) and Ca percentage

(%) at 0-10 cm (left) and 20-30 cm (right).

Figure 42. Linear relationship between pH

(CaCl2) and exchangeable K percentage (%)

at 0-10 cm.

Figure 43. Linear relationship between

exchangeable Mg percentage (%) and K

percentage (%) at 0-10 cm.

Soil ESP was moderately-negatively correlated with exchangeable Ca percentage

at both depths (R2 = 0.44 at 0-10 cm, R2 = 0.47 at 20-30 cm; Figure 44), but was not

correlated with exchangeable Mg percentage (data not shown).

R² = 0.7490

1

2

3

4

5

4 5 6 7 8

Ex. M

g (c

mo

l(+)

/kg)

pHCa

0-10 cm

R² = 0.695910

20

30

40

50

4 5 6 7 8

Ex. M

g (%

)

pHCa

0-10 cm

R² = 0.8057

30

40

50

60

70

80

10 20 30 40 50

Ex. C

a (%

)

Ex. Mg (%)

0-10 cm

R² = 0.7401

40

50

60

70

80

10 15 20 25 30 35

Ex. C

a (%

)

Ex. Mg (%)

20-30 cm

R² = 0.4537

5

8

11

14

17

20

4 5 6 7 8

Ex. K

(%

)

pHCa

0-10 cm

R² = 0.372

5

8

11

14

17

20

10 20 30 40 50

Ex. K

(%

)

Ex. Mg (%)

0-10 cm


nutrition

43

Figure 44. Linear relationship between exchangeable Na percentage (ESP, %) and Ca

percentage (%) at 0-10 cm (left) and 20-30 cm (right).

A decrease in exchangeable Ca may be associated with CaCO3 precipitation, but

analysis indicated no correlation between soil CCE and exchangeable Ca percentage (R2

= 0.08 at 0-10 cm, R2 = 0.02 at 20-30 cm) or ESP (R2 = 0.00 at 0-10 cm and 20-30 cm).

Soil pHCa was also not correlated with CCE (R2 = 0.06 at 0-10 cm, R2 = 0.01 at 20-30 cm).

Strong to very strong correlations were also found between exchangeable Na

concentration and soil EC (R2 = 0.76 at 0-10 cm, R2 = 0.87 at 20-30 cm; Figure 45) as well

as with ESP (R2 = 0.69 at 0-10 cm, R2 = 0.89 at 20-30 cm; Figure 46).

Figure 45. Linear relationship between electrical conductivity (EC, dS/m) and exchangeable

Na concentration (cmol(+)/kg) at 0-10 cm (left) and 20-30 cm (right).

Exchangeable Al concentrations and percentage were strongly-positively

correlated (R2 = 0.71 at 0-10 cm, R2 = 0.78 at 20-30 cm; Figure 47). However, there was

very weak to no correlation between pHCa and exchangeable Al percentage (R2 = 0.28 at

0-10 cm, R2 = 0.04 at 20-30 cm).

R² = 0.4416

30

40

50

60

70

80

0 2 4 6 8 10

Ex. C

a (%

)

ESP (%)

0-10 cm

R² = 0.4655

40

50

60

70

80

0 2 4 6 8 10

Ex. C

a (%

)

ESP (%)

20-30 cm

R² = 0.75570.00

0.10

0.20

0.30

0.40

0.0 0.2 0.4 0.6 0.8 1.0

EC (

dS/

m)

Ex. Na (cmol(+)/kg)

0-10 cm

R² = 0.86770.00

0.08

0.16

0.24

0.32

0.0 0.2 0.4 0.6 0.8

EC (

dS/

m)

Ex. Na (cmol(+)/kg)

20-30 cm


nutrition

44

Figure 46. Linear relationship between exchangeable Na concentration (cmol(+)/kg) and Na

percentage (ESP, %) at 0-10 cm (left) and 20-30 cm (right).

Figure 47. Linear relationship between exchangeable Al concentration (cmol(+)/kg) and Al

percentage (%) at 0-10 cm (left) and 20-30 cm (right).

R² = 0.69130

2

4

6

8

10

0.0 0.2 0.4 0.6 0.8 1.0

ESP

(%

)

Ex. Na (cmol(+)/kg)

0-10 cm

R² = 0.88850

2

4

6

8

10

0.0 0.2 0.4 0.6 0.8

ESP

(%

)

Ex. Na (cmol(+)/kg)

20-30 cm

R² = 0.70680

2

4

6

8

0.00 0.05 0.10 0.15 0.20 0.25

Ex. A

l (%

)

Ex. Al (cmol(+)/kg)

0-10 cm

R² = 0.77920

1

2

3

4

5

6

0.0 0.1 0.2 0.3

Ex. A

l (%

)

Ex. Al (cmol(+)/kg)

20-30 cm

Table 6. Correlation (R2) between soil properties at 0-10 cm, using only Span 3 data from baseline to December 2013 based on Pivots 1-8, 10 and 11.

EC pHCa CCE OC NO3-N NH4-N Total N C/N Colwell P Total P PRI Colwell K Total K Ex. Ca Ex. Mg Ex. Na Ex. K Ex. Al ECEC Ca% Mg% ESP K% Al% As Cd Cr Pb

EC 1.00 0.06 0.00 0.18 0.04 0.05 0.12 0.01 0.00 0.35 0.23 0.06 0.12 0.13 0.28 0.76 0.12 0.03 0.27 0.23 0.17 0.68 0.09 0.11 0.10 0.02 0.00 0.03 pHCa 0.06 1.00 0.07 0.05 0.11 0.03 0.16 0.00 0.00 0.15 0.01 0.08 0.02 0.38 0.75 0.28 0.16 0.04 0.60 0.32 0.70 0.06 0.45 0.28 0.06 0.05 0.11 0.07 CCE 0.00 0.07 1.00 0.00 0.01 0.02 0.06 0.06 0.01 0.01 0.04 0.09 0.00 0.01 0.05 0.00 0.06 0.08 0.03 0.08 0.09 0.00 0.00 0.08 0.01 0.01 0.00 0.00 OC 0.18 0.05 0.00 1.00 0.05 0.04 0.11 0.33 0.00 0.22 0.03 0.15 0.16 0.28 0.12 0.14 0.23 0.04 0.23 0.00 0.01 0.02 0.04 0.19 0.00 0.01 0.00 0.01 NO3-N 0.04 0.11 0.01 0.05 1.00 0.02 0.00 0.06 0.06 0.01 0.08 0.01 0.04 0.03 0.07 0.02 0.01 0.00 0.04 0.02 0.09 0.00 0.15 0.01 0.01 0.00 0.02 0.03 NH4-N 0.05 0.03 0.02 0.04 0.02 1.00 0.05 0.19 0.08 0.03 0.00 0.06 0.02 0.00 0.02 0.02 0.08 0.00 0.01 0.07 0.04 0.01 0.01 0.02 0.00 0.01 0.02 0.00 Total N 0.12 0.16 0.06 0.11 0.00 0.05 1.00 0.29 0.01 0.19 0.02 0.11 0.08 0.45 0.30 0.21 0.19 0.09 0.41 0.00 0.04 0.01 0.13 0.21 0.01 0.07 0.19 0.00 C/N 0.01 0.00 0.06 0.33 0.06 0.19 0.29 1.00 0.01 0.00 0.00 0.01 0.01 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 0.01 0.10 0.01 Colwell P 0.00 0.00 0.01 0.00 0.06 0.08 0.01 0.01 1.00 0.00 0.02 0.12 0.05 0.00 0.00 0.01 0.13 0.09 0.00 0.01 0.00 0.03 0.14 0.03 0.07 0.00 0.00 0.06 Total P 0.35 0.15 0.01 0.22 0.01 0.03 0.19 0.00 0.00 1.00 0.33 0.21 0.28 0.26 0.37 0.43 0.31 0.00 0.39 0.16 0.17 0.17 0.06 0.10 0.03 0.00 0.00 0.03 PRI 0.23 0.01 0.04 0.03 0.08 0.00 0.02 0.00 0.02 0.33 1.00 0.08 0.20 0.05 0.16 0.27 0.10 0.01 0.13 0.14 0.12 0.19 0.02 0.06 0.03 0.01 0.00 0.02 Colwell K 0.06 0.08 0.09 0.15 0.01 0.06 0.11 0.01 0.12 0.21 0.08 1.00 0.36 0.34 0.19 0.06 0.94 0.21 0.33 0.01 0.02 0.01 0.07 0.35 0.03 0.00 0.01 0.04 Total K 0.12 0.02 0.00 0.16 0.04 0.02 0.08 0.01 0.05 0.28 0.20 0.36 1.00 0.09 0.03 0.07 0.40 0.04 0.09 0.00 0.00 0.01 0.09 0.07 0.17 0.05 0.00 0.00 Ex. Ca 0.13 0.38 0.01 0.28 0.03 0.00 0.45 0.00 0.00 0.26 0.05 0.34 0.09 1.00 0.61 0.32 0.46 0.17 0.87 0.00 0.10 0.00 0.28 0.49 0.02 0.03 0.06 0.03 Ex. Mg 0.28 0.75 0.05 0.12 0.07 0.02 0.30 0.01 0.00 0.37 0.16 0.19 0.03 0.61 1.00 0.63 0.32 0.08 0.90 0.35 0.67 0.19 0.44 0.36 0.00 0.01 0.10 0.03 Ex. Na 0.76 0.28 0.00 0.14 0.02 0.02 0.21 0.00 0.01 0.43 0.27 0.06 0.07 0.32 0.63 1.00 0.14 0.03 0.56 0.35 0.43 0.69 0.35 0.20 0.04 0.00 0.02 0.00 Ex. K 0.12 0.16 0.06 0.23 0.01 0.08 0.19 0.01 0.13 0.31 0.10 0.94 0.40 0.46 0.32 0.14 1.00 0.22 0.48 0.03 0.05 0.00 0.02 0.42 0.04 0.00 0.02 0.04 Ex. Al 0.03 0.04 0.08 0.04 0.00 0.00 0.09 0.00 0.09 0.00 0.01 0.21 0.04 0.17 0.08 0.03 0.22 1.00 0.13 0.01 0.00 0.00 0.00 0.71 0.02 0.01 0.06 0.01 ECEC 0.27 0.60 0.03 0.23 0.04 0.01 0.41 0.00 0.00 0.39 0.13 0.33 0.09 0.87 0.90 0.56 0.48 0.13 1.00 0.12 0.37 0.09 0.36 0.47 0.01 0.02 0.08 0.03 Ca% 0.23 0.32 0.08 0.00 0.02 0.07 0.00 0.00 0.01 0.16 0.14 0.01 0.00 0.00 0.35 0.35 0.03 0.01 0.12 1.00 0.81 0.44 0.08 0.01 0.01 0.01 0.02 0.01 Mg% 0.17 0.70 0.09 0.01 0.09 0.04 0.04 0.00 0.00 0.17 0.12 0.02 0.00 0.10 0.67 0.43 0.05 0.00 0.37 0.81 1.00 0.31 0.37 0.11 0.02 0.00 0.06 0.02 ESP 0.68 0.06 0.00 0.02 0.00 0.01 0.01 0.00 0.03 0.17 0.19 0.01 0.01 0.00 0.19 0.69 0.00 0.00 0.09 0.44 0.31 1.00 0.17 0.03 0.03 0.03 0.00 0.03 K% 0.09 0.45 0.00 0.04 0.15 0.01 0.13 0.01 0.14 0.06 0.02 0.07 0.09 0.28 0.44 0.35 0.02 0.00 0.36 0.08 0.37 0.17 1.00 0.07 0.02 0.05 0.04 0.01 Al% 0.11 0.28 0.08 0.19 0.01 0.02 0.21 0.01 0.03 0.10 0.06 0.35 0.07 0.49 0.36 0.20 0.42 0.71 0.47 0.01 0.11 0.03 0.07 1.00 0.01 0.01 0.08 0.00 As 0.10 0.06 0.01 0.00 0.01 0.00 0.01 0.01 0.07 0.03 0.03 0.03 0.17 0.02 0.00 0.04 0.04 0.02 0.01 0.01 0.02 0.03 0.02 0.01 1.00 0.59 0.19 0.41 Cd 0.02 0.05 0.01 0.01 0.00 0.01 0.07 0.01 0.00 0.00 0.01 0.00 0.05 0.03 0.01 0.00 0.00 0.01 0.02 0.01 0.00 0.03 0.05 0.01 0.59 1.00 0.43 0.27 Cr 0.00 0.11 0.00 0.00 0.02 0.02 0.19 0.10 0.00 0.00 0.00 0.01 0.00 0.06 0.10 0.02 0.02 0.06 0.08 0.02 0.06 0.00 0.04 0.08 0.19 0.43 1.00 0.04 Pb 0.03 0.07 0.00 0.01 0.03 0.00 0.00 0.01 0.06 0.03 0.02 0.04 0.00 0.03 0.03 0.00 0.04 0.01 0.03 0.01 0.02 0.03 0.01 0.00 0.41 0.27 0.04 1.00

Strength of relationship: 0.80 to 0.99 (very strong); 0.60 to 0.79 (strong); 0.40 to 0.59 (moderate); 0.20 to 0.39 (weak); and 0.00 to 0.19 (very weak). All moderate to very strong correlations are significant at the 0.01 level (2-tailed).

Table 7. Correlation (R2) between soil properties at 20-30 cm, using only Span 3 data from baseline to December 2013 based on Pivots 1-8, 10 and 11.

EC pHCa CCE OC NO3-N NH4-N Total N C/N Colwell P Total P PRI Colwell K Total K Ex. Ca Ex. Mg Ex. Na Ex. K Ex. Al ECEC Ca% Mg% ESP K% Al% As Cd Cr Pb

EC 1.00 0.08 0.00 0.01 0.34 0.00 0.08 0.00 0.08 0.21 0.06 0.11 0.01 0.22 0.53 0.87 0.14 0.01 0.48 0.20 0.12 0.69 0.23 0.03 0.00 0.05 0.13 0.00 pHCa 0.08 1.00 0.03 0.16 0.11 0.05 0.03 0.05 0.15 0.01 0.00 0.00 0.03 0.20 0.27 0.12 0.01 0.00 0.25 0.00 0.05 0.07 0.32 0.04 0.02 0.02 0.01 0.05 CCE 0.00 0.03 1.00 0.00 0.00 0.09 0.24 0.11 0.09 0.00 0.02 0.03 0.02 0.01 0.00 0.00 0.00 0.00 0.01 0.02 0.01 0.00 0.01 0.00 0.01 0.00 0.07 0.00 OC 0.01 0.16 0.00 1.00 0.06 0.15 0.01 0.49 0.02 0.05 0.01 0.01 0.05 0.02 0.04 0.02 0.01 0.05 0.03 0.02 0.01 0.03 0.03 0.01 0.11 0.05 0.06 0.10 NO3-N 0.34 0.11 0.00 0.06 1.00 0.00 0.00 0.07 0.14 0.24 0.02 0.01 0.00 0.06 0.26 0.54 0.00 0.09 0.19 0.16 0.09 0.54 0.37 0.01 0.03 0.01 0.00 0.03 NH4-N 0.00 0.05 0.09 0.15 0.00 1.00 0.00 0.09 0.09 0.02 0.03 0.05 0.03 0.03 0.00 0.00 0.00 0.00 0.01 0.08 0.06 0.01 0.02 0.00 0.11 0.01 0.02 0.01 Total N 0.08 0.03 0.24 0.01 0.00 0.00 1.00 0.37 0.01 0.00 0.05 0.00 0.02 0.03 0.07 0.04 0.02 0.02 0.05 0.01 0.03 0.03 0.02 0.05 0.01 0.02 0.15 0.00 C/N 0.00 0.05 0.11 0.49 0.07 0.09 0.37 1.00 0.03 0.04 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.05 0.00 0.01 0.00 0.01 0.00 0.03 0.13 0.01 0.15 0.03 Colwell P 0.08 0.15 0.09 0.02 0.14 0.09 0.01 0.03 1.00 0.03 0.01 0.11 0.05 0.06 0.09 0.09 0.07 0.01 0.07 0.00 0.03 0.07 0.41 0.00 0.00 0.00 0.04 0.03 Total P 0.21 0.01 0.00 0.05 0.24 0.02 0.00 0.04 0.03 1.00 0.16 0.09 0.14 0.18 0.31 0.27 0.16 0.10 0.32 0.06 0.04 0.19 0.10 0.00 0.01 0.01 0.01 0.02 PRI 0.06 0.00 0.02 0.01 0.02 0.03 0.05 0.04 0.01 0.16 1.00 0.09 0.09 0.01 0.09 0.05 0.10 0.02 0.04 0.05 0.06 0.03 0.00 0.06 0.01 0.03 0.01 0.00 Colwell K 0.11 0.00 0.03 0.01 0.01 0.05 0.00 0.01 0.11 0.09 0.09 1.00 0.10 0.28 0.18 0.07 0.85 0.11 0.32 0.00 0.01 0.01 0.10 0.26 0.04 0.01 0.00 0.01 Total K 0.01 0.03 0.02 0.05 0.00 0.03 0.02 0.00 0.05 0.14 0.09 0.10 1.00 0.06 0.02 0.00 0.21 0.00 0.06 0.01 0.02 0.00 0.04 0.03 0.09 0.02 0.00 0.01 Ex. Ca 0.22 0.20 0.01 0.02 0.06 0.03 0.03 0.00 0.06 0.18 0.01 0.28 0.06 1.00 0.39 0.19 0.46 0.03 0.86 0.15 0.06 0.03 0.17 0.30 0.05 0.02 0.01 0.01 Ex. Mg 0.53 0.27 0.00 0.04 0.26 0.00 0.07 0.00 0.09 0.31 0.09 0.18 0.02 0.39 1.00 0.57 0.25 0.00 0.72 0.18 0.35 0.36 0.31 0.12 0.00 0.00 0.01 0.02 Ex. Na 0.87 0.12 0.00 0.02 0.54 0.00 0.04 0.00 0.09 0.27 0.05 0.07 0.00 0.19 0.57 1.00 0.08 0.03 0.47 0.29 0.16 0.89 0.33 0.01 0.01 0.03 0.06 0.00 Ex. K 0.14 0.01 0.00 0.01 0.00 0.00 0.02 0.00 0.07 0.16 0.10 0.85 0.21 0.46 0.25 0.08 1.00 0.11 0.48 0.02 0.02 0.00 0.06 0.34 0.05 0.00 0.01 0.00 Ex. Al 0.01 0.00 0.00 0.05 0.09 0.00 0.02 0.05 0.01 0.10 0.02 0.11 0.00 0.03 0.00 0.03 0.11 1.00 0.00 0.13 0.02 0.07 0.10 0.78 0.05 0.00 0.02 0.08 ECEC 0.48 0.25 0.01 0.03 0.19 0.01 0.05 0.00 0.07 0.32 0.04 0.32 0.06 0.86 0.72 0.47 0.48 0.00 1.00 0.00 0.01 0.19 0.25 0.22 0.02 0.01 0.02 0.02 Ca% 0.20 0.00 0.02 0.02 0.16 0.08 0.01 0.01 0.00 0.06 0.05 0.00 0.01 0.15 0.18 0.29 0.02 0.13 0.00 1.00 0.74 0.47 0.02 0.13 0.05 0.00 0.00 0.00 Mg% 0.12 0.05 0.01 0.01 0.09 0.06 0.03 0.00 0.03 0.04 0.06 0.01 0.02 0.06 0.35 0.16 0.02 0.02 0.01 0.74 1.00 0.24 0.10 0.01 0.01 0.02 0.00 0.00 ESP 0.69 0.07 0.00 0.03 0.54 0.01 0.03 0.01 0.07 0.19 0.03 0.01 0.00 0.03 0.36 0.89 0.00 0.07 0.19 0.47 0.24 1.00 0.31 0.00 0.03 0.02 0.04 0.00 K% 0.23 0.32 0.01 0.03 0.37 0.02 0.02 0.00 0.41 0.10 0.00 0.10 0.04 0.17 0.31 0.33 0.06 0.10 0.25 0.02 0.10 0.31 1.00 0.00 0.00 0.02 0.00 0.03 Al% 0.03 0.04 0.00 0.01 0.01 0.00 0.05 0.03 0.00 0.00 0.06 0.26 0.03 0.30 0.12 0.01 0.34 0.78 0.22 0.13 0.01 0.00 0.00 1.00 0.07 0.00 0.03 0.03 As 0.00 0.02 0.01 0.11 0.03 0.11 0.01 0.13 0.00 0.01 0.01 0.04 0.09 0.05 0.00 0.01 0.05 0.05 0.02 0.05 0.01 0.03 0.00 0.07 1.00 0.63 0.21 0.40 Cd 0.05 0.02 0.00 0.05 0.01 0.01 0.02 0.01 0.00 0.01 0.03 0.01 0.02 0.02 0.00 0.03 0.00 0.00 0.01 0.00 0.02 0.02 0.02 0.00 0.63 1.00 0.49 0.35 Cr 0.13 0.01 0.07 0.06 0.00 0.02 0.15 0.15 0.04 0.01 0.01 0.00 0.00 0.01 0.01 0.06 0.01 0.02 0.02 0.00 0.00 0.04 0.00 0.03 0.21 0.49 1.00 0.08 Pb 0.00 0.05 0.00 0.10 0.03 0.01 0.00 0.03 0.03 0.02 0.00 0.01 0.01 0.01 0.02 0.00 0.00 0.08 0.02 0.00 0.00 0.00 0.03 0.03 0.40 0.35 0.08 1.00


47

3.4.2. PARTICLE SIZE AND SOIL CHEMICAL PROPERTIES

Bivariate correlation and linear regression analyses between soil particle size

(March 2014) and soil chemical properties (December 2013) were assessed, using Span

3 results based on Pivots 1-8, 10 and 11 (Table 8).

Table 8. Correlation (R2) between soil particle size and soil chemical properties at 0-10 cm and

20-30 cm, using Span 3 results based on Pivots 1-8, 10 and 11.

0-10 cm 20-30 cm Sand Silt Clay Sand Silt Clay Sand 1.00 0.14 0.56 1.00 0.05 0.92 Silt - 1.00 0.12 - 1.00 0.24 Clay - - 1.00 - - 1.00 Electrical conductivity, EC 0.23 0.06 0.10 0.45 0.02 0.42 pHCa 0.49 0.11 0.22 0.01 0.01 0.01 CaCO3 equivalent, CCE 0.15 0.29 0.00 0.03 0.02 0.01 Organic C, OC 0.44 0.00 0.49 0.00 0.00 0.00 NO3-N 0.00 0.08 0.08 0.05 0.04 0.02 NH4-N 0.01 0.16 0.04 0.08 0.07 0.03 Total N 0.10 0.01 0.15 0.08 0.23 0.15 C/N ratio 0.39 0.00 0.41 0.03 0.02 0.03 Colwell P 0.17 0.33 0.00 0.17 0.12 0.22 Total P 0.35 0.00 0.42 0.61 0.15 0.66 Phosphorus retention index, PRI

0.27 0.07 0.11 0.26 0.01 0.23

Colwell K 0.07 0.04 0.16 0.43 0.07 0.44 Total K 0.31 0.02 0.45 0.60 0.00 0.47 Ex. Ca 0.02 0.02 0.06 0.47 0.00 0.38 Ex. Mg 0.02 0.04 0.09 0.53 0.00 0.40 Ex. Na 0.25 0.05 0.11 0.53 0.01 0.47 Ex. K 0.05 0.06 0.17 0.54 0.04 0.51 Ex. Al 0.00 0.03 0.00 0.11 0.44 0.24 Effective cation exchange capacity, ECEC

0.04 0.02 0.09 0.54 0.00 0.43

Ex. Ca percentage 0.01 0.00 0.01 0.17 0.00 0.14 Ex. Mg percentage 0.09 0.09 0.01 0.15 0.01 0.14 Ex. Na percentage (ESP) 0.24 0.11 0.07 0.00 0.05 0.02 Ex. K percentage 0.00 0.01 0.00 0.05 0.24 0.12 Ex. Al percentage 0.01 0.01 0.03 0.36 0.30 0.48 As 0.15 0.04 0.06 0.20 0.13 0.25 Cd 0.01 0.05 0.01 0.01 0.03 0.02 Cr 0.00 0.01 0.00 0.01 0.01 0.01 Pb 0.06 0.06 0.01 0.00 0.02 0.00 Strength of relationship: 0.80 to 0.99 (very strong); 0.60 to 0.79 (strong); 0.40 to 0.59 (moderate); 0.20 to 0.39 (weak); and 0.00 to 0.19 (very weak).

Sand and clay fractions of the soil appear to be moderately to strongly negatively

correlated at both 0-10 cm (R2 = 0.56) and 20-30 cm (R2 = 0.92), while silt fractions were

not related. A few soil chemical properties were related to particle size at 0-10 cm but

were not greatly important. On the other hand, there was a greater degree of association

between soil chemical properties and particle size at 20-30 cm, with correlations


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48

generally reflecting the moderate-strong relationships between soil nutrients with

either sand or clay percentage.

3.4.3. LEAF NUTRIENT COMPOSITION AND SOIL PROPERTIES

Most leaf nutrient concentrations were not correlated with soil properties (see

Tables 17 and 18 in Appendix A). A few moderate correlations existed, but were not

insightful. Leaf Cr concentrations were moderately and positively correlated with soil Cr

concentrations (R2 = 0.47 at 0-10 cm, R2 = 0.41 at 20-30 cm). However, Figure 48 showed

these correlations were clearly influenced by outliers – i.e., results from December 2013.

All December leaf tissue samples had unusually high Cr concentrations (see Figure 36)

and their removal resulted in no correlation between Cr concentrations in soil and leaf

tissue.

Figure 48. Linear relationship between chromium concentrations (Cr, mg/kg) in leaf tissue

and soil at 0-10 cm (left) and 20-30 cm (right), based on Span 3 results from March to

December 2013 with December 2013 outliers included (top) and removed (bottom).

R² = 0.47260

1

2

3

4

5

6

7

0 100 200 300 400 500 600

Cr

(mg/

kg)

in le

af

Cr (mg/kg) in soil

0-10 cm(Dec 2013 included)

R² = 0.40780

1

2

3

4

5

6

7

0 100 200 300 400 500

Cr

(mg/

kg)

in le

af

Cr (mg/kg) in soil

20-30 cm(Dec 2013 included)

R² = 0.08870.0

0.2

0.4

0.6

0.8

1.0

0 100 200 300 400

Cr

(mg/

kg)

in le

af

Cr (mg/kg) in soil

0-10 cm(Dec 2013 removed)

R² = 0.04120.0

0.2

0.4

0.6

0.8

1.0

0 100 200 300 400

Cr

(mg/

kg)

in le

af

Cr (mg/kg) in soil

20-30 cm(Dec 2013 removed)

49

3.5. WATER QUALITY AND GEOCHEMICAL MODELLING

The WEB-PHREEQ modelling program was used to determine possible mineral

precipitation from irrigation water with and without added nutrients, using water

quality data from December 2013 (Table 9). Saturation indices (SI) for all saturated and

oversaturated solid phases in source water and fertigation mixture are summarised in

Table 10 (see Appendix B for output data).

Table 9. Composition of dewatering surplus and fertigation mixture sampled in December 2013.

Parameter Units Source water Fertigation mixture

Temperature* oC 29.5 31.9

pH* pH units 8.2 8.0

Electrical conductivity, EC, at 25oC

dS/m 0.84 0.99

Total dissolved solids, TDS mg/L 528 580

Total alkalinity as CaCO3* mg/L 240 220

Ca* mg/L 61 61

Mg* mg/L 50 50 Na* mg/L 42 43

K* mg/L 13 31

HCO3 mg/L 290 270

Cl* mg/L 120 120

SO4* mg/L 76 92

NO3-N mg/L 0.36 14

NH4-N mg/L <0.005 15

Total N* mg/L 0.36 60

Total P* mg/L 0.01 7.2

Al* mg/L <0.02 <0.02

B* mg/L 0.3 0.3

Cd* mg/L <0.001 <0.001

Co mg/L <0.01 <0.01

Cu* mg/L 0.016 0.005

Fe* mg/L <0.02 <0.02

Pb* mg/L <0.02 <0.02

Mn mg/L 0.007 0.21

Mo mg/L <0.01 0.02

Se mg/L <0.05 <0.05

Zn* mg/L 0.08 0.26

*parameters used in WEB-PHREEQ modelling

The model shows both the source water and fertigation mixture were

oversaturated with respect to carbonate and (hydr)oxide minerals of Ca, Mg, Fe and Mn,

and with phosphate as apatite. In particular, dolomite, hausmannite, hematite and

hydroxyapatite appear to be minerals most likely to precipitate from irrigation waters

due to their relatively high saturation index.


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Table 10. Saturation indices of solid phases in source water (pH 8.2) and fertigation mixture (pH

8.0) sampled in December 2013, calculated from WEB-PHREEQ using input values in Table 9 –

Al, Cd, Pb and Fe concentrations are half their detection limit.

Phase Source water Fertigation mixture Aragonite, CaCO3 1.21 0.57 Calcite, CaCO3 1.35 0.71 Dolomite, CaMg(CO3)2 3.03 1.76 Iron (III) hydroxide, Fe(OH)3 (a) 0.45 0.43 Goethite, FeOOH 6.50 6.57 Hausmannite, Mn3O4 2.34 2.77 Hematite, Fe2O3 15.03 15.17 Hydroxyapatite, Ca5(PO4)3OH 1.53 8.04 Manganite, MnOOH 1.04 0.70 Pyrolusite, MnO2 2.58 1.74 Rhodochrosite, MnCO3 -0.76 0.46

Relative to source water, the fertigation mixture was less oversaturated with

respect to aragonite, calcite, dolomite, manganite and pyrolusite, but more oversaturated

with respect to hausmannite, hematite, hydroxyapatite and rhodochrosite. No major

change occurred for iron (III) hydroxide and goethite after fertiliser addition to source

water. Fertiliser addition appears to have slightly lowered the potential for aragonite,

calcite and dolomite to precipitate, but not to the extent that they will not precipitate if

given suitable conditions for nucleation and crystal growth. The formation of insoluble

carbonate, (hydr)oxide and phosphate (apatite) minerals of Ca, Mg, Fe and Mn from the

fertigation mixture could therefore impose a risk for nutrient immobilisation.

