Influence of surface runoff on episodic recharge of groundwater in the wheatbelt of Western Australia

 

 

Kai Kinkela

Supervisor: Dr. Neil Coles

School of Environmental Systems Engineering,

University of Western Australia

October 2009

   

Abstract Widespread land clearing of native vegetation has resulted in rising groundwater levels and increased

salinisation throughout the agricultural region of Western Australia. Localised management practices

to reduce the spread of salinity are aimed at reducing groundwater recharge, mainly through

revegetation. An understanding of groundwater recharge processes in the wheatbelt is required to

optimise salinity management strategies. Some sites show evidence of recharge being ‘event driven’

rather than occurring as steady ‘inflow’ during the year. It is hypothesised that this irregular episodic

recharge is a result of large rainfall events causing increased runoff and surface water ponding. If this

is the case, recharge management should be focussed towards managing these episodic recharge

events. Alternatively, if recharge is substantially generated by surface runoff collecting in the lower

landscape, then reduced rainfall as a result of climate variability will result in a disproportionate

decrease in recharge and a diminished risk of salinity.

This study examined long-term groundwater monitoring records from two sites in the Western

Australian wheatbelt. The catchments in Cuballing and East Perenjori vary in rainfall regimes,

landscape geomorphology and underlying geological structures. Both catchments have a network of

observation bores and piezometers, monitored for continuous changes in groundwater level by

capacitance probes. The water level data used for this study extended over an eleven year period.

Piezometric heads were adjusted to remove the influence of barometric pressure. Groundwater

recharge processes were characterised based on local topography, rainfall patterns and field

observations. A water balance approach was used to quantify the recharge components of in situ

infiltration, lateral throughflow and surface water ponding.

Recharge in the two catchments was event-driven but governed by different recharge mechanisms.

The Cuballing catchment experienced downslope seasonal saturation from hillside seepage and

surface runoff. Saturation and surface runoff in the East Perenjori site was episodic but contributed to

significant recharge in all areas of the catchment. Quantifying the role of surface runoff in recharge

processes was limited by a lack of shallow groundwater and surface water monitoring in each of the

catchments.

   

‐ ii ‐ 

List of Acronyms AARR Accumulative Annual Residual Rainfall

AHD Australian Height Datum

AMRR Accumulative Monthly Residual Rainfall

ARI Annual Recurrence Interval

BE Barometric Efficiency

BoM Bureau of Meterology

CSIRO Commonwealth Scientific and Industrial Research Organisation

DAFWA Department of Agriculture and Food Western Australia

DEM Digital Elevation Model

DoW Department of Water

HARTT Hydrograph Analysis: Rainfall and Time Trends

IFD Intensity-Frequency-Duration

MSLP Mean Sea Level Pressure

WA Western Australia

   

‐ iii ‐ 

Acknowledgements First and foremost I would like to thank Neil for all the time and effort you spent guiding and advising

me along every step of the journey. I’m grateful for the patience you showed in keeping me on track

and helping me put together a meaningful story from the results. Thanks for always managing to find

time to sit down with me and sort out the many issues that came up.

I’d also like to thank everyone from the Centre for Ecohydrology for all their input throughout the

course of the project. In particular I’d like to acknowledge David Stanton, Ben Cohen, James

Newman, Tim Pope, Karen Holmes and Chun Baek for always being available to help me out. I

appreciate the willingness you have all shown to advise me in any capacity that I’ve needed.

I would like to acknowledge the advice from the following people regarding the barometric pressure

correction part of this study – Professor Todd Rasmussen (University of Georgia), Michael Smith

(Department of Agriculture and Food Western Australia) and Nick Cox (Department of Water).

I also acknowledge and thank MWH for awarding me the inaugural MWH Undergraduate Scholarship

in Hydrogeology. This award was a great honour for me personally and funded the field work

associated with this study.

Finally I’d like to thank everyone at the School of Environmental Systems Engineering for making

my time here a positive experience and one that I will look back on fondly in years to come. Thanks

to all my fellow students for putting up with me over this past year and I wish everyone the best of

luck for the future.

‐ iv ‐ 

Table of Contents

 1  Introduction .................................................................................................................................... 1 

2  Background ..................................................................................................................................... 2 

2.1  Dryland Salinity ....................................................................................................................... 2 

2.2  Wheatbelt Landscapes ............................................................................................................ 2 

2.2.1  Zone of Rejuvenated Drainage ........................................................................................ 3 

2.2.2  Zone of Ancient Drainage................................................................................................ 3 

2.3  Groundwater Recharge Processes .......................................................................................... 4 

2.3.1  Matrix Flow ..................................................................................................................... 4 

2.3.2  Preferential Flow ............................................................................................................. 5 

2.4  Groundwater Recharge Models .............................................................................................. 6 

2.4.1  Hillslope Model ............................................................................................................... 6 

2.4.2  Valley Floor Model .......................................................................................................... 8 

2.5  Episodic Recharge ................................................................................................................... 8 

2.6  Climate Variability Implications .............................................................................................. 9 

2.7  Effect of Barometric Pressure on Bore Water Levels ........................................................... 10 

3  Site Background ............................................................................................................................ 11 

3.1  Cuballing ................................................................................................................................ 11 

3.2  East Perenjori ........................................................................................................................ 14 

4  Methodology ................................................................................................................................. 18 

4.1  Field Data Collection ............................................................................................................. 18 

4.1.1  Groundwater Data ........................................................................................................ 18 

4.1.2  Rainfall Data .................................................................................................................. 19 

4.1.3  Bore Hydraulic Conductivity ......................................................................................... 20 

4.2  Field Data Conversion and Calibration .................................................................................. 21 

4.2.1  Converting Capacitance Data to Groundwater Levels .................................................. 21 

4.2.2  Calibrating and Verifying Groundwater Levels ............................................................. 22 

4.2.3  Calculating Bore Hydraulic Conductivity ....................................................................... 24 

4.3  Barometric Pressure Correction ........................................................................................... 25 

4.3.1  Barometric Pressure Data ............................................................................................. 25 

4.3.2  Barometric Efficiency Method ...................................................................................... 26 

4.3.3  Multiple Regression Method ........................................................................................ 27 

‐ v ‐ 

4.4  Rainfall Analysis..................................................................................................................... 29 

4.4.1  Rainfall Data .................................................................................................................. 29 

4.4.2  Identifying Significant Rainfall Events ........................................................................... 30 

4.5  Catchment Delineation and Groundwater Contours ............................................................ 30 

4.6  HARTT .................................................................................................................................... 31 

4.7  Water Balance ....................................................................................................................... 32 

4.7.1  Storage Term ................................................................................................................. 33 

4.7.2  Leakage Term ................................................................................................................ 34 

4.7.3  Throughflow Term ........................................................................................................ 35 

5  Results ........................................................................................................................................... 36 

5.1  Site Characterisation ............................................................................................................. 36 

5.2  Barometric Pressure Correction ........................................................................................... 37 

5.3  Rainfall .................................................................................................................................. 44 

5.3.1  Cuballing ........................................................................................................................ 44 

5.3.2  East Perenjori ................................................................................................................ 46 

5.4  Groundwater Recharge in Cuballing ..................................................................................... 48 

5.4.1  Seasonal Recharge ........................................................................................................ 48 

5.4.2  Shallow Aquifer Response ............................................................................................. 49 

5.4.3  High Intensity Events..................................................................................................... 50 

5.4.4  Low Intensity Events ..................................................................................................... 51 

5.4.5  Episodic Recharge ......................................................................................................... 51 

5.5  Groundwater Recharge in East Perenjori ............................................................................. 52 

5.5.1  Seasonal Response ........................................................................................................ 53 

5.5.2  High Intensity Events..................................................................................................... 53 

5.5.3  Episodic Recharge ......................................................................................................... 54 

5.6  Hydraulic Conductivity .......................................................................................................... 56 

5.7  HARTT .................................................................................................................................... 56 

5.8  Water Balance ....................................................................................................................... 57 

6  Discussion...................................................................................................................................... 59 

6.1  Barometric Pressure Correction ........................................................................................... 59 

6.2  Groundwater Recharge in Cuballing ..................................................................................... 60 

6.2.1  Shallow Aquifer ............................................................................................................. 60 

6.2.2  Deep Aquifers ................................................................................................................ 63 

6.3  Groundwater Recharge in East Perenjori ............................................................................. 64 

‐ vi ‐ 

6.3.1  Upslope Bores ............................................................................................................... 64 

6.3.2  Lower Valley Bores ........................................................................................................ 65 

6.4  Quantifying Recharge via a Simple Water Balance ............................................................... 65 

7  Conclusions ................................................................................................................................... 67 

8  Recommendations ........................................................................................................................ 68 

9  References .................................................................................................................................... 69 

 

Appendix A – Groundwater Hydrographs 

Appendix B – Maximum Response Times 

Appendix C – Bail‐Down Plots 

Appendix D – IFD Curves 

   

‐ vii ‐ 

List of Tables Table 1 Depths of bores in the Cuballing catchment ............................................................................ 13 Table 2 Depths of bores in the East Perenjori catchment .................................................................... 16 Table 3 Details of BoM MSLP monitoring stations ............................................................................... 25 Table 4 Dates and periods of no data for the rain gauge in East Perenjori .......................................... 29 Table 5 Barometric efficiency for the nested bores in Cuballing .......................................................... 38 Table 6 Magnitude and duration of rainfall events greater than a 1 year ARI from the Cuballing rain gauge ..................................................................................................................................................... 45 Table 7 Magnitude and duration of rainfall events greater than a 1 year ARI captured by the Perenjori rain gauge .............................................................................................................................. 47 Table 8 Rainfall events that caused quick responses in Cuballing 5B ................................................... 50 Table 9 Hydraulic conductivities calculated using bail‐down tests for selected bores in the Cuballing catchment ............................................................................................................................................. 56 Table 10 Results of HARTT analysis for Cuballing bores ....................................................................... 57 Table 11 Results of HARTT analysis for East Perenjori bores ................................................................ 57 Table 12 Results of water balance for unconfined aquifer in Cuballing ............................................... 58 Table 13 Results of water balance for semi‐confined aquifer in Cuballing .......................................... 58 