Sensitivity analysis was conducted by adjusting pH values to identify the

threshold at which calcite and dolomite would remain undersaturated (Table 11; see

Appendix B for output data).

Table 11. Saturation indices of carbonates, (hydr)oxides and apatite in source water and

fertigation mixture, modelled at pH 7.

Phase Source water Fertigation mixture Aragonite, CaCO3 -0.36 -0.39 Calcite, CaCO3 -0.22 -0.25 Dolomite, CaMg(CO3)2 -0.12 -0.17 Iron (III) hydroxide, Fe(OH)3 (a) 0.41 0.29 Gibbsite, Al(OH)3 0.83 0.73 Goethite, FeOOH 6.46 6.42 Hausmannite, Mn3O4 -11.66 -6.63 Hematite, Fe2O3 14.95 14.88 Hydroxyapatite, Ca5(PO4)3OH -5.01 3.70 Manganite, MnOOH -4.58 -3.10 Pyrolusite, MnO2 -5.91 -4.06 Rhodochrosite, MnCO3 -1.77 -0.31


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51

Results showed that pH 7.0 was required to achieve this for both source water

and fertigation mixture. Thus, calcite, dolomite and other Mn minerals should not

precipitate if the pH of the fertigation mixture is ≤ 7. However, this does not appear to

significantly affect the SI of iron (hydr)oxides. The fertigation mixture would still remain

oversaturated with respect hydroxyapatite (SI = 3.70). Moreover, both the source water

and fertigation mixture were predicted to be oversaturated with respect to gibbsite at

pH 7.

3.6. ASH ALKALINITY DETERMINATION AND MASS BALANCE

Ash contents ranged from 9.3-10.8 % w/w and ash alkalinity from 0.28-0.37

meq/g with a mean of 0.33 meq/g (Table 12). Net alkalinity was calculated from a mass

balance of alkalinity added from irrigation water less that removed from hay yield (Table

13).

Table 12. Ash content (%) and ash alkalinity (eq/g) of duplicate hay subsamples from Pivots 1-5

collected in February 2014 for the growth cycle between November 2013 and January 2014 -

titration of 50 ml of 0.0494 M HCl and hay ash with 0.05 M Na2CO3.

Pivot # Cut # Volume of

Na2CO3 used (ml)

Dry weight of hay sample (g)

Ash content (%) Ash alkalinity

(meq/g)

1 8 23.1 0.507 9.9 0.32 1 8 23.1 0.506 9.3 0.32 2* 7 23.2 0.499 - 0.30 2 7 22.8 0.516 9.9 0.37 3 6 22.9 0.506 10.7 0.36 3 6 22.8 0.511 10.4 0.37 4 7 22.9 0.500 10.6 0.36 4 7 23.1 0.502 10.8 0.32 5* 7 23.3 0.500 - 0.28 5 7 23.2 0.502 10.0 0.30 Mean 10.2 (± 0.2) 0.33 (± 0.01) *ash content not available due to procedural error

Calculations showed a net gain in alkalinity due to irrigation, ranging from 301-

535 kg CaCO3/ha with an overall mean of 409 kg CaCO3/ha for the growth cycle between

November 2013 and January 2014 (approximately 6-8 weeks). The amount of alkalinity

applied during this period exceeded the amount removed from pasture growth by about

five times (P < 0.01). Based on total irrigation and hay produced throughout October

2012 to January 2014, the total net gain in alkalinity ranged from 3206-4139 kg

CaCO3/ha with a mean of 3735(± 164) kg CaCO3/ha (Table 14). On average, the amount


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of alkalinity added was more than 12 times the amount removed and could thus explain

significant increases in soil pH. Annually, this would equate to a net gain of 3168(± 67)

kg CaCO3/ha.

Table 13. Mean net alkalinity values determined from a mass balance of alkalinity added from irrigation and removed by hay production for Pivots 1-5 between

November 2013 and January 2014 – based on the total alkalinity of irrigation water measured in November 2013, using unpublished hay yield and irrigation data

(Rio Tinto Iron Ore, 2014).

Pivot # Gross irrigation

(ML/ha) Total dry hay weight (t/ha)

Alkalinity added from irrigation Alkalinity removed from hay Net alkalinity as CaCO3 (kg/ha): added

- removed Total alkalinity as CaCO3

(mg/L) Overall total alkalinity

as CaCO3 (kg/ha) Ash alkalinity (meq/g)

Overall ash alkalinity as CaCO3 (kg/ha)

1 1.774 5.950 230 408.0 0.32 (± 0.00) 94.0 (± 0.1) 314.0 (± 0.1)

2 2.900 7.911 230 667.0 0.33 (± 0.03) 132.3 (± 13.4) 534.7 (± 13.4)

3 2.806 6.527 230 645.4 0.36 (± 0.01) 118.7 (± 2.6) 526.6 (± 2.6)

4 1.990 5.376 230 457.7 0.34 (± 0.02) 91.2 (± 5.5) 366.5 (± 5.5)

5 1.568 4.121 230 360.6 0.29 (± 0.01) 59.6 (± 1.9) 300.9 (± 1.9)

Overall mean 507.7 (± 62.6) 0.33 (± 0.01) 99.2 (± 12.5) 408.6 (± 51.1)

Table 14. Total net alkalinity gained from irrigated pastures for Pivots 1-5 throughout the study period from October 2012 to January 2014 – assuming relatively

constant total alkalinity of irrigation water, using unpublished hay yield and irrigation data (Rio Tinto Iron Ore, 2014).

Pivot # Total days of

growth

Gross Irrigation (ML/ha)

Total dry weight of hay

(t/ha)

Alkalinity added from irrigation Alkalinity removed from hay Net alkalinity as CaCO3 (kg/ha):

added - removed

Net rate of alkalinity as

CaCO3 (kg/ha/year)

Total alkalinity as CaCO3 (mg/L)

Overall total alkalinity as

CaCO3 (kg/ha)

Ash alkalinity (meq/g)

Overall ash alkalinity as

CaCO3 (kg/ha)

1 456 19.3 18.9 230 4441 0.32 302 4139 3313

2 448 19.0 21.9 230 4377 0.33 361 4016 3272

3 400 15.3 18.0 230 3529 0.36 323 3206 2925

4 427 17.5 18.6 230 4016 0.34 316 3700 3163

5 417 17.0 19.7 230 3901 0.29 285 3616 3165

Overall mean 4053 (± 166) 0.33 (± 0.01) 318 (± 13) 3735 (± 164) 3168 (± 67)

54

4. DISCUSSION

4.1. OVERVIEW

Groundwater from the Marandoo iron ore mine in the central Pilbara region of

Western Australia is utilised for irrigation at the Hamersley Agricultural Project (HAP).

After amendment with nutrients, the water was slightly alkaline with pH 8.0 and total

alkalinity of 220 mg CaCO3/L, and slightly brackish-sodic with an EC of 0.99 dS/m and

TDS of 580 mg/L. The major cations include Ca, Mg and Na, and the dominant anion was

HCO3.

Over 15 months of irrigation, analysis showed: (1) significant increases in soil

sodicity, whereby ESP levels had exceeded 5% at 0-10 cm and 7% at 20-30 cm, and (2)

alkalinisation, especially within the 0-10 cm soil layer, that could result in high soil pH

(~8.2) that may adversely affect nutrient availability. However, in contrast to initial

findings on sodicity, a subsequent study indicated that the increases in ESP were

overestimated since results did not account for the increasing soluble salts in the soil.

When samples were pre-washed to remove soluble salts there was little increase in ESP

and hence no evidence of sodicity in HAP soils after 15 months (Samaraweera, 2015).

Given suitable conditions for nucleation and crystal growth, the precipitation of

carbonate, (hydr)oxide and phosphate (apatite) minerals of Ca, Mg, Fe and Mn could also

impose a risk for immobilising nutrients applied from irrigation water. Moreover, other

implications may also arise from changes in the relative abundance of soil exchangeable

cations whereby exchangeable Mg2+ as a percentage of cation exchange capacity

significantly increased while exchangeable Ca2+ and K+ percentages have significantly

decreased.

Many other soil chemical properties were also shown to significantly change over

15 months, but were not as important and/or consistent. Total As was, however, already

present in the soil at relatively high concentrations that could adversely affect sensitive

plant species. But, at this stage, leaf tissue analysis did not identify abnormalities in the

nutrient composition of C. gayana between March and December 2013, with the

exception of a spike in Cr concentration in December. In general, overall leaf

compositions have remained unaffected by changes in soil chemistry which may in part

reflect the high tolerance of C. gayana to current conditions as well as the short duration

of irrigation (≤ 15 months).


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The implications of irrigation with slightly alkaline and slightly brackish-sodic

water for soil properties and pasture nutrition at the HAP site are discussed in detail,

based on the author’s initial findings. Long-term predictions will be made about the

sustainability of irrigation on the site, along with recommendations for remediation.

Suggestions for future soil and plant monitoring strategies are discussed in Appendix G.

4.2. MAJOR FINDINGS

4.2.1. EXCHANGEABLE SODIUM AND SODICITY

Significant increases in ESP by 1.5-3.7 % were already observed within the first

four months of continuous irrigation (Figure 23). After 15 months, ESP levels exceeded

5% at 0-10 cm and 7% at 20-30 cm. Soil sodicity is usually characterised by an ESP ≥ 15

(United States Soil Laboratory Staff, 1954) corresponding with a sharp deterioration in

soil physical properties (Abrol et al., 1988). However, a single value of ESP cannot be

used as a critical threshold for all conditions (Kijne et al., 1998). Soil degradation has

been observed in Australian soils when the ESP exceeds 6% (Rengasamy and Olsson,

1991), or even as low as 4% in Pakistan soils (Condom et al., 1999).

While such ESP levels indicate sodicity could emerge as an issue for future soil

management at the HAP, subsequent laboratory analysis utilising the pre-treatment

method for removal of soluble salts (Samaraweera, 2015; see Appendix H) concluded

that the addition of irrigation water had not caused a measurable change in the sodicity

of the HAP soils. Samaraweera (2015) found that almost all the sodium in the soil were

as soluble Na+ and not found in the cation exchange complex, and hence determination

of ESP in soils samples in the future should be carried out by employing methods that

include pre-treatment for soluble salts to avoid overestimation. It also means that

present conditions do not indicate significant increases in ESP or an imminent concern

about sodicity.

Increases in ESP levels over time need to be monitored given the

disproportionately high concentration of Na+ in the irrigation water and/or the

precipitation of Ca2+ and Mg2+ from irrigation water (or soil solution) which increases

the sodium adsorption ratio (SAR; Bower et al., 1968). Correlation analyses (Tables 6

and 7) strongly suggest that elevated ESP levels were directly due to high Na+


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56

concentrations applied from irrigation water. Since no significant change occurred in soil

CCE over time, Ca and Mg carbonate precipitation is not a major issue at this stage.

Moreover, no correlation was found between CCE and exchangeable Ca2+ percentage, or

with ESP, and hence elevated ESP is likely due to irrigation with sodic water.

Sodicity, if it develops, may restrict plant growth via poor soil physical conditions

(Warrence and Bauder, 2001, Stearns et al., 2005, Saqib et al., 2008), as well as induce

osmotic stress and specific ion toxicity in sensitive species (Yang et al., 2008a, Yang et al.,

2009, Davis et al., 2012), including nutritional imbalances (e.g., impaired uptake of Ca;

Huang et al., 2012b). In cases of severe alkalinisation, the injurious effects may also be

compounded by high pH (Peng et al., 2008, Yang et al., 2008b, Kukavica et al., 2013).

Nevertheless, leaf Na concentrations did not significantly change between March and

December which may in part reflect the exceptionally high tolerance of C. gayana to

exchangeable Na+ (i.e., ESP > 60; Pearson, 1960). For that reason, it is usually the poor

physical condition caused by sodicity that results in stunting of Na-tolerant species and

not Na toxicity (Pearson, 1960).

4.2.1.1. FUTURE RISK OF SODICITY

The critical threshold for Na-induced dispersion not only depends on the ESP,

but also on the ionic strength of the soil solution (Guerrero-Alves et al., 2002), soil type

(Frenkel et al., 1992) and clay mineralogy (Alperovitch et al., 1985, Shainberg and Levy,

1992, Rengasamy, 2010). Given the current EC of irrigation water, which, while not saline

was nevertheless about 0.99 dS/m (or SAR ~1, see Appendix F), dispersion may not

occur until higher ESP values are recorded. This is because salinity has a flocculating

effect on soils by promoting clay particle aggregation (i.e., usually when irrigation water

> 0.5 dS/m; Warrence et al., 2002).

The degree of dispersion will, however, differ with soil type and clay mineralogy

(Warrence et al., 2002, Ruiz-Vera and Wu, 2006). Because clay soils, as opposed to sandy

soils, have a lower leaching fraction and greater surface area to adsorb Na+ ions (i.e.,

higher cation exchange capacity), soils with a high clay fraction are inherently more

prone to dispersion (Warrence et al., 2002) and swelling (Shainberg and Levy, 1992).

Moreover, the structure of the crystal lattice of clays will have a determining role. Clays

such as smectite become easily hydrated (i.e., adsorb water molecules) due to their 2:1

lattice structure and thus, under certain conditions, become prone to swelling and

dispersion (Boulding and Ginn, 2004). Generally, soils high in 2:1 layer silicate clays are


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most dispersive, while those dominated by 1:1 layer silicates, such as kaolinite, are least

dispersive (Alperovitch et al., 1985).

Given mean ECEC values were < 10 cmol(+)/kg, kaolinite is likely the dominant

clay in HAP soils (Boulding and Ginn, 2004) and hence clay dispersion is unlikely to occur

at the present ESP level. Furthermore, due to the low active interlayer surface area of

kaolinite, swelling does not occur much and thus ESP will have a negligible effect on clay

swelling (Shainberg and Singer, 1990). In this study, changes in hydraulic conductivity

and clay dispersion were not measured, but may be closely examined if there is evidence

that soil ESP is increasing in the future.

4.2.2. SOIL PH AND ALKALINISATION

Since the commencement of sampling in October 2012, soil pHCa significantly

increased from 4.9 to 6.9 and 5.0 to 5.5 in the 0-10 cm and 20-30 cm soil layers,

respectively. Despite this, soil pHCa is still within the ideal range for C. gayana (between

5.5 and 7.5) and hence should not adversely affect plant growth (Pengelly et al., 2006).

However, an increase of 2.0 pH units at 0-10 cm, which is equivalent to a 100-fold

increase in the hydroxide (OH-) concentration, within 15 months is considerable and can

be explained by the accumulation of alkaline solutes from irrigation. In the subsoil,

however, alkalinisation is occurring at a slower rate.

There is compelling evidence that alkalinisation will continue to occur due to

irrigation. Based on mass balance calculations (Tables 13 and 14), there was an average

net gain of approximately 3.8 t CaCO3/ha (equivalent to ~0.1% CaCO3 in the 0-30 cm soil

layer) over the 15-month study period. Therefore, as irrigation continues into the future,

soil pH will rise until a new pH-buffer threshold is reached.

The magnitude of pH increase will largely depend on the abundance of salt(s)

capable of undergoing alkaline hydrolysis (Abrol et al., 1988). Here, changes in soil pH

were strongly associated with exchangeable Mg2+ concentrations rather than Na+,

suggesting that Na+ salts were not undergoing alkaline hydrolysis. WEB-PHREEQ

modelling also shows that calcite and dolomite were the major carbonate minerals in

irrigation water. Therefore, due to their relatively limited solubility, the soil will likely be

buffered at a slightly alkaline pH of ~8.0 to 8.2 (Abrol et al., 1988). The fact that the pH

of irrigation water is 8.0 also suggests that soil pH will not rise significantly higher. Once

exceeding their solubility, the rate of precipitation of Ca and Mg carbonates will increase

as will their accumulation in the soil profile (Ayers and Westcot, 1976). Excessive


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mineral precipitation may present other issues for plant growth and this is discussed in

Section 4.2.3.

In alkaline-sodic soils, problems with high pH are usually due to the

accumulation of NaHCO3 and Na2CO3 (Guerrero-Alves et al., 2002). Due to their greater

solubility, there is a greater potential for hydrolysis and therefore tend to produce a

higher pH, usually > 8.5 (Guerrero-Alves et al., 2002), to as high as 10 to 10.5 when

present in appreciable amounts (Abrol et al., 1988). Nevertheless, an increase from pH 5

to 8 is very significant and can exert a marked influence on nutrient availability

(Kaupenjohann et al., 1989) by affecting their solubility and the ability of plant roots to

absorb nutrients (Atwell et al., 1999).

4.2.2.1. IMPLICATIONS FOR PASTURE NUTRITION

Nutrient deficiencies are a principal limiting factor for plant productivity (Marlet

et al., 1998) that causes the impaired function and growth of roots (López-Bucio et al.,

2003). Under alkaline soil conditions, nutrient disorders may induce leaf symptoms such

as chlorosis (Ksouri et al., 2005).

Though the study showed no significant change in leaf N, an increased pH above

7.5 (Francis et al., 2008) may dramatically reduce the availability of N in the soil through

increased NH3 volatilisation (Ryan et al., 1981, Marlet et al., 1998) particularly where

urea is used as the fertiliser. Increases in soil pH may also restrict P availability for plant

uptake due to the formation of insoluble Ca-P compounds (Hopkins and Ellsworth,

2005). However, current trends indicate P, Ca and Mg concentrations in leaf tissue to

have significantly increased even though initial leaf P concentrations were low (see Table

15 in Section 4.3.1).

Generally, as the soil pH increases above 7, the bioavailability of most trace

elements such as B (Gupta, 2007), Cu (Kopsell and Kopsell, 2007), Fe (Römheld and

Nikolic, 2007), Mn (Humphries et al., 2007), Ni (Brown, 2007) and Zn (Bolan et al., 2003)

may become substantially reduced due to their limited solubility (Valdez-Aguilar et al.,

2009). At pH 8.2, trace elements may be further immobilised due to complexation with

Ca and Mg carbonates (Storey, 2007); hence, irrigation could likely exacerbate this

problem. However, unlike these trace elements, Mo bioavailability in soils increases

under alkaline conditions (Bolan et al., 2003) such that for each unit increase in soil pH

above pH 5.0 the soluble Mo concentration increases 100-fold (Gupta and Lipsett, 1981,

Hamlin, 2007). Therefore, increasing the pH from 5.0 to 8.2 could result in sufficiently


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high Mo concentrations that may affect plant growth, though, under most agricultural

conditions Mo toxicity in plants is rare (Kaiser et al., 2005). High Mo in plant tissue is

likely more of a risk to animal health from Mo toxicity and Cu deprivation (Suttle, 2010).

In particular, since bicarbonate ions are able to maintain a high pH (7.5-8.0) in

the soil (Lucena et al., 2007), elevated bicarbonate concentrations may significantly

depress root growth by pH-buffering in the root apoplast and direct interference on root

metabolism (Peiter et al., 2001, Javid et al., 2012). For instance, bicarbonate can diminish

both Fe solubility and root ferric reductase activity which prevents plants from locally

acidifying the rhizosphere to mobilise Fe from the soil (Lucena et al., 2007, Javid et al.,

2012). At this stage, there has been no significant change in leaf Fe concentration.

Nonetheless, with soil pH changing relatively slowly in the 20-30 cm soil layer, B,

Cu, Fe, Mn and Zn availability should not change significantly unless (co-)precipitation

and surface adsorption is occurring. Leaf tissue analysis confirms this by: (1) a significant

increase in B and Zn concentration and (2) no significant change in Cu, Fe and Mn

concentrations. Leaf Ni concentrations, however, consistently decreased after 9 months

of irrigation. Nickel deficiency may be a result of competing elements such as Cu, Mn, Mg,

Fe, Ca, and Zn (Brown, 2007), but analysis (Table 19, see Appendix A) indicated no

correlation between Ni and Ca, Mg or Zn concentrations in leaf tissue.

No significant changes in leaf K concentrations occurred. Given the naturally high

reserves in the soil, K+ availability is likely to remain adequate for plant uptake unless

significantly displaced by exchangeable Mg+ and/or depleted by continuous cutting of

hay (Barrow, 1968). However, in the instance of high salinity and alkalinity, the

adsorption of K+ in roots may become greatly restricted by high levels of other cations

due to alkali stress (Wang et al., 2011). High pH (> 8.5) could disrupt plant

photosynthetic activities (Yang et al., 2008b) and anti-oxidative metabolism (Kukavica

et al., 2013), as well as further interfering with ion uptake and mineral nutrition (Peng

et al., 2008).

4.2.3. MINERAL PRECIPITATION

Both source water from Marandoo and the fertigation mixture for irrigation were

oversaturated with respect to carbonate and (hydr)oxide minerals of Ca, Mg, Fe and Mn,

as well as phosphate as apatite (Table 10). Since groundwater partial pressures, such as

CO2, are typically ~10-100 times higher than atmospheric partial pressures,

groundwater abstraction (as in the case of mine dewatering) results in CO2 degassing


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(Macpherson, 2009). With respect to Ca and Mg carbonates, findings were also

consistent with PHREEQC models by Crisalis International Pty Ltd (2012), showing

groundwater from production bores at Marandoo, Hope Downs 1 and Nammuldi iron

ore mines were indeed saturated (calcite) to oversaturated (dolomite) and became

strongly oversaturated on equilibrium with air. Consequently, mineral precipitation

from these waters may be expected (Wetland Research & Management, 2012).

However, oversaturation alone is not sufficient cause for the salts to crystallise

(Chew, 2006). The formation of a new crystalline entity is governed by two major

mechanisms: nucleation and crystal growth (De Yoreo and Vekilov, 2003). Precipitation

begins from the nucleation process which involves the formation of ordered molecular

aggregates or nucleus (Melia and Moffitt, 1964). However, spontaneous crystal growth

will not occur until the nucleus achieves a critical size (Cubillas and Anderson, 2010).

The probability that nucleation will occur nonetheless increases exponentially as a

function of the degree of oversaturation (Huang et al., 2012a), and even more so in the

presence of foreign particles or surfaces (heterogeneous nucleation) than in bulk

solution (homogeneous nucleation; Melia and Moffitt, 1964, Chew, 2006). The

temperature of water is also an important factor influencing solubility and hence mineral

crystallisation.

Considering their relatively high degree of oversaturation in the fertigation

mixture, dolomite, hausmannite, hematite and hydroxyapatite are the mineral forms

most likely to precipitate from the irrigation water (Table 10).

4.2.3.1. IMPLICATIONS FOR NUTRIENT AVAILABILITY

The immobilisation of Ca, Mg, P, Fe and Mn in irrigation water will clearly affect

their availability in the soil solution, especially due to elevated soil pH (Huang et al.,

2012a). More importantly, P availability may be substantially reduced due to

precipitation of Ca-P compounds such as hydroxyapatite from irrigation water and/or

soil solution (Brady, 1990), including the adsorption of P to insoluble Fe and Mn

(hydr)oxide and lime particles (von Wandruszka, 2006, Elzinga and Sparks, 2007).

Likewise, (co-)precipitation and adsorption reactions may also have a major influence

on trace element availability (Han, 2007).

Precipitation and surface adsorption are two major mechanisms for P retention

(von Wandruszka, 2006). Geochemical modelling suggests that the precipitation of

hydroxyapatite from irrigation water could initially be an issue for P availability.


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Furthermore, surface adsorption by Fe and Mn (hydr)oxides and Ca and Mg carbonates

added from irrigation water may also significantly contribute to P retention in the soil

(Kitano et al., 1978b, von Wandruszka, 2006) as reflected by increases in PRI over 15

months of sampling. In acid soils, P occlusion frequently occurs in the presence of Fe, Al

and Mn ions and even more extensively with their insoluble hydrous oxides by forming

insoluble hydroxy phosphate (Lewis et al., 1981, Brady, 1990, Søvik and Kløve, 2005, von

Wandruszka, 2006). In alkaline and calcareous soils (pH > 7), Ca2+ ions released from the

exchange complex or solubilised from carbonate phases (Tunesi et al., 1999) will have a

greater determining role by precipitating P as insoluble Ca-P compounds such as apatite

(Brady, 1990, Søvik and Kløve, 2005).

By comparing their relative importance, Ca and Mg carbonates will likely have a

greater influence on P availability than Fe and Mn (hydr)oxides because the amount of

carbonate added from irrigation water, relative to added P, greatly exceeds inputs of Fe

and Mn which are present in far lower concentrations. Hence, Fe and Mn (hydr)oxides

will generally make only a small contribution to P retention in these soils (e.g., Tunesi et

al., 1999). However, despite the potential net gain in CCE from irrigation water, there

was no significant change in soil CCE throughout the study (Table 4). Moreover, the real

CCE value could not be confirmed by either of the two procedures for determining soil

CCE (see Appendix E). Notwithstanding the stable CCE values over time, there remains

some doubt as to the amount of carbonate present in the soils.

Increases in the PRI, which were thought to be associated with soil carbonate,

were also not correlated (R2 ≤ 0.04; Tables 6 and 7). But despite clear evidence that PRI

had consistently increased, leaf P concentrations significantly increased from deficient

levels at the start of sampling to near-adequate levels after 15 months. This suggests the

P contained in fertigation mixture was counterbalancing any P sorption and thus the P

available for uptake by C. gayana. In the future, on-going precipitation and adsorption

reactions as a result of accumulating Ca and Mg carbonates, and possibly by Fe and Mn

(hydr)oxides, in the soil may continue to limit P uptake by C. gayana, however this can

be compensated by additional P applications in fertiliser.

The availability of certain micronutrients in the soil solution may also be greatly

affected by (1) dissolution and (co-)precipitation, (2) adsorption and desorption, (3)

complexation and (4) redox reactions (Han, 2007). Mineral dissolution and precipitation

reactions often govern the activities of trace elements (Deverel et al., 2011), particularly


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62

in arid and semi-arid environments where carbonates, sulphates, phosphates and

hydroxides exert a major influence on their solubility (Han, 2007, Hooda, 2010).

Adsorption reactions are also relatively important mechanisms since trace element

activities are often too low to be controlled by precipitation and dissolution (Deverel et

al., 2011). This may involve adsorption to (hydr)oxides of Fe, Mn, and Al, organic matter,

clay minerals, and carbonates such as calcite and dolomite (Deverel et al., 2011, Hooda,

2010).

The precipitation of Ca and Mg carbonates and Fe and Mn (hydr)oxides from

irrigation water could thus have a significant role in the removal of plant micronutrients

(e.g., B, Cu, Fe, Mn, Ni and Zn) from the soil solution via (co-)precipitation and surface

adsorption (e.g., Kitano et al., 1978a). Though, in many instances, these mechanisms help

limit their toxicity and bioavailability (e.g., contaminated soils; Martinez and McBride,

1998, Bolan et al., 2003), micronutrient deficiencies may also occur if initial

concentrations in the soil are low (Yoshida and Tanaka, 1969, Keren and Bingham, 1985,

Manda, 2009). At this stage, no abnormalities were recorded in leaf tissue samples, but

ongoing monitoring of plant samples is needed.

4.2.3.2. CARBONATE ACCUMULATION AND SOIL CEMENTATION

Due to high evaporation and evapotranspiration rates in the study area, and

continuous irrigation with dolomitic waters, the concentrations of Ca2+, Mg2+ and HCO3-

in the soil will cause carbonates to increase (Nash and Smith, 2003, Durand et al., 2010).

Through time, carbonate precipitation may plug soil pores and develop soils with some

degree of cementation (Nash and Smith, 2003, Duniway et al., 2010) which may impede

the foraging ability of roots to uptake water and nutrients (Passioura, 1991). However,

the effect of reduced pore space and soil cementation will depend on the amount of

carbonate precipitation and its distribution (e.g., along the irrigation supply line, at the

soil surface and/or at a specific depth in the soil profile).

Although there was no observable increase in soil CCE, mass balance calculations

indicated that, on average, approximately 3.2 t CaCO3/ha could accumulate in the soil

annually. If carbonate accumulation occurs within the 0-10 cm depth, and assuming a

soil bulk density of 1.5 t/m3, CaCO3 and MgCO3 may comprise 4.3% of the soil mass after

20 years. That is, soil cementation may occur when sufficient amounts of carbonate have

accumulated in the future. Long-term investigations could measure changes in the

compressive strength of the soil where precipitation has occurred (e.g., Park et al., 2014).


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63

However, it is still unclear as to whether reduced soil porosity and increased

cementation from carbonate precipitation will occur, including its effects on plant

growth (e.g., van Alphen and de los Rios Romero, 1971, Saporetti-Junior et al., 2012).

In addition, carbonate precipitation has the potential to cause equipment

blockages and damage pressure gauges due to excessive clogging (Yiasoumi et al., 2005),

but no significant problems have been reported at present (S. Mathwin 2014, HAP

Superintendent pers. Comm., 6 May).

4.3. MINOR FINDINGS

4.3.1. EFFECT ON EXCHANGEABLE BASE CATIONS

Significant decreases in exchangeable Ca2+ percentage (by 10.4% at 0-10 cm and

7.1% at 20-30 cm; Table 4), and to a lesser extent exchangeable K+ percentage (by 4.5%

at 0-10 cm and 3.0% at 20-30 cm), were primarily attributed to the increase of

exchangeable Mg2+ as a proportion of cation exchange capacity. Indeed, all exchangeable

cations, except K+ at 20-30 cm, increased in concentration with Mg2+ increasing more

than others. Although ESP also significantly increased (by 2.0% at 0-10 cm and 6.4% at

20-30 cm), Na+ was a lesser cation contributing to the decline in exchangeable Ca2+

percentage presumably because Na+ is weakly sorbed on exchange sites relative to the

divalent Ca2+. However, a subsequent study found that almost all the sodium in the soil

were as soluble Na+ and not found in the exchangeable form (Figures 70 and 71;

Samaraweera, 2015).

More importantly, increases in soil pHCa were strongly correlated with increases

in exchangeable Mg2+ at 0-10 cm (Table 6), suggesting the predominance of Mg

bicarbonates in irrigation water. Exchangeable Ca2+, on the other hand, was not

correlated with pH change. The prevalence of dolomite and, to a lesser degree, calcite

was also supported by geochemical models (Table 10). This type of water is generated

when the groundwater is in contact with dolomite formations (Mazor, 2004) which,

according to geological reports, is primarily attributed to the Wittenoom Formation that

constitutes the deeper aquifer unit at Marandoo (Rio Tinto Iron Ore, 2008).

Changes in the proportion of exchangeable bases in the soil may adversely affect

plant nutrition by causing deficiencies in cations such as Ca2+ (e.g., Davis et al., 2012).


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When soil cation ratios are in balance, the relative proportions of exchangeable bases in

the soil are: Ca2+ 65-70 %, Mg2+ 15-20 %, K+ 5 % and Na+ < 5 % (Hall, 2008). After 15

months of irrigation, overall mean abundance of cations at 0-10 cm and 20-30 cm were

approximately: Ca2+ 48 and 55 %, Mg2+ 37 and 26 %, K+ 10 %, and Na+ 5 and 7 %,

respectively. The proportion of exchangeable Mg-2+ was thus relatively high at 0-10 cm,

while that of exchangeable Ca2+ was comparatively low. Excessive Mg2+ concentrations

may adversely affect C. gayana due to their relatively low tolerance as compared to that

of high Na+ (Pengelly et al., 2006). Moreover, high Mg2+ will alter soil physical properties,

such as hydraulic conductivity, by causing the clay to become dispersed with decreased

macroporosity which in turn limits drainage, root penetration and thus nutrient

availability (Hall, 2008). Leaf tissue analysis, however, showed no deficiencies in Ca or

K, and no excess of Na or Mg despite being slightly higher than the normal concentration

range reported by Cameron (2001; Table 15). While this suggests C. gayana growth was

not adversely affected, the consequences of ongoing loading of soils with Mg2+ and Na+

need to be monitored through plant analysis.

Table 15. Comparing mean leaf nutrient concentrations of C. gayana in December 2013 with

"normal"/adequate nutrient concentration ranges for C. gayana and Phalaris aquatica.

Parameter Units

Chloris gayana Phalaris aquatica

HAP Dec-13 Cameron (2001) Reuter and

Robinson (1997) Reuter and

Robinson (1997)

Total N % 2.10 (± 0.08) 1.0 - 2.0-3.2

P % 0.19 (± 0.01) 0.14-0.27 < 0.20 (deficient),

0.24-0.34 (adequate)

0.20-0.25

K % 1.85 (± 0.06) 1.60-1.70 > 0.50 1.7-2.0

Ca % 0.56 (± 0.01) 0.40 - 0.14-0.20

Mg % 0.22 (± 0.01) 0.13-0.14 - 0.16-0.22

Na % 0.47 (± 0.12) 0.34-0.38 - -

S % 0.31 (± 0.01) 0.19-0.27 >0.12 0.21-0.25

Cu mg/kg 7.3 (± 0.3) 4.0 - 2.0-4.0

Fe mg/kg 113 (± 6) 121-341 - 40-60

Mn mg/kg 208 (± 16) - > 700 (toxic) 20-30

Zn mg/kg 32.4 (± 1.7) 15-18 - 12-15

B mg/kg 8.1 (± 0.6) - > 150 (toxic) 8-15

4.3.2. HEAVY METALS AND METALLOIDS

Generally, heavy metals and metalloids including Al, B, Cd, Co, Cu, Fe, Pb, Mn, Mo

and Zn in irrigation water (Table 9) did not exceed long-term trigger values (i.e., for

irrigation up to 100 years), and Se concentrations did not exceed the short-term trigger

value (i.e., for irrigation up to 20 years; ANZECC/ARMCANZ, 2000). Thus, over the next


nutrition

65

20 years, heavy metals and metalloids are unlikely to accumulate in excessive levels as a

direct response to irrigation.

Total As, Cd and Pb concentrations in the soil did not significantly change over

15 months of irrigation. However, Cd and Pb concentrations in leaf tissue were

significantly higher in December, but were not nearly high enough to induce

phytotoxicity. On the contrary, As was detected at reasonably high concentrations in the

soil, around 15-17 mg/kg (Table 4), which could raise concern for C. gayana. Although

different plant species may tolerate concentrations from 1 to 50 mg As/kg in the soil

(Mascher et al., 2002), rates of 10 mg As/kg may begin to impede plant growth

(ANZECC/ARMCANZ, 2000) by inhibiting root proliferation and biomass accumulation

(Finnegan and Chen, 2012), as well as reducing photosynthetic efficiency and chlorophyll

biosynthesis (Sharma, 2012). At higher concentrations, As will interfere with critical

metabolic processes which can lead to various physiological and structural disorders

including death (Burló et al., 1999, Azizur Rahman et al., 2007, Finnegan and Chen, 2012).

Since As usually interferes with P metabolism (Gomes et al., 2012), adequate P in the soil

is important.

Chromium concentrations in the soil were significantly higher after 15 months

(300-350 mg/kg) despite a lack of consistency with previous sampling times – i.e., 70%

higher than the mean concentration 3 months prior (~200 mg/kg; Figure 27). In

comparison, mean leaf tissue concentrations in December (~4.8 mg Cr/kg) were at least

15 times higher than in September (~0.3 mg Cr/kg; Figure 36), but analysis showed no

correlation between soil and leaf Cr concentrations (Table 17 and 18). The resulting

spike in leaf Cr concentration could be due to analytical error and should thus be verified

with March 2014 and subsequent sampling data.

Conversely, if subsequent monitoring confirms that leaf Cr concentrations were

high, it is likely that prevailing oxidative conditions (facilitated by Fe and Mn oxides from

irrigation water) and an increased soil pH caused Cr(VI) to predominate in the system

(Hooda, 2010). The extent of Cr accumulation and phytotoxicity will vary depending on

its oxidation state, with Cr(VI) highly toxic and more mobile than Cr(III) (Shanker et al.,

2005). Due to its greater solubility, Cr(VI) is more readily absorbed by plants which

causes Cr to bioaccumulate at higher concentrations (Hooda, 2010). There is, then, a

possibility that irrigation could have resulted in the increased mobility and availability

of Cr(VI) despite variation in the total Cr concentration in the soil solution. Toxicity limits


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66

for Cr(VI) may range from 5 mg/kg to 500 mg/kg, while toxicity of Cr(III) may occur from

50 mg/kg to 5000 mg/kg, depending on the tolerance of plant species and soil type

(ANZECC/ARMCANZ, 2000). Should toxicity levels be verified, Cr could severely impair

photosynthetic and respiration processes, and the uptake of water and nutrients (Singh

et al., 2013). Based on the current leaf nutrient status of C. gayana, results suggest no

adverse impact from heavy metals and metalloids on plant growth.

4.3.2.1. IMPLICATIONS FOR FEED QUALITY

While it is important to ensure pastures and forage crops grow vigorously, it is

crucial that heavy metal and metalloid concentrations in the harvested forage hay are

maintained under maximum tolerable levels for livestock. Toxicosis may arise in

ruminant livestock (e.g., cattle), and subsequently in humans, as a result of excessive

exposure to elements such as Al, As, B, Cu, Cd, Cr, Fe, Mn, Ni, Pb, and Zn (Underwood and

Suttle, 1999).

Table 16. Comparing December 2013 concentrations in leaf tissue of C. gayana with maximum

tolerable levels (National Research Council, 2000) and overall toxicity limits (Underwood and

Suttle, 1999) for ruminant livestock (e.g., such as cattle and sheep).

Concentration in leaf tissue

of C. gayana (mg/kg) Maximum tolerable level

(mg/kg) Toxicity limit (mg/kg)

Ess

enti

al e

lem

ents

Cu 7.3 100 > 50 (calves) > 900 (after weaning)

Fe 113 1000 > 1000

Mn 208 1000 > 1000 (pre-ruminant calves) > 2600 (after weaning)

Zn 32.4 500 > 500-700 (pre-ruminant calves)

Occ

asio

nal

ly

ben

efic

ial B 8.1 > 10-100

Cr 4.6 1000 > 1000

Ni 2.0 50 > 50 (as NiCl3) > 250 (as NiCO3)

Po

ten

tial

ly t

oxi

c Al 31.5 1000 > 2000 (lambs)

As 0.08 50 (100 mg/kg for organic

forms)

Cd 0.03 0.5 > 50

Pb 0.09 30 > 2000

The maximum tolerable concentration for a mineral has been defined as the “dietary level that, when fed for a limited period, will not impair animal performance and should not produce unsafe residues in human food derived from the animal" (National Research Council, 2000).


nutrition

67

To date, results show their overall mean concentrations were relatively low in

leaf tissue and well below the established maximum tolerable levels (National Research

Council, 2000; Table 16). Therefore, the current concentration of heavy metals and

metalloids should not adversely affect the feed quality of C. gayana.

4.3.3. VOLATILISATION OF NITROGEN FERTILISERS

It is well known that substantial amounts of N applied as urea to moist alkaline

soils under warm conditions can be lost via volatilisation of NH3 gas (Ryan et al., 1981,

Marlet et al., 1998). This may affect the efficiency of N use, particularly as soils become

more alkaline over time. The implications of this loss pathway are not explored in this

thesis, but are an area for future investigation, particularly in regards to the optimum

rates of N fertilizer required to maintain crop growth.

4.4. MANAGEMENT IMPLICATIONS

In the future, alkalinisation could emerge as an important issue for the HAP

whereby soil pH may increase to levels that can compromise soil nutritional balance for

C. gayana. Additionally, given suitable conditions for nucleation, the precipitation of

carbonate and (hydr)oxide minerals of Ca, Mg, Fe and Mn, as well as phosphate as apatite

may further reduce the bioavailability of nutrients in the soil, including other

micronutrients such as B, Cu, Fe, Mn, Ni and Zn due mainly to enhanced (co-

)precipitation and surface adsorption reactions. It is, therefore, important that irrigation

water and soil quality is managed effectively to alleviate or mitigate adverse impact(s)

on the long-term sustainability of pasture production, keeping in mind the fate of the site

after decommissioning (e.g., site rehabilitation).

A number of strategies could be assessed and trialled to determine an

appropriate treatment regime for HAP. This primarily includes the neutralisation of

excess alkalinity in irrigation water and/or in the soil, such that soil alkalinisation ceases

and soil pH can be maintained within an ideal range.

Excess alkalinity in irrigation water may be neutralised by injecting equivalent

quantities of sulphuric acid to the bulk solution before irrigation (Kidder and Hanlon,

1998). Applying elemental sulphur (Spiers and Braswell, 1992) and/or ammonium

sulphate fertiliser will also help lower the pH (Gearhart and Collamer, 2009). To prevent

mineral precipitation from occurring in irrigation water or the soil, the pH of the


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68

fertigation solution should be adjusted ≤ 7.0 (Table 11) to ensure calcite and dolomite,

and Mn minerals, remain undersaturated in irrigation water. Note that Fe minerals and

hydroxyapatite will still remain oversaturated in the fertigation solution; however, P

availability may be corrected by addition of more P directly to the soil as granular

fertiliser (Scientific Staff of the International Plant Nutrition Institute, 2010).

In the same way that gypsum helps to improve soil flocculation (e.g., by

increasing the ionic strength of the soil solution and displacing exchangeable Na by Ca;

Sumner, 1993), resulting increases in SO42- and Ca2+ concentration after sulphuric acid

injection could also help reduce the risk of dispersion developing in the soil. Sulphuric

acid has been recognised as an effective agent for reclaiming sodic soils by releasing

soluble Ca2+ from free lime (Abrol et al., 1988).

Given that irrigation water per se already contains Ca2+ and Mg2+, this may also

be sufficient to prevent excessive dispersion should sodicity continue to rise in the long-

term – i.e., the system reaches equilibrium at a moderate but not harmful ESP. However,

further study should be undertaken to confirm this based on laboratory tests using

columns leached continuously with Ca-/Mg-rich water. The Hydrus model, a public

domain Windows-based modelling environment (Šimůnek et al., 2008), may also be used

to predict long term changes in cation retention and leaching. Moreover, soil properties

should be monitored for hydraulic conductivity and the Emerson aggregate test

(Emerson, 1967) conducted periodically to identify any potential problems with clay

dispersion. This can be done both on existing, retained soil samples, and future samples.

After neutralising excess irrigation alkalinity, ongoing monitoring should

examine consequential changes in: (1) soil pH, (2) exchangeable cations, and (3) nutrient

availability. This will determine if further treatment with gypsum is required to manage

sodicity. In cases of extreme sodicity, occasional deep cultivation with gypsum will

further improve water penetration and aeration (Hughes, 1999).

4.4.1. OTHER IRRIGATION PROJECTS IN THE REGION

Another irrigation project commencing in the Pilbara region is the Nammuldi-

Silvergrass Agricultural Project that utilises surplus water from the Nammuldi-

Silvergrass Rio Tinto Iron Ore Project (Rio Tinto Iron Ore, 2012). As the composition of

source water is relatively similar to that at Marandoo (e.g., Crisalis International Pty Ltd,

2012), this study should provide useful insights into the potential implications of

irrigation for long-term pasture production and soil management.


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69

4.4.2. REHABILITATION AFTER DECOMMISSIONING

Following the cessation of below-watertable mining at Marandoo, the HAP will

undergo decommissioning and the disturbed land will require rehabilitation. Where

practicable, some areas will also be progressively rehabilitated as they are no longer

needed (Hamersley Iron Pty Ltd, 2011). Thus, it is imperative that current irrigation and

soil management practices, over the next 20 years, maintain conditions suitable for

restoring local provenance plant species. In the future, substantial changes in soil

properties may warrant research on the implications for rehabilitation.


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5. CONCLUSION

The continuous irrigation of slightly alkaline and slightly brackish-sodic

groundwater at the HAP has caused significant changes to soil properties over 15

months. Although C. gayana was not adversely affected at this stage, irrigation is planned

to continue for the next 20 years, based on the life of the MMP2 project. While subsequent

analysis has shown that irrigation has not caused a measurable change in sodicity,

alkalinisation could however emerge as a problem by reducing the availability of various

nutrients under alkaline soil pH. Moreover, given suitable conditions for nucleation and

crystal growth, the precipitation of Ca and Mg carbonates, iron oxides and phosphorus

as apatite, may occur which could further immobilise plant nutrients. However, further

investigation is required to determine specifically the effect of mineral precipitation on

trace element mobility.

As the current rate of alkalinisation is relatively slow in the subsoil, nutrient

deficiencies should not occur rapidly and, due to limited solubility of Ca and Mg

carbonates, soil pH is unlikely to exceed ~8.2. Despite initial reports of high ESP levels

(> 5-7 %), a follow-up study suggested there was no significant change in the ESP and

hence no imminent risk of soil sodicity. It is therefore recommended that the

determination of ESP in soils samples in the future should be carried out by employing

methods that include pre-treatment for soluble salts to avoid overestimating the Na

concentration in the cation exchange complex. While the critical threshold value for

dispersion in these soils has not been determined, examining changes in hydraulic

conductivity and clay dispersion along with routine monitoring and field tests (e.g. the

Emerson aggregate test) may provide additional information.

Increases in soil pH may occur less gradually through time as the system reaches

equilibrium. But, to ensure that thresholds are not exceeded, the pH of the irrigation

water can be corrected to ≤ 7. Various methods, such as sulphuric acid injection or

applying elemental sulphur or ammonium sulphate fertiliser, may be used to neutralise

excess alkalinity. This may also help prevent mineral precipitation and arrest

alkalinisation, while also increasing SO42- and Ca+ concentrations that could counteract

sodicity by increasing the ionic strength of the soil solution and displacing exchangeable

Na+ by Ca2+.

In relation to in-stream discharge, similar physicochemical changes to the soil

could also occur and have significant implications for stream and riparian vegetation. In


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71

particular, the uncontrolled and undisturbed accumulation of insoluble carbonates from

continuous discharge may have a greater potential for cementation in the creek-bed (e.g.,

as in the case at Weeli Wolli Creek; Wetland Research & Management, 2010, Crisalis

International Pty Ltd, 2012) than in irrigated soil. Therefore, as in-stream discharge

becomes increasingly practiced, this could become an important area of research.


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APPENDIX A: CORRELATION ANALYSIS

SOIL PROPERTIES AND LEAF NUTRIENT COMPOSITION

Table 17. Correlation (R2) between leaf nutrient composition and soil properties at 0-10 cm, using only Span 3 data from March to December 2013

Leaf nutrients and trace elements Total N NO3-N P K Ca Mg Na Cl S Cu Fe Mn Zn B Al As Cd Cr Pb Ni

Soil

pro

per

ties

EC 0.01 0.08 0.00 0.00 0.17 0.00 0.04 0.00 0.01 0.00 0.01 0.01 0.06 0.02 0.00 0.05 0.09 0.04 0.00 0.00 pHCa 0.00 0.07 0.05 0.01 0.11 0.19 0.02 0.00 0.22 0.00 0.00 0.02 0.04 0.34 0.03 0.00 0.01 0.23 0.23 0.15

CCE 0.03 0.03 0.07 0.06 0.06 0.03 0.03 0.23 0.00 0.02 0.30 0.06 0.12 0.02 0.05 0.10 0.07 0.00 0.04 0.02 OC 0.00 0.00 0.00 0.01 0.19 0.04 0.00 0.02 0.04 0.01 0.00 0.01 0.00 0.11 0.02 0.00 0.04 0.01 0.01 0.05 NO3-N 0.07 0.09 0.02 0.04 0.12 0.07 0.09 0.11 0.07 0.00 0.00 0.06 0.02 0.14 0.01 0.17 0.01 0.00 0.10 0.27 NH4-N 0.05 0.03 0.00 0.08 0.03 0.04 0.02 0.07 0.05 0.01 0.00 0.02 0.07 0.01 0.00 0.05 0.00 0.07 0.04 0.01 Total N 0.03 0.09 0.04 0.05 0.06 0.00 0.04 0.13 0.06 0.00 0.00 0.04 0.08 0.04 0.00 0.09 0.07 0.37 0.03 0.01 C/N 0.03 0.06 0.02 0.03 0.01 0.02 0.03 0.06 0.15 0.01 0.01 0.02 0.13 0.17 0.02 0.06 0.01 0.32 0.07 0.01 Colwell P 0.06 0.01 0.10 0.02 0.04 0.07 0.12 0.01 0.00 0.05 0.04 0.01 0.22 0.00 0.05 0.00 0.04 0.07 0.06 0.17 Total P 0.01 0.06 0.10 0.00 0.03 0.06 0.06 0.03 0.09 0.00 0.02 0.03 0.07 0.01 0.00 0.00 0.32 0.05 0.06 0.05 PRI 0.08 0.11 0.03 0.03 0.01 0.01 0.08 0.04 0.01 0.05 0.03 0.05 0.00 0.02 0.01 0.03 0.16 0.02 0.06 0.08 Colwell K 0.03 0.01 0.06 0.03 0.00 0.02 0.00 0.01 0.00 0.19 0.14 0.13 0.13 0.03 0.05 0.02 0.16 0.04 0.00 0.02 Total K 0.03 0.03 0.00 0.00 0.18 0.01 0.01 0.00 0.04 0.10 0.02 0.00 0.02 0.05 0.14 0.01 0.10 0.00 0.02 0.13 Ex. Ca 0.02 0.09 0.02 0.00 0.02 0.10 0.00 0.01 0.02 0.07 0.00 0.00 0.01 0.06 0.01 0.00 0.11 0.14 0.16 0.03 Ex. Mg 0.04 0.23 0.04 0.03 0.00 0.20 0.01 0.00 0.07 0.02 0.01 0.01 0.07 0.20 0.00 0.00 0.11 0.32 0.32 0.11 Ex. Na 0.05 0.21 0.00 0.01 0.06 0.05 0.07 0.00 0.01 0.00 0.00 0.00 0.14 0.02 0.00 0.03 0.13 0.15 0.11 0.05 Ex. K 0.04 0.04 0.05 0.02 0.01 0.01 0.00 0.00 0.00 0.17 0.09 0.09 0.08 0.03 0.05 0.00 0.16 0.05 0.01 0.02 Ex. Al 0.00 0.00 0.15 0.00 0.03 0.00 0.09 0.03 0.00 0.26 0.27 0.00 0.19 0.03 0.24 0.00 0.08 0.25 0.07 0.08 ECEC 0.04 0.17 0.03 0.01 0.01 0.14 0.01 0.00 0.04 0.05 0.01 0.01 0.03 0.11 0.01 0.00 0.14 0.22 0.22 0.06 Ca % 0.03 0.14 0.01 0.09 0.08 0.06 0.04 0.09 0.03 0.02 0.00 0.06 0.06 0.09 0.00 0.02 0.01 0.06 0.04 0.06 Mg % 0.02 0.22 0.02 0.08 0.13 0.20 0.02 0.05 0.11 0.02 0.00 0.03 0.13 0.28 0.01 0.01 0.01 0.22 0.27 0.20 ESP 0.04 0.09 0.01 0.01 0.07 0.00 0.09 0.00 0.00 0.01 0.02 0.01 0.14 0.01 0.00 0.08 0.01 0.02 0.00 0.02 K % 0.01 0.08 0.01 0.00 0.00 0.12 0.04 0.00 0.05 0.04 0.10 0.07 0.33 0.05 0.05 0.01 0.00 0.09 0.20 0.23 Al % 0.02 0.06 0.14 0.00 0.04 0.02 0.03 0.02 0.01 0.26 0.17 0.00 0.07 0.09 0.16 0.00 0.13 0.28 0.19 0.01 As 0.17 0.26 0.02 0.04 0.22 0.00 0.08 0.00 0.09 0.10 0.05 0.06 0.01 0.02 0.02 0.01 0.00 0.01 0.02 0.00 Cd 0.20 0.11 0.06 0.13 0.01 0.01 0.18 0.14 0.10 0.00 0.10 0.00 0.00 0.05 0.08 0.02 0.11 0.19 0.00 0.02 Cr 0.03 0.00 0.02 0.04 0.00 0.00 0.20 0.24 0.06 0.01 0.05 0.00 0.01 0.15 0.09 0.11 0.03 0.47 0.10 0.03 Pb 0.07 0.01 0.02 0.07 0.17 0.09 0.08 0.11 0.00 0.02 0.00 0.14 0.00 0.00 0.07 0.06 0.00 0.04 0.00 0.03


Table 18. Correlation (R2) between leaf nutrient composition and soil properties at 20-30 cm, using only Span 3 data from March to December 2013

Leaf nutrients and trace elements Total N NO3-N P K Ca Mg Na Cl S Cu Fe Mn Zn B Al As Cd Cr Pb Ni

Soil

pro

per

ties

EC 0.00 0.09 0.17 0.00 0.00 0.12 0.01 0.01 0.10 0.03 0.10 0.02 0.06 0.16 0.02 0.02 0.31 0.51 0.13 0.02 pHCa 0.00 0.00 0.02 0.00 0.07 0.06 0.00 0.00 0.03 0.01 0.06 0.00 0.03 0.01 0.17 0.00 0.02 0.00 0.00 0.03 CCE 0.00 0.02 0.10 0.04 0.04 0.00 0.04 0.20 0.01 0.00 0.17 0.03 0.03 0.02 0.01 0.21 0.06 0.01 0.02 0.05 OC 0.00 0.11 0.04 0.00 0.00 0.00 0.00 0.00 0.07 0.00 0.01 0.02 0.03 0.08 0.01 0.07 0.03 0.33 0.12 0.03 NO3-N 0.12 0.14 0.03 0.02 0.01 0.15 0.06 0.08 0.08 0.00 0.00 0.02 0.08 0.10 0.01 0.00 0.06 0.05 0.09 0.20 NH4-N 0.00 0.04 0.01 0.03 0.09 0.00 0.00 0.06 0.02 0.03 0.09 0.12 0.25 0.00 0.00 0.07 0.00 0.02 0.02 0.03 Total N 0.13 0.00 0.00 0.11 0.09 0.03 0.11 0.19 0.00 0.00 0.01 0.03 0.00 0.00 0.03 0.15 0.00 0.11 0.01 0.27 C/N 0.09 0.04 0.01 0.06 0.06 0.01 0.07 0.15 0.02 0.02 0.01 0.07 0.04 0.02 0.01 0.24 0.01 0.30 0.02 0.06 Colwell P 0.00 0.08 0.00 0.01 0.06 0.22 0.00 0.03 0.23 0.07 0.05 0.00 0.42 0.22 0.12 0.05 0.02 0.15 0.29 0.28 Total P 0.04 0.06 0.04 0.00 0.04 0.02 0.08 0.04 0.06 0.00 0.01 0.06 0.06 0.01 0.02 0.03 0.20 0.00 0.05 0.06 PRI 0.00 0.07 0.06 0.00 0.01 0.00 0.01 0.01 0.01 0.02 0.01 0.09 0.01 0.01 0.00 0.01 0.11 0.03 0.00 0.00 Colwell K 0.04 0.05 0.07 0.08 0.00 0.01 0.01 0.05 0.01 0.21 0.29 0.17 0.13 0.02 0.20 0.05 0.26 0.03 0.02 0.01 Total K 0.02 0.00 0.02 0.00 0.34 0.12 0.01 0.03 0.14 0.12 0.01 0.05 0.03 0.15 0.06 0.00 0.00 0.01 0.08 0.09 Ex. Ca 0.01 0.04 0.03 0.00 0.00 0.12 0.00 0.00 0.03 0.02 0.03 0.01 0.04 0.04 0.01 0.01 0.24 0.11 0.08 0.01 Ex. Mg 0.07 0.24 0.00 0.04 0.01 0.13 0.04 0.01 0.02 0.02 0.01 0.02 0.07 0.08 0.00 0.01 0.09 0.11 0.14 0.04 Ex. Na 0.01 0.18 0.12 0.01 0.02 0.14 0.00 0.00 0.11 0.05 0.10 0.03 0.04 0.23 0.02 0.02 0.29 0.55 0.23 0.08 Ex. K 0.06 0.07 0.03 0.03 0.01 0.00 0.01 0.01 0.02 0.23 0.17 0.08 0.06 0.00 0.22 0.00 0.23 0.04 0.01 0.04 Ex. Al 0.00 0.03 0.06 0.00 0.00 0.00 0.04 0.02 0.01 0.19 0.06 0.00 0.07 0.00 0.02 0.00 0.03 0.14 0.00 0.10 ECEC 0.03 0.11 0.03 0.00 0.00 0.13 0.01 0.00 0.03 0.04 0.04 0.03 0.05 0.07 0.02 0.01 0.25 0.15 0.12 0.02 Ca % 0.02 0.11 0.01 0.11 0.04 0.00 0.02 0.04 0.00 0.00 0.00 0.02 0.00 0.02 0.00 0.00 0.03 0.00 0.01 0.02 Mg % 0.03 0.14 0.04 0.06 0.04 0.01 0.04 0.03 0.00 0.01 0.03 0.00 0.04 0.01 0.02 0.00 0.06 0.00 0.01 0.03 ESP 0.00 0.16 0.10 0.01 0.05 0.07 0.02 0.00 0.13 0.03 0.07 0.02 0.02 0.27 0.00 0.00 0.13 0.52 0.20 0.13 K % 0.00 0.01 0.00 0.03 0.04 0.19 0.00 0.00 0.22 0.17 0.11 0.01 0.43 0.09 0.22 0.02 0.00 0.07 0.13 0.27 Al % 0.01 0.09 0.07 0.00 0.00 0.00 0.01 0.01 0.00 0.20 0.06 0.00 0.02 0.02 0.02 0.00 0.11 0.18 0.02 0.03 As 0.03 0.13 0.01 0.00 0.12 0.03 0.02 0.00 0.00 0.00 0.06 0.03 0.10 0.00 0.00 0.03 0.01 0.08 0.07 0.03 Cd 0.10 0.14 0.03 0.10 0.00 0.03 0.12 0.11 0.01 0.01 0.09 0.01 0.02 0.00 0.03 0.00 0.09 0.04 0.01 0.12 Cr 0.07 0.00 0.09 0.06 0.00 0.00 0.14 0.21 0.06 0.01 0.08 0.01 0.01 0.10 0.07 0.07 0.04 0.41 0.04 0.01 Pb 0.00 0.00 0.01 0.00 0.00 0.01 0.06 0.01 0.00 0.10 0.00 0.05 0.02 0.00 0.02 0.01 0.00 0.19 0.00 0.00


LEAF NUTRIENT COMPOSITION

Table 19. Correlation (R2) between leaf composition, using only Span 3 data from March to December 2013

Total N P K Ca Mg Na Cl S Cu Fe Mn Zn B NO3-N Al As Cd Cr Pb Ni

Total N 1.00 0.08 0.53 0.01 0.00 0.45 0.18 0.18 0.47 0.13 0.13 0.00 0.03 0.67 0.06 0.19 0.16 0.01 0.00 0.18

P 0.08 1.00 0.18 0.01 0.01 0.20 0.02 0.44 0.01 0.03 0.00 0.00 0.23 0.00 0.02 0.04 0.16 0.24 0.09 0.01

K 0.53 0.18 1.00 0.12 0.02 0.56 0.46 0.24 0.26 0.00 0.00 0.02 0.01 0.35 0.00 0.08 0.07 0.01 0.01 0.10

Ca 0.01 0.01 0.12 1.00 0.18 0.06 0.28 0.08 0.03 0.12 0.12 0.00 0.18 0.00 0.02 0.03 0.00 0.00 0.02 0.18

Mg 0.00 0.01 0.02 0.18 1.00 0.02 0.03 0.09 0.02 0.03 0.22 0.21 0.22 0.00 0.00 0.05 0.06 0.05 0.14 0.10

Na 0.45 0.20 0.56 0.06 0.02 1.00 0.60 0.16 0.04 0.01 0.01 0.02 0.10 0.25 0.00 0.10 0.03 0.14 0.00 0.12

Cl 0.18 0.02 0.46 0.28 0.03 0.60 1.00 0.01 0.00 0.03 0.03 0.01 0.00 0.07 0.00 0.17 0.00 0.11 0.00 0.14

S 0.18 0.44 0.24 0.08 0.09 0.16 0.01 1.00 0.28 0.03 0.04 0.14 0.48 0.03 0.01 0.00 0.11 0.14 0.22 0.15

Cu 0.47 0.01 0.26 0.03 0.02 0.04 0.00 0.28 1.00 0.02 0.09 0.17 0.05 0.33 0.00 0.04 0.02 0.04 0.00 0.00

Fe 0.13 0.03 0.00 0.12 0.03 0.01 0.03 0.03 0.02 1.00 0.35 0.17 0.15 0.14 0.70 0.07 0.35 0.04 0.07 0.07

Mn 0.13 0.00 0.00 0.12 0.22 0.01 0.03 0.04 0.09 0.35 1.00 0.01 0.17 0.25 0.19 0.22 0.37 0.00 0.00 0.03

Zn 0.00 0.00 0.02 0.00 0.21 0.02 0.01 0.14 0.17 0.17 0.01 1.00 0.05 0.04 0.17 0.01 0.02 0.03 0.02 0.12

B 0.03 0.23 0.01 0.18 0.22 0.10 0.00 0.48 0.05 0.15 0.17 0.05 1.00 0.00 0.03 0.00 0.07 0.30 0.35 0.11

NO3-N 0.67 0.00 0.35 0.00 0.00 0.25 0.07 0.03 0.33 0.14 0.25 0.04 0.00 1.00 0.10 0.16 0.13 0.05 0.02 0.20

Al 0.06 0.02 0.00 0.02 0.00 0.00 0.00 0.01 0.00 0.70 0.19 0.17 0.03 0.10 1.00 0.10 0.15 0.00 0.03 0.13

As 0.19 0.04 0.08 0.03 0.05 0.10 0.17 0.00 0.04 0.07 0.22 0.01 0.00 0.16 0.10 1.00 0.11 0.04 0.03 0.35

Cd 0.16 0.16 0.07 0.00 0.06 0.03 0.00 0.11 0.02 0.35 0.37 0.02 0.07 0.13 0.15 0.11 1.00 0.08 0.02 0.05

Cr 0.01 0.24 0.01 0.00 0.05 0.14 0.11 0.14 0.04 0.04 0.00 0.03 0.30 0.05 0.00 0.04 0.08 1.00 0.18 0.00

Pb 0.00 0.09 0.01 0.02 0.14 0.00 0.00 0.22 0.00 0.07 0.00 0.02 0.35 0.02 0.03 0.03 0.02 0.18 1.00 0.18

Ni 0.18 0.01 0.10 0.18 0.10 0.12 0.14 0.15 0.00 0.07 0.03 0.12 0.11 0.20 0.13 0.35 0.05 0.00 0.18 1.00 Strength of relationship: 0.80 to 0.99 (very strong); 0.60 to 0.79 (strong); 0.40 to 0.59 (moderate); 0.20 to 0.39 (weak); and 0.00 to 0.19 (very weak). All moderate to very strong correlations are significant at the 0.01 level (2-tailed).