List of Figures Figure 1 Locations of the zone of rejuvenated drainage and the zone of ancient drainage (Commander et al. 2001) ........................................................................................................................ 3 Figure 2 Geological features of a wheatbelt valley in the zone of ancient drainage (Commander et al. 2001) ....................................................................................................................................................... 4 Figure 3 Infiltration model showing spatial distribution of infiltration during matrix flow (Peranginangin 2002) .............................................................................................................................. 5 Figure 4 Infiltration model showing spatial distribution of infiltration during matrix flow (Peranginangin 2002) .............................................................................................................................. 6 Figure 5 Flow routes followed by subsurface runoff on hillslopes (Atkinson 1978)............................... 7 Figure 6 Local geomorphology causing hillslope seepage (adapted from George, McFarlane & Nulsen 1997) ....................................................................................................................................................... 7 Figure 7 Study site locations with the agricultural region indicated in green ...................................... 11 Figure 8 Map of the Cuballing catchment showing bore locations and extent of clearing .................. 12 Figure 9 Composite water level map showing the eastern shallow system (1), the unconfined‐semiconfined system (2) and the confined system (3) (Salama et al. 1993b) ...................................... 14 Figure 10 Map of East Perenjori catchment showing bore locations and extent of clearing ............... 15 Figure 11 Hydrogeological east‐west cross section of the East Perenjori catchment showing the main groundwater systems (adapted from Henschke 1989) ........................................................................ 17 Figure 12 Scott Parsons Electronics capacitance probe (left), data logger (centre) and electrical connection (right) (Scott Parsons Electronics n.d.) ............................................................................... 18 Figure 13 Capacitance probe being cleaned. ........................................................................................ 19 Figure 14 Tipping bucket rain gauge with the collector attached (left) and without collector showing the tipping buckets (right). ................................................................................................................... 20 

‐ viii ‐ 

Figure 15 Measuring the hydraulic conductivity by a bail‐down test in bore 5C at Cuballing. ............ 21 Figure 16 Hydrograph for Cuballing 5C showing physically unrealistic fluctuations, beginning in mid‐November 2005 .................................................................................................................................... 23 Figure 17 Hydrograph for Cuballing 5B showing the difference between the manually measured water levels (red) and the continuous levels (blue) ............................................................................. 23 Figure 18 Step response function for East Perenjori bore 8C with a maximum response time of 18 hours ..................................................................................................................................................... 28 Figure 19 Nested bore water balance components .............................................................................. 32 Figure 20 DEM with overlayed groundwater contours for the Cuballing catchment .......................... 36 Figure 21 DEM with overlayed groundwater contours for the East Perenjori catchment ................... 37 Figure 22 Plot of barometric pressure (green) and groundwater levels (blue) in Cuballing bore 5A for a three month period in 2004 ............................................................................................................... 38 Figure 23 Plot of barometric pressure (green) and groundwater levels (blue) in Cuballing bore 5B in February 2007 ....................................................................................................................................... 39 Figure 24 Plot of barometric pressure (green) and piezometric heads (blue) in Cuballing bore 8C for a three month period in 2002 .................................................................................................................. 41 Figure 25 Plot of measured piezometric head (blue) against heads corrected for barometric pressure fluctuations (red) using the multiple regression technique in Cuballing bore 8C for a three month period in 2002 ....................................................................................................................................... 41 Figure 26 Plot of barometric pressure (green) and piezometric heads (blue) in East Perenjori bore 9C for a three month period in 2007 ......................................................................................................... 43 Figure 27 Plot of measured piezometric head (blue) against heads corrected for barometric pressure fluctuations (red) using the multiple regression technique in East Perenjori bore 9C for a three month period in 2007 ........................................................................................................................... 43 Figure 28 Observed annual rainfall compared to the long‐term average annual rainfall in Cuballing 44 Figure 29 Measured average monthly rainfall compared to the long‐term monthly average rainfall in Cuballing ............................................................................................................................................... 45 Figure 30 Annual rainfall in 1998 to 2008 compared to the long‐term average annual rainfall in East Perenjori ................................................................................................................................................ 46 Figure 31 Average monthly rainfall during the study period compared to the long‐term monthly average rainfall in East Perenjori .......................................................................................................... 47 Figure 32 Seasonal groundwater fluctuations of Cuballing bores 5B and 5C over the 11 years of record .................................................................................................................................................... 48 Figure 33 Rapid water table response of Cuballing 5B to a 5 min, 10 year ARI event in March and a 3 hour, <1 year ARI event in May 1998 ................................................................................................... 49 Figure 34 Groundwater response of Cuballing bores 7C and 8C to a 1 hour, 100 year ARI event in April 2003 .............................................................................................................................................. 50 Figure 35 Groundwater response of Cuballing bores 5B, 5C and 7C to a 72 hour, 5 year ARI event in August 1998 .......................................................................................................................................... 51 Figure 36 Groundwater response of Cuballing bores 7C and 8C to 129mm of monthly rainfall in January 2000 ......................................................................................................................................... 52 Figure 37 Seasonal groundwater fluctuations of East Perenjori bores 8B, 8C and 7C over the 11 years of record ................................................................................................................................................ 53 Figure 38 Groundwater response of East Perenjori bores EPC1, 7C and 20C to a 1 hour, 100 year ARI event in February 2004 ......................................................................................................................... 54 

‐ ix ‐ 

‐ x ‐ 

Figure 39 Groundwater response of East Perenjori bores 8A, EPC1 and 9C to a 125mm over 3 days in May 1999 .............................................................................................................................................. 55 Figure 40 Hydrographs of East Perenjori bores 9C and 20C for 1998 to 2008 ..................................... 56 Figure 41 Phases of groundwater response in the intermediate observation bore Cuballing 5B from April 1998 to March 1999 ..................................................................................................................... 61 Figure 42 Hillside seepage in Cuballing occurring upslope of the nested bore site (September 2009)62 

 

Introduction 

1 INTRODUCTION Dryland salinity is the foremost cause of land degradation in the agricultural region of Western

Australia. Land cleared for agriculture has changed the hydrological water balance and led to

increased groundwater recharge. Rising water tables transport dissolved salt to the surface and inhibit

vegetation growth (Salama, Otto & Fitzpatrick 1999). Localised management practices aim to stop the

spread of salinity by reducing groundwater recharge.

A greater understanding of groundwater recharge mechanisms will improve the effectiveness of

management strategies. Previous research has shown that groundwater in the wheatbelt rises

‘episodically’ in response to irregular rainfall events rather than linearly over time (Lewis &

McConnell 1998; Nulsen et al. 1998; Speed & Kendle 2008). It is hypothesised that these significant

episodic recharge events are due to surface water runoff and ponding in downslope areas of a

catchment. If this is the case, managing surface runoff could substantially reduce groundwater

recharge and hence the spread of salinity.

This study aims to investigate the role of surface runoff on episodic recharge in two wheatbelt

catchments. The catchments in Cuballing and East Perenjori are representative of the differing

landscapes in the wheatbelt due to variations in rainfall regimes, topography and underlying geology.

Long-term groundwater hydrographs were analysed in relation to rainfall, catchment characteristics

and field observations. A water balance approach was used to determine whether the dominant

recharge mechanism for each catchment was in situ rainfall infiltration, subsurface throughflow or

surface runoff.

Future management strategies aimed at reducing the spread of salinity will be influenced by changing

rainfall patterns. Predictions for reduced rainfall will cause disproportionately larger declines in

surface runoff (Bari et al. 2005). If surface runoff is found to be a significant component of

groundwater recharge in typical wheatbelt landscapes, this will need to be considered when adopting

salinity management strategies.

 

‐ 1 ‐ 

Background 

2 BACKGROUND

2.1 Dryland Salinity

Dryland salinity is the accumulation of salts to levels that inhibit plant growth due to human activities

in non-irrigated landscapes (Pannell & Ewing 2006). The National Land and Water Resources Audit

(2001) estimates that 16% (4.4 million hectares) of the south-west region of Western Australia (WA)

has a high potential for developing salinity from shallow water tables with that figure predicted to rise

to 33% by 2050. The majority of salinised land in WA is concentrated in the wheatbelt region with

over 1.8 million hectares currently salt-affected (Hatton, Ruprecht & George 2003). Salinity is

particularly prevalent in the wheatbelt due to the extensive agricultural activity in the region.

Dryland salinity in the agricultural region of WA is a result of widespread clearing of native

vegetation for agricultural development. Perennial native forests and woodlands were replaced with

annual crops and pastures altering the hydrological balance (Farrington & Salama 1996). The non-

native vegetation consumes less water leading to increased groundwater recharge and rising water

tables. The rising groundwater mobilises salts stored within the regolith and, depending on geology,

soils and landscape, can cause the water table to rise. When groundwater rises to within the root zone

of salt intolerant agricultural crops, the land is considered saline (Rengasamy 2006).

Current management options aimed at preventing the spread of salinity attempt to restore the pre-

clearing water balance. Revegetation of cleared landscapes with deep-rooted perennials has been

shown to lower water tables but the extent of land required is prohibitively large for agricultural

production (Clarke et al. 2002; Pannell & Ewing 2006). Shallow and deep drains can reduce

groundwater recharge (Ali et al. 2004) but the safe disposal of saline water is a significant obstacle

(Pannell & Ewing 2006). Adapting agricultural practices to incorporate deep-rooted vegetation can be

achieved using alley farming although this is only effective for certain crop types (Hatton & Nulsen

1999). Reducing groundwater recharge is essential to salinity management.

2.2 Wheatbelt Landscapes

Drainage systems in the wheatbelt have been defined according to landscape, soil type and geology.

Two distinct drainage zones are the zone of rejuvenated drainage and the zone of ancient drainage,

pictured in Figure 1. The boundary between the two zones is defined by the Meckering Line (Mulcahy

& Bettenay 1972).

‐ 2 ‐ 

Background 

 

Figure 1 Locations of the zone of rejuvenated drainage and the zone of ancient drainage

(Commander et al. 2001)

2.2.1 Zone of Rejuvenated Drainage

The zone of rejuvenated drainage is typified by low hills and undulating landforms (Salama et al.

2003). The lateritic landscape is deeply incised by rivers and streams leading to thin soils over

exposed laterite (McFarlane & Williamson 2002). The gradients for this landscape tend to be in the

order of 1:100 to 1:500 (Dogramaci 2004). The main soil types are duplex sandy gravels, loamy

gravels and deep sands. The creeks and rivers in the zone of rejuvenated drainage do not necessarily

follow the course of ancient rivers and tend to flow every winter (Tille, Mathwin & George 2001).

The moderate slopes in the zone of rejuvenated drainage are crucial to groundwater recharge

processes.

2.2.2 Zone of Ancient Drainage

The zone of ancient drainage is characterised by low topographic gradients and broad valley floor

systems (Salama et al. 2003). The valley floors tend to be 2 to 10km wide and have low gradients in

the order of 1:500 to 1:1500. The valley floors are occupied by palaeochannels that rarely flow along

the entire drainage system due to reduced rainfall (Tille, Mathwin & George 2001). The valley slopes

are underlain by deep sandy and gravelly soils with valley floors tending to be infilled by alluvium

and colluvium (Nulsen et al. 1998). Saline lake chains have developed in the valley floors, shown in

Figure 2. The low gradients in the zone of ancient drainage control groundwater recharge processes.

Meckering Line

‐ 3 ‐ 

Background 

 

Figure 2 Geological features of a wheatbelt valley in the zone of ancient drainage (Commander

et al. 2001)

2.3 Groundwater Recharge Processes

Groundwater recharge is defined as “the entry into the saturated zone of water made available at the

water table surface” (Sophocleous 2004). Groundwater recharge is either direct or indirect. Direct

recharge is areally distributed recharge due to precipitation or irrigation whereas indirect recharge

occurs through the beds of surface water courses, ponding in topographic depressions or via

concentration in subsurface joints (de Vries & Simmers 2002; Sophocleous 2004; Scanlon et al.

2006). Recharge to groundwater aquifers is usually a combination of direct and indirect recharge via

diffuse percolation (matrix flow) or preferential flow (de Vries & Simmers 2002).

2.3.1 Matrix Flow

Soil water movement via matrix flow, also known as piston flow, occurs when water flows through a

homogenous soil profile (Hiscock 2005). In soil pores with diameters less than 3mm, gravity and

capillary forces between pores drives the process (Sophocleous 2004). Soil pores become filled with

water and the water flows downwards through interconnected pores (Fetter 1994). Figure 3 shows the

uniform wetting front associated with matrix flow. This process is slower than preferential flow and is

usually measured in metres per year (Seiler & Gat 2007). Previous studies have indicated that matrix

flow is evident in wheatbelt catchments. Engel, McFarlane & Street (1987) discovered that matrix

flow is the dominant process in highly permeable upper slope soils on a wheatbelt hillslope. Johnston

(1987) showed that matrix flow was contributing to recharge in some wheatbelt catchments, along

with macropore flow.

‐ 4 ‐ 

Background 

 

Figure 3 Infiltration model showing spatial distribution of infiltration during matrix flow

(Peranginangin 2002)

2.3.2 Preferential Flow

A much quicker form of soil water movement is preferential flow, also known as macropore flow.

Groundwater percolating through the regolith will preferentially follow paths of high permeability

such as macropores caused by cracks, worms and old root channels as well as geological

discontinuities (Petheram et al. 2002). The presence of macropores leads to an uneven wetting front,

demonstrated in Figure 4. Capillary action between pores is much weaker in macropores and the

process is dominated by viscous forces and gravity. Consequently, the velocity with which water

flows through preferential pathways is often orders of magnitude greater than matrix flow

(Sophocleous 2004). Flow through preferential pathways have been shown to cause significant

groundwater recharge in the wheatbelt (Nulsen & Henschke 1981) and can bypass aquitards leading

to deep drainage (Johnston 1987). In areas dominated by preferential flow paths, the temporal

variability of rainfall is the main determinant of groundwater recharge (Petheram et al. 2002).

‐ 5 ‐ 

Background 

 

Figure 4 Infiltration model showing spatial distribution of infiltration during matrix flow

(Peranginangin 2002)

2.4 Groundwater Recharge Models

2.4.1 Hillslope Model

Groundwater recharge on hillslopes is a combination of direct and indirect recharge via surface and

subsurface flow. Runoff is generated by intense rainfall leading to infiltration excess or sustained

rainfall causing saturation excess. Surface water is transported downslope over short distances

(typically less than a kilometre) before entering a surface storage, evaporating, infiltrating or

becoming stream flow (Tille, Mathwin & George 2001). Infiltration occurs over most of the landscape

and water percolates down to the water table via vertical and lateral movement (Figure 5).

Alternatively, sodic soils can restrict downward movement of water and promote surface runoff and

shallow groundwater movement downslope (Salama, Otto & Fitzpatrick 1999). Subsurface water

flow occurs via unsaturated flow in the surface soil layers and saturated flow below the water table

(Stolte, George & McFarlane 1999). Both are driven downslope by the topographic gradient of the

landscape. Local hydrogeological conditions can cause hillside seepage in downslope areas. These

discharge areas can be a result of groundwater being forced to the surface due to bedrock highs or due

to changes in soil type or gradient (George, McFarlane & Nulsen 1997), as shown in Figure 6.

Hydrological processes on hillslope landscapes like those found in the zone of rejuvenated drainage

are gradient driven localised systems.

‐ 6 ‐ 

Background 

 

Figure 5 Flow routes followed by subsurface runoff on hillslopes (Atkinson 1978)

 

Figure 6 Local geomorphology causing hillslope seepage (adapted from George, McFarlane &

Nulsen 1997)

‐ 7 ‐ 

Background 

2.4.2 Valley Floor Model

Indirect recharge in the broad valley floors of the zone of ancient drainage is driven by surface runoff

and ponding. Valley landscapes can be divided into two distinct hydrological units. The upper

catchment slopes are considered ‘shedding landscapes’ where runoff is generated. The valley floors

are classified as ‘receiving landscapes’ where low gradients promote runoff accumulation and

waterlogging (Coles et al. 2004). The low gradients of the valley floors reduce the ability for water to

be transmitted laterally in these landscapes. This makes the valley floors susceptible to water logging

and flooding (Hatton, Ruprecht & George 2003). Ponding occurs when rainfall and surface run-on

exceed the ability of the landscape to discharge water by vertical and horizontal drainage and

evapotranspiration (McFarlane & Williamson 2002). Direct valley floor recharge contributes more to

rising valley water tables than indirect recharge occurring on contributing hillopes (George, Bennet &

Speed 2004). Recharge in valley floor landscapes is a combination of direct recharge from rainfall and

indirect recharge from surface run-on and ponding.

2.5 Episodic Recharge

Some groundwater hydrographs in the wheatbelt of WA show evidence of recharge not occurring as

frequent inflows but rather in episodic, irregular event (Lewis & McConnell 1998; Speed & Kendle

2008). Episodic recharge is defined as recharge that occurs irregularly and infrequently (Lewis &

Walker 2002). This form of recharge is common in regions with irregular rainfall such as those

subject to tropical cyclones or intense spring and summer thunderstorms. In the semi-arid climate of

the wheatbelt, 60 to 70% of rainfall occurs between May and October (Anderson & Garlinge 2000),

although summer thunderstorms are common in the southern regions of the wheatbelt (Tille, Mathwin

& George 2001). Variability of rainfall increases as the mean annual rainfall decreases so the rainfall

regime of the wheatbelt favours episodic recharge (Lewis & Walker 2002).

Previous research into episodic recharge in the wheatbelt by Lewis (1998) and Lewis & Walker

(2002) used simplistic water balance modelling to predict the potential for episodic recharge. The

model utilised daily rainfall and evaporation data, soil types and rooting depths to simulate direct

episodic recharge. The modelling found that episodic recharge contributed the largest percentage of

recharge at the site with the lowest mean annual rainfall and greatest rainfall variability, whilst the

largest amount of episodic recharge was generated at the site with the highest annual rainfall (Lewis

1998). The results from Lewis & Walker (2002) showed that most significant episodic recharge

events occurred over a few days in winter although summer storms are also capable of producing

episodic recharge.

The modelling by Lewis (1998) and Lewis & Walker (2002) is acknowledged by the authors to be a

simplification of actual processes and should be considered qualitative and indicative. The model does

not take into account losses due to interception or runoff or the influence of preferred pathways in

‐ 8 ‐ 

Background 

groundwater recharge (Lewis & Walker 2002). The model only accounts for direct episodic recharge

whereas indirect recharge is considered to be the dominant process in semi-arid and arid environments

(Lerner, Issar & Simmars 1990).

2.6 Climate Variability Implications

Predictions for decreased mean annual rainfall and increased rainfall variability are likely to have

significant implications for future groundwater recharge. Since the mid 1970s, rainfall in the early

months of winter has declined by 17% in the south-west of WA (Hope, Timbal & Fawcett 2009). This

has been attributed to variations in global atmospheric circulation (Indian Ocean Climate Initiative

Panel 2007). It is arguable that a further decline has occurred since the late 1990s (Hope, Timbal &

Fawcett 2009) and rainfall records in some areas of the wheatbelt show evidence of declines since

2000 (Speed & Kendle 2008). As extensive groundwater monitoring networks were not in place prior

to 1970, the effects of the initial step-change could not be compared to long-term groundwater trends.

The more recent decrease in rainfall can give insights into the effect of future climate variability.

Analysis by George et al. (2008) showed that across the wheatbelt the number of bores with rising

trends and the rates of rise have declined since 2000. This is especially evident in the northern

wheatbelt region where groundwater levels are predominantly declining, irrespective of geology,

depth to groundwater or land management (Speed & Kendle 2008). In contrast, other regions of the

wheatbelt have not had the same degree of reduction, such as in the south-west where no obvious

change in trend is evident. It is suggested that as some catchments have not reached hydrological

equilibrium, they are less responsive to changing rainfall regimes (McFarlane & Ruprecht 2005;

George et al. 2008). The reduced winter rainfall since 2000 has decreased the rate of land salinisation

in the wheatbelt (McFarlane & Ruprecht 2005).

Further variations in the volume, intensity and spatial distribution of rainfall are expected to occur in

the future. Research by the Intergovernmental Panel on Climate Change predicts that annual rainfall

in the south-west of WA will be up to 15% less by 2020 and up to 80% less based on 1990 levels for a

range of scenarios. This will be coupled with increases in extreme daily rainfall, suggesting more

intense rainfall events (Hennessy et al. 2007).