93

APPENDIX B: WEB-PHREEQ OUTPUT DATA

DEWATERING SURPLUS

TITLE Dewatering surplus (December 2013)

SOLUTION 1

pH 8.2

temp 29.5

pe

units mg/L

Alkalinity 240

Al 0.01

B 0.3

Cd 0.0005

Ca 61

C 270 as HCO3

Cl 120

Cu 0.016

Fe 0.01

Pb 0.01

Mg 50

Mn 0.007

N 0.36

P 0.01

K 13

Na 42

S 76 as SO4-2

Zn 0.08

END

-----

TITLE

-----

Dewatering surplus (December 2013)

-------------------------------------------

Beginning of initial solution calculations.

-------------------------------------------

Initial solution 1.

pH will be adjusted to obtain desired alkalinity.

-----------------------------Solution composition------------------------------

Elements Molality Moles

Al 3.709e-07 3.709e-07

Alkalinity 4.800e-03 4.800e-03

B 2.778e-05 2.778e-05

C 4.429e-03 4.429e-03

Ca 1.523e-03 1.523e-03

Cd 4.452e-09 4.452e-09

Cl 3.388e-03 3.388e-03

Cu 2.520e-07 2.520e-07

Fe 1.792e-07 1.792e-07

K 3.328e-04 3.328e-04

Mg 2.058e-03 2.058e-03

Mn 1.275e-07 1.275e-07

N 2.572e-05 2.572e-05

Na 1.828e-03 1.828e-03

P 3.231e-07 3.231e-07

Pb 4.831e-08 4.831e-08

S 7.918e-04 7.918e-04

Zn 1.225e-06 1.225e-06

----------------------------Description of solution----------------------------

pH = 8.672 Adjust alkalinity

pe = 8.200

Activity of water = 1.000

Ionic strength = 1.241e-02


nutrition

94

Mass of water (kg) = 1.000e+00

Total CO2 (mol/kg) = 4.429e-03

Temperature (deg C) = 29.500

Electrical balance (eq) = -4.423e-04

Percent error, 100*(Cat-|An|)/(Cat+|An|) = -2.57

Iterations = 10

Total H = 1.110166e+02

Total O = 5.552275e+01

----------------------------Distribution of species----------------------------

Log Log Log

Species Molality Activity Molality Activity Gamma

OH- 7.370e-06 6.558e-06 -5.133 -5.183 -0.051

H+ 2.350e-09 2.128e-09 -8.629 -8.672 -0.043

H2O 5.551e+01 9.998e-01 -0.000 -0.000 0.000

Al 3.709e-07

Al(OH)4- 3.706e-07 3.306e-07 -6.431 -6.481 -0.050

Al(OH)3 3.482e-10 3.492e-10 -9.458 -9.457 0.001

Al(OH)2+ 4.103e-12 3.661e-12 -11.387 -11.436 -0.050

AlOH+2 1.071e-15 6.784e-16 -14.970 -15.168 -0.198

Al+3 2.652e-19 1.088e-19 -18.576 -18.963 -0.387

AlSO4+ 1.578e-19 1.408e-19 -18.802 -18.851 -0.050

Al(SO4)2- 1.969e-21 1.757e-21 -20.706 -20.755 -0.050

AlHSO4+2 4.376e-29 2.773e-29 -28.359 -28.557 -0.198

B 2.778e-05

H3BO3 2.089e-05 2.095e-05 -4.680 -4.679 0.001

H2BO3- 6.885e-06 6.143e-06 -5.162 -5.212 -0.050

C(-4) 0.000e+00

CH4 0.000e+00 0.000e+00 -115.987 -115.986 0.001

C(4) 4.429e-03

HCO3- 3.944e-03 3.533e-03 -2.404 -2.452 -0.048

CO3-2 1.316e-04 8.481e-05 -3.881 -4.072 -0.191

CaCO3 1.293e-04 1.297e-04 -3.888 -3.887 0.001

MgCO3 1.000e-04 1.003e-04 -4.000 -3.999 0.001

MgHCO3+ 5.480e-05 4.889e-05 -4.261 -4.311 -0.050

CaHCO3+ 4.424e-05 3.964e-05 -4.354 -4.402 -0.048

CO2 1.604e-05 1.609e-05 -4.795 -4.793 0.001

NaCO3- 3.596e-06 3.208e-06 -5.444 -5.494 -0.050

NaHCO3 3.218e-06 3.227e-06 -5.492 -5.491 0.001

Zn(CO3)2-2 8.349e-07 5.290e-07 -6.078 -6.277 -0.198

ZnCO3 2.909e-07 2.917e-07 -6.536 -6.535 0.001

MnCO3 9.826e-08 9.854e-08 -7.008 -7.006 0.001

PbCO3 3.582e-08 3.592e-08 -7.446 -7.445 0.001

Pb(CO3)2-2 1.208e-08 7.652e-09 -7.918 -8.116 -0.198

ZnHCO3+ 8.595e-09 7.669e-09 -8.066 -8.115 -0.050

MnHCO3+ 5.163e-09 4.606e-09 -8.287 -8.337 -0.050

CdHCO3+ 2.417e-10 2.156e-10 -9.617 -9.666 -0.050

CdCO3 1.296e-10 1.300e-10 -9.887 -9.886 0.001

PbHCO3+ 7.666e-11 6.840e-11 -10.115 -10.165 -0.050

Cd(CO3)2-2 5.502e-11 3.487e-11 -10.259 -10.458 -0.198

FeCO3 2.232e-16 2.238e-16 -15.651 -15.650 0.001

FeHCO3+ 4.357e-17 3.887e-17 -16.361 -16.410 -0.050

Ca 1.523e-03

Ca+2 1.283e-03 8.262e-04 -2.892 -3.083 -0.191

CaCO3 1.293e-04 1.297e-04 -3.888 -3.887 0.001

CaSO4 6.622e-05 6.641e-05 -4.179 -4.178 0.001

CaHCO3+ 4.424e-05 3.964e-05 -4.354 -4.402 -0.048

CaOH+ 7.220e-08 6.442e-08 -7.141 -7.191 -0.050

CaPO4- 4.332e-08 3.865e-08 -7.363 -7.413 -0.050

CaHPO4 3.188e-08 3.197e-08 -7.496 -7.495 0.001

CaH2PO4+ 5.606e-11 5.001e-11 -10.251 -10.301 -0.050

CaHSO4+ 9.839e-13 8.778e-13 -12.007 -12.057 -0.050

Cd 4.452e-09

Cd+2 3.045e-09 1.930e-09 -8.516 -8.715 -0.198

CdCl+ 6.322e-10 5.641e-10 -9.199 -9.249 -0.050

CdHCO3+ 2.417e-10 2.156e-10 -9.617 -9.666 -0.050

CdSO4 2.204e-10 2.210e-10 -9.657 -9.656 0.001

CdCO3 1.296e-10 1.300e-10 -9.887 -9.886 0.001

CdOH+ 1.174e-10 1.048e-10 -9.930 -9.980 -0.050

Cd(CO3)2-2 5.502e-11 3.487e-11 -10.259 -10.458 -0.198

CdCl2 7.188e-12 7.208e-12 -11.143 -11.142 0.001

Cd(OH)2 1.897e-12 1.902e-12 -11.722 -11.721 0.001

Cd(SO4)2-2 1.439e-12 9.115e-13 -11.842 -12.040 -0.198


nutrition

95

CdCl3- 1.644e-14 1.466e-14 -13.784 -13.834 -0.050

Cd(OH)3- 1.124e-16 1.003e-16 -15.949 -15.999 -0.050

Cd(OH)4-2 6.627e-22 4.199e-22 -21.179 -21.377 -0.198

Cl 3.388e-03

Cl- 3.388e-03 3.016e-03 -2.470 -2.521 -0.050

CdCl+ 6.322e-10 5.641e-10 -9.199 -9.249 -0.050

MnCl+ 2.014e-10 1.797e-10 -9.696 -9.745 -0.050

ZnCl+ 1.907e-10 1.702e-10 -9.720 -9.769 -0.050

CdCl2 7.188e-12 7.208e-12 -11.143 -11.142 0.001

PbCl+ 3.661e-12 3.266e-12 -11.436 -11.486 -0.050

ZnCl2 5.455e-13 5.470e-13 -12.263 -12.262 0.001

MnCl2 2.359e-13 2.366e-13 -12.627 -12.626 0.001

CdCl3- 1.644e-14 1.466e-14 -13.784 -13.834 -0.050

PbCl2 1.433e-14 1.437e-14 -13.844 -13.843 0.001

ZnCl3- 2.131e-15 1.901e-15 -14.671 -14.721 -0.050

MnCl3- 2.203e-16 1.965e-16 -15.657 -15.707 -0.050

PbCl3- 3.965e-17 3.538e-17 -16.402 -16.451 -0.050

ZnCl4-2 4.697e-18 2.976e-18 -17.328 -17.526 -0.198

FeCl+ 5.134e-19 4.580e-19 -18.290 -18.339 -0.050

PbCl4-2 8.340e-20 5.284e-20 -19.079 -19.277 -0.198

FeCl+2 3.512e-22 2.225e-22 -21.454 -21.653 -0.198

FeCl2+ 2.920e-24 2.605e-24 -23.535 -23.584 -0.050

FeCl3 7.834e-28 7.856e-28 -27.106 -27.105 0.001

Cu(1) 2.131e-16

Cu+ 2.131e-16 1.889e-16 -15.671 -15.724 -0.052

Cu(2) 2.520e-07

Cu(OH)2 2.516e-07 2.523e-07 -6.599 -6.598 0.001

CuOH+ 2.884e-10 2.571e-10 -9.540 -9.590 -0.050

Cu+2 8.427e-11 5.472e-11 -10.074 -10.262 -0.187

Cu(OH)3- 8.006e-12 7.143e-12 -11.097 -11.146 -0.050

CuSO4 4.440e-12 4.452e-12 -11.353 -11.351 0.001

Cu(OH)4-2 1.057e-15 6.696e-16 -14.976 -15.174 -0.198

Fe(2) 4.704e-16

FeCO3 2.232e-16 2.238e-16 -15.651 -15.650 0.001

Fe+2 1.694e-16 1.100e-16 -15.771 -15.959 -0.187

FeHCO3+ 4.357e-17 3.887e-17 -16.361 -16.410 -0.050

FeOH+ 2.551e-17 2.276e-17 -16.593 -16.643 -0.050

FeSO4 8.177e-18 8.200e-18 -17.087 -17.086 0.001

FeCl+ 5.134e-19 4.580e-19 -18.290 -18.339 -0.050

FeHPO4 2.838e-20 2.846e-20 -19.547 -19.546 0.001

FeH2PO4+ 1.343e-22 1.198e-22 -21.872 -21.922 -0.050

FeHSO4+ 1.310e-25 1.169e-25 -24.883 -24.932 -0.050

Fe(HS)2 0.000e+00 0.000e+00 -235.142 -235.141 0.001

Fe(HS)3- 0.000e+00 0.000e+00 -347.120 -347.170 -0.050

Fe(3) 1.792e-07

Fe(OH)3 1.127e-07 1.130e-07 -6.948 -6.947 0.001

Fe(OH)4- 6.484e-08 5.785e-08 -7.188 -7.238 -0.050

Fe(OH)2+ 1.725e-09 1.539e-09 -8.763 -8.813 -0.050

FeOH+2 1.319e-14 8.360e-15 -13.880 -14.078 -0.198

FeSO4+ 1.112e-20 9.925e-21 -19.954 -20.003 -0.050

Fe+3 5.175e-21 2.123e-21 -20.286 -20.673 -0.387

FeCl+2 3.512e-22 2.225e-22 -21.454 -21.653 -0.198

Fe(SO4)2- 9.570e-23 8.539e-23 -22.019 -22.069 -0.050

FeHPO4+ 4.809e-23 4.290e-23 -22.318 -22.367 -0.050

FeCl2+ 2.920e-24 2.605e-24 -23.535 -23.584 -0.050

FeH2PO4+2 1.959e-24 1.241e-24 -23.708 -23.906 -0.198

Fe2(OH)2+4 9.717e-27 1.566e-27 -26.012 -26.805 -0.793

FeCl3 7.834e-28 7.856e-28 -27.106 -27.105 0.001

FeHSO4+2 8.942e-29 5.666e-29 -28.049 -28.247 -0.198

Fe3(OH)4+5 5.793e-33 3.345e-34 -32.237 -33.476 -1.238

H(0) 2.435e-37

H2 1.218e-37 1.221e-37 -36.914 -36.913 0.001

K 3.328e-04

K+ 3.318e-04 2.954e-04 -3.479 -3.530 -0.050

KSO4- 9.713e-07 8.666e-07 -6.013 -6.062 -0.050

KOH 4.798e-10 4.811e-10 -9.319 -9.318 0.001

KHPO4- 4.194e-11 3.742e-11 -10.377 -10.427 -0.050

Mg 2.058e-03

Mg+2 1.783e-03 1.157e-03 -2.749 -2.937 -0.188

MgSO4 1.172e-04 1.175e-04 -3.931 -3.930 0.001

MgCO3 1.000e-04 1.003e-04 -4.000 -3.999 0.001

MgHCO3+ 5.480e-05 4.889e-05 -4.261 -4.311 -0.050

MgOH+ 3.300e-06 2.945e-06 -5.481 -5.531 -0.050

MgPO4- 8.182e-08 7.300e-08 -7.087 -7.137 -0.050

MgHPO4 6.036e-08 6.053e-08 -7.219 -7.218 0.001


nutrition

96

MgH2PO4+ 9.996e-11 8.918e-11 -10.000 -10.050 -0.050

Mn(2) 1.275e-07

MnCO3 9.826e-08 9.854e-08 -7.008 -7.006 0.001

Mn+2 2.253e-08 1.463e-08 -7.647 -7.835 -0.187

MnHCO3+ 5.163e-09 4.606e-09 -8.287 -8.337 -0.050

MnSO4 1.091e-09 1.094e-09 -8.962 -8.961 0.001

MnOH+ 2.842e-10 2.535e-10 -9.546 -9.596 -0.050

MnCl+ 2.014e-10 1.797e-10 -9.696 -9.745 -0.050

MnCl2 2.359e-13 2.366e-13 -12.627 -12.626 0.001

MnCl3- 2.203e-16 1.965e-16 -15.657 -15.707 -0.050

Mn(NO3)2 1.801e-30 1.806e-30 -29.745 -29.743 0.001

Mn(3) 3.821e-25

Mn+3 3.821e-25 1.369e-25 -24.418 -24.864 -0.446

N(-3) 0.000e+00

NH4+ 0.000e+00 0.000e+00 -46.481 -46.534 -0.052

NH3 0.000e+00 0.000e+00 -46.971 -46.970 0.001

NH4SO4- 0.000e+00 0.000e+00 -48.787 -48.836 -0.050

N(0) 2.572e-05

N2 1.286e-05 1.290e-05 -4.891 -4.889 0.001

N(3) 1.408e-17

NO2- 1.408e-17 1.251e-17 -16.851 -16.903 -0.052

N(5) 6.302e-12

NO3- 6.302e-12 5.597e-12 -11.201 -11.252 -0.052

PbNO3+ 2.261e-21 2.017e-21 -20.646 -20.695 -0.050

Mn(NO3)2 1.801e-30 1.806e-30 -29.745 -29.743 0.001

Na 1.828e-03

Na+ 1.818e-03 1.624e-03 -2.740 -2.789 -0.049

NaSO4- 3.627e-06 3.236e-06 -5.440 -5.490 -0.050

NaCO3- 3.596e-06 3.208e-06 -5.444 -5.494 -0.050

NaHCO3 3.218e-06 3.227e-06 -5.492 -5.491 0.001

NaOH 5.027e-09 5.042e-09 -8.299 -8.297 0.001

NaHPO4- 2.307e-10 2.058e-10 -9.637 -9.687 -0.050

O(0) 1.502e-17

O2 7.510e-18 7.531e-18 -17.124 -17.123 0.001

P 3.231e-07

HPO4-2 1.029e-07 6.498e-08 -6.988 -7.187 -0.199

MgPO4- 8.182e-08 7.300e-08 -7.087 -7.137 -0.050

MgHPO4 6.036e-08 6.053e-08 -7.219 -7.218 0.001

CaPO4- 4.332e-08 3.865e-08 -7.363 -7.413 -0.050

CaHPO4 3.188e-08 3.197e-08 -7.496 -7.495 0.001

H2PO4- 2.432e-09 2.172e-09 -8.614 -8.663 -0.049

NaHPO4- 2.307e-10 2.058e-10 -9.637 -9.687 -0.050

MgH2PO4+ 9.996e-11 8.918e-11 -10.000 -10.050 -0.050

CaH2PO4+ 5.606e-11 5.001e-11 -10.251 -10.301 -0.050

PO4-3 4.227e-11 1.504e-11 -10.374 -10.823 -0.449

KHPO4- 4.194e-11 3.742e-11 -10.377 -10.427 -0.050

FeHPO4 2.838e-20 2.846e-20 -19.547 -19.546 0.001

FeH2PO4+ 1.343e-22 1.198e-22 -21.872 -21.922 -0.050

FeHPO4+ 4.809e-23 4.290e-23 -22.318 -22.367 -0.050

FeH2PO4+2 1.959e-24 1.241e-24 -23.708 -23.906 -0.198

Pb 4.831e-08

PbCO3 3.582e-08 3.592e-08 -7.446 -7.445 0.001

Pb(CO3)2-2 1.208e-08 7.652e-09 -7.918 -8.116 -0.198

PbOH+ 2.502e-10 2.232e-10 -9.602 -9.651 -0.050

PbHCO3+ 7.666e-11 6.840e-11 -10.115 -10.165 -0.050

Pb(OH)2 4.069e-11 4.080e-11 -10.391 -10.389 0.001

Pb+2 3.846e-11 2.437e-11 -10.415 -10.613 -0.198

PbSO4 5.282e-12 5.297e-12 -11.277 -11.276 0.001

PbCl+ 3.661e-12 3.266e-12 -11.436 -11.486 -0.050

Pb(OH)3- 2.467e-13 2.201e-13 -12.608 -12.657 -0.050

Pb(SO4)2-2 1.696e-14 1.074e-14 -13.771 -13.969 -0.198

PbCl2 1.433e-14 1.437e-14 -13.844 -13.843 0.001

Pb(OH)4-2 3.738e-16 2.369e-16 -15.427 -15.625 -0.198

PbCl3- 3.965e-17 3.538e-17 -16.402 -16.451 -0.050

Pb2OH+3 3.400e-19 1.218e-19 -18.469 -18.914 -0.446

PbCl4-2 8.340e-20 5.284e-20 -19.079 -19.277 -0.198

PbNO3+ 2.261e-21 2.017e-21 -20.646 -20.695 -0.050

S(-2) 0.000e+00

HS- 0.000e+00 0.000e+00 -114.015 -114.066 -0.051

H2S 0.000e+00 0.000e+00 -115.854 -115.853 0.001

S-2 0.000e+00 0.000e+00 -117.987 -118.180 -0.193

Fe(HS)2 0.000e+00 0.000e+00 -235.142 -235.141 0.001

Fe(HS)3- 0.000e+00 0.000e+00 -347.120 -347.170 -0.050

S(6) 7.918e-04

SO4-2 6.039e-04 3.865e-04 -3.219 -3.413 -0.194


nutrition

97

MgSO4 1.172e-04 1.175e-04 -3.931 -3.930 0.001

CaSO4 6.622e-05 6.641e-05 -4.179 -4.178 0.001

NaSO4- 3.627e-06 3.236e-06 -5.440 -5.490 -0.050

KSO4- 9.713e-07 8.666e-07 -6.013 -6.062 -0.050

ZnSO4 1.612e-09 1.616e-09 -8.793 -8.791 0.001

MnSO4 1.091e-09 1.094e-09 -8.962 -8.961 0.001

CdSO4 2.204e-10 2.210e-10 -9.657 -9.656 0.001

HSO4- 9.905e-11 8.837e-11 -10.004 -10.054 -0.050

Zn(SO4)2-2 7.744e-12 4.907e-12 -11.111 -11.309 -0.198

PbSO4 5.282e-12 5.297e-12 -11.277 -11.276 0.001

CuSO4 4.440e-12 4.452e-12 -11.353 -11.351 0.001

Cd(SO4)2-2 1.439e-12 9.115e-13 -11.842 -12.040 -0.198

CaHSO4+ 9.839e-13 8.778e-13 -12.007 -12.057 -0.050

Pb(SO4)2-2 1.696e-14 1.074e-14 -13.771 -13.969 -0.198

FeSO4 8.177e-18 8.200e-18 -17.087 -17.086 0.001

AlSO4+ 1.578e-19 1.408e-19 -18.802 -18.851 -0.050

FeSO4+ 1.112e-20 9.925e-21 -19.954 -20.003 -0.050

Al(SO4)2- 1.969e-21 1.757e-21 -20.706 -20.755 -0.050

Fe(SO4)2- 9.570e-23 8.539e-23 -22.019 -22.069 -0.050

FeHSO4+ 1.310e-25 1.169e-25 -24.883 -24.932 -0.050

FeHSO4+2 8.942e-29 5.666e-29 -28.049 -28.247 -0.198

AlHSO4+2 4.376e-29 2.773e-29 -28.359 -28.557 -0.198

NH4SO4- 0.000e+00 0.000e+00 -48.787 -48.836 -0.050

Zn 1.225e-06

Zn(CO3)2-2 8.349e-07 5.290e-07 -6.078 -6.277 -0.198

ZnCO3 2.909e-07 2.917e-07 -6.536 -6.535 0.001

Zn(OH)2 4.777e-08 4.791e-08 -7.321 -7.320 0.001

Zn+2 2.691e-08 1.724e-08 -7.570 -7.763 -0.193

ZnOH+ 1.393e-08 1.243e-08 -7.856 -7.905 -0.050

ZnHCO3+ 8.595e-09 7.669e-09 -8.066 -8.115 -0.050

ZnSO4 1.612e-09 1.616e-09 -8.793 -8.791 0.001

ZnCl+ 1.907e-10 1.702e-10 -9.720 -9.769 -0.050

Zn(OH)3- 7.977e-11 7.117e-11 -10.098 -10.148 -0.050

Zn(SO4)2-2 7.744e-12 4.907e-12 -11.111 -11.309 -0.198

ZnCl2 5.455e-13 5.470e-13 -12.263 -12.262 0.001

Zn(OH)4-2 8.363e-15 5.299e-15 -14.078 -14.276 -0.198

ZnCl3- 2.131e-15 1.901e-15 -14.671 -14.721 -0.050

ZnCl4-2 4.697e-18 2.976e-18 -17.328 -17.526 -0.198

------------------------------Saturation indices-------------------------------

Phase SI log IAP log KT

Al(OH)3(a) -3.46 7.05 10.51 Al(OH)3

Alunite -13.27 -15.21 -1.95 KAl3(SO4)2(OH)6

Anglesite -6.26 -14.03 -7.77 PbSO4

Anhydrite -2.11 -6.50 -4.38 CaSO4

Aragonite 1.21 -7.15 -8.37 CaCO3

Calcite 1.35 -7.15 -8.51 CaCO3

Cd(OH)2 -5.02 8.63 13.65 Cd(OH)2

CdSO4 -11.87 -12.13 -0.26 CdSO4

Cerrusite -1.61 -14.68 -13.08 PbCO3

CH4(g) -113.09 -156.39 -43.30 CH4

CO2(g) -3.27 -21.42 -18.14 CO2

Dolomite 3.03 -14.16 -17.19 CaMg(CO3)2

Fe(OH)3(a) 0.45 18.26 17.81 Fe(OH)3

FeS(ppt) -117.44 -154.35 -36.91 FeS

Gibbsite -0.81 7.05 7.86 Al(OH)3

Goethite 6.50 18.26 11.76 FeOOH

Gypsum -1.91 -6.50 -4.58 CaSO4:2H2O

H2(g) -33.74 -33.74 -0.00 H2

H2O(g) -1.40 -0.00 1.40 H2O

H2S(g) -114.81 -155.73 -40.93 H2S

Halite -6.90 -5.31 1.59 NaCl

Hausmannite 2.34 62.27 59.93 Mn3O4

Hematite 15.03 36.51 21.48 Fe2O3

Hydroxyapatite 1.53 -39.21 -40.74 Ca5(PO4)3OH

Jarosite-K -10.79 18.40 29.19 KFe3(SO4)2(OH)6

Mackinawite -116.70 -154.35 -37.64 FeS

Manganite 1.04 26.38 25.34 MnOOH

Melanterite -17.22 -19.37 -2.16 FeSO4:7H2O

N2(g) -1.61 -208.57 -206.95 N2

NH3(g) -48.65 -154.90 -106.25 NH3

O2(g) -14.14 67.49 81.63 O2

Otavite -0.69 -12.79 -12.10 CdCO3


nutrition

98

Pb(OH)2 -1.27 6.73 8.00 Pb(OH)2

Pyrite -191.99 -276.34 -84.34 FeS2

Pyrochroite -5.69 9.51 15.20 Mn(OH)2

Pyrolusite 2.58 43.25 40.67 MnO2

Rhodochrosite -0.76 -11.91 -11.15 MnCO3

Siderite -9.11 -20.03 -10.92 FeCO3

Smithsonite -1.79 -11.83 -10.05 ZnCO3

Sphalerite -101.63 -146.15 -44.52 ZnS

Sulfur -86.89 -121.99 -35.10 S

Vivianite -33.52 -69.52 -36.00 Fe3(PO4)2:8H2O

Zn(OH)2(e) -1.92 9.58 11.50 Zn(OH)2

------------------

End of simulation.