The implications for groundwater recharge are twofold. Precipitation reductions could result in less

direct groundwater recharge and diminished risk of salinity (George, Clarke & English 2008).

Concurrently, indirect groundwater recharge via overland flow would decrease disproportionately to

rainfall reductions. Modelling by Bari et al. (2005) showed that for a predicted 11% decrease in

annual rainfall by 2050, streamflow would decrease by 31% in a drinking water catchment in south-

west WA. Conversely, the more frequent intense rainfall events are likely to cause episodic recharge,

particularly in downslope valley floor systems. The groundwater response to climate variability will

be catchment specific and dependent on catchment conditions such as topography, gradient and

‐ 9 ‐ 

Background 

‐ 10 ‐ 

vegetation cover and hydrogeological properties such as aquifer connectivity and groundwater lag

times between recharge and discharge (George, Clarke & English 2008).

2.7 Effect of Barometric Pressure on Bore Water Levels

Barometric pressure fluctuations have been shown to affect piezometric levels in groundwater bores

open to the atmosphere (Rasmussen & Crawford 1997; Spane 2002; Gonthier 2007). Atmospheric

pressure applies a stress to both the land surface and the open bore water surface. As the total water

head is the sum of water surface elevation head and barometric pressure head, variations in barometric

pressure influence the measured piezometric head (Toll & Rasmussen 2007). An inverse relationship

exists where increases in barometric pressure cause decreases in piezometric head and vice versa

(Rasmussen & Crawford 1997). An aquifer’s response to barometric pressure is dependent on the

level of aquifer confinement and storage characteristics of the bore/aquifer system (Spane 2002).

Theoretically, water levels in bores screened above the water table in unconfined aquifers should

show no response to pressure fluctuations as the water head is in equilibrium with the atmosphere

(Gonthier 2007) Alternatively, air bubbles trapped in pores within the aquifer may cause water level

fluctuations in response to atmospheric pressure changes (Hiscock 2005; Brassington 2007). The

delayed effects of pressure fluctuations on piezometric heads complicates correcting for barometric

pressure effects (Toll & Rasmussen 2007).

Site Background 

3 SITE BACKGROUND The two sites used in this study are located in the agricultural region of south-west WA. The site

locations are given in Figure 7.

Figure 7 Study site locations with the agricultural region indicated in green

3.1 Cuballing

The Cuballing site is located on Falls Farm about 15km northeast of Narrogin in the south west region

of the wheatbelt. The site is a small first-order catchment that covers an area of 1.78km2 and ranges in

elevation from 415m to 340m above sea level (Salama et al. 1992). Annual rainfall at the site averages

462mm, of which the majority falls between May and October (Salama et al. 1993b). The site was

progressively cleared until 1960 and is currently around 70% cleared. The catchment drains

northwards into an ephemeral tributary of the Hotham River (Salama et al. 1993d). The catchment is

1300m wide with steep valley gradients of 1:12 in the south declining to 1:50 to the north (Sudmeyer

1987). Figure 8 shows the location of the rain gauge and the groundwater bores mentioned in this

study. The uncleared section of vegetation around bore site 5 borders the ephemeral stream.

‐ 11 ‐ 

Site Background 

 

Figure 8 Map of the Cuballing catchment showing bore locations and extent of clearing

The groundwater bores used in this study were originally drilled in 1982 by the then WA Department

of Agriculture. Eleven sites were drilled and at each site a shallow and intermediate observation bore

and a deep piezometer to bedrock (where possible) was installed. The observation bores were fully

slotted while the piezometers were slotted over the bottom 1.5 to 2m. In 1989 the Commonwealth

Scientific and Industrial Research Organisation (CSIRO) drilled an additional thirteen sites to

investigate the effects of groundwater pumping (Salama et al. 1992). Since 1988, the piezometer

levels in the seven bores shown in Figure 8 have been continuously monitored using capacitance

probes and downhole loggers. These bores are all from the original drilling in 1982. The depths to

which the bores were installed are outlined in Table 1, taken from Salama et al. (1992). Bores 5A and

5B are the only observation bores that have been monitored with the remaining bores all being

piezometers installed down to bedrock.

‐ 12 ‐ 

Site Background 

Table 1 Depths of bores in the Cuballing catchment

Bore Name 

Depth to which PVC tubing was installed (m 

below ground) 

5A  1.22 

5B  3.39 

5C  18.67 

7C  21.05 

8C  20.07 

10C  27.43 

11C  25.97 

Previous research by Salama et al. (1993b) has identified three groundwater systems in the catchment,

as shown in Figure 9. The general flow pattern is in a northerly direction, following the topography of

the catchment. The system in the eastern region of the catchment is a phreatic, unconfined system due

to the shallow, outcropping granite on the eastern valley slope. The bedrock in this area extends only

2 to 10m below the surface and winter rainfall readily sheds off this part of the catchment (Salama et

al. 1993b). The central channel system is unconfined to semi-confined in highly weathered granites in

the upslope region to alluvial sediments within the central channel. The deep, confined system in the

western slopes occurs in a preferentially weathered subsurface channel of the catchment (Salama et al.

1993c). Basement highs in northern and central regions of the catchment are due to east-west dolerite

dykes which act as barriers to groundwater flow. These basement highs cause the central stream to act

as a discharge area for all three aquifers (Salama et al. 1994).

‐ 13 ‐ 

Site Background 

 

Figure 9 Composite water level map showing the eastern shallow system (1), the unconfined-

semiconfined system (2) and the confined system (3) (Salama et al. 1993b)

3.2 East Perenjori

The East Perenjori catchment is located 30km east of Perenjori in the northern wheatbelt region. It is a

small first order catchment (57km2) and ranges in elevation from 270m to 366m above mean sea level

(Salama et al. 1993a). Annual rainfall in the catchment averages 310mm of which 65% falls within

May and September. The native vegetation of the catchment was cleared beginning in 1967 and was

77% cleared by 1977. The catchment drains north towards Mongers Lake (Henschke 1989).

catchment is shaped like a narrow basin with a broad valley floor (Farrington & Salama 1996) and is

effectively split into two compartments due to a basement high underlying Wanarra Road (adjacent to

bore MS5). The southern portion of the catchment is the focus of this study as the monitoring bores

are all located in this area (Figure 10). Soil surveys by Henscke (1989) found that the upslope areas of

the catchment were mostly gravelly earthy sands and the valley floors were dominated by loamy

sands and clays.

‐ 14 ‐ 

Site Background 

 

Figure 10 Map of East Perenjori catchment showing bore locations and extent of clearing

The East Perenjori bores used in this study are from two separate drilling programs by the WA

Department of Agriculture and the CSIRO. In 1983, the WA Department of Agriculture drilled bores

at twenty sites and installed observation wells at shallow and intermediate depths and a piezometer to

bedrock (where possible). The observation bores were fully slotted while the piezometers were slotted

over the bottom 1.5 to 2m. In 1984, the CSIRO drilled and installed piezometers to bedrock at twenty

sites (Salama et al. 1993a). The bores used in this study are from both the 1983 and 1984 drilling

programs and have all been continuously monitored since 1989. The depths to which the bores were

installed are outlined in Table 2, taken from Salama et al. (1993a). Bores EPC1 and MS5 were from

the drilling undertaken by the CSIRO in 1984, with the remaining bores are from the WA Department

of Agriculture drilling of 1983.

‐ 15 ‐ 

Site Background 

Table 2 Depths of bores in the East Perenjori catchment

Bore Name 

Depth to which PVC tubing was installed (m 

below ground) 

EPC1  28.3 

7C  17.4 

8A  2.6 

8B  4.3 

8C  20.8 

MS5  5.63 

9C  21.02 

Previous research by Salama et al. (1993c) and Henschke (1989) into the hydrogeology of the site has

characterised three groundwater systems, shown in Figure 11. The first is an ephemeral, shallow

unconfined system that develops in response to intense rain events but dissipates in the absence of

continuing rain (Henschke 1989). A permanent perched, unconfined aquifer is present above calcrete

layers in the sandplain slopes of the catchment and in the absence of the hardpan layer, the aquifer sits

atop a clay layer (Salama et al. 1993c). This aquifer has an average thickness of 1.5m upslope, which

contracts downslope. The third groundwater system is a deep, regional aquifer that is semi-confined to

confined and extends across 90% of the catchment (Henschke 1989). The aquifer is present in

weathered bedrock 10 to 40m below ground in the upper slopes and less than 3m below ground in the

fluvial sediments of the valley floor (Henschke 1989; Salama et al. 1993c).

‐ 16 ‐ 

Site Background 

‐ 17 ‐ 

Figure 11 Hydrogeological east-west cross section of the East Perenjori catchment showing the

main groundwater systems (adapted from Henschke 1989)

Methodology 

4 METHODOLOGY

4.1 Field Data Collection

4.1.1 Groundwater Data

Piezometer levels were measured manually from when the bores were drilled and then continuously

using capacitance probes and downhole loggers since 1988. The manual measurements were taken

every one to two months from 1983 to 1988 using a groundwater plopper. This device is essentially a

tape measure with a metal cylinder on the end that can be heard making contact with the water

surface. From 1988 until 1997, ‘Wesdata’ capacitance probes and downhole loggers were used, with a

time interval between readings of between thirty minutes to one hour (Salama et al. 1992). From 1997

until 2006 ‘Dataflow’ probes and loggers were used and from 2006 until 2009, ‘Scott Parsons

Electronics’ probes and loggers (Figure 12) were used. The probes varied from 1.5 to 3 metres in

length. Capacitance probes measure the capacitance of the water every hour and logs the data if the

capacitance has changed by more than 50mV (approximately 7mm of water). If the capacitance has

not changed for twenty four hours, a reading is logged at midnight to indicate the probe is still

functioning.

 

Figure 12 Scott Parsons Electronics capacitance probe (left), data logger (centre) and electrical

connection (right) (Scott Parsons Electronics n.d.)

The three sites were visited irregularly between 1988 and 2009. The time between site visits varied

from three months to eighteen months. During each visit, the memory of the data logger was

downloaded to a laptop computer. The bore water level was measured manually using a groundwater

plopper. If it was suspected that the water level was in danger of overtopping or falling below the

probe, the length of the wire connecting the probe to the PVC bore cap (sensor to cap) would be

‐ 18 ‐ 

Methodology 

varied accordingly. The sensor to cap value would be used to calculate the water level below the

ground surface from the logger data.

The capacitance probes were calibrated at irregular intervals between 1988 and 2009. Calibration of

the probes occurred at the same time as the logger data was downloaded however not each download

visit resulted in the probes being calibrated. The time between calibrations varied from three months

to eighteen months for each of the three sites. The calibration process required the probe being

removed from the bore, placed in a column of water and the capacitance measured at two points on

the probe. For a two metre probe, the two points would be 200mm and 1700mm along the probe, both

measured from the bottom of the probe. The probe was then cleaned using a cloth to remove any silt,

algae or other residue (Figure 13) before being recalibrated. The build up of residue reduces the

accuracy of the capacitance probes so the dirty calibration was used to correct for this when

converting the water level from millivolts to metres (section 4.2.1).

 

Figure 13 Capacitance probe being cleaned.

4.1.2 Rainfall Data

Rainfall data was collected using tipping bucket rain gauges at each of the two sites. This type of rain

gauge consists of a circular collector that directs precipitation into a central funnel and onto two small

buckets (Figure 14). The buckets are balanced over a lever and every 0.2mm of rainfall causes the

lever to tip. The data logger records the date and time of each tip to the nearest second. The rainfall

data was downloaded at each site visit and calibrated at less regular intervals. The rain gauge was

calibrated by pouring 10mm of water into a plastic bottle with a small hole in the base to drip feed the

water into the collector. The rain gauge should then record 50 tips. If the recording was not correct,

‐ 19 ‐ 

Methodology 

the screws connecting the gauge to the base were loosened or tightened and a spirit level used to

ensure the gauge was level. The gauge was then recalibrated until it recorded 50 tips.

 

Figure 14 Tipping bucket rain gauge with the collector attached (left) and without collector

showing the tipping buckets (right).

4.1.3 Bore Hydraulic Conductivity

The hydraulic conductivities of five bores in the Cuballing catchment were measured using bail-down

tests. The five bores tested were 5B, 5C, 6C, 7C and 8C. Although groundwater levels in bore 6C had

not been monitored since 1992, the hydraulic conductivity was measured to give an indication of

subsurface throughflow between 7C and 8C. The equilibrium of the water level in the bore was

disrupted by withdrawing water using a bailer; a hollow cylinder with a check valve at the bottom

(Kasenow 1997). A 1m long aluminium bailer with a capacity of 500mL was used to remove water

from the bores as shown in Figure 15. The number of bails withdrawn from each bore varied from

around 5 to 10 depending on the depth of water in the bore, with deeper bores requiring more bails.

After bailing of the bore, a plopper and stopwatch was used to measure the rate at which water level

in the bore returned to equilibrium. The water level height was initially measured approximately every

15 seconds after the bore was bailed for the first two minutes and then every 30 seconds subsequently.

Measurement continued until the rate at which the water level changed had stabilised or until the

water returned to the original level. This time varied from 5 to 45 minutes.

‐ 20 ‐ 

Methodology 

 

Figure 15 Measuring the hydraulic conductivity by a bail-down test in bore 5C at Cuballing.

4.2 Field Data Conversion and Calibration

4.2.1 Converting Capacitance Data to Groundwater Levels

The raw capacitance data was uploaded into the Hydstra database and converted into groundwater

levels. The calibration readings taken in the field were converted to a slope reading using equation 1.

Equation 1

Where s: slope (mV/mm)

c1: capacitance at point 1 (mV)

c2: capacitance at point 2 (mV); c2 > c1

h1: height on probe at point 1 (mm)

h2: height on probe at point 2 (mm); h2 > h1

The calibration slope and capacitance readings at point 1 were then used to calculate a zero point,

which is the capacitance reading equivale t the probe, using equation 2. nt to no wa er on

Equation 2

Where z: zero point (mV)

‐ 21 ‐ 

Methodology 

The slope and zero point were used to calibrate and convert the capacitance data into groundwater

levels in accordance with the standard protocols outlined in Pope (2009) and shown in equation 3. The

offset is required to indicate how far below ground level the probe is located.

  . Equation 3

Where GWL: ground water level (metres below ground surface)

x: capacitance observation (mV)

o: offset, equal to the sensor to cap measurement (m)

The dirty and clean calibrations were used to correct for the change in accuracy of the capacitance

probe as silt, algae and other residue accumulated on the sensor. Hydstra allows the dirty and clean

calibrations to phase into each other so there is not an abrupt change following a field calibration. At

the time when the clean calibration occurred, the slope is completely determined by that calibration.

At the halfway point between the clean and dirty calibration, the slope is equally influenced by both

calibration values (KISTERS 2008). This has the effect of linearly distributing the change in slope

between the two calibrations.

4.2.2 Calibrating and Verifying Groundwater Levels

The accuracy and consistency of the groundwater level data was verified based on visual observations

of the groundwater hydrographs. The water level record for each bore was examined for inconsistent

data that was considered not physically realistic. An example of this inaccurate data is the highly

variable water level fluctuations shown in Figure 16 for Cuballing bore 5C. Beginning midway

through November 2005, the water level began to oscillate over a daily time period with the amplitude

increasing over time to as much as 0.6m by December. The fluctuating levels are significantly

different from the more realistic readings seen in October 2005 and for the rest of the record (not

pictured). The inaccurate data can be attributed to the capacitance probe failing either due to water

flooding the sensor or residue build-up. Groundwater levels considered inaccurate were removed from

the database and not included in any further analysis.

‐ 22 ‐ 

Methodology 

 

Figure 16 Hydrograph for Cuballing 5C showing physically unrealistic fluctuations, beginning

in mid-November 2005

The continuous logger record was compared against the manual measurements to verify the accuracy

of the logged data. For the majority of bore water level records it was found that the logger record

often did not match the field observations and could vary by as much as 1m. The magnitude of the

difference between the two data records varied temporally. An example of this is shown in Figure 17

for Cuballing bore 5B where the manually measured water levels vary from the logger record by 0.3m

in February 2005 and 0.1m in September 2006. The variation between the two records may be

attributed to errors in uploading capacitance data into the database or errors in the probe calibration.

 

Figure 17 Hydrograph for Cuballing 5B showing the difference between the manually measured

water levels (red) and the continuous levels (blue)

To correct for this difference, the continuous water level data was calibrated to match the measured

groundwater levels. The field observations were treated as calibration points with the continuous

‐ 23 ‐ 

Methodology 

record made to equal these points at those points in time. Between calibration points, the difference

between the original logged data and the calibrated data was distributed linearly to prevent sudden

changes and preserve the original water level fluctuation pattern.

The record of manual measurements was available for the period 1997 to 2009 for the two sites.

Although continuous water level measurements were made since 1988, the manual measurements

were not available to verify the accuracy of the data. Consequently, only the calibrated records from

1997 onwards were used for further analysis in this study to ensure consistency in the data.

4.2.3 Calculating Bore Hydraulic Conductivity

The bore responses measured using the bail-down tests were converted to hydraulic conductivity

using the Hvorslev equation, described in Fetter (1994). This method was chosen as it can be applied

to both confined and unconfined bores and the bores met the prerequisite that the length of the well

screen be greater than eight times the well radius (Weight 2004). The drawdown measured at time

zero was considered h0 and all subsequent drawdowns, h(t), were plotted relative to h0 on a semi-log

plot. An exponential line of best fit was fitted to the data. Where the graph appeared to have a ‘tailing

effect’ as described by Weight (2004), only the initial straight line segment was used to calculate the

exponential line of best fit.

To calculate T0, the time taken for the water level to rise to 37% of the initial change, h/h0 = 0.37, was

substituted into the exponential line of best fit equation for each bore. Equation 4 was then used to

estimate the hydraulic conductivity (Fetter 1994).

 

Equation 4

Where K: hydraulic conductivity (m/s)

r: radius of the well casing (m)

R: radius of the well screen (m); this includes the gravel around the screen

Le: length of the well screen (m)

T0: time taken for the water level to rise to 37% of the initial change (s)

All bores had a well casing diameter of 40mm, equivalent to a well radius of 0.02m. The radius of the

well screen was assumed to be 0.05m. The length of the well screen for piezometers was 2m (Salama

et al. 1993b) and for observation bores was the entire PVC length as detailed in Salama et al. (1992).

Bail-down tests provide order of magnitude estimates of hydraulic conductivity as only the area

around the well is being measured (Kasenow 1997)

‐ 24 ‐ 

Methodology 

4.3 Barometric Pressure Correction

4.3.1 Barometric Pressure Data

Mean sea level pressure (MSLP) data was obtained from the Australian Government Bureau of

Meteorology (BoM). Data was taken from weather stations which were selected based on frequency

of data collection, period of record and proximity to the study catchments. To capture the diurnal

fluctuations in atmospheric pressure, stations that monitored MSLP at an hourly frequency were

required. As the calibrated groundwater data extends over the period 1998 to 2009, it was necessary

for the MSLP data to reflect this length of record. The ‘Katanning’ BoM station commenced

measurements in 1999 so the adjacent station ‘Katanning Comparison’ was used to extend the record

of data. The ‘Katanning Comparison’ station monitored MSLP at only a frequency of two to seven

times per day. The details of the stations used to provide MSLP for the Cuballing and East Perenjori

catchments are summarised in Table 3.

Table 3 Details of BoM MSLP monitoring stations

Catchment Station

Number

Station

Name

Period of

Record

Frequency of

Monitoring

Height

above Sea

Level (m)

Approximate

Distance from

Catchment

(km)

Cuballing 10579 Katanning

Comparison

Jan 1957 to

Apr 2001

2 – 7 times per

day 320.0 107

Cuballing 10916 Katanning Jan 1999 to

Apr 2009 Hourly 320.0 105

East

Perenjori 8297 Dalwallinu

May 1997

to Apr 2009 Hourly 324.5 85

MSLP was converted to barometric pressure using equation 5, which is a simplified estimation to the

algorithms used by BoM. Station height above sea level was taken from Table 3 and a constant

temperature of 288.15K (15.15°C) was assumed for simplicity (C Lovitt, BoM, pers. comm.).