------------------

SENSITIVITY ANALYSIS

TITLE Dewatering surplus (December 2013): adjusted pH

SOLUTION 1

pH 7.0

temp 29.5

pe

units mg/L

Alkalinity 240

Al 0.01

B 0.3

Cd 0.0005

Ca 61

Cl 120

Cu 0.016

Fe 0.01

Pb 0.01

Mg 50

Mn 0.007

N 0.36

P 0.01

K 13

Na 42

S 76 as SO4-2

Zn 0.08

END

-----

TITLE

-----

Dewatering surplus (December 2013): adjusted pH

-------------------------------------------


-------------------------------------------

Initial solution 1.



Al 3.708e-07 3.708e-07


B 2.777e-05 2.777e-05

Ca 1.523e-03 1.523e-03

Cd 4.451e-09 4.451e-09

Cl 3.387e-03 3.387e-03

Cu 2.519e-07 2.519e-07

Fe 1.792e-07 1.792e-07

K 3.327e-04 3.327e-04

Mg 2.058e-03 2.058e-03


nutrition

99

Mn 1.275e-07 1.275e-07

N 2.572e-05 2.572e-05

Na 1.828e-03 1.828e-03

P 3.230e-07 3.230e-07

Pb 4.829e-08 4.829e-08

S 7.916e-04 7.916e-04

Zn 1.225e-06 1.225e-06


pH = 7.000

pe = 7.000




Total carbon (mol/kg) = 5.673e-03





Iterations = 11

Total H = 1.110173e+02

Total O = 5.552560e+01


Log Log Log


OH- 1.571e-07 1.396e-07 -6.804 -6.855 -0.052

H+ 1.106e-07 1.000e-07 -6.956 -7.000 -0.044

H2O 5.551e+01 9.997e-01 -0.000 -0.000 0.000

Al 3.708e-07

Al(OH)4- 3.470e-07 3.090e-07 -6.460 -6.510 -0.050

Al(OH)3 1.529e-08 1.534e-08 -7.816 -7.814 0.001

Al(OH)2+ 8.483e-09 7.555e-09 -8.071 -8.122 -0.050

AlOH+2 1.046e-10 6.579e-11 -9.980 -10.182 -0.201

Al+3 1.224e-12 4.958e-13 -11.912 -12.305 -0.392

AlSO4+ 7.076e-13 6.302e-13 -12.150 -12.201 -0.050

Al(SO4)2- 8.669e-15 7.720e-15 -14.062 -14.112 -0.050

AlHSO4+2 9.269e-21 5.830e-21 -20.033 -20.234 -0.201

B 2.777e-05

H3BO3 2.758e-05 2.766e-05 -4.559 -4.558 0.001

H2BO3- 1.938e-07 1.726e-07 -6.713 -6.763 -0.050

C(4) 5.673e-03

HCO3- 4.649e-03 4.158e-03 -2.333 -2.381 -0.048

CO2 8.871e-04 8.897e-04 -3.052 -3.051 0.001

MgHCO3+ 6.724e-05 5.988e-05 -4.172 -4.223 -0.050

CaHCO3+ 5.622e-05 5.029e-05 -4.250 -4.299 -0.048

NaHCO3 3.785e-06 3.796e-06 -5.422 -5.421 0.001

CaCO3 3.492e-06 3.502e-06 -5.457 -5.456 0.001

CO3-2 3.320e-06 2.124e-06 -5.479 -5.673 -0.194

MgCO3 2.607e-06 2.615e-06 -5.584 -5.583 0.001

ZnHCO3+ 2.632e-07 2.344e-07 -6.580 -6.630 -0.050

ZnCO3 1.892e-07 1.898e-07 -6.723 -6.722 0.001

NaCO3- 9.017e-08 8.030e-08 -7.045 -7.095 -0.050

PbCO3 4.134e-08 4.146e-08 -7.384 -7.382 0.001

MnHCO3+ 2.388e-08 2.126e-08 -7.622 -7.672 -0.050

Zn(CO3)2-2 1.370e-08 8.618e-09 -7.863 -8.065 -0.201

MnCO3 9.652e-09 9.680e-09 -8.015 -8.014 0.001

PbHCO3+ 4.166e-09 3.710e-09 -8.380 -8.431 -0.050

Pb(CO3)2-2 3.517e-10 2.212e-10 -9.454 -9.655 -0.201

CdHCO3+ 3.008e-10 2.679e-10 -9.522 -9.572 -0.050

FeHCO3+ 7.737e-11 6.890e-11 -10.111 -10.162 -0.050

FeCO3 8.418e-12 8.443e-12 -11.075 -11.073 0.001

CdCO3 3.427e-12 3.437e-12 -11.465 -11.464 0.001

Cd(CO3)2-2 3.671e-14 2.309e-14 -13.435 -13.637 -0.201

Ca 1.523e-03

Ca+2 1.393e-03 8.906e-04 -2.856 -3.050 -0.194

CaSO4 7.009e-05 7.029e-05 -4.154 -4.153 0.001

CaHCO3+ 5.622e-05 5.029e-05 -4.250 -4.299 -0.048

CaCO3 3.492e-06 3.502e-06 -5.457 -5.456 0.001

CaHPO4 3.404e-08 3.414e-08 -7.468 -7.467 0.001

CaH2PO4+ 2.818e-09 2.509e-09 -8.550 -8.600 -0.050

CaOH+ 1.659e-09 1.478e-09 -8.780 -8.830 -0.050


nutrition

100

CaPO4- 9.860e-10 8.781e-10 -9.006 -9.056 -0.050

CaHSO4+ 4.903e-11 4.366e-11 -10.310 -10.360 -0.050

Cd 4.451e-09

Cd+2 3.239e-09 2.037e-09 -8.490 -8.691 -0.201

CdCl+ 6.673e-10 5.943e-10 -9.176 -9.226 -0.050

CdHCO3+ 3.008e-10 2.679e-10 -9.522 -9.572 -0.050

CdSO4 2.285e-10 2.291e-10 -9.641 -9.640 0.001

CdCl2 7.555e-12 7.577e-12 -11.122 -11.120 0.001

CdCO3 3.427e-12 3.437e-12 -11.465 -11.464 0.001

CdOH+ 2.643e-12 2.354e-12 -11.578 -11.628 -0.050

Cd(SO4)2-2 1.475e-12 9.280e-13 -11.831 -12.032 -0.201

Cd(CO3)2-2 3.671e-14 2.309e-14 -13.435 -13.637 -0.201

CdCl3- 1.727e-14 1.538e-14 -13.763 -13.813 -0.050

Cd(OH)2 9.069e-16 9.096e-16 -15.042 -15.041 0.001

Cd(OH)3- 1.146e-21 1.020e-21 -20.941 -20.991 -0.050

Cd(OH)4-2 1.445e-28 9.092e-29 -27.840 -28.041 -0.201

Cl 3.387e-03

Cl- 3.387e-03 3.009e-03 -2.470 -2.522 -0.051

ZnCl+ 4.952e-09 4.410e-09 -8.305 -8.356 -0.050

MnCl+ 7.898e-10 7.034e-10 -9.102 -9.153 -0.050

CdCl+ 6.673e-10 5.943e-10 -9.176 -9.226 -0.050

PbCl+ 1.687e-10 1.502e-10 -9.773 -9.823 -0.050

ZnCl2 1.410e-11 1.415e-11 -10.851 -10.849 0.001

CdCl2 7.555e-12 7.577e-12 -11.122 -11.120 0.001

MnCl2 9.212e-13 9.240e-13 -12.036 -12.034 0.001

FeCl+ 7.730e-13 6.884e-13 -12.112 -12.162 -0.050

PbCl2 6.574e-13 6.594e-13 -12.182 -12.181 0.001

ZnCl3- 5.508e-14 4.905e-14 -13.259 -13.309 -0.050

CdCl3- 1.727e-14 1.538e-14 -13.763 -13.813 -0.050

PbCl3- 1.819e-15 1.620e-15 -14.740 -14.791 -0.050

MnCl3- 8.599e-16 7.658e-16 -15.066 -15.116 -0.050

ZnCl4-2 1.218e-16 7.662e-17 -15.914 -16.116 -0.201

FeCl+2 3.355e-17 2.110e-17 -16.474 -16.676 -0.201

PbCl4-2 3.838e-18 2.414e-18 -17.416 -17.617 -0.201

FeCl2+ 2.768e-19 2.465e-19 -18.558 -18.608 -0.050

FeCl3 7.395e-23 7.417e-23 -22.131 -22.130 0.001

Cu(1) 4.074e-12

Cu+ 4.074e-12 3.603e-12 -11.390 -11.443 -0.053

Cu(2) 2.519e-07

Cu(OH)2 1.372e-07 1.376e-07 -6.863 -6.861 0.001

Cu+2 1.021e-07 6.588e-08 -6.991 -7.181 -0.190

CuOH+ 7.401e-09 6.586e-09 -8.131 -8.181 -0.051

CuSO4 5.248e-09 5.263e-09 -8.280 -8.279 0.001

Cu(OH)3- 9.306e-14 8.287e-14 -13.031 -13.082 -0.050

Cu(OH)4-2 2.628e-19 1.653e-19 -18.580 -18.782 -0.201

Fe(2) 3.564e-10

Fe+2 2.569e-10 1.657e-10 -9.590 -9.781 -0.190

FeHCO3+ 7.737e-11 6.890e-11 -10.111 -10.162 -0.050

FeSO4 1.209e-11 1.213e-11 -10.917 -10.916 0.001

FeCO3 8.418e-12 8.443e-12 -11.075 -11.073 0.001

FeOH+ 8.193e-13 7.296e-13 -12.087 -12.137 -0.050

FeCl+ 7.730e-13 6.884e-13 -12.112 -12.162 -0.050

FeHPO4 4.233e-14 4.246e-14 -13.373 -13.372 0.001

FeH2PO4+ 9.430e-15 8.398e-15 -14.025 -14.076 -0.050

FeHSO4+ 9.123e-18 8.124e-18 -17.040 -17.090 -0.050

Fe(HS)2 0.000e+00 0.000e+00 -179.683 -179.682 0.001

Fe(HS)3- 0.000e+00 0.000e+00 -267.021 -267.071 -0.050

Fe(3) 1.788e-07

Fe(OH)3 1.032e-07 1.035e-07 -6.986 -6.985 0.001

Fe(OH)2+ 7.436e-08 6.622e-08 -7.129 -7.179 -0.050

Fe(OH)4- 1.266e-09 1.127e-09 -8.898 -8.948 -0.050

FeOH+2 2.688e-11 1.691e-11 -10.571 -10.772 -0.201

FeSO4+ 1.040e-15 9.262e-16 -14.983 -15.033 -0.050

Fe+3 4.981e-16 2.018e-16 -15.303 -15.695 -0.392

FeCl+2 3.355e-17 2.110e-17 -16.474 -16.676 -0.201

Fe(SO4)2- 8.786e-18 7.825e-18 -17.056 -17.107 -0.050

FeH2PO4+2 8.730e-18 5.491e-18 -17.059 -17.260 -0.201

FeHPO4+ 4.535e-18 4.039e-18 -17.343 -17.394 -0.050

FeCl2+ 2.768e-19 2.465e-19 -18.558 -18.608 -0.050

Fe2(OH)2+4 4.093e-20 6.406e-21 -19.388 -20.193 -0.805

FeHSO4+2 3.950e-22 2.485e-22 -21.403 -21.605 -0.201

FeCl3 7.395e-23 7.417e-23 -22.131 -22.130 0.001

Fe3(OH)4+5 1.068e-24 5.888e-26 -23.971 -25.230 -1.259

H(0) 1.351e-31

H2 6.754e-32 6.774e-32 -31.170 -31.169 0.001


nutrition

101

K 3.327e-04

K+ 3.317e-04 2.947e-04 -3.479 -3.531 -0.051

KSO4- 9.535e-07 8.492e-07 -6.021 -6.071 -0.050

KHPO4- 4.153e-11 3.698e-11 -10.382 -10.432 -0.050

KOH 1.019e-11 1.022e-11 -10.992 -10.991 0.001

Mg 2.058e-03

Mg+2 1.868e-03 1.204e-03 -2.729 -2.919 -0.191

MgSO4 1.197e-04 1.201e-04 -3.922 -3.921 0.001

MgHCO3+ 6.724e-05 5.988e-05 -4.172 -4.223 -0.050

MgCO3 2.607e-06 2.615e-06 -5.584 -5.583 0.001

MgOH+ 7.323e-08 6.522e-08 -7.135 -7.186 -0.050

MgHPO4 6.222e-08 6.240e-08 -7.206 -7.205 0.001

MgH2PO4+ 4.851e-09 4.320e-09 -8.314 -8.365 -0.050

MgPO4- 1.798e-09 1.601e-09 -8.745 -8.796 -0.050

Mn(2) 1.275e-07

Mn+2 8.895e-08 5.738e-08 -7.051 -7.241 -0.190

MnHCO3+ 2.388e-08 2.126e-08 -7.622 -7.672 -0.050

MnCO3 9.652e-09 9.680e-09 -8.015 -8.014 0.001

MnSO4 4.202e-09 4.214e-09 -8.377 -8.375 0.001

MnCl+ 7.898e-10 7.034e-10 -9.102 -9.153 -0.050

MnOH+ 2.376e-11 2.116e-11 -10.624 -10.674 -0.050

MnCl2 9.212e-13 9.240e-13 -12.036 -12.034 0.001

MnCl3- 8.599e-16 7.658e-16 -15.066 -15.116 -0.050

Mn(NO3)2 0.000e+00 0.000e+00 -61.215 -61.214 0.001

Mn(3) 9.616e-26

Mn+3 9.616e-26 3.388e-26 -25.017 -25.470 -0.453

N(-3) 6.499e-37

NH4+ 6.424e-37 5.682e-37 -36.192 -36.246 -0.053

NH3 4.415e-39 4.428e-39 -38.355 -38.354 0.001

NH4SO4- 3.119e-39 2.778e-39 -38.506 -38.556 -0.050

N(0) 2.572e-05

N2 1.286e-05 1.290e-05 -4.891 -4.890 0.001

N(3) 7.267e-28

NO2- 7.267e-28 6.441e-28 -27.139 -27.191 -0.052

N(5) 5.864e-28

NO3- 5.864e-28 5.197e-28 -27.232 -27.284 -0.052

PbNO3+ 9.696e-36 8.634e-36 -35.013 -35.064 -0.050

Mn(NO3)2 0.000e+00 0.000e+00 -61.215 -61.214 0.001

Na 1.828e-03

Na+ 1.821e-03 1.624e-03 -2.740 -2.790 -0.050

NaHCO3 3.785e-06 3.796e-06 -5.422 -5.421 0.001

NaSO4- 3.567e-06 3.176e-06 -5.448 -5.498 -0.050

NaCO3- 9.017e-08 8.030e-08 -7.045 -7.095 -0.050

NaHPO4- 2.288e-10 2.037e-10 -9.641 -9.691 -0.050

NaOH 1.069e-10 1.072e-10 -9.971 -9.970 0.001

O(0) 4.881e-29

O2 2.441e-29 2.448e-29 -28.613 -28.611 0.001

P 3.230e-07

H2PO4- 1.134e-07 1.011e-07 -6.945 -6.995 -0.050

HPO4-2 1.027e-07 6.436e-08 -6.989 -7.191 -0.203

MgHPO4 6.222e-08 6.240e-08 -7.206 -7.205 0.001

CaHPO4 3.404e-08 3.414e-08 -7.468 -7.467 0.001

MgH2PO4+ 4.851e-09 4.320e-09 -8.314 -8.365 -0.050

CaH2PO4+ 2.818e-09 2.509e-09 -8.550 -8.600 -0.050

MgPO4- 1.798e-09 1.601e-09 -8.745 -8.796 -0.050

CaPO4- 9.860e-10 8.781e-10 -9.006 -9.056 -0.050

NaHPO4- 2.288e-10 2.037e-10 -9.641 -9.691 -0.050

KHPO4- 4.153e-11 3.698e-11 -10.382 -10.432 -0.050

PO4-3 9.063e-13 3.170e-13 -12.043 -12.499 -0.456

FeHPO4 4.233e-14 4.246e-14 -13.373 -13.372 0.001

FeH2PO4+ 9.430e-15 8.398e-15 -14.025 -14.076 -0.050

FeH2PO4+2 8.730e-18 5.491e-18 -17.059 -17.260 -0.201

FeHPO4+ 4.535e-18 4.039e-18 -17.343 -17.394 -0.050

Pb 4.829e-08

PbCO3 4.134e-08 4.146e-08 -7.384 -7.382 0.001

PbHCO3+ 4.166e-09 3.710e-09 -8.380 -8.431 -0.050

Pb+2 1.786e-09 1.123e-09 -8.748 -8.950 -0.201

Pb(CO3)2-2 3.517e-10 2.212e-10 -9.454 -9.655 -0.201

PbOH+ 2.459e-10 2.190e-10 -9.609 -9.660 -0.050

PbSO4 2.390e-10 2.397e-10 -9.622 -9.620 0.001

PbCl+ 1.687e-10 1.502e-10 -9.773 -9.823 -0.050

Pb(OH)2 8.491e-13 8.516e-13 -12.071 -12.070 0.001

Pb(SO4)2-2 7.591e-13 4.775e-13 -12.120 -12.321 -0.201

PbCl2 6.574e-13 6.594e-13 -12.182 -12.181 0.001

PbCl3- 1.819e-15 1.620e-15 -14.740 -14.791 -0.050


nutrition

102

Pb(OH)3- 1.098e-16 9.775e-17 -15.960 -16.010 -0.050

Pb2OH+3 1.563e-17 5.506e-18 -16.806 -17.259 -0.453

PbCl4-2 3.838e-18 2.414e-18 -17.416 -17.617 -0.201

Pb(OH)4-2 3.559e-21 2.239e-21 -20.449 -20.650 -0.201

PbNO3+ 9.696e-36 8.634e-36 -35.013 -35.064 -0.050

S(-2) 0.000e+00

HS- 0.000e+00 0.000e+00 -89.374 -89.426 -0.052

H2S 0.000e+00 0.000e+00 -89.542 -89.540 0.001

S-2 0.000e+00 0.000e+00 -95.015 -95.212 -0.196

Fe(HS)2 0.000e+00 0.000e+00 -179.683 -179.682 0.001

Fe(HS)3- 0.000e+00 0.000e+00 -267.021 -267.071 -0.050

S(6) 7.916e-04

SO4-2 5.972e-04 3.795e-04 -3.224 -3.421 -0.197

MgSO4 1.197e-04 1.201e-04 -3.922 -3.921 0.001

CaSO4 7.009e-05 7.029e-05 -4.154 -4.153 0.001

NaSO4- 3.567e-06 3.176e-06 -5.448 -5.498 -0.050

KSO4- 9.535e-07 8.492e-07 -6.021 -6.071 -0.050

ZnSO4 4.110e-08 4.122e-08 -7.386 -7.385 0.001

CuSO4 5.248e-09 5.263e-09 -8.280 -8.279 0.001

HSO4- 4.579e-09 4.078e-09 -8.339 -8.390 -0.050

MnSO4 4.202e-09 4.214e-09 -8.377 -8.375 0.001

PbSO4 2.390e-10 2.397e-10 -9.622 -9.620 0.001

CdSO4 2.285e-10 2.291e-10 -9.641 -9.640 0.001

Zn(SO4)2-2 1.954e-10 1.229e-10 -9.709 -9.910 -0.201

CaHSO4+ 4.903e-11 4.366e-11 -10.310 -10.360 -0.050

FeSO4 1.209e-11 1.213e-11 -10.917 -10.916 0.001

Cd(SO4)2-2 1.475e-12 9.280e-13 -11.831 -12.032 -0.201

Pb(SO4)2-2 7.591e-13 4.775e-13 -12.120 -12.321 -0.201

AlSO4+ 7.076e-13 6.302e-13 -12.150 -12.201 -0.050

Al(SO4)2- 8.669e-15 7.720e-15 -14.062 -14.112 -0.050

FeSO4+ 1.040e-15 9.262e-16 -14.983 -15.033 -0.050

FeHSO4+ 9.123e-18 8.124e-18 -17.040 -17.090 -0.050

Fe(SO4)2- 8.786e-18 7.825e-18 -17.056 -17.107 -0.050

AlHSO4+2 9.269e-21 5.830e-21 -20.033 -20.234 -0.201

FeHSO4+2 3.950e-22 2.485e-22 -21.403 -21.605 -0.201

NH4SO4- 3.119e-39 2.778e-39 -38.506 -38.556 -0.050

Zn 1.225e-06

Zn+2 7.039e-07 4.478e-07 -6.153 -6.349 -0.196

ZnHCO3+ 2.632e-07 2.344e-07 -6.580 -6.630 -0.050

ZnCO3 1.892e-07 1.898e-07 -6.723 -6.722 0.001

ZnSO4 4.110e-08 4.122e-08 -7.386 -7.385 0.001

Zn(CO3)2-2 1.370e-08 8.618e-09 -7.863 -8.065 -0.201

ZnOH+ 7.716e-09 6.871e-09 -8.113 -8.163 -0.050

ZnCl+ 4.952e-09 4.410e-09 -8.305 -8.356 -0.050

Zn(OH)2 5.618e-10 5.635e-10 -9.250 -9.249 0.001

Zn(SO4)2-2 1.954e-10 1.229e-10 -9.709 -9.910 -0.201

ZnCl2 1.410e-11 1.415e-11 -10.851 -10.849 0.001

ZnCl3- 5.508e-14 4.905e-14 -13.259 -13.309 -0.050

Zn(OH)3- 2.000e-14 1.781e-14 -13.699 -13.749 -0.050

ZnCl4-2 1.218e-16 7.662e-17 -15.914 -16.116 -0.201

Zn(OH)4-2 4.488e-20 2.823e-20 -19.348 -19.549 -0.201



Al(OH)3(a) -1.82 8.69 10.51 Al(OH)3

Alunite -3.34 -5.29 -1.95 KAl3(SO4)2(OH)6

Anglesite -4.60 -12.37 -7.77 PbSO4

Anhydrite -2.09 -6.47 -4.38 CaSO4

Aragonite -0.36 -8.72 -8.37 CaCO3

Calcite -0.22 -8.72 -8.51 CaCO3

Cd(OH)2 -8.34 5.31 13.65 Cd(OH)2

CdSO4 -11.85 -12.11 -0.26 CdSO4

Cerrusite -1.55 -14.62 -13.08 PbCO3

CO2(g) -1.53 -19.67 -18.14 CO2

Dolomite -0.12 -17.32 -17.19 CaMg(CO3)2

Fe(OH)3(a) 0.41 18.22 17.81 Fe(OH)3

FeS(ppt) -88.29 -125.20 -36.91 FeS

Gibbsite 0.83 8.69 7.86 Al(OH)3


Gypsum -1.89 -6.47 -4.58 CaSO4:2H2O

H2(g) -28.00 -28.00 -0.00 H2

H2O(g) -1.40 -0.00 1.40 H2O

H2S(g) -88.49 -129.42 -40.93 H2S


nutrition

103

Halite -6.90 -5.31 1.59 NaCl

Hausmannite -11.66 48.28 59.93 Mn3O4

Hematite 14.95 36.44 21.48 Fe2O3

Hydroxyapatite -5.01 -45.75 -40.74 Ca5(PO4)3OH


Mackinawite -87.56 -125.20 -37.64 FeS

Manganite -4.58 20.76 25.34 MnOOH


N2(g) -1.61 -4.89 -3.27 N2

NH3(g) -40.03 -44.44 -4.41 NH3

O2(g) -25.63 56.00 81.63 O2

Otavite -2.26 -14.36 -12.10 CdCO3

Pb(OH)2 -2.95 5.05 8.00 Pb(OH)2

Pyrite -142.28 -226.62 -84.34 FeS2


Pyrolusite -5.91 34.76 40.67 MnO2


Siderite -4.54 -15.45 -10.92 FeCO3


Sphalerite -77.25 -121.77 -44.52 ZnS

Sulfur -66.32 -101.42 -35.10 S


Zn(OH)2(e) -3.85 7.65 11.50 Zn(OH)2

------------------

End of simulation.

------------------

FERTIGATION MIXTURE

TITLE Fertigation mixture (December 2013)

SOLUTION 1

pH 8.0

temp 31.9

pe

units mg/L

Alkalinity 220

Al 0.01

B 0.3

Cd 0.0005

Ca 61

Cl 120

Cu 0.005

Fe 0.01

Pb 0.01

Mg 50

Mn 0.21

N 60

P 7.2

K 31

Na 43

S 92 as SO4-2

Zn 0.26

END

-----

TITLE

-----

Fertigation mixture (December 2013)

-------------------------------------------


-------------------------------------------

Initial solution 1.