Equation 5

Where P: station level pressure (Pa)

P0: mean sea level pressure (Pa)

‐ 25 ‐ 

Methodology 

T: temperature (K)

z: height of station above sea level (m)

R: universal gas constant for air = 8.314472 J / (mol K)

g: gravitational acceleration = 9.80665 m/s2

M: molar mass of air = 0.0289644 kg/mol

For the Cuballing catchment, barometric pressure data had to be combined from two BoM stations to

ensure the entire record of water level data had accompanying barometric pressure data. As the two

stations had overlapping periods of record (Jan 1999 to Apr 2001), linear regression was used to

quantify the relationship between the two stations’ pressure measurements and extend the period of

record for the ‘Katanning’ site. The MSLP was converted to barometric pressure and linear regression

was applied for when the two datasets both had measurements for a particular date and time. The

correlation coefficient between the two stations equalled 0.9814, indicative of a very strong linear

relationship between the two records. A linear line of best fit was used to derive values for barometric

pressure using the record of ‘Katanning Comparison’.

4.3.2 Barometric Efficiency Method

One method of correcting bore water level changes due to barometric fluctuations is to adjust water

levels using the barometric efficiency (BE) of a well. BE is defined as the change in water level

divided by the change in pressure over the same time interval, as shown in equation 6 (Brassington

2007; Gonthier 2007; Rasmussen & Crawford 1997).

∆W∆

Equation 6

Where BE: barometric efficiency of a well (dimensionless)

ΔW: change in water level (m)

ΔB: change in barometric pressure (m H2O)

BE varies from zero to one with values typically between 0.2 to 0.8 (Todd 1980; Brassington 2007).

Gonthier (2007) identifies five methods of determining the BE of a well: the average of ratios method,

the median of ratios method, the Clark method, the slope method and the graphical method. The

Department of Water (DoW) commonly uses the slope method described by Brassington (2007) to

calculate BE (N. Cox, DoW, pers. comm.). This method utilises a plot of barometric pressure (x-axis)

against water levels (y-axis). The barometric pressure is expressed in metres H2O and the bore levels

are in positive metres below ground level. Ordinary least squares regression is used to calculate the

slope of the plot which provides an estimate of BE.

‐ 26 ‐ 

Methodology 

The slope method described in Gonthier (2007) differs slightly from that of Brassington (2007).

Gonthier (2007) plots the change in barometric pressure against the change in groundwater level. BE

is estimated as the slope of the plot, again using ordinary least squares regression. Gonthier (2007)

describes this method as more mathematically accurate as it more closely resembles the definition of

BE (equation 6) and produces less scatter when plotted. Consequently, the Gonthier (2007) slope

method was adopted to calculate the BE of each of the wells.

Calculation of BE requires the same time interval between the barometric pressure and water level

data. As the barometric pressure data varied from as few as two measurements per day to hourly,

linear interpolation was used to create hourly point data. The capacitance probes used to measure bore

water level only recorded the water level if the capacitance changed by greater than 50mV.

Consequently, the time interval between readings was variable and so linear interpolation was also

used to create hourly water level data.

Water levels were corrected for the barometric pressure effects using the calculated BE as a correction

factor as shown in equation 7 (Brassin 2007; G 007gton onthier 2 ).

Equation 7

Where W(t) corr: water level at time t, corrected for barometric pressure (m)

W(t) uncorr: uncorrected water level at time t (m)

BE: barometric efficiency (dimensionless)

(Bt-1 – Bt): change in barometric pressure from time t-1 to time t (m H2O)

4.3.3 Multiple Regression Method

An alternative barometric pressure correction method uses multiple regression deconvolution

techniques. Convolution in the time domain is used to account for the temporal variability in

barometric pressure effects on bore water levels (Rasmussen & Crawford 1997). Unlike the

barometric efficiency method, the multiple regression technique does not assume the response of

water levels to changes in barometric pressure is instantaneous. The time lag response between

pressure and water level change is determined using regression deconvolution for a linear set of

equations as defined in equation 8 (Toll & Rasmussen 2007).

∆ ∑ ∆ Equation 8

Where ΔW: change in water level over time t (m)

ΔB(t – i): change in barometric pressure i time steps before t (m H2O)

α(i): unit response function at lag i (dimensionless)

‐ 27 ‐ 

Methodology 

m: maximum time lag (hours)

The unit response parameter is a variable barometric efficiency that is a function of the lag time, i,

between barometric pressure changes and the response of bore water level (Rasmussen & Crawford

1997). It is calculated using ordinary least squares regression in the same manner as the slope method

of Gonthier (2007) for each lag time i. The barometric step response function is then the sum of the

unit response parameters as shown in eq 9 Tol asmussen 2007). uation ( l & R

∑ Equation 9

Where A(i): barometric step response function (dimensionless)

α(i): unit response function at lag i (dimensionless)

The maximum time lag m was set to a sufficiently large number to incorporate all long-term

responses. A period of 12 to 24 hours is usually sufficient in most confined wells (Toll & Rasmussen

2007). The maximum response time is analogous to the time taken for a bore to respond to a slug test

(T. Rasmussen, University of Georgia, pers. comm.). To estimate the maximum response time m, lag

time i was plotted against step response A(i). The maximum response time was then estimated as

when the step response begins to level out as lag time increases. An example plot is shown in Figure

18 for East Perenjori bore 8C. In this plot the step response function levels out at a step response of

about 0.5 and first begins to do this at 18 hours, which becomes the estimated maximum response

time.

 

Figure 18 Step response function for East Perenjori bore 8C with a maximum response time of

18 hours

Using the unit response function α(i), a correction variable for each observation is calculated using

equation 10 (Toll & Rasmussen 2007). The correction variable for each observation Wt* is then added

to the original water level to correct for barometric pressure.

‐ 28 ‐ 

Methodology 

∆∆∆

∆

∆∆∆

∆

∆∆∆

∆

∆∆∆

∆

Equation 10

Where W*t: correction variable for observation t within m to n

n: total number of observations

The software program BETCO (Barometric and Earth Tide Correction) was used to apply the multiple

regression technique. BETCO requires hourly observations of water level and barometric pressure

(Toll 2005) so the barometric pressure and water level data were both linearly interpolated to derive

hourly values. The maximum response time is the only required variable.

4.4 Rainfall Analysis

4.4.1 Rainfall Data

Each catchment has a tipping bucket rain gauge that measures rainfall in 0.2mm amounts. In East

Perenjori the rain gauge had an incomplete record, likely due to the data logger failing. The dates

showing the periods that have no rainfall data are shown in Table 4. The cumulative length of time

without rainfall data was significant. Of the twelve year span of monitoring, there is no data for over

four years. To estimate rainfall when the rain gauge had failed, synthetic rainfall data was used based

on rainfall recorded in nearby stations.

Table 4 Dates and periods of no data for the rain gauge in East Perenjori

Start Date End Date Length of Gap (days)

14/7/1998 9/9/1999 422

21/2/2000 22/1/2002 701

31/12/2002 14/12/2003 348

8/3/2007 19/6/2007 103

The ‘Data Drill’ tool, developed by the Queensland Department of Natural Resources & Mines, uses

splining and kriging techniques to interpolate meteorological data from nearby BoM monitoring

stations (Jeffrey et al. 2001). Data Drill was used to create daily interpolated rainfall data for the East

Perenjori catchment. The interpolated rainfall was compared to known rainfall from the East Perenjori

‐ 29 ‐ 

Methodology 

rain gauge and the correlation coefficient was determined using linear regression. The two data sets

had a correlation coefficient of 0.77, indicative of a reasonably strong correlation. For the days where

the raingauge at East Perenjori failed to record data, the Data Drill results were used to provide an

estimate of daily rainfall.

Data Drill was also used to create synthetic daily rainfall data going back to 1900 for both catchments.

This was used to calculate long-term averages both annually and monthly. The rainfall recorded in the

rain gauges were then compared to the long-term results derived from Data Drill to demonstrate the

climate variability during the study periods.

4.4.2 Identifying Significant Rainfall Events

Rainfall events greater than a 1 year annual recurrence interval (ARI) were identified using intensity-

frequency-duration (IFD) curves and Hydstra’s HYRINT program. IFD curves for the catchments

were produced using the BoM ‘Rainfall IFD Data System’ (BoM 2009), which uses the methods

outlined in Australian Rainfall and Runoff (IEA 2001). Site coordinates were the only input

requirement for the BoM tool. The IFD charts for the two sites are shown in Appendix D.

The IFD table provided threshold rainfall intensities for standard durations and ARI’s. The threshold

intensities for 1yr ARI events were used in Hydstra’s HYRINT function to identify events that exceed

that threshold intensity for each standard duration. The standard rainfall durations chosen were 5min,

6min, 10min, 20min, 30min, 1 hour, 2 hours, 3 hours, 6 hours, 12 hours, 1 day, 2 days and 3 days as

outlined in IEA (2001). The events identified by HYRINT were then given an ARI classification

based on which threshold rainfall intensity was exceeded for a particular duration from the IFD tables.

The highest threshold intensity exceeded by an event determined what ARI was assigned to that

event. The duration was estimated based on visually observing the rainfall distribution.

4.5 Catchment Delineation and Groundwater Contours

Catchment boundaries were determined based on topographic contours and previous research. Digital

elevation models were created using 10m contours in ArcGIS (version 9.2) by ESRI. Previous

catchment delineations by Salama et al. (1992) and Salama et al. (1993a) were used to provide

approximate indications of where the catchment divides are located and the DEMs were used to refine

these approximations. As the East Perenjori site in this study is only the lower catchment of the study

by Salama et al. (1993a), Wanarra Road was used as the catchment divide.

Groundwater contours for the deep aquifer were created to provide indicative directions of

groundwater flow. Piezometric heads were converted to metres AHD and contours were created using

Surfer (version 8.00) by Golden Software. The instantaneous head during arbitrary periods when all

the deep bores had data was used to generate the contours. The temporal variation in head was found

‐ 30 ‐ 

Methodology 

to only have a limited effect on the overall direction and shape of the contours so the arbitrary time

was considered appropriate. Kriging interpolation was used to generate the contours in Surfer.