nutrition

104


Al 3.709e-07 3.709e-07


B 2.777e-05 2.777e-05

Ca 1.523e-03 1.523e-03

Cd 4.451e-09 4.451e-09

Cl 3.387e-03 3.387e-03

Cu 7.874e-08 7.874e-08

Fe 1.792e-07 1.792e-07

K 7.933e-04 7.933e-04

Mg 2.058e-03 2.058e-03

Mn 3.825e-06 3.825e-06

N 4.287e-03 4.287e-03

Na 1.872e-03 1.872e-03

P 2.326e-04 2.326e-04

Pb 4.830e-08 4.830e-08

S 9.584e-04 9.584e-04

Zn 3.980e-06 3.980e-06


pH = 8.000

pe = 8.000









Iterations = 10

Total H = 1.110167e+02

Total O = 5.552338e+01


Log Log Log


OH- 1.866e-06 1.656e-06 -5.729 -5.781 -0.052

H+ 1.106e-08 1.000e-08 -7.956 -8.000 -0.044

H2O 5.551e+01 9.997e-01 -0.000 -0.000 0.000

Al 3.709e-07

Al(OH)4- 3.692e-07 3.286e-07 -6.433 -6.483 -0.051

Al(OH)3 1.562e-09 1.567e-09 -8.806 -8.805 0.001

Al(OH)2+ 7.368e-11 6.558e-11 -10.133 -10.183 -0.051

AlOH+2 7.485e-14 4.697e-14 -13.126 -13.328 -0.202

Al+3 7.534e-17 3.039e-17 -16.123 -16.517 -0.394

AlSO4+ 5.412e-17 4.817e-17 -16.267 -16.317 -0.051

Al(SO4)2- 8.109e-19 7.218e-19 -18.091 -18.142 -0.051

AlHSO4+2 7.280e-26 4.568e-26 -25.138 -25.340 -0.202

B 2.777e-05

H3BO3 2.587e-05 2.595e-05 -4.587 -4.586 0.001

H2BO3- 1.898e-06 1.689e-06 -5.722 -5.772 -0.051

C(4) 4.128e-03

HCO3- 3.866e-03 3.455e-03 -2.413 -2.461 -0.049

CO2 7.211e-05 7.232e-05 -4.142 -4.141 0.001

MgHCO3+ 5.326e-05 4.740e-05 -4.274 -4.324 -0.051

CaHCO3+ 4.555e-05 4.072e-05 -4.341 -4.390 -0.049

CaCO3 3.031e-05 3.040e-05 -4.518 -4.517 0.001

CO3-2 2.882e-05 1.840e-05 -4.540 -4.735 -0.195

MgCO3 2.202e-05 2.209e-05 -4.657 -4.656 0.001

NaHCO3 3.217e-06 3.226e-06 -5.493 -5.491 0.001

ZnCO3 1.717e-06 1.723e-06 -5.765 -5.764 0.001

MnCO3 1.607e-06 1.612e-06 -5.794 -5.793 0.001

Zn(CO3)2-2 1.080e-06 6.775e-07 -5.967 -6.169 -0.202

NaCO3- 8.980e-07 7.993e-07 -6.047 -6.097 -0.051

MnHCO3+ 3.817e-07 3.397e-07 -6.418 -6.469 -0.051

ZnHCO3+ 2.294e-07 2.041e-07 -6.639 -6.690 -0.051

PbCO3 4.403e-08 4.416e-08 -7.356 -7.355 0.001

Pb(CO3)2-2 3.252e-09 2.041e-09 -8.488 -8.690 -0.202

PbHCO3+ 4.260e-10 3.791e-10 -9.371 -9.421 -0.051

CdHCO3+ 2.461e-10 2.191e-10 -9.609 -9.659 -0.051


nutrition

105

CdCO3 2.921e-11 2.930e-11 -10.534 -10.533 0.001

Cd(CO3)2-2 2.716e-12 1.705e-12 -11.566 -11.768 -0.202

FeCO3 6.724e-15 6.744e-15 -14.172 -14.171 0.001

FeHCO3+ 5.932e-15 5.280e-15 -14.227 -14.277 -0.051

Ca 1.523e-03

Ca+2 1.322e-03 8.434e-04 -2.879 -3.074 -0.195

CaSO4 8.206e-05 8.231e-05 -4.086 -4.085 0.001

CaHCO3+ 4.555e-05 4.072e-05 -4.341 -4.390 -0.049

CaHPO4 3.282e-05 3.292e-05 -4.484 -4.483 0.001

CaCO3 3.031e-05 3.040e-05 -4.518 -4.517 0.001

CaPO4- 9.937e-06 8.844e-06 -5.003 -5.053 -0.051

CaH2PO4+ 2.687e-07 2.392e-07 -6.571 -6.621 -0.051

CaOH+ 1.572e-08 1.399e-08 -7.803 -7.854 -0.051

CaHSO4+ 5.938e-12 5.285e-12 -11.226 -11.277 -0.051

Cd 4.451e-09

Cd+2 3.195e-09 2.005e-09 -8.496 -8.698 -0.202

CdCl+ 6.618e-10 5.890e-10 -9.179 -9.230 -0.051

CdSO4 2.759e-10 2.767e-10 -9.559 -9.558 0.001

CdHCO3+ 2.461e-10 2.191e-10 -9.609 -9.659 -0.051

CdOH+ 3.089e-11 2.749e-11 -10.510 -10.561 -0.051

CdCO3 2.921e-11 2.930e-11 -10.534 -10.533 0.001

CdCl2 7.548e-12 7.570e-12 -11.122 -11.121 0.001

Cd(CO3)2-2 2.716e-12 1.705e-12 -11.566 -11.768 -0.202

Cd(SO4)2-2 2.131e-12 1.337e-12 -11.671 -11.874 -0.202

Cd(OH)2 8.924e-14 8.950e-14 -13.049 -13.048 0.001

CdCl3- 1.787e-14 1.590e-14 -13.748 -13.799 -0.051

Cd(OH)3- 1.128e-18 1.004e-18 -17.948 -17.998 -0.051

Cd(OH)4-2 1.426e-24 8.945e-25 -23.846 -24.048 -0.202

Cl 3.387e-03

Cl- 3.387e-03 3.008e-03 -2.470 -2.522 -0.052

MnCl+ 1.518e-08 1.351e-08 -7.819 -7.869 -0.051

ZnCl+ 5.746e-09 5.114e-09 -8.241 -8.291 -0.051

CdCl+ 6.618e-10 5.890e-10 -9.179 -9.230 -0.051

PbCl+ 2.196e-11 1.955e-11 -10.658 -10.709 -0.051

MnCl2 1.769e-11 1.774e-11 -10.752 -10.751 0.001

ZnCl2 1.650e-11 1.655e-11 -10.782 -10.781 0.001

CdCl2 7.548e-12 7.570e-12 -11.122 -11.121 0.001

PbCl2 8.191e-14 8.216e-14 -13.087 -13.085 0.001

ZnCl3- 6.534e-14 5.816e-14 -13.185 -13.235 -0.051

CdCl3- 1.787e-14 1.590e-14 -13.748 -13.799 -0.051

MnCl3- 1.651e-14 1.470e-14 -13.782 -13.833 -0.051

PbCl3- 2.299e-16 2.046e-16 -15.638 -15.689 -0.051

ZnCl4-2 1.474e-16 9.248e-17 -15.832 -16.034 -0.202

FeCl+ 7.128e-17 6.344e-17 -16.147 -16.198 -0.051

PbCl4-2 4.944e-19 3.103e-19 -18.306 -18.508 -0.202

FeCl+2 3.785e-20 2.375e-20 -19.422 -19.624 -0.202

FeCl2+ 2.895e-22 2.577e-22 -21.538 -21.589 -0.051

FeCl3 7.727e-26 7.750e-26 -25.112 -25.111 0.001

Cu(1) 2.360e-15

Cu+ 2.360e-15 2.086e-15 -14.627 -14.681 -0.054

Cu(2) 7.874e-08

Cu(OH)2 7.770e-08 7.793e-08 -7.110 -7.108 0.001

Cu+2 5.798e-10 3.732e-10 -9.237 -9.428 -0.191

CuOH+ 4.195e-10 3.731e-10 -9.377 -9.428 -0.051

CuSO4 3.656e-11 3.666e-11 -10.437 -10.436 0.001

Cu(OH)3- 5.275e-13 4.695e-13 -12.278 -12.328 -0.051

Cu(OH)4-2 1.492e-17 9.364e-18 -16.826 -17.029 -0.202

Fe(2) 4.266e-14

Fe+2 2.374e-14 1.528e-14 -13.625 -13.816 -0.191

FeCO3 6.724e-15 6.744e-15 -14.172 -14.171 0.001

FeHCO3+ 5.932e-15 5.280e-15 -14.227 -14.277 -0.051

FeHPO4 3.807e-15 3.818e-15 -14.419 -14.418 0.001

FeSO4 1.407e-15 1.412e-15 -14.852 -14.850 0.001

FeOH+ 8.984e-16 7.996e-16 -15.047 -15.097 -0.051

FeH2PO4+ 8.376e-17 7.455e-17 -16.077 -16.128 -0.051

FeCl+ 7.128e-17 6.344e-17 -16.147 -16.198 -0.051

FeHSO4+ 1.076e-22 9.575e-23 -21.968 -22.019 -0.051

Fe(HS)2 0.000e+00 0.000e+00 -218.236 -218.235 0.001

Fe(HS)3- 0.000e+00 0.000e+00 -322.832 -322.883 -0.051

Fe(3) 1.792e-07

Fe(OH)3 1.493e-07 1.498e-07 -6.826 -6.825 0.001

Fe(OH)4- 2.012e-08 1.791e-08 -7.696 -7.747 -0.051

Fe(OH)2+ 9.738e-09 8.667e-09 -8.012 -8.062 -0.051

FeOH+2 3.231e-13 2.027e-13 -12.491 -12.693 -0.202

FeHPO4+ 4.994e-18 4.445e-18 -17.302 -17.352 -0.051


nutrition

106

FeSO4+ 1.387e-18 1.235e-18 -17.858 -17.909 -0.051

FeH2PO4+2 8.817e-19 5.533e-19 -18.055 -18.257 -0.202

Fe+3 5.235e-19 2.112e-19 -18.281 -18.675 -0.394

FeCl+2 3.785e-20 2.375e-20 -19.422 -19.624 -0.202

Fe(SO4)2- 1.431e-20 1.273e-20 -19.844 -19.895 -0.051

FeCl2+ 2.895e-22 2.577e-22 -21.538 -21.589 -0.051

Fe2(OH)2+4 5.400e-24 8.372e-25 -23.268 -24.077 -0.810

FeCl3 7.727e-26 7.750e-26 -25.112 -25.111 0.001

FeHSO4+2 5.297e-26 3.324e-26 -25.276 -25.478 -0.202

Fe3(OH)4+5 1.498e-29 8.137e-31 -28.825 -30.090 -1.265

H(0) 1.320e-35

H2 6.600e-36 6.620e-36 -35.180 -35.179 0.001

K 7.933e-04

K+ 7.904e-04 7.019e-04 -3.102 -3.154 -0.052

KSO4- 2.862e-06 2.548e-06 -5.543 -5.594 -0.051

KHPO4- 9.651e-08 8.589e-08 -7.015 -7.066 -0.051

KOH 2.426e-10 2.433e-10 -9.615 -9.614 0.001

Mg 2.058e-03

Mg+2 1.759e-03 1.132e-03 -2.755 -2.946 -0.192

MgSO4 1.445e-04 1.449e-04 -3.840 -3.839 0.001

MgHPO4 5.954e-05 5.972e-05 -4.225 -4.224 0.001

MgHCO3+ 5.326e-05 4.740e-05 -4.274 -4.324 -0.051

MgCO3 2.202e-05 2.209e-05 -4.657 -4.656 0.001

MgPO4- 1.798e-05 1.601e-05 -4.745 -4.796 -0.051

MgOH+ 8.484e-07 7.551e-07 -6.071 -6.122 -0.051

MgH2PO4+ 4.591e-07 4.086e-07 -6.338 -6.389 -0.051

Mn(2) 3.825e-06

Mn+2 1.713e-06 1.103e-06 -5.766 -5.957 -0.191

MnCO3 1.607e-06 1.612e-06 -5.794 -5.793 0.001

MnHCO3+ 3.817e-07 3.397e-07 -6.418 -6.469 -0.051

MnSO4 1.021e-07 1.024e-07 -6.991 -6.990 0.001

MnCl+ 1.518e-08 1.351e-08 -7.819 -7.869 -0.051

MnOH+ 5.518e-09 4.911e-09 -8.258 -8.309 -0.051

MnCl2 1.769e-11 1.774e-11 -10.752 -10.751 0.001

MnCl3- 1.651e-14 1.470e-14 -13.782 -13.833 -0.051

Mn(NO3)2 1.152e-34 1.155e-34 -33.939 -33.937 0.001

Mn(3) 2.604e-23

Mn+3 2.604e-23 9.127e-24 -22.584 -23.040 -0.455

N(-3) 0.000e+00

NH4+ 0.000e+00 0.000e+00 -42.257 -42.311 -0.054

NH3 0.000e+00 0.000e+00 -43.349 -43.348 0.001

NH4SO4- 0.000e+00 0.000e+00 -44.488 -44.539 -0.051

N(0) 4.287e-03

N2 2.143e-03 2.150e-03 -2.669 -2.668 0.001

N(3) 4.079e-19

NO2- 4.079e-19 3.613e-19 -18.389 -18.442 -0.053

N(5) 5.834e-15

NO3- 5.834e-15 5.168e-15 -14.234 -14.287 -0.053

PbNO3+ 1.186e-23 1.056e-23 -22.926 -22.976 -0.051

Mn(NO3)2 1.152e-34 1.155e-34 -33.939 -33.937 0.001

Na 1.872e-03

Na+ 1.863e-03 1.660e-03 -2.730 -2.780 -0.050

NaSO4- 4.481e-06 3.989e-06 -5.349 -5.399 -0.051

NaHCO3 3.217e-06 3.226e-06 -5.493 -5.491 0.001

NaCO3- 8.980e-07 7.993e-07 -6.047 -6.097 -0.051

NaHPO4- 2.283e-07 2.032e-07 -6.641 -6.692 -0.051

NaOH 1.093e-09 1.097e-09 -8.961 -8.960 0.001

O(0) 2.846e-20

O2 1.423e-20 1.427e-20 -19.847 -19.845 0.001

P 2.326e-04

HPO4-2 1.003e-04 6.277e-05 -3.999 -4.202 -0.204

MgHPO4 5.954e-05 5.972e-05 -4.225 -4.224 0.001

CaHPO4 3.282e-05 3.292e-05 -4.484 -4.483 0.001

MgPO4- 1.798e-05 1.601e-05 -4.745 -4.796 -0.051

H2PO4- 1.093e-05 9.734e-06 -4.962 -5.012 -0.050

CaPO4- 9.937e-06 8.844e-06 -5.003 -5.053 -0.051

MgH2PO4+ 4.591e-07 4.086e-07 -6.338 -6.389 -0.051

CaH2PO4+ 2.687e-07 2.392e-07 -6.571 -6.621 -0.051

NaHPO4- 2.283e-07 2.032e-07 -6.641 -6.692 -0.051

KHPO4- 9.651e-08 8.589e-08 -7.015 -7.066 -0.051

PO4-3 9.305e-09 3.238e-09 -8.031 -8.490 -0.458

FeHPO4 3.807e-15 3.818e-15 -14.419 -14.418 0.001

FeH2PO4+ 8.376e-17 7.455e-17 -16.077 -16.128 -0.051

FeHPO4+ 4.994e-18 4.445e-18 -17.302 -17.352 -0.051

FeH2PO4+2 8.817e-19 5.533e-19 -18.055 -18.257 -0.202


nutrition

107

Pb 4.830e-08

PbCO3 4.403e-08 4.416e-08 -7.356 -7.355 0.001

Pb(CO3)2-2 3.252e-09 2.041e-09 -8.488 -8.690 -0.202

PbHCO3+ 4.260e-10 3.791e-10 -9.371 -9.421 -0.051

PbOH+ 3.025e-10 2.692e-10 -9.519 -9.570 -0.051

Pb+2 2.201e-10 1.381e-10 -9.657 -9.860 -0.202

PbSO4 3.557e-11 3.567e-11 -10.449 -10.448 0.001

PbCl+ 2.196e-11 1.955e-11 -10.658 -10.709 -0.051

Pb(OH)2 1.044e-11 1.047e-11 -10.981 -10.980 0.001

Pb(SO4)2-2 1.370e-13 8.597e-14 -12.863 -13.066 -0.202

PbCl2 8.191e-14 8.216e-14 -13.087 -13.085 0.001

Pb(OH)3- 1.350e-14 1.202e-14 -13.870 -13.920 -0.051

PbCl3- 2.299e-16 2.046e-16 -15.638 -15.689 -0.051

Pb(OH)4-2 4.387e-18 2.753e-18 -17.358 -17.560 -0.202

Pb2OH+3 2.376e-18 8.325e-19 -17.624 -18.080 -0.455

PbCl4-2 4.944e-19 3.103e-19 -18.306 -18.508 -0.202

PbNO3+ 1.186e-23 1.056e-23 -22.926 -22.976 -0.051

S(-2) 0.000e+00

HS- 0.000e+00 0.000e+00 -106.633 -106.685 -0.052

H2S 0.000e+00 0.000e+00 -107.828 -107.827 0.001

S-2 0.000e+00 0.000e+00 -111.205 -111.402 -0.197

Fe(HS)2 0.000e+00 0.000e+00 -218.236 -218.235 0.001

Fe(HS)3- 0.000e+00 0.000e+00 -322.832 -322.883 -0.051

S(6) 9.584e-04

SO4-2 7.243e-04 4.593e-04 -3.140 -3.338 -0.198

MgSO4 1.445e-04 1.449e-04 -3.840 -3.839 0.001

CaSO4 8.206e-05 8.231e-05 -4.086 -4.085 0.001

NaSO4- 4.481e-06 3.989e-06 -5.349 -5.399 -0.051

KSO4- 2.862e-06 2.548e-06 -5.543 -5.594 -0.051

MnSO4 1.021e-07 1.024e-07 -6.991 -6.990 0.001

ZnSO4 5.305e-08 5.321e-08 -7.275 -7.274 0.001

HSO4- 5.856e-10 5.212e-10 -9.232 -9.283 -0.051

Zn(SO4)2-2 3.005e-10 1.886e-10 -9.522 -9.724 -0.202

CdSO4 2.759e-10 2.767e-10 -9.559 -9.558 0.001

CuSO4 3.656e-11 3.666e-11 -10.437 -10.436 0.001

PbSO4 3.557e-11 3.567e-11 -10.449 -10.448 0.001

CaHSO4+ 5.938e-12 5.285e-12 -11.226 -11.277 -0.051

Cd(SO4)2-2 2.131e-12 1.337e-12 -11.671 -11.874 -0.202

Pb(SO4)2-2 1.370e-13 8.597e-14 -12.863 -13.066 -0.202

FeSO4 1.407e-15 1.412e-15 -14.852 -14.850 0.001

AlSO4+ 5.412e-17 4.817e-17 -16.267 -16.317 -0.051

FeSO4+ 1.387e-18 1.235e-18 -17.858 -17.909 -0.051

Al(SO4)2- 8.109e-19 7.218e-19 -18.091 -18.142 -0.051

Fe(SO4)2- 1.431e-20 1.273e-20 -19.844 -19.895 -0.051

FeHSO4+ 1.076e-22 9.575e-23 -21.968 -22.019 -0.051

AlHSO4+2 7.280e-26 4.568e-26 -25.138 -25.340 -0.202

FeHSO4+2 5.297e-26 3.324e-26 -25.276 -25.478 -0.202

NH4SO4- 0.000e+00 0.000e+00 -44.488 -44.539 -0.051

Zn 3.980e-06

ZnCO3 1.717e-06 1.723e-06 -5.765 -5.764 0.001

Zn(CO3)2-2 1.080e-06 6.775e-07 -5.967 -6.169 -0.202

Zn+2 7.392e-07 4.692e-07 -6.131 -6.329 -0.197

ZnHCO3+ 2.294e-07 2.041e-07 -6.639 -6.690 -0.051

ZnOH+ 9.639e-08 8.579e-08 -7.016 -7.067 -0.051

Zn(OH)2 5.887e-08 5.904e-08 -7.230 -7.229 0.001

ZnSO4 5.305e-08 5.321e-08 -7.275 -7.274 0.001

ZnCl+ 5.746e-09 5.114e-09 -8.241 -8.291 -0.051

Zn(SO4)2-2 3.005e-10 1.886e-10 -9.522 -9.724 -0.202

Zn(OH)3- 2.097e-11 1.867e-11 -10.678 -10.729 -0.051

ZnCl2 1.650e-11 1.655e-11 -10.782 -10.781 0.001

ZnCl3- 6.534e-14 5.816e-14 -13.185 -13.235 -0.051

Zn(OH)4-2 4.713e-16 2.957e-16 -15.327 -15.529 -0.202

ZnCl4-2 1.474e-16 9.248e-17 -15.832 -16.034 -0.202



Al(OH)3(a) -2.88 7.48 10.36 Al(OH)3

Alunite -9.15 -11.38 -2.23 KAl3(SO4)2(OH)6

Anglesite -5.44 -13.20 -7.75 PbSO4

Anhydrite -2.01 -6.41 -4.40 CaSO4

Aragonite 0.57 -7.81 -8.38 CaCO3

Calcite 0.71 -7.81 -8.52 CaCO3

Cd(OH)2 -6.35 7.30 13.65 Cd(OH)2


nutrition

108

CdSO4 -11.69 -12.04 -0.34 CdSO4

Cerrusite -1.55 -14.59 -13.05 PbCO3

CO2(g) -2.60 -20.74 -18.14 CO2

Dolomite 1.76 -15.49 -17.25 CaMg(CO3)2

Fe(OH)3(a) 0.43 18.18 17.75 Fe(OH)3

FeS(ppt) -108.59 -145.15 -36.57 FeS

Gibbsite -0.25 7.48 7.73 Al(OH)3


Gypsum -1.83 -6.41 -4.59 CaSO4:2H2O

H2(g) -32.00 -32.00 -0.00 H2

H2O(g) -1.34 -0.00 1.34 H2O

H2S(g) -106.75 -147.34 -40.58 H2S

Halite -6.90 -5.30 1.60 NaCl

Hausmannite 2.77 62.13 59.36 Mn3O4

Hematite 15.17 36.37 21.20 Fe2O3



Mackinawite -107.85 -145.15 -37.30 FeS

Manganite 0.70 26.04 25.34 MnOOH


N2(g) 0.61 -2.67 -3.28 N2

NH3(g) -44.98 -49.33 -4.35 NH3

O2(g) -16.85 64.00 80.85 O2

Otavite -1.33 -13.43 -12.10 CdCO3

Pb(OH)2 -1.78 6.14 7.92 Pb(OH)2

Pyrite -176.89 -260.49 -83.60 FeS2


Pyrolusite 1.74 42.04 40.30 MnO2

Rhodochrosite 0.46 -10.69 -11.15 MnCO3

Siderite -7.62 -18.55 -10.93 FeCO3


Sphalerite -93.53 -137.67 -44.13 ZnS

Sulfur -80.55 -115.34 -34.79 S


Zn(OH)2(e) -1.83 9.67 11.50 Zn(OH)2

------------------

End of simulation.

------------------

SENSITIVITY ANALYSIS

TITLE Fertigation mixture (December 2013): adjusted pH

SOLUTION 1

pH 7

temp 31.9

pe

units mg/L

Alkalinity 220

Al 0.01

B 0.3

Cd 0.0005

Ca 61

Cl 120

Cu 0.005

Fe 0.01

Pb 0.01

Mg 50

Mn 0.21

N 60

P 7.2

K 31

Na 43

S 92 as SO4-2

Zn 0.26

END

-----

TITLE


nutrition

109

-----

Fertigation mixture (December 2013): adjusted pH

-------------------------------------------


-------------------------------------------

Initial solution 1.



Al 3.709e-07 3.709e-07


B 2.777e-05 2.777e-05

Ca 1.523e-03 1.523e-03

Cd 4.451e-09 4.451e-09

Cl 3.387e-03 3.387e-03

Cu 7.874e-08 7.874e-08

Fe 1.792e-07 1.792e-07

K 7.933e-04 7.933e-04

Mg 2.058e-03 2.058e-03

Mn 3.825e-06 3.825e-06

N 4.287e-03 4.287e-03

Na 1.872e-03 1.872e-03

P 2.326e-04 2.326e-04

Pb 4.830e-08 4.830e-08

S 9.584e-04 9.584e-04

Zn 3.980e-06 3.980e-06


pH = 7.000

pe = 7.000









Iterations = 10

Total H = 1.110171e+02

Total O = 5.552532e+01


Log Log Log


OH- 1.867e-07 1.656e-07 -6.729 -6.781 -0.052

H+ 1.107e-07 1.000e-07 -6.956 -7.000 -0.044

H2O 5.551e+01 9.997e-01 -0.000 -0.000 0.000

Al 3.709e-07

Al(OH)4- 3.491e-07 3.105e-07 -6.457 -6.508 -0.051

Al(OH)3 1.476e-08 1.480e-08 -7.831 -7.830 0.001

Al(OH)2+ 6.966e-09 6.195e-09 -8.157 -8.208 -0.051

AlOH+2 7.094e-11 4.437e-11 -10.149 -10.353 -0.204

Al+3 7.155e-13 2.871e-13 -12.145 -12.542 -0.397

AlSO4+ 5.077e-13 4.515e-13 -12.294 -12.345 -0.051

Al(SO4)2- 7.549e-15 6.714e-15 -14.122 -14.173 -0.051

AlHSO4+2 6.845e-21 4.282e-21 -20.165 -20.368 -0.204

B 2.777e-05

H3BO3 2.757e-05 2.765e-05 -4.560 -4.558 0.001

H2BO3- 2.024e-07 1.800e-07 -6.694 -6.745 -0.051

C(4) 5.006e-03

HCO3- 4.116e-03 3.677e-03 -2.385 -2.435 -0.049

CO2 7.673e-04 7.696e-04 -3.115 -3.114 0.001

MgHCO3+ 5.791e-05 5.150e-05 -4.237 -4.288 -0.051

CaHCO3+ 4.971e-05 4.441e-05 -4.304 -4.353 -0.049

NaHCO3 3.421e-06 3.432e-06 -5.466 -5.464 0.001

CaCO3 3.306e-06 3.316e-06 -5.481 -5.479 0.001


nutrition

110

CO3-2 3.075e-06 1.958e-06 -5.512 -5.708 -0.196

MgCO3 2.392e-06 2.400e-06 -5.621 -5.620 0.001

ZnHCO3+ 7.779e-07 6.918e-07 -6.109 -6.160 -0.051

MnHCO3+ 6.443e-07 5.730e-07 -6.191 -6.242 -0.051

ZnCO3 5.820e-07 5.838e-07 -6.235 -6.234 0.001

MnCO3 2.711e-07 2.719e-07 -6.567 -6.566 0.001

NaCO3- 9.559e-08 8.501e-08 -7.020 -7.071 -0.051

PbCO3 4.126e-08 4.138e-08 -7.384 -7.383 0.001

Zn(CO3)2-2 3.906e-08 2.443e-08 -7.408 -7.612 -0.204

PbHCO3+ 3.995e-09 3.553e-09 -8.398 -8.449 -0.051

Pb(CO3)2-2 3.253e-10 2.035e-10 -9.488 -9.691 -0.204

CdHCO3+ 2.641e-10 2.348e-10 -9.578 -9.629 -0.051

FeHCO3+ 4.543e-11 4.040e-11 -10.343 -10.394 -0.051

FeCO3 5.145e-12 5.160e-12 -11.289 -11.287 0.001

CdCO3 3.131e-12 3.141e-12 -11.504 -11.503 0.001

Cd(CO3)2-2 3.108e-14 1.944e-14 -13.507 -13.711 -0.204

Ca 1.523e-03

Ca+2 1.359e-03 8.644e-04 -2.867 -3.063 -0.196

CaSO4 8.345e-05 8.370e-05 -4.079 -4.077 0.001

CaHCO3+ 4.971e-05 4.441e-05 -4.304 -4.353 -0.049

CaHPO4 2.484e-05 2.491e-05 -4.605 -4.604 0.001

CaCO3 3.306e-06 3.316e-06 -5.481 -5.479 0.001

CaH2PO4+ 2.035e-06 1.810e-06 -5.691 -5.742 -0.051

CaPO4- 7.525e-07 6.693e-07 -6.123 -6.174 -0.051

CaOH+ 1.613e-09 1.434e-09 -8.792 -8.843 -0.051

CaHSO4+ 6.043e-11 5.374e-11 -10.219 -10.270 -0.051

Cd 4.451e-09

Cd+2 3.229e-09 2.020e-09 -8.491 -8.695 -0.204

CdCl+ 6.667e-10 5.929e-10 -9.176 -9.227 -0.051

CdSO4 2.758e-10 2.766e-10 -9.559 -9.558 0.001

CdHCO3+ 2.641e-10 2.348e-10 -9.578 -9.629 -0.051

CdCl2 7.591e-12 7.614e-12 -11.120 -11.118 0.001

CdCO3 3.131e-12 3.141e-12 -11.504 -11.503 0.001

CdOH+ 3.114e-12 2.769e-12 -11.507 -11.558 -0.051

Cd(SO4)2-2 2.120e-12 1.326e-12 -11.674 -11.877 -0.204

Cd(CO3)2-2 3.108e-14 1.944e-14 -13.507 -13.711 -0.204

CdCl3- 1.797e-14 1.598e-14 -13.745 -13.796 -0.051

Cd(OH)2 8.990e-16 9.017e-16 -15.046 -15.045 0.001

Cd(OH)3- 1.137e-21 1.011e-21 -20.944 -20.995 -0.051

Cd(OH)4-2 1.441e-28 9.011e-29 -27.841 -28.045 -0.204

Cl 3.387e-03

Cl- 3.387e-03 3.005e-03 -2.470 -2.522 -0.052

MnCl+ 2.407e-08 2.141e-08 -7.619 -7.669 -0.051

ZnCl+ 1.830e-08 1.628e-08 -7.737 -7.788 -0.051

CdCl+ 6.667e-10 5.929e-10 -9.176 -9.227 -0.051

PbCl+ 1.934e-10 1.720e-10 -9.713 -9.764 -0.051

ZnCl2 5.247e-11 5.263e-11 -10.280 -10.279 0.001

MnCl2 2.800e-11 2.808e-11 -10.553 -10.552 0.001

CdCl2 7.591e-12 7.614e-12 -11.120 -11.118 0.001

PbCl2 7.202e-13 7.224e-13 -12.143 -12.141 0.001

FeCl+ 5.126e-13 4.558e-13 -12.290 -12.341 -0.051

ZnCl3- 2.078e-13 1.848e-13 -12.682 -12.733 -0.051

MnCl3- 2.614e-14 2.324e-14 -13.583 -13.634 -0.051

CdCl3- 1.797e-14 1.598e-14 -13.745 -13.796 -0.051

PbCl3- 2.021e-15 1.798e-15 -14.694 -14.745 -0.051

ZnCl4-2 4.693e-16 2.936e-16 -15.329 -15.532 -0.204

FeCl+2 2.728e-17 1.707e-17 -16.564 -16.768 -0.204

PbCl4-2 4.354e-18 2.723e-18 -17.361 -17.565 -0.204

FeCl2+ 2.080e-19 1.850e-19 -18.682 -18.733 -0.051

FeCl3 5.543e-23 5.560e-23 -22.256 -22.255 0.001

Cu(1) 1.294e-12

Cu+ 1.294e-12 1.143e-12 -11.888 -11.942 -0.054

Cu(2) 7.874e-08

Cu(OH)2 4.258e-08 4.271e-08 -7.371 -7.369 0.001

Cu+2 3.187e-08 2.045e-08 -7.497 -7.689 -0.193

CuOH+ 2.301e-09 2.045e-09 -8.638 -8.689 -0.051

CuSO4 1.988e-09 1.994e-09 -8.702 -8.700 0.001

Cu(OH)3- 2.893e-14 2.573e-14 -13.539 -13.590 -0.051

Cu(OH)4-2 8.204e-20 5.132e-20 -19.086 -19.290 -0.204

Fe(2) 2.576e-10

Fe+2 1.712e-10 1.099e-10 -9.767 -9.959 -0.193

FeHCO3+ 4.543e-11 4.040e-11 -10.343 -10.394 -0.051

FeHPO4 2.021e-11 2.027e-11 -10.694 -10.693 0.001

FeSO4 1.004e-11 1.007e-11 -10.998 -10.997 0.001

FeCO3 5.145e-12 5.160e-12 -11.289 -11.287 0.001


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FeH2PO4+ 4.451e-12 3.958e-12 -11.352 -11.403 -0.051

FeOH+ 6.465e-13 5.750e-13 -12.189 -12.240 -0.051

FeCl+ 5.126e-13 4.558e-13 -12.290 -12.341 -0.051

FeHSO4+ 7.682e-18 6.832e-18 -17.115 -17.165 -0.051

Fe(HS)2 0.000e+00 0.000e+00 -180.386 -180.385 0.001

Fe(HS)3- 0.000e+00 0.000e+00 -267.985 -268.036 -0.051

Fe(3) 1.789e-07

Fe(OH)3 1.074e-07 1.077e-07 -6.969 -6.968 0.001

Fe(OH)2+ 7.008e-08 6.233e-08 -7.154 -7.205 -0.051

Fe(OH)4- 1.448e-09 1.288e-09 -8.839 -8.890 -0.051

FeOH+2 2.331e-11 1.458e-11 -10.633 -10.836 -0.204

FeH2PO4+2 4.696e-15 2.937e-15 -14.328 -14.532 -0.204

FeHPO4+ 2.653e-15 2.360e-15 -14.576 -14.627 -0.051

FeSO4+ 9.905e-16 8.809e-16 -15.004 -15.055 -0.051

Fe+3 3.785e-16 1.519e-16 -15.422 -15.819 -0.397

FeCl+2 2.728e-17 1.707e-17 -16.564 -16.768 -0.204

Fe(SO4)2- 1.014e-17 9.017e-18 -16.994 -17.045 -0.051

FeCl2+ 2.080e-19 1.850e-19 -18.682 -18.733 -0.051

Fe2(OH)2+4 2.827e-20 4.329e-21 -19.549 -20.364 -0.815

FeHSO4+2 3.791e-22 2.372e-22 -21.421 -21.625 -0.204

FeCl3 5.543e-23 5.560e-23 -22.256 -22.255 0.001

Fe3(OH)4+5 5.678e-25 3.026e-26 -24.246 -25.519 -1.273

H(0) 1.320e-31

H2 6.600e-32 6.620e-32 -31.180 -31.179 0.001

K 7.933e-04

K+ 7.904e-04 7.013e-04 -3.102 -3.154 -0.052

KSO4- 2.840e-06 2.526e-06 -5.547 -5.598 -0.051

KHPO4- 7.125e-08 6.337e-08 -7.147 -7.198 -0.051

KOH 2.424e-11 2.431e-11 -10.616 -10.614 0.001

Mg 2.058e-03

Mg+2 1.802e-03 1.155e-03 -2.744 -2.937 -0.193

MgSO4 1.464e-04 1.468e-04 -3.834 -3.833 0.001

MgHCO3+ 5.791e-05 5.150e-05 -4.237 -4.288 -0.051

MgHPO4 4.488e-05 4.502e-05 -4.348 -4.347 0.001

MgH2PO4+ 3.464e-06 3.081e-06 -5.460 -5.511 -0.051

MgCO3 2.392e-06 2.400e-06 -5.621 -5.620 0.001

MgPO4- 1.357e-06 1.207e-06 -5.867 -5.918 -0.051

MgOH+ 8.670e-08 7.710e-08 -7.062 -7.113 -0.051

Mn(2) 3.825e-06

Mn+2 2.724e-06 1.749e-06 -5.565 -5.757 -0.193

MnHCO3+ 6.443e-07 5.730e-07 -6.191 -6.242 -0.051

MnCO3 2.711e-07 2.719e-07 -6.567 -6.566 0.001

MnSO4 1.607e-07 1.612e-07 -6.794 -6.793 0.001

MnCl+ 2.407e-08 2.141e-08 -7.619 -7.669 -0.051

MnOH+ 8.755e-10 7.786e-10 -9.058 -9.109 -0.051

MnCl2 2.800e-11 2.808e-11 -10.553 -10.552 0.001

MnCl3- 2.614e-14 2.324e-14 -13.583 -13.634 -0.051

Mn(NO3)2 0.000e+00 0.000e+00 -55.739 -55.737 0.001

Mn(3) 4.158e-24

Mn+3 4.158e-24 1.447e-24 -23.381 -23.840 -0.458

N(-3) 5.615e-36

NH4+ 5.538e-36 4.891e-36 -35.257 -35.311 -0.054

NH3 4.472e-38 4.486e-38 -37.349 -37.348 0.001

NH4SO4- 3.229e-38 2.871e-38 -37.491 -37.542 -0.051

N(0) 4.287e-03

N2 2.143e-03 2.150e-03 -2.669 -2.668 0.001

N(3) 4.083e-26

NO2- 4.083e-26 3.613e-26 -25.389 -25.442 -0.053

N(5) 5.839e-26

NO3- 5.839e-26 5.168e-26 -25.234 -25.287 -0.053

PbNO3+ 1.046e-33 9.298e-34 -32.981 -33.032 -0.051

Mn(NO3)2 0.000e+00 0.000e+00 -55.739 -55.737 0.001

Na 1.872e-03

Na+ 1.864e-03 1.660e-03 -2.730 -2.780 -0.050

NaSO4- 4.449e-06 3.956e-06 -5.352 -5.403 -0.051

NaHCO3 3.421e-06 3.432e-06 -5.466 -5.464 0.001

NaHPO4- 1.686e-07 1.500e-07 -6.773 -6.824 -0.051

NaCO3- 9.559e-08 8.501e-08 -7.020 -7.071 -0.051

NaOH 1.093e-10 1.096e-10 -9.961 -9.960 0.001

O(0) 2.846e-28

O2 1.423e-28 1.427e-28 -27.847 -27.846 0.001

P 2.326e-04

H2PO4- 8.073e-05 7.187e-05 -4.093 -4.143 -0.050

HPO4-2 7.432e-05 4.634e-05 -4.129 -4.334 -0.205

MgHPO4 4.488e-05 4.502e-05 -4.348 -4.347 0.001


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CaHPO4 2.484e-05 2.491e-05 -4.605 -4.604 0.001

MgH2PO4+ 3.464e-06 3.081e-06 -5.460 -5.511 -0.051

CaH2PO4+ 2.035e-06 1.810e-06 -5.691 -5.742 -0.051

MgPO4- 1.357e-06 1.207e-06 -5.867 -5.918 -0.051

CaPO4- 7.525e-07 6.693e-07 -6.123 -6.174 -0.051

NaHPO4- 1.686e-07 1.500e-07 -6.773 -6.824 -0.051

KHPO4- 7.125e-08 6.337e-08 -7.147 -7.198 -0.051

PO4-3 6.920e-10 2.390e-10 -9.160 -9.622 -0.462

FeHPO4 2.021e-11 2.027e-11 -10.694 -10.693 0.001

FeH2PO4+ 4.451e-12 3.958e-12 -11.352 -11.403 -0.051

FeH2PO4+2 4.696e-15 2.937e-15 -14.328 -14.532 -0.204

FeHPO4+ 2.653e-15 2.360e-15 -14.576 -14.627 -0.051

Pb 4.830e-08

PbCO3 4.126e-08 4.138e-08 -7.384 -7.383 0.001

PbHCO3+ 3.995e-09 3.553e-09 -8.398 -8.449 -0.051

Pb+2 1.945e-09 1.216e-09 -8.711 -8.915 -0.204

Pb(CO3)2-2 3.253e-10 2.035e-10 -9.488 -9.691 -0.204

PbSO4 3.108e-10 3.117e-10 -9.508 -9.506 0.001

PbOH+ 2.666e-10 2.371e-10 -9.574 -9.625 -0.051

PbCl+ 1.934e-10 1.720e-10 -9.713 -9.764 -0.051

Pb(SO4)2-2 1.192e-12 7.456e-13 -11.924 -12.128 -0.204

Pb(OH)2 9.195e-13 9.222e-13 -12.036 -12.035 0.001

PbCl2 7.202e-13 7.224e-13 -12.143 -12.141 0.001

PbCl3- 2.021e-15 1.798e-15 -14.694 -14.745 -0.051

Pb(OH)3- 1.190e-16 1.059e-16 -15.924 -15.975 -0.051

Pb2OH+3 1.856e-17 6.458e-18 -16.732 -17.190 -0.458

PbCl4-2 4.354e-18 2.723e-18 -17.361 -17.565 -0.204

Pb(OH)4-2 3.875e-21 2.424e-21 -20.412 -20.615 -0.204

PbNO3+ 1.046e-33 9.298e-34 -32.981 -33.032 -0.051

S(-2) 0.000e+00

HS- 0.000e+00 0.000e+00 -89.636 -89.688 -0.052

H2S 0.000e+00 0.000e+00 -89.832 -89.830 0.001

S-2 0.000e+00 0.000e+00 -95.207 -95.405 -0.199

Fe(HS)2 0.000e+00 0.000e+00 -180.386 -180.385 0.001

Fe(HS)3- 0.000e+00 0.000e+00 -267.985 -268.036 -0.051

S(6) 9.584e-04

SO4-2 7.209e-04 4.557e-04 -3.142 -3.341 -0.199

MgSO4 1.464e-04 1.468e-04 -3.834 -3.833 0.001

CaSO4 8.345e-05 8.370e-05 -4.079 -4.077 0.001

NaSO4- 4.449e-06 3.956e-06 -5.352 -5.403 -0.051

KSO4- 2.840e-06 2.526e-06 -5.547 -5.598 -0.051

ZnSO4 1.677e-07 1.682e-07 -6.776 -6.774 0.001

MnSO4 1.607e-07 1.612e-07 -6.794 -6.793 0.001

HSO4- 5.815e-09 5.172e-09 -8.235 -8.286 -0.051

CuSO4 1.988e-09 1.994e-09 -8.702 -8.700 0.001

Zn(SO4)2-2 9.455e-10 5.914e-10 -9.024 -9.228 -0.204

PbSO4 3.108e-10 3.117e-10 -9.508 -9.506 0.001

CdSO4 2.758e-10 2.766e-10 -9.559 -9.558 0.001

CaHSO4+ 6.043e-11 5.374e-11 -10.219 -10.270 -0.051

FeSO4 1.004e-11 1.007e-11 -10.998 -10.997 0.001

Cd(SO4)2-2 2.120e-12 1.326e-12 -11.674 -11.877 -0.204

Pb(SO4)2-2 1.192e-12 7.456e-13 -11.924 -12.128 -0.204

AlSO4+ 5.077e-13 4.515e-13 -12.294 -12.345 -0.051

Al(SO4)2- 7.549e-15 6.714e-15 -14.122 -14.173 -0.051

FeSO4+ 9.905e-16 8.809e-16 -15.004 -15.055 -0.051

Fe(SO4)2- 1.014e-17 9.017e-18 -16.994 -17.045 -0.051

FeHSO4+ 7.682e-18 6.832e-18 -17.115 -17.165 -0.051

AlHSO4+2 6.845e-21 4.282e-21 -20.165 -20.368 -0.204

FeHSO4+2 3.791e-22 2.372e-22 -21.421 -21.625 -0.204

NH4SO4- 3.229e-38 2.871e-38 -37.491 -37.542 -0.051

Zn 3.980e-06

Zn+2 2.361e-06 1.495e-06 -5.627 -5.825 -0.199

ZnHCO3+ 7.779e-07 6.918e-07 -6.109 -6.160 -0.051

ZnCO3 5.820e-07 5.838e-07 -6.235 -6.234 0.001

ZnSO4 1.677e-07 1.682e-07 -6.776 -6.774 0.001

Zn(CO3)2-2 3.906e-08 2.443e-08 -7.408 -7.612 -0.204

ZnOH+ 3.073e-08 2.733e-08 -7.512 -7.563 -0.051

ZnCl+ 1.830e-08 1.628e-08 -7.737 -7.788 -0.051

Zn(OH)2 1.875e-09 1.881e-09 -8.727 -8.726 0.001

Zn(SO4)2-2 9.455e-10 5.914e-10 -9.024 -9.228 -0.204

ZnCl2 5.247e-11 5.263e-11 -10.280 -10.279 0.001

ZnCl3- 2.078e-13 1.848e-13 -12.682 -12.733 -0.051

Zn(OH)3- 6.685e-14 5.945e-14 -13.175 -13.226 -0.051

ZnCl4-2 4.693e-16 2.936e-16 -15.329 -15.532 -0.204

Zn(OH)4-2 1.506e-19 9.419e-20 -18.822 -19.026 -0.204


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Al(OH)3(a) -1.90 8.46 10.36 Al(OH)3

Alunite -3.23 -5.46 -2.23 KAl3(SO4)2(OH)6

Anglesite -4.50 -12.26 -7.75 PbSO4

Anhydrite -2.01 -6.40 -4.40 CaSO4

Aragonite -0.39 -8.77 -8.38 CaCO3

Calcite -0.25 -8.77 -8.52 CaCO3

Cd(OH)2 -8.34 5.31 13.65 Cd(OH)2

CdSO4 -11.69 -12.04 -0.34 CdSO4

Cerrusite -1.57 -14.62 -13.05 PbCO3

CO2(g) -1.57 -19.71 -18.14 CO2

Dolomite -0.17 -17.42 -17.25 CaMg(CO3)2

Fe(OH)3(a) 0.29 18.04 17.75 Fe(OH)3

FeS(ppt) -88.73 -125.30 -36.57 FeS

Gibbsite 0.73 8.46 7.73 Al(OH)3


Gypsum -1.82 -6.40 -4.59 CaSO4:2H2O

H2(g) -28.00 -28.00 -0.00 H2

H2O(g) -1.34 -0.00 1.34 H2O

H2S(g) -88.76 -129.34 -40.58 H2S

Halite -6.90 -5.30 1.60 NaCl

Hausmannite -6.63 52.73 59.36 Mn3O4

Hematite 14.88 36.08 21.20 Fe2O3



Mackinawite -88.00 -125.30 -37.30 FeS

Manganite -3.10 22.24 25.34 MnOOH


N2(g) 0.61 -2.67 -3.28 N2

NH3(g) -38.98 -43.33 -4.35 NH3

O2(g) -24.85 56.00 80.85 O2

Otavite -2.30 -14.40 -12.10 CdCO3

Pb(OH)2 -2.83 5.08 7.92 Pb(OH)2

Pyrite -143.04 -226.64 -83.60 FeS2


Pyrolusite -4.06 36.24 40.30 MnO2


Siderite -4.74 -15.67 -10.93 FeCO3


Sphalerite -77.03 -121.17 -44.13 ZnS

Sulfur -66.55 -101.34 -34.79 S


Zn(OH)2(e) -3.33 8.17 11.50 Zn(OH)2

------------------

End of simulation.

------------------


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APPENDIX C: ASH ALKALINITY

STANDARDISATION OF STRONG ACID WITH WEAK BASE

Known volume of ~0.05 M hydrochloric acid, HCl, was standardised against

0.05 M sodium carbonate, Na2CO3, and Table 20 summarises the volume of Na2CO3 used

to reach endpoint.

Table 20. Standardisation of ~0.05 M HCl with 0.05 M Na2CO3

Trial Initial (ml) Final (ml) Titre (ml) 1 0 24.8 24.8 2 0 24.6 24.6 3 0 24.7 24.7 4 0 24.7 24.7 Mean titre 24.7 ± 0.02

Based on equation [5], two moles of HCl are required for every one mole of

Na2CO3. Stoichiometric calculations using equation [6] therefore show that 24.7 ml of

0.05 M Na2CO3 was required to reach endpoint with 50 ml of 0.0494 (or 0.05 M) M HCl.

2HCl (aq) + Na2CO3 (aq) ⇄ 2NaCl (aq) + H2O (l) + CO2 (g) [5]

c1v2 = c2v2 [6]

where, c1 and v1 is the concentration and volume of HCl, and c2 and v2 is the

concentration and volume of Na2CO3.

COMPARISON OF FINELY MILLED AND NON-MILLED SAMPLES

With regards to the preparation of hay samples for ash alkalinity determination,

results showed no significant difference between finely milled and non-milled hay

samples (P = 0.99). Table 21 summarises these results for the November 2013 to January

2014 growth cycle.

NEUTRALISING EXCESS ALKALINITY TO PREVENT SOIL ALKALINISATION

The equivalent quantity of sulphuric required to neutralise net alkalinity gained

from irrigation can be calculated. The mean net gain in alkalinity in the system was


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approximately 409 (± 51) kg CaCO3/ha between November 2013 and January 2014

growth cycle. This is equivalent to a mean total alkalinity of 185 (± 2) mg CaCO3/L

present in excess in irrigation water (Table 22). This shows that pasture production has

the capacity to neutralise approximately 45 mg CaCO3/L and thus the remaining 185 mg

CaCO3/L should be neutralised by equivalent quantities of H2SO4 to cease soil

alkalinisation.

Due to 1:1 acid:base stoichiometry, the number of moles of H2SO4 is equivalent

to the number of moles of CaCO3. Therefore, assuming 1.83 x 10-3 mol CaCO3 is present

in excess for every 1 L of irrigation water, approximately 1.83 x 10-3 mol of H2SO4 is

required to completely neutralise CaCO3. According to equation [6], the acid can be

prepared by adding 1.0 ml H2SO4 (98%, 18.4 M) to 100 ml deionised water and diluted

to 10.0 L. That is, for every 10 L of irrigation water, 1 ml of 18.4 M H2SO4 is required for

neutralisation.

Table 21. Comparing ash alkalinity and net alkalinity results for finely milled and non-milled

duplicate hay subsamples for Pivots 1-5 between November 2013 and January 2014

Pivot #

Total alkalinity

from irrigation (kg

CaCO3 /ha)

Ash alkalinity (kg CaCO3 /ha)

Net alkalinity (kg CaCO3 /ha): added - removed

Milled Non-milled Milled Non-milled

1 408.0 94 81 314 327

1 408.0 94 89 314 319

2 667.0 119 140 548 527

2 667.0 146 134 521 533

3 645.4 116 136 529 509

3 645.4 121 110 524 536

4 457.7 97 80 361 377

4 457.7 86 85 372 373

5 360.6 58 69 303 291

5 360.6 62 65 299 295

Mean 99 (± 9) 99 (± 9) 409 (± 34) 409 (± 33)

Min 58 65 299 291

Max 146 140 548 536

Table 22. Calculated excess total alkalinity (mg CaCO3/L) in irrigation water to be neutralised

by sulphuric acid (H2SO4) to cease soil alkalinisation, based on results in Table 17

Pivot # Gross

irrigation (ML/ha)

Total alkalinity (mg CaCO3/L) in irrigation water

Overall net gain in alkalinity (kg

CaCO3/ha) from irrigation

*Excess total alkalinity (mg CaCO3/L) in irrigation water


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1 1.774 230 314.0 (± 0.1) 177.0 (± 0.0)

2 2.900 230 534.7 (± 13.4) 184.4 (± 4.6)

3 2.806 230 526.6 (± 2.6) 187.7 (± 0.9)

4 1.990 230 366.5 (± 5.5) 184.2 (± 2.8)

5 1.568 230 300.9 (± 1.9) 191.9 (± 1.2)

Overall mean 408.6 (± 51.1) 185.0 (± 2.4)

*excess total alkalinity (mg CaCO3/L) in irrigation water to be neutralized

117

APPENDIX D: CLUSTER ANALYSIS – STRATIFYING IRRIGATION

PIVOTS

As an exploratory data analysis tool that combines the principles of hierarchical

and partitioning methods, the SPSS two-step cluster analysis was used to stratify the

remaining 10 irrigation pivots by their soil characteristics. One-way ANOVA and

bivariate correlation analysis were also used in diagnostics for determining suitable soil

properties for cluster analysis. Here, cluster analysis is used to identify representative

pivots for future monitoring where stratified sampling can be achieved.

RESULTS

Two independent variables were selected from a suite of soil properties to

construct a specified 4-cluster solution, employing Span 3 results from December 2013

at the 20-30 cm soil layer. Additionally, soil particle size from March 2014 was used to

determine if pivots were similar by soil texture (e.g., clay percentage). Two variables

were used since using too many could increase the odds that the variables are "no longer

dissimilar" (Mooi and Sarstedt, 2011). Suitable variables should not be highly correlated

with one another (Table 7) and not be significantly different between monitoring spans

(Table 1).

As the quality of variables will reflect the quality of the cluster solution, multiple

tests were performed using different combinations of 'high quality' solutions. The quality

of these solutions can be determined by the ‘predictor importance’ generated from the

output data. Variables equally important in the clustering algorithm are considered a

good combination and hence should reflect a high quality cluster solution. Figure 49

provides an example of a three-variable combination.

Three cluster solutions were selected from a variety of tests and the cluster

membership of each pivot is summarised in Table 23 and colour-coded for convenience.

Of the 10 pivots, results show distinct groups of pivots that are similar in all three tests:

(a) Pivots 2 and 3, (b) Pivots 6, 7 and 11, and (c) Pivots 8 and 10.


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Figure 49. Comparing a good combination (left) and a bad combination (right) of three variables

used in two-step cluster analysis

Table 23. Designated cluster memberships for irrigation pivots using a specified 4-cluster

solution, based on Span 3 soil properties from December 2013 and particle size from March

2014 at the 20-30 cm layer. Colour coding is independent for each test.

Pivot # Test 1: EC, Ex. Al% Test 2: CCE, C/N ratio Test 3: clay%, As

1 2 4 1

2* 2 1 2

3* 2 1 2

4 1 3 2

5 3 2 4

6* 3 4 3

7* 3 4 3

8* 4 4 3

10* 4 4 3

11* 3 4 3

*consistent clustering of irrigation pivots throughout all three tests

Test 1 (Figure 50) shows Pivots 2 and 3 were grouped in Cluster 2, with a mean

EC of 0.20 dS/m and a mean exchangeable Al percentage of 1.2%. Pivots 6, 7 and 11 were

grouped in Cluster 3, with a mean EC of 0.13 dS/m and a mean exchangeable Al

percentage of 2.3%. Lastly, Pivots 8 and 10 were grouped in Cluster 4, with a mean EC of

0.20 dS/m and a mean exchangeable Al percentage of 2.1%.


CCE of 0.39% and a mean C/N ratio of 5.0. Pivots 6, 7, 8, 10 and 11 were grouped together

in Cluster 4, with a mean CCE of 0.22% and a mean C/N ratio of 5.3.


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Figure 50. Test 1 clustering of 10 active irrigation pivots at the HAP, based on electrical

conductivity (EC, dS/m) and exchangeable Al percentage (%) and colour coded: Cluster 1

(red), Cluster 2 (blue), Cluster 3 (purple) and Cluster 4 (green).

Figure 51. Test 2 clustering of 10 active irrigation pivots at the HAP, based on CaCO3

equivalent (CCE, %) and carbon/nitrogen (C/N) ratio and colour coded: Cluster 1 (red),

Cluster 2 (blue), Cluster 3 (purple) and Cluster 4 (green).


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clay content of 28.8% and a mean As concentration of 14.2 mg/kg. Pivots 6, 7, 8, 10 and

11 were grouped together in Cluster 3, with a mean clay content of 26.6% and a mean As

concentration of 16.2 mg/kg.

Figure 52. Test 3 clustering of 10 active irrigation pivots at the HAP, based on clay content

(%) and arsenic concentration (mg As/kg) and colour coded: Cluster 1 (red), Cluster 2 (blue),

Cluster 3 (purple) and Cluster 4 (green).

Consistent with all three cluster solutions, Pivots 2 and 3, Pivots 6, 7 and 11, and

Pivots 8 and 10 are, to a degree, similar in terms of EC, CCE, C/N ratio, exchangeable Al

percentage, As concentration and clay content. One-way ANOVA was also used to identify

any significant differences in soil properties among these clusters (Table 24), as

summarised:

1. Clusters in Test 1 were significantly different in exchangeable Ca (P < 0.05) and

Na concentrations (P < 0.05), exchangeable Ca (P < 0.01) and Mg percentages (P

< 0.01), and As (P < 0.01) and Cd concentrations (P = 0.05).

2. Clusters in Test 2 were significantly different in OC (P < 0.05), and exchangeable

Ca (P = 0.01) and Mg percentages (P < 0.01).


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3. Clusters in Test 3 were significantly different in OC (P = 0.05), C/N ratio (P < 0.05),

PRI (P < 0.05), exchangeable Al concentration (P < 0.05) and percentage (P <

0.01), and sand content (P < 0.05).

It is uncertain as to why Pivots 4 and 5 were not similar given their close

proximity and similar gross irrigation use (Figure 53). However, Pivot 1 was somewhat

similar to Pivots 2 and 3 (Test 1), and Pivots 6, 7, 8, 10 and 11 (Test 2), but this was not

confirmed in Test 3. Nonetheless, stratified monitoring is an option where only

representative pivots of the irrigated HAP area are monitored rather than every pivot.

From the three groups presented, it is then possible to decide which pivots require

monitoring. For example, monitoring may cease in Pivots 3, 7, 10 and 11, leaving the

remaining six (Pivots 1, 2, 4, 5, 6 and 8) to be routinely monitored. However, note cluster

analysis cannot guarantee absolute similarity since: (1) results depend on the variables

used (i.e., soil properties), (2) soil properties change over time and with irrigation, (2)

results are only as accurate as the data provided, and (3) random error due to variability.

Table 24. One-way ANOVA between clusters for soil properties at 20-30 cm, using Span 3

December 2013 results

Parameters Test 1 Test 2 Test 3

F P F P F P Electrical conductivity, EC - - 1.88 0.23 1.59 0.29 pHCa 1.49 0.31 0.70 0.58 0.85 0.52 CaCO3 equivalent, CCE 1.30 0.36 - - 3.93 0.07 Organic carbon, OC 0.30 0.83 6.51 0.03 4.78 0.05 NO3-N 2.80 0.13 1.60 0.29 4.00 0.07 NH4-N 0.70 0.59 1.60 0.29 0.70 0.59 Total N 0.50 0.69 0.40 0.76 0.57 0.65 C/N ratio 0.62 0.63 - - 5.68 0.03 Colwell P - - 3.04 0.11 4.30 0.06 Total P 0.61 0.63 1.89 0.23 2.40 0.17 Phosphorus retention index, PRI 0.26 0.85 3.03 0.12 6.92 0.02 Colwell K 1.89 0.23 2.62 0.15 2.04 0.21 Total K 1.75 0.26 3.69 0.08 2.39 0.17 Ex. Ca 5.34 0.04 3.07 0.11 1.41 0.33 Ex. Mg 1.50 0.31 0.34 0.80 1.16 0.40 Ex. Na 6.33 0.03 1.63 0.28 4.06 0.07 Ex. K 2.37 0.17 2.39 0.17 1.30 0.36 Ex. Al 3.95 0.07 0.56 0.66 6.29 0.03 ECEC 3.58 0.09 1.90 0.23 1.41 0.33 Ex. Ca percentage 16.43 0.00 10.20 0.01 1.16 0.40 Ex. Mg percentage 17.05 0.00 16.63 0.00 1.09 0.42 Ex. Na percentage, ESP 1.33 0.35 0.48 0.71 1.38 0.34 Ex. K percentage 0.13 0.94 2.29 0.18 2.12 0.20 Ex. Al percentage - - 1.13 0.41 18.44 0.00 As 14.10 0.00 1.39 0.33 - - Cd 5.10 0.04 0.91 0.49 0.93 0.48 Cr 2.67 0.14 1.01 0.45 1.42 0.33


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Pb 2.49 0.16 0.57 0.65 0.78 0.55 Sand 1.33 0.35 1.13 0.41 5.77 0.03 Silt 0.36 0.79 0.12 0.95 0.64 0.62 Clay 1.63 0.28 1.13 0.41 - -

Figure 53. Gross irrigation volumes used at each irrigation pivot at the Hamersley Agricultural Project (HAP) for the baseline (blue) period, and periods between

baseline and December 2013 (red), and baseline and February 2014 (green), based on unpublished data (Rio Tinto Iron Ore, 2014).

0

5

10

15

20

25

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Gro

ss ir

riga

tio

n (

ML/

ha)

Irrigation pivot

Gross irrigation (ML/ha) duringbaseline period (October 2012 toFebruary 2013)

Gross irrigation (ML/ha) betweenbaseline period (October 2012 toFebruary 2013) and December2013

Gross irrigation (ML/ha) betweenbaseline period (October 2012 toFebruary 2013) and February 2014

Investigating the impacts of groundwater on soil properties and pasture nutrition

TEST 1: ELECTRICAL CONDUCTIVITY AND EXCHANGEABLE ALUMINIUM PERCENTAGE

Figure 54. Level of importance of variables (EC and exchangeable Al %) used

in test 1

Figure 55. Description of cluster size and mean values for variables (EC and

exchangeable Al %) in test 1


Figure 56. Comparing the distribution of individual clusters in test 1 (EC and exchangeable Al %) with the overall distribution of the December 2013 soil (20-30

cm layer, Span 3) data set


TEST 2: CALCIUM CARBONATE EQUIVALENT AND CARBON/NITROGEN RATIO

Figure 57. Level of importance of variables (CCE and C/N ratio) used in test

2

Figure 58. Description of cluster size and mean values for variables (CCE and C/N

ratio) in test 2


Figure 59. Comparing the distribution of individual clusters in test 2 (CCE and C/N ratio) with the overall distribution of the December 2013 soil (20-30 cm layer,

Span 3) data set


TEST 3: CLAY CONTENT AND ARSENIC CONCENTRATION

Figure 60. Level of importance of variables (clay % and As concentration)

used in test 3

Figure 61. Description of cluster size and mean values for variables (clay % and

As concentration) in test 3


Figure 62. Comparing the distribution of individual clusters in test 3 (clay % and As concentration) with the overall distribution of the December 2013 soil (20-

30 cm layer, Span 3) data set


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APPENDIX E: SOIL CARBONATE DETERMINATION – A

METHODOLOGY DEVELOPMENT EXERCISE

METHODS AND MATERIALS

Two routine methods for determination of soil CaCO3 equivalent (CCE) were

used in a methodology development exercise to: (1) verify the CCE of several September

2013 and December 2013 samples from the HAP; and, (2) determine the precision and

accuracy of Method 1 and 2 for carbonate determine based on standard additions of

CaCO3.

METHOD 1

Method 1 is a procedure based on pressure changes in carbon dioxide, CO2, from

reaction with dilute hydrochloric acid, HCl (see Rayment and Lyons, 2011, p. 420). The

pressure is measured in a closed vessel at constant temperature using a corrosion-

resistant gas pressure transducer with a direct current voltage. Assuming the reaction

goes to completion, the pressure increase is proportional to the amount of carbonate in

the soil (Rayment and Lyons, 2011). This method was performed externally by the CSBP

Soil and Plant Analysis Laboratory, Western Australia.

METHOD 2

An alternative procedure involves measuring the pH of the soil supernatant after

reaction with dilute acetic acid, CH3COOH (Loeppert et al., 1984, Moore et al., 1987). The

equivalent CaCO3 content is empirically calculated from the pH by means of an algorithm

obtained from calibration runs using standards prepared from known masses of CaCO3

(Ashworth, 1997).

Soils were air-dried and weighed to 2.0 g (< 2 mm particle size) to the nearest 1

mg and transferred to 50 ml polypropylene centrifuge tubes. The standard curve was

prepared using 2.0 g samples with known masses of powdered CaCO3: 10, 30, 50, 70, 90,

110 and 130 mg CaCO3. Note, the sole use of CaCO3 in calibration runs (e.g., Loeppert et

al., 1984, Moore et al., 1987) was highlighted by Ashworth (1997) to give "false positive"

readings for soils with no free lime (e.g., acidic soils). Thus, to reduce this tendency, tests

were calibrated against soils amended with known weights of CaCO3 and not pure CaCO3


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alone (Ashworth, 1997). As a further modification to Ashworth (1997), standards were

added with deionised water to form a saturated paste/mixture and later left to air-dry in

a glasshouse for a week. This aims to encourage physical and chemical bonding between

soil and CaCO3 particles similar to how carbonates would naturally occur in the soil

environment. Samples were stirred to break up any remaining aggregates.