4.6 HARTT

To quantify lag times between rainfall and changes in piezometric heads, the Hydrograph Analysis:

Rainfall and Time Trends (HARTT) method was used. HARTT represents rainfall as an accumulation

of deviations from average rainfall in order to determine the lag between rainfall and its impact on

groundwater. HARTT compares the accumulative monthly residual rainfall (AMRR) and the

accumulative annual residual rainfall (AARR) to monthly groundwater levels. The AMRR is

calculated using equation 11 and AARR using equation 12 (Ferdowsian et al. 2001).

AMRR M , M Equation 11

Where RRt: accumulative monthly residual rainfall at time t (mm) AM

: rainfall in month i and the jth month of the year (mm) ,

: mean monthly rainfall for the jth month of the year (mm)

t: months since observations began

AARR M A Equation 12

Where ARRt: accumulative annual residual rainfall at time t (mm) A

mean annual rainfall (mm) :

, : rainfall in month i and the jth month of the year (mm)

The program HARTT-XLS (version 5.0.4), developed by Lote-Tree Software (Ferdowsian, McCarron

& Majidi 2009), was used to create a regression model. HARTT-XLS uses ordinary least squares

regression and the AMRR and AARR to solve equation 13 by estimating the parameters k0, k1 and k2

(Ferdowsian et al. 2001). The length of time lag L is varied until the highest correlation coefficient is

achieved. Depending on which gives a higher correlation coefficient, either the AMRR or AARR is

used in equation 13.

Equation 13

Where: Deptht: depth of the watertable below the ground surface (m)

t: time since observations began (months)

L: length of time lag (months)

‐ 31 ‐ 

Methodology 

k0: initial depth to groundwater (m)

k1: impact of above or below average rainfall on groundwater (dimensionless)

k2: average rate of groundwater change over time (m/month)

The highest resolution of data that is accepted by HARTT-XLS is monthly groundwater levels. The

instantaneous head at the start of each month for each bore was used to fulfil the input requirements of

the program. This systematic method was chosen to provide a random representation of groundwater

heads not influenced by the fluctuations present within the data record.

4.7 Water Balance

A single cell water balance model was developed to quantify water fluxes in the nested bore area for

the Cuballing catchment. The nested bore site was chosen as the model area in order to compare the

magnitudes of vertical fluxes across the semi-confining/confining layers and lateral throughflow to

the deeper aquifer. The components of the water balance are represented in Figure 19.

 

Figure 19 Nested bore water balance components

The water balance was divided into two sections to represent the shallow unconfined aquifer and the

deeper semi-confined aquifer. Equation 14 defines the terms used for the shallow aquifer water

balance and equation 15 defines the deeper aquifer water balance. In equation 14, the unknown

components of the water balance are runoff and throughflow. If in situ rainfall is not sufficient to

cause the observed change in storage than the model would indicate that surface runoff or

throughflow from upslope is contributing to recharge. In equation 15, the unknown term is

throughflow out of the system. A negative throughflow out of the system would suggest that there is

not enough leakage or throughflow into the system to account for the change in storage observed.

‐ 32 ‐ 

Methodology 

∆ , , , Equation 14

Where ΔQS,B: change in storage in the shallow aquifer, B (m3)

R: rainfall (m3)

E: evaporation (m3)

RO: runoff (m3)

QL: leakage from the shallow aquifer to the deeper aquifer (m3)

QT,Bin: lateral throughflow into aquifer B (m3)

QT,Bout: lateral thr hfl u quif (m3) oug ow o t of a er B

∆ , , , Equation 15

Where ΔQS,C: change in storage in the deep aquifer, C (m3)

QL: leakage from the shallow aquifer to the deeper aquifer (m3)

QT,Cin: lateral throughflow into aquifer C (m3)

QT,Cout: lateral throughflow out of aquifer C (m3)

The areal extent for the single cell model was taken as the lower catchment in Cuballing. This was

calculated to be 494,000m2. Synthetic evaporation data was provided using Data Drill. Daily pan

evaporation data measured at BoM monitoring stations was interpolated for the site location. Rainfall

and evaporation were expressed in units of m3 by multiplying by the surface area of the model.

A daily time step was used to calculate the components of the water balance. This was chosen as the

interpolated rainfall and evaporation data was provided as daily subtotals. Due to the daily

fluctuations of the piezometric head record, the storage term ΔQS would alternate from positive to

negative accordingly. As this ‘noise’ was not caused by daily changes in leakage or throughflow

(equation 15), the daily water balance terms were summed up over recharge and discharge periods.

For example, Cuballing bore 5C shows a rising trend between the dates 31/7/01 and 21/10/01. So the

terms in equation 15 were calculated on a daily basis for each day within that recharge period and

summed together to compare magnitudes.

4.7.1 Storage Term

The change in storage was calculated using the known piezometric head records for the shallow and

deep aquifers in the nested site. Equation 16 defines how the change in storage is calculated over one

timestep Δt (Spitz & Moreno 1996).

∆ ∆ Equation 16

‐ 33 ‐ 

Methodology 

Where ΔQS: change in storage in the aquifer (m3)

A: surface area of the aquifer (m2)

S: storage coefficient (dimensionless)

h(t+Δt) – h(t): difference in piezometric head over time step Δt (m)

The storage coefficient is defined in equation 17 (Fetter 1994). In unconfined aquifers, the specific

yield is orders of magnitude greater than specific storage so the storage coefficient is effectively the

specific yield. In semi-confined and confined aquifers the storage coefficient is equivalent to specific

storage multiplied by the aquifer thickness (Fetter 1994).

Equation 17

Where: S: storage coefficient (dimensionless)

Sy: specific yield (dimensionless)

b: aquifer thickness (m)

SS: specific storage (m-1)

The storage coefficient was estimated based on previous studies and common values for leaky

aquifers. The storage coefficient for the shallow aquifer in Cuballing was set to the value of 0.1. This

was the value used by Salama et al. (1994) for the same site and conforms with estimates by Nulsen

(1998) that wheatbelt watertables had specific yields in the range of 0.02 and 0.1. The storage

coefficient in the deeper semi-confined aquifer was assumed to be 0.001, also based on estimates by

Salama et al. (1994). The storativity estimates for the deeper aquifers are at the lower end of published

estimates of storativity for semi-confined/leaky aquifers with Kasenow (1997) suggesting a range of

0.001 and 0.1 and Weight (2004) suggesting between 0.001 and 0.01.

4.7.2 Leakage Term

The interaction between the shallow aquifer and the deep aquifer at the nested sites was estimated

based on the degree of leakage across the confining layer. The piezometric heads of the shallow and

deep bores was used to estimate vertical flux as defined in equation 18 (Spitz & Moreno 1996).

Equation 18

Where: QL: leakage across the confining layer (m3)

K: hydraulic conductivity of the aquitard (m/day)

d: thickness of aquitard (m)

A: surface area of the aquifer (m2)

‐ 34 ‐ 

Methodology 

‐ 35 ‐ 

hc: piezometric head in deep aquifer, C (m)

hB: piezometric head in shallow aquifer, B (m)

The hydraulic conductivity of the aquitard between the shallow and deep aquifers was estimated

based on the bore logs and published values of hydraulic conductivity. The confining layer in the

Cuballing catchment is described as a “brown gritty clay” with a thickness of 5.3m (Salama et al.

1992). An initial value of hydraulic conductivity of 0.001m/day was assumed for the aquitard, which

is on the upper end of the range suggested by Fetter (1994) as 10-6 to 10-3 m/day for clays.

4.7.3 Throughflow Term

Throughflow for the deeper aquifers was estimated using the hydraulic gradient between upslope

bores and the deep nested bore. Equation 15 defines the terms used to calculate subsurface

throughflow (Spitz & Moreno 1996).

Equation 19

Where: QT: throughflow into the deep aquifer (m3)

T: transmissivity (m2/day)

B: lateral boundary length between upslope and downslope deep aquifers (m)

hU: piezometric head of bore upslope of the nested bores (m)

hC: piezometric head of deep nested bore (m)

L: distance between upslope and downslope bore (m)

The transmissivity of the deep aquifers were estimated using hydraulic conductivities and the aquifer

width. Hydraulic conductivity was calculated using the results of the bail-down tests described in

section 4.1.3. The hydraulic conductivity was converted to transmissivity by multiplying by the

aquifer widths described in the bore logs (Salama et al. 1992). Transmissivity was estimated at

2m2/day.

The lateral boundary length B, and distance between upslope and downslope bores L were calculated

using ArcGIS. The upslope bore used to calculate throughflow was 7C. This bore is in the same

groundwater flow system defined by Salama et al. (1993b) as flowing into the nested bore system as

shown in Figure 9. The lateral boundary length was estimated as 500m and the distance between bores

5C and 7C was 580m.

Results 

5 RESULTS

5.1 Site Characterisation

DEMs developed for the two study catchments represent the ground surface topography. The DEM

for the Cuballing site is shown in Figure 20 and depicts the northwards slope of the terrain. Runoff

generated upslope, near bores 11C and 7C flows towards the central part of the catchment into the

ephemeral stream (see Figure 8). The nested bores (5ABC) and bore 8C are considered to be

‘downslope’ with the remaining bores classified as ‘upslope.’ Groundwater contours for the semi-

confined aquifer for the catchment show the direction of flow, which generally follows the surface

topography. The exception to this is the head levels around bore 10C. As this is located in an

uncleared area of the catchment (Figure 8), the vegetation consumes groundwater and causes this

region to be a groundwater sink. As the contours were created using the piezometric heads in the

monitored bores, groundwater heads in regions such as the eastern area of the catchment were

extrapolated and may not be representative of the actual head distribution.

 

Figure 20 DEM with overlayed groundwater contours for the Cuballing catchment

The DEM for the East Perenjori catchment shows the valley landscape representative of the zone of

ancient drainage in the wheatbelt (Figure 21). The valley flanks at the sides of the catchment shed

runoff into the central valley floor system. The two bores 9C and 20C were considered upslope bores

due to their position in the landscape. The remaining bores were classified as lower valley and valley

‐ 36 ‐ 

Results 

floor bores. Groundwater contours for the deep aquifer follows the surface topography with flow

tending towards the central flat valley region and northwards towards bore MS5.