All samples were treated with 25 ml aliquot of 0.4 M acetic acid and swirled by

hand for 10 seconds before being placed on a reciprocating shaking water bath (model

RW1812) for approximately 16 hours overnight. To allow the evolved CO2 gas to escape

as well as minimising the evaporative losses of H2O and CH3COOH, all lids were

punctured with nine 1 mm pinholes. Following total dissolution and equilibration, the

pH of the supernatant was determined using a HI8424 pH meter, swirling by hand for 1

minute and allowing the suspension to settle for another minute before recording.

The addition of a known excess quantity of acetic acid, CH3COOH, to a given

quantity of sample is based on the reaction with soil carbonates, as summarised below:

CaCO3 + 2CH3COOH → Ca2+ + 2CH3OO- + H2O + CO2 [7]

The equivalents of CH3COO- produced by the reaction are stoichiometrically

equal to the equivalents of CaCO3 dissolved from the soil sample (Moore et al., 1987). The

dissolution of acetic acid in equation [7] is expressed as:

CH3COOH ⇄ H+ + CH3COO- [8]

In terms of pH, the thermodynamic equilibrium expression of equation [8] is:

pH = pKa + log [CH3COO−]

[CH3COOH] [9]

and, based on the assumption that the quantity of CH3COO- is proportional to

equivalents of CaCO3, equation [9] may be rewritten as:

pH = 𝑎 × log [CaCO3

𝑇−CaCO3] + 𝑏

[10]

where, T is the total amount of CaCO3 (i.e., 500 mg) for complete neutralisation

with the added 25 ml aliquot of 0.4 M acetic acid; CaCO3 is the unknown amount of CaCO3

(mg) present in the sample; and coefficients a and b are the gradient and y-intercept of

the standard curve, respectively. In accordance with equation [10], the plot of pH versus


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log[CaCO3 / (T – CaCO3)] is linear, thus the CaCO3 content (mg) of a soil sample can be

empirically determined (Figure 63).

Figure 63. Standard curve for Method 2 using 0.4 M CH3COOH and CaCO3 weights

of 10, 30, 50, 70, 90, 110 and 130 mg (linear relationship: y = 0.767x + 4.409 and

R2 = 0.996)

To determine CCE, equation [10] was combined with equation [11]:

CCE = CaCO3

𝑆× 100

[11]

where, S is the air-dried soil weight (mg), to form equation [12]:

CCE = 100𝑇

𝑆(1+10[(𝑏−pH) 𝑎⁄ ])

[12]

PRECISION AND ACCURACY OF METHODS 1 AND 2

Standard additions of CaCO3 prepared from three unknown soil samples were

used to assess the precision and accuracy of Methods 1 and 2. To determine appropriate

CaCO3 weights for standard additions, preliminary tests were conducted using Method

3.0

3.2

3.4

3.6

3.8

4.0

4.2

-2.0 -1.5 -1.0 -0.5 0.0

pH

log[CaCO3 / (T - CaCO3)]


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2, based on the standard curve from Figure 63. Results indicate samples contained an

average CCE of 0.20% (or ~2.0 mg/g; Table 25) and hence bulk samples were prepared

with standard additions of 0, 2, 4, 6, 8, 10 and 100 mg CaCO3/g.

Table 25. Preliminary CaCO3 content (mg) and calculated CaCO3 equivalent (CCE, %) of

unknown samples using Method 2

Sample Trial CaCO3 (mg) in

2 g soil CCE (%)

A 1 3.30 0.17 2 3.40 0.17 3 3.02 0.15 B 1 4.19 0.21 2 4.19 0.21 3 3.61 0.18 C 1 5.17 0.26 2 4.87 0.24 3 4.72 0.24 Mean 4.05 (± 0.25) 0.20 (± 0.01)

RESULTS

Since carbonate should not persist as stable compounds in acid soils due to

neutralisation, an overall mean CCE of 0.23% (or 2300 mg/kg CaCO3) in soils with pHCa

~5.0 (see Table 3 and 4) raised question about the accuracy of CaCO3 determination

using Method 1. The CCE of 8 samples from both September and December 2013 batches

were thus verified using Method 2 and a re-calibrated standard curve (Figure 64).

Figure 64. Standard curve for Method 2 using 0.4 M CH3COOH and CaCO3 weights of

10, 30, 50, 70, 90, 110 and 130 mg (linear relationship: y = 0.772x + 4.435 and R2 =

0.999)

3.0

3.2

3.4

3.6

3.8

4.0

4.2

-2.0 -1.5 -1.0 -0.5 0.0

pH

log[CaCO3 / (T - CaCO3)]


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Results showed soil CCE reported by Method 1 were 0.17% ± 0.03% higher than

values reported by Method 2 (Table 26) – i.e., roughly double. When plotted together

(Figure 65), CCE values from Methods 1 and 2 did not correlate which may further raise

question about analytical error. To further compare results, CCE values were plotted

against their respective soil pHCa (Figure 66). However, results showed no correlation

between pHCa and Method 1 (R2 = 0.00), although a moderate positive correlation is

evident with Method 2 (R2 = 0.56).

Table 26. Comparing calcium carbonate equivalent (CCE, %) assessed by Method 1 and 2 for

eight September 2013 and December 2013 soil samples and their respective soil pHCa values –

pivot and span denoted as ‘P’ and ‘S’, respectively

R² = 0.020.05

0.07

0.09

0.11

0.13

0.15

0.17

0.19

0.21

0 0.1 0.2 0.3 0.4 0.5 0.6

Me

tho

d 2

(%

)

Method 1 (%)

Sample Depth (cm) pHCa

CCE (%) Difference in CCE (%, M1-M2) Method 1 (M1) Method 2 (M2)

Sep

tem

ber

20

13

P2-S1 0-10 6.6 0.28 0.18 0.10 P5-S1 20-30 5.8 0.31 0.16 0.15 P6-S2 20-30 5.0 0.28 0.13 0.15 P12-S1 20-30 4.9 0.30 0.11 0.19 P14-S2 0-10 6.0 0.31 0.12 0.19 P17-S1 0-10 6.9 0.44 0.19 0.25 P17-S3 0-10 6.5 0.17 0.18 -0.01 P17-S3 20-30 5.6 0.10 0.14 -0.04

Dec

emb

er 2

01

3

P1-S1 0-10 6.7 0.19 0.16 0.03 P2-S3 20-30 4.9 0.37 0.10 0.27 P3-S3 20-30 5.5 0.41 0.11 0.30 P4-S1 20-30 5.1 0.46 0.11 0.35 P5-S1 20-30 6.1 0.24 0.11 0.13 P6-S1 0-10 6.4 0.51 0.13 0.38 P8-S1 0-10 6.8 0.29 0.14 0.15 P11-S3 20-30 5.2 0.19 0.10 0.09

Mean 0.30 (± 0.03) 0.14 (± 0.01) 0.17 (± 0.03)


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Figure 65. Calcium carbonate equivalent (CCE, %) of eight September 2013 and

December 2013 soil samples determined by Methods 1 and 2

Figure 66. Correlation between pH (CaCl2) and calcium carbonate equivalent (CCE, %) of eight

September and December 2013 soil samples determined using Method 1 (left) and Method 2

(right)

By making standard additions of 0, 2, 4, 6, 8, 10 and 100 mg/g CaCO3, reported

CCE values from Methods 1 and 2 were compared with expected values (Table 27).

Expected values were calculated from the sum of CaCO3 added and the mean CCE of soil

samples (0.20% ± 0.01%).

Table 27. Comparing expected soil calcium carbonate equivalent (CCE, %) and reported values

from Methods 1 and 2 using standard additions of 0, 2, 4, 6, 8, 10 and 100 mg CaCO3/g

Standard additions (mg CaCO3/g)

Expected CCE (%)

Reported CCE (%) Method 1 Method 2

0 0.20 0.32 0.21 (± 0.00) 2 0.40 0.79 0.28 (± 0.01) 4 0.60 0.81 0.30 (± 0.01) 6 0.80 1.04 0.47 (± 0.02) 8 1.00 1.26 0.47 (± 0.00) 10 1.20 1.43 0.64 (± 0.00) 100 10.20 11.54 8.27 (± 0.13) Reported values from Method 2 are a mean (± SE) of 3 replicates.

In Figure 67, standard additions of 100 mg/g CaCO3 were not included (outlier).

Results showed the reported CCE values from Method 1 were 0.24% ± 0.04% higher than

expected, while values reported from Method 2 were 0.31% ± 0.09% lower than

expected (Figure 67). By and large, CCE values reported from Method 1 were 0.55% ±

R² = 0.000

0.1

0.2

0.3

0.4

0.5

0.6

4.5 5.0 5.5 6.0 6.5 7.0 7.5

Me

tho

d 1

(%

)

pH

R² = 0.560.07

0.09

0.11

0.13

0.15

0.17

0.19

0.21

4.5 5.0 5.5 6.0 6.5 7.0 7.5

Me

tho

d 2

(%

)

pHCa


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0.10% higher than from Method 2, representing a marked difference (P < 0.01) between

these two routine methods in detecting CCE at relatively low levels.

Figure 67. Comparing expected and reported CCE (%) values from Method 1 (blue)

and Method 2 (red) from standard additions of 0, 2, 4, 6, 8 and 10 mg CaCO3/g

DISCUSSION

Methods were unable to determine the real CCE value of untreated soils. Method

1 tended to give a relatively higher CCE, but had quantitative recovery of added CaCO3.

On the other hand, Method 2 tended to give a relatively lower CCE and a lower recovery

of added CaCO3 and, but showed greater sensitivity to changes in soil pH than Method 1.

The precision of these methods could not be assessed properly due to insufficient or no

sample replication. Thus, a more thorough approach is required to properly compare the

accuracy and precision of both methods.

A possible factor affecting the overestimation of CCE in the soil sample could be

a result of clay content and organic matter by consuming H+ via a mechanism of ion

exchange onto surfaces (Loeppert et al., 1984, Moore et al., 1987). In contrast, this study

showed the corresponding method (Method 2) to underestimate CCE. Changes to the

original procedure for preparing standards are suspected to have influenced results to

some degree – i.e., the amendment of standard additions with CaCO3 and DI water to

make slurry, including air drying for 1 week (delayed treatment with acetic acid), rather

than the immediate treatment of a dry mixture of soil and powdered CaCO3 with acetic

acid. However, it is not known whether such procedural changes had affected soil

R² = 1

R² = 0.9513

R² = 0.934

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

0 2 4 6 8 10 12

CC

E (%

)

CaCO3 added (mg/g)

Expected

Method 1

Method 2


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carbonate concentration (e.g., carbonate loss during sample preparation) and/or

prevented complete neutralisation of soil carbonate with acetic acid.

Nonetheless,, Loeppert et al. (1984) noted soils with relatively low CaCO3

contents generally had greater potential for error, including (1) dissolution of soil

components other than CaCO3, (2) incomplete dissolution of CaCO3, (3) effect of high PCO2

on pH, (4) volatilisation of acetic acid, and (5) errors in pH determination (Loeppert et

al., 1984). Errors due to volatilisation of acetic acid would have been minimal by using

lids with several pin-holes. However, insufficient ventilation of CO2 gas generated from

the acid-base reaction would increase the partial pressure of CO2, causing the soil pH to

remain low and hence underestimate CCE. And, as mentioned, incomplete dissolution of

CaCO3 may also result in its underestimation.


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APPENDIX F: SOIL TEXTURE

Table 28. Texture classifications from physical observations of texture and particle size analysis

using mid-infrared reflectance (MIR) spectroscopy (Rayment and Lyons, 2011, p. 80)

Pivot# Depth (cm) Visual texture class Sand (%) Silt (%) Clay (%) MIR texture class 01-S1 0-10 3.5 59 7.7 33.3 Sandy clay loam 20-30 3.5 56.3 7 36.7 Sandy clay 01-S2 0-10 3 59.6 10.7 29.7 Sandy clay loam 20-30 3 57.8 7.6 34.6 Sandy clay loam 01-S3 0-10 3.5 57.9 13.8 28.3 Sandy clay loam 20-30 3.5 57.2 7 35.8 Sandy clay 02-S1 0-10 3.5 65.1 7.3 27.6 Sandy clay loam 20-30 3.5 57.4 6 36.6 Sandy clay 02-S2 0-10 3.5 58.4 13.3 28.3 Sandy clay loam 20-30 3.5 55.8 7.6 36.6 Sandy clay 02-S3 0-10 3.5 60.5 10.3 29.2 Sandy clay loam 20-30 3.5 66.7 7.5 25.8 Sandy clay loam 03-S1 0-10 3 63.4 7.8 28.8 Sandy clay loam 20-30 3 56.7 6.9 36.4 Sandy clay 03-S2 0-10 3 60.7 11.7 27.6 Sandy clay loam 20-30 3.5 61.7 8.7 29.6 Sandy clay loam 03-S3 0-10 3 66.4 7.2 26.4 Sandy clay loam 20-30 3.5 61.8 8.8 29.4 Sandy clay loam 04-S1 0-10 3.5 62.3 9.4 28.3 Sandy clay loam 20-30 3.5 54 6.8 39.2 Sandy clay 04-S2 0-10 3 59.2 9.6 31.2 Sandy clay loam 20-30 3 58.5 5.3 36.2 Sandy clay 04-S3 0-10 3.5 55 12.5 32.5 Sandy clay loam 20-30 3.5 60.9 8 31.1 Sandy clay loam 05-S1 0-10 3 66.8 12 21.2 Sandy clay loam 20-30 3 61.6 10.7 27.7 Sandy clay loam 05-S2 0-10 3 70.4 12.4 17.2 Sandy loam 20-30 3 71.8 5.8 22.4 Sandy clay loam 05-S3 0-10 3 65.7 15.2 19.1 Sandy loam 20-30 3.5 69.2 9 21.8 Sandy clay loam 06-S1 0-10 3.5 65.4 10 24.6 Sandy clay loam 20-30 3 62.3 6.5 31.2 Sandy clay loam 06-S2 0-10 3 63.2 9 27.8 Sandy clay loam 20-30 3.5 70.4 7.1 22.5 Sandy clay loam 06-S3 0-10 3 61.1 15 23.9 Sandy clay loam 20-30 3 64.8 7.2 28 Sandy clay loam 07-S1 0-10 3.5 71.5 10.9 17.6 Sandy loam 20-30 3.5 62.1 5.7 32.2 Sandy clay loam 07-S2 0-10 3.5 66.9 10.8 22.3 Sandy clay loam 20-30 3.5 68.5 7.7 23.8 Sandy clay loam 07-S3 0-10 3.5 66.9 9.7 23.4 Sandy clay loam 20-30 3 66.4 7.8 25.8 Sandy clay loam 08-S1 0-10 3.5 66.5 9.7 23.8 Sandy clay loam 20-30 3.5 65.3 4.9 29.8 Sandy clay loam 08-S2 0-10 3.5 64.7 8.7 26.6 Sandy clay loam 20-30 3 61.7 6.6 31.7 Sandy clay loam 08-S3 0-10 3.5 62.7 8.6 28.7 Sandy clay loam 20-30 3 65.6 8.1 26.3 Sandy clay loam 09-S2 0-10 2.5 80 5.3 14.7 Sandy loam 20-30 2.5 68.5 9.6 21.9 Sandy clay loam 10-S1 0-10 3.5 58.2 12.2 29.6 Sandy clay loam 20-30 3 56.9 7.2 35.9 Sandy clay 10-S2 0-10 3 67.2 8.4 24.4 Sandy clay loam 20-30 3 62.2 6.2 31.6 Sandy clay loam 10-S3 0-10 3.5 60.8 11.1 28.1 Sandy clay loam 20-30 3 62.7 9.1 28.2 Sandy clay loam 11-S1 0-10 3.5 68.4 4.9 26.7 Sandy clay loam 20-30 3.5 70 11.2 18.8 Sandy loam 11-S2 0-10 3.5 58.7 12.3 29 Sandy clay loam 20-30 3.5 63.2 7.9 28.9 Sandy clay loam 11-S3 0-10 3.5 61.6 12.1 26.3 Sandy clay loam 20-30 3.5 64.4 10.7 24.9 Sandy clay loam 12-S2 0-10 3 60.6 8.5 30.9 Sandy clay loam 20-30 3 59.2 5.7 35.1 Sandy clay Visual texture classes: sand (1.0), loamy sand (1.5), loam (2.0), clay loam (2.5), Clay (3.0) and heavy clay (3.5).


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IRRIGATION WATER QUALITY AND RISK FOR CLAY DISPERSION

According to the water quality guidelines of the California Fertilizer Association

(1995), the risk for clay dispersion in soils containing ≥ 30 % clay (as is the case at the

HAP) is reasonably low at this stage (Table 29). Thus, by using slightly brackish irrigation

water (EC = 0.99 dS/m, SAR = 0.99, TDS = 580 mg/L), the risk of causing clay dispersion

in sandy clay loam soils dominated by kaolinite should be relatively low as compared

with soils more finely-textured (i.e., greater clay content) and dominated by smectites.

Table 29. Water quality guidelines for risk of dispersion, crusting and swelling of soils with > 30

% swelling clay (California Fertilizer Association, 1995). The location of the HAP in this

framework is indicated by the highlighted row.

SAR Electrical

conductivity (dS/m) Total dissolved solids (mg/L)

*Risk

0-3 < 0.2 < 128 Very High 0.2-0.7 128-428 Moderate > 0.7 > 428 Low 3-6 < 0.3 < 192 Very High 0.3-1.2 192-768 Moderate > 1.2 > 768 Low 6-12 < 0.5 < 320 Very High 1.9-0.5 320 - 1216 Moderate > 1.9 > 1216 Low 12-20 < 1.3 < 832 Very High 2.9 - 1.3 832 - 1856 Moderate > 2.9 832-1856 Moderate 20-40 < 2.9 < 1856 Very High 2.9 - 5.0 1856 - 3200 Moderate > 5.0 > 3200 Low *Risk of dispersion, swelling, and crusting applies especially to soils with more than 30 % clay: clay loam, silty clay loam, sandy clay loam, or silty clay textural classes.

CALCULATING THE SODIUM ADSORPTION RATIO

The tendency of water to replace adsorbed calcium and magnesium with sodium

can be expressed by the sodium adsorption ratio (SAR; Gupta, 2011):

SAR =(Na+)

√[(Ca2+)+(Mg2+)]

2

[13]

where, Na+, Ca2+ and Mg2+ are concentrations expressed in meq/L of sodium,

calcium and magnesium ions.


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To convert a concentration in mg/L to meq/L, divide the concentration by the

equivalent weight (g/eq or mg/meq) of the substance. The equivalent weight of a

substance is equal to its atomic weight (g/mol) divided by its valence or ionic charge

(Vesilind et al., 2010, p. 296).

i. Na (meq/L) = 43 mg/L / 22.99 mg/meq = 1.87 meq/L

ii. Ca (meq/L) = 61 mg/L / 20.04 mg/meq = 3.04 meq/L

iii. Mg (meq/L) = 50 mg/L / 12.15 mg/meq = 4.12 meq/L

Therefore, from equation [12] the SAR of the fertigation mixture is equal to 0.99.


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APPENDIX G: FUTURE SOIL AND LEAF MONITORING

RECOMMENDATIONS

Routine monitoring for soil and plants is required to ensure that irrigation over

the next 20 years does not adversely affect soil quality and pasture productivity at the

HAP, including the conditions for rehabilitation after decommissioning. To date, the

sampling program has provided invaluable baseline information for soil properties and

has identified potential issues that could emerge in the future. However, as considerable

labour is involved, an efficient and a cost-effective method of sampling (e.g., minimal

sampling intensity) is desirable (Colwell, 1971) to detect significant changes as earlier

as possible.

Based on the magnitude of change and consistency of trends, the frequency and

intensity (sample size) of soil and leaf tissue sampling can be revised as a biannual,

stratified regime rather than a quarterly, systematic regime. These options are discussed.

SAMPLING FREQUENCY – TEMPORAL VARIABILITY

Sampling intervals may vary from several months to several years depending on

the purpose of monitoring. At the HAP, it is critical that any possible impacts as a result

of irrigation are identified and appropriately managed. Time trends have shown that

increased alkalinity and sodicity could become a problem for pasture growth and long-

term productivity due in part to their effects on nutrient availability and soil physical

condition. Monitoring should thus provide sufficient information for decision-makers to

identify any adverse trends to evaluate adequately the level of risk (Supervision of

Financial Institutions, 2007). This will in turn provide timely and effective management

responses for preventing threshold limits from being reached or exceeded.

Despite significant increases in soil pH and ESP, the rate at which these soil

properties change will likely slow down due to system equilibration. Therefore,

problems such as nutrient deficiencies/toxicities and soil dispersion are unlikely to arise

suddenly and unnoticed. For instance, alkalinisation is occurring at a slower rate at depth

than at the soil surface; therefore, it is possible to reduce the sampling frequency at this

stage, particularly for the subsoil. Other soil properties, such as EC, CCE, N, P, PRI,

exchangeable cations and ECEC, showed reasonably constant and/or consistent patterns

and hence increasing the sampling interval should not compromise the decision-makers’


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ability to discern temporal changes. However, current variability in leaf composition has

made it difficult to accurately discern real trends from random noise due to patterns of

'rise and fall' (e.g. P and Cd, concentrations). This may perhaps be explicable by seasonal

variation and/or natural variation in the physiological age of the plants being sampled,

because the nutritional status in plants may differ substantially at different stages of

growth (Hochmuth et al., 2012), including soil processes at that point in time (Vitosh et

al., 1995). Thus, to minimise error, it is crucial that soil and plant sampling is conducted

in a standardised manner - e.g., sampling technique and sampling period within growth

cycle.

With distinct summer wet and winter dry seasons, rainfall generally occurs

between December and March (Figure 68). However, the overall low rainfall in this

region is unlikely to significantly affect soil properties and plant nutrition compared to

continuous irrigation with added nutrients. This is consistent with time trends which

show no noticeable influence of rainfall on both soil properties and leaf composition over

the 15 month study period. However, heavy rainfall events from cyclones that pass

inland from the Pilbara coast could strongly influence soil and plant condition by causing

erosion, waterlogging, anaerobicity and reduced nutrient availability due to leaching

(Gornall et al., 2010).

Generally, soil properties in July appeared to be relatively inconsistent or ‘out of

place’ from current data set (e.g., soil properties such as EC, CCE, total N, C/N ratio and

ESP). Considering that July is typical of low temperatures and low rainfall, this may

coincide with such trends in soil properties (Figure 68).

Figure 68. Mean monthly rainfall and temperature at Wittenoom in the Pilbara region, Western

Australia

0

5

10

15

20

25

30

35

40

45

50

0

20

40

60

80

100

120

140

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Tem

per

atu

re (

oC

)

Rai

nfa

ll (m

m)


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In arid and semi-arid regions, abiotic factors such as temperature could have a

greater influence on irrigated pasture (e.g., evapotranspiration) than rainfall. Soil and

leaf tissue sampling should then occur in months with similar temperature ranges to

minimise error due to variations in temperature and evapotranspiration. For example,

biannual sampling of soil and plants in March and September, or April and October,

minimises effects of temperature on pasture growth and avoids months where heavy

rainfall and flooding events are likely to occur – this is usually between mid-December

and April (Bureau of Meteorology, 2014b). Therefore, as long as soil and leaf samples are

collected in a standardised way, this should reduce error attributed to temporal

variability.

By and large, a reduced soil and plant sampling regime from every 3 months

(quarterly) to every 6 months (biannually) is possible. Since alkalinisation is occurring

slowly in the subsoil, sampling at 20-30 cm may even occur once a year. In doing so,

information can be efficiently obtained. Where temporal changes are likely to occur less

gradually through time, routine monitoring thereafter may be generally reduced to

annual sampling as equilibrium becomes established. Nonetheless, further evaluation of

2014 monitoring data will be required.

SAMPLE SIZE – SPATIAL VARIABILITY

In general, the study site has low spatial variability since irrigation water quality

and soil type (i.e., sandy clay loam) are relatively homogenous (Kristiansen et al., 2010).

The variability among irrigation pivots, in terms of soil characteristics, provides a basis

for estimating desirable sampling intensities (Colwell, 1971). Given that most soil

properties and leaf nutrient parameters showed relatively little variation among

irrigation pivots, it is also possible to reduce the sampling intensity at the HAP.

Note seven irrigation pivots are no longer active (i.e., Pivots 9, and Pivots 12-17)

and therefore do not require monitoring. Pivots 12, 14, and 16 were non-operational

throughout the study, while Pivots 9, 15 and 17 ceased hay production after a certain

period of time (i.e., in October 2013, May 2013, and May 2013, respectively).

Reduced sampling intensity can be achieved by means of stratified sampling in

lieu of the current systematic procedure. Stratification improves the efficiency of

obtaining data (Mäkipää et al., 2012) while requiring fewer areas (irrigation pivots) for


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monitoring that would still provide the same degree of representation. In the stratified

area, systematic sampling should be conducted to ensure good representation.

Cluster analysis was employed to stratify the remaining known irrigation pivots

(Pivots 1-8, 10 and 11) by their soil characteristics (see Appendix D). Results show that

Pivots 2 and 3, Pivots 6, 7 and 11, and Pivots 8 and 10 shared a high degree of similarity

in terms of EC, CCE, C/N ratio, exchangeable Al percentage, As concentration and clay

content. Consequently, monitoring may cease in, for example, Pivots 3, 7, 10 and 11 while

leaving the remaining six (Pivots 1, 2, 4, 5, 6 and 8) to be routinely monitored. However,

note cluster analysis cannot guarantee absolute similarity since: (1) results depend on

the variables used (i.e., soil properties), (2) soil properties change over time and with

irrigation, (2) results are only as accurate as the data provided, and (3) random error

due to variability. Nonetheless, cluster analysis provides an effective method for

decision-makers to determine if stratified monitoring is practicable.

SOIL SAMPLING DEPTH

Differences in the magnitude of spatial variability also occur with soil depth

(Lawrence et al., 2013). As there are distinct changes and trends in soil properties at the

0-10 cm and 20-30 cm soil layers (e.g., pH and ESP), it is essential that soil be continually

monitored at 0-10 cm and 20-30 cm.


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APPENDIX H: CHANGES WITH TIME OF EXCHANGEABLE

SODIUM PERCENTAGE (ESP) AND SODICITY OF HAMERSLEY

AGRICULTURE PROJECT SOILS

By Sunil Samaraweera

Soil testing during the last 18 months has indicates that there is a steady increase in the

exchangeable sodium percentage (ESP) of the Hamersley Agriculture Project area; and

there is a tendency for the soil under irrigation to become sodic (ESP >6) and the HAP

soil in the long term may need amelioration (see Figure 69).

Figure 69. Trends in mean exchangeable sodium percentage (ESP,% ± SEM) at

two depths (0-10 cm and 20-30 cm)of the soil profile of the HAP area.

However, these determinations of ESP by the CSBP laboratory have been carried out

employing method 15A1 (Rayment and Lyons, 2011) and does not include the removal

of soluble salts prior to determination of the exchangeable cations. As such, ESP values

obtained by this method tend to overestimate the Na concentrations in the cation

exchange complex. Therefore, the impact of irrigation on soil sodicity was examined by

determining the Na concentrations in the cation complex by employing two methods: 15

A1 that does not include pre-treatment of soluble salts; and 15C1 that includes pre-

treatment for soluble salts (by washing with 60% aqueous ethanol and 20% aqueous

glycerol).

A total of 28 samples collected from 7 locations at 2 depths from HAP area were analysed

and the results are summarised in Figures 70 and 71. It can be seen that washing with

0

1

2

3

4

5

6

7

8

9

Baseline Mar-13 Jul-13 Sep-13 Dec-13 Mar-14

Exch

ange

able

Na

(%)

0-10 cm

20-30 cm


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aqueous ethanol and aqueous glycerol has removed the soluble salt in the soil and the

exchangeable sodium concentrations in most samples were below the detection limit (<

0.1 meq/100g of soil).

Figure 70. Mean (± SEM) of exchangeable Na (meq/100g of soil) of a total of

28 soil samples taken at two depths, 0-10 cm (14 samples) and 20-30 cm (14

samples).

Figure 71. Mean (± SEM) of exchangeable sodium percentage (ESP) of a total

of 28 soil samples taken at 0-10 cm (14 samples) and 20-30 cm (14 samples).

Conclusion

It can be concluded that:

1. addition of irrigation water has not caused a measurable change in the sodicity of the HAP soils;

0

0.1

0.2

0.3

0.4

0.5

0.6

Without pre-wash With pre-wash

Exc.

Na

(me

q/1

00

g)

0 - 10 cm

20 - 30 cm

0

1

2

3

4

5

6

7

8

Without pre-wash With pre-wash

ESP

(%

)

0 - 10 cm

20 - 30 cm


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2. the method currently employed by the CSBP laboratory tends to overestimate the Na concentrations (and hence the ESP) in the cation exchange complex;

3. almost all the sodium in the soil are as soluble Na+ and not found in the cation exchange complex; and

4. determination of ESP in the soils samples in future should be carried out by employing methods that include pre-treatment for soluble salts.

Reference

RAYMENT, G. E. & LYONS, D. J. 2011. Soil Chemical Methods – Australasia, Victoria, CSIRO

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