 

Figure 21 DEM with overlayed groundwater contours for the East Perenjori catchment

5.2 Barometric Pressure Correction

The BE of wells in the Cuballing nested site were calculated for calendar years that had a complete

record of groundwater data. The computed BE for the three nested bores in the Cuballing catchment is

shown in Table 5. The average BE’s were 0.02 for the shallow observation bore, 0.10 for the

intermediate observation bore and 0.23 for the deep piezometer. The BE’s are not constant over time.

The values for the shallow bore vary from 0.004 to 0.057 with no consistent pattern to the changes.

BE’s for the intermediate bore ranged from 0.05 to 0.19 and from 0.12 to 0.31 for the deep aquifer.

These values show a general increasing trend over time

‐ 37 ‐ 

Results 

Table 5 Barometric efficiency for the nested bores in Cuballing

5A  5B  5C 

1998  ‐  0.06  0.12 

1999  0.004  0.05  0.13 

2000  0.030  0.05  ‐ 

2001  0.057  0.19  0.18 

2002  ‐  ‐  0.20 

2003  0.005  ‐  0.27 

2004  0.027  ‐  0.31 

2005  0.019  0.10  ‐ 

2006  ‐  0.16  0.31 

2007  0.017  0.12  0.23 

2008  ‐  ‐  0.30 

Groundwater levels in the shallow observation bores of both the Cuballing and East Perenjori

catchments showed limited response to barometric pressure fluctuations. Figure 22 compares water

table fluctuations in the observation bore 5A in the Cuballing catchment to barometric pressure

changes. Figure 22 is representative of the general relationship between barometric pressure and water

level in the shallow observation bores of both sites for the entire length of record. The peaks and

troughs of the barometric pressure series correlate to minor responses in the water table record.

 

Figure 22 Plot of barometric pressure (green) and groundwater levels (blue) in Cuballing bore

5A for a three month period in 2004

‐ 38 ‐ 

Results 

Groundwater levels in the intermediate observation bores for both catchments did show a response to

changes in barometric pressure when there was no underlying groundwater trend. Figure 23 compares

the changes in water level to barometric pressure in Cuballing intermediate bore 5B during February

2007. The water level response to changes in barometric pressure is an inverse one and is only evident

when the water table is showing an overall neutral trend. When an increasing or decreasing trend is

present in the water table, any fluctuations due to barometric pressure changes are not evident. The

intermediate bore response of Cuballing 5B to barometric pressure is the same as that seen for the

East Perenjori intermediate observation bore 8B (not pictured).

 

Figure 23 Plot of barometric pressure (green) and groundwater levels (blue) in Cuballing bore

5B in February 2007

Piezometric heads in the semi-confined and confined aquifers of the two catchments show a clear

inverse response to changes in barometric pressure. Figure 24 shows a three month period of

piezometric heads for the bore 8C in the Cuballing site compared to the barometric pressure record.

The peaks and troughs of the barometric pressure data correspond to the troughs and peaks of the

hydrograph, respectively. The observable inverse relationship between barometric pressure and

piezometric heads shown in Figure 24 is indicative of the general relationship for all semi-confined

and confined aquifers in the two catchments throughout the period of record.

The multiple regression method had some success in removing pressure fluctuations from the

piezometric head record. Figure 25 shows the measured and corrected piezometric heads for

Cuballing bore 8C over the same time period as Figure 24. The hydrograph of corrected heads retains

the same general fluctuations as the uncorrected hydrograph but the magnitudes of the oscillations

have been diminished. In January, the fluctuations of the uncorrected piezometric heads extend over

‐ 39 ‐ 

Results 

approximately 10cm from peak to trough. For the same period, the corrected heads fluctuate over a

range of 4cm from peak to trough. Although the magnitudes of the fluctuations have been reduced,

the effect of barometric pressure variability has not been completely removed.

 

‐ 40 ‐ 

Results 

 

Figure 24 Plot of barometric pressure (green) and piezometric heads (blue) in Cuballing bore

8C for a three month period in 2002

Figure 25 Plot of measured piezometric head (blue) against heads corrected for barometric

pressure fluctuations (red) using the multiple regression technique in Cuballing bore 8C for a

three month period in 2002

 

‐ 41 ‐ 

Results 

Hydrographs for the semi-confined and confined aquifers in East Perenjori catchment had identical

relationships to barometric pressure as those in Cuballing. A three month period of barometric

pressure and piezometric heads for bore 9C is shown in Figure 26. Like the results shown in Figure 24

for Cuballing bore 8C, the peaks and troughs of the barometric pressure series correlate strongly with

the troughs and peaks of the piezometric heads of 9C, respectively. The corrected piezometric heads

for 9C for the same period as Figure 26 are shown in Figure 27. As with the corrected heads for

Cuballing bore 8C, the multiple regression correction reduced the magnitude of the fluctuations but

retained the general trend of the measured heads.

The maximum response time for each bore is shown in Appendix B.

‐ 42 ‐ 

Results 

 

Figure 26 Plot of barometric pressure (green) and piezometric heads (blue) in East Perenjori

bore 9C for a three month period in 2007

 

Figure 27 Plot of measured piezometric head (blue) against heads corrected for barometric

pressure fluctuations (red) using the multiple regression technique in East Perenjori bore 9C for

a three month period in 2007

 

‐ 43 ‐ 

Results 

5.3 Rainfall

5.3.1 Cuballing

Annual rainfall in Cuballing during the study period was lower than the long-term average. The

average annual rainfall for the eleven years of record was 396mm and the long-term average is

490mm (Figure 28). The driest year was in 2006 where only 318mm was recorded and the wettest

year was in 1999 which had 555mm of rainfall. The monthly rainfall distributions (Figure 29) shows

that rainfall over the wet months May, June and July is less than the average during the study period

but is slightly higher in August. Average rainfall in January from 1998 to 2008 was higher than the

long-term average of 11mm due to 129mm falling in 2000 and 77mm falling in 2006.

 

Figure 28 Observed annual rainfall compared to the long-term average annual rainfall in

Cuballing

0

100

200

300

400

500

600

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

Rainfall (m

m)

Year

Annual Rainfall

Average Annual Rainfall

‐ 44 ‐ 

Results 

 

Figure 29 Measured average monthly rainfall compared to the long-term monthly average

rainfall in Cuballing

Significant rainfall events were classified according to ARI and duration. Table 6 shows the

significant events captured by the Cuballing rain gauge between 1997 and 2008. A one hour, 100 year

ARI event occurred in April 2003 which produced 53mm of rainfall. Three 10 year ARI events of 5

minute, 6 hour and 10 minute duration took place in March 1998, January 2000 and June 2003,

respectively.

Table 6 Magnitude and duration of rainfall events greater than a 1 year ARI from the

Cuballing rain gauge

Date Rainfall (mm)

ARI (years) Duration

10/03/1998 8.8 10 5 min 27/08/1998 84.8 5 72 hr 27/05/1999 15.2 2 1 hr 22/01/2000 45.0 10 6 hr 30/01/2000 21.8 5 3 hr 6/05/2001 16.0 2 1 hr 29/07/2001 59.8 2 48 hr 30/11/2001 19.4 2 2hr 22/11/2002 12.8 5 20 min 5/04/2003 53.4 100 1hr 25/06/2003 12.2 10 10 min 3/08/2003 21.8 2 3 hr 21/10/2004 9.6 2 20 min 18/05/2005 41.4 2 12 hr

0102030405060708090100

Jan

Feb

Mar

Apr

May Jun Jul

Aug Sep

Oct

Nov Dec

Rainfall (m

m)

Month

Monthly Average 1998 to 2008

Long‐term Average

‐ 45 ‐ 

Results 

5.3.2 East Perenjori

Annual rainfall in East Perenjori during the study period was lower than the long-term average. The

average annual rainfall for the eleven years of record was 241mm and the long-term average is

310mm (Figure 30). The driest year was in 2007 where only 121mm was recorded and the wettest

year was in 1999 which had 355mm of rainfall. The monthly rainfall distribution (Figure 31) shows

that rainfall over the wet months May to August was less than the average during the study period.

Rainfall during the normally drier months from November to March was higher during 1998 to 2008

in comparison to the long-term average.

 

Figure 30 Annual rainfall in 1998 to 2008 compared to the long-term average annual rainfall in

East Perenjori

0

50

100

150

200

250

300

350

400

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

Rainfall (m

m)

Year

Annual Rainfall

Average Annual Rainfall

‐ 46 ‐ 

Results 

Figure 31 Average monthly rainfall during the study period compared to the long-term monthly

average rainfall in East Perenjori

Table 7 shows the significant rainfall events in the East Perenjori catchment measured by the rain

gauge. For periods using interpolated rainfall (Table 4), intensities and durations could not be

calculated as rainfall totals were only available in daily periods. A one hour, 100 year ARI event took

place in February 2004 which produced 51mm of rainfall. One 50 year, one 20 year and two 10 year

ARI events occurred within the monitored period.

Table 7 Magnitude and duration of rainfall events greater than a 1 year ARI captured by the

Perenjori rain gauge

Date Rainfall (mm)

ARI (years) Duration

14/01/2000 17.0 10 20 min 22/01/2000 31.4 50 30 min 23/12/2002 21.2 5 1 hr 19/02/2004 51.4 100 1 hr 1/03/2004 13.6 2 20 min 12/01/2006 63.0 20 6 hr 11/02/2006 10.8 5 10 min 31/03/2006 43.6 2 24 hr 1/02/2008 8.0 2 10 min 20/02/2008 48.8 5 24 hr 28/01/2009 17.4 5 30 min 21/04/2009 16.6 10 20 min

0

10

20

30

40

50

60

Jan

Feb

Mar

Apr

May Jun Jul

Aug Sep

Oct

Nov Dec

Rainfall (m

m)

Month

Monthly Average 1998 to 2008

Long‐term Average

‐ 47 ‐ 

Results 

5.4 Groundwater Recharge in Cuballing

The groundwater response to rainfall in the Cuballing catchment can be summarised as follows:

• The downslope bores showed seasonal fluctuations of recharge and discharge with quick response

times to rainfall. This was particularly evident in the nested bores (5A, 5B and 5C);

• The shallow aquifer in the nested site (5B) showed rapid responses to some rainfall events;

• High intensity events in dry months did not cause substantial recharge anywhere in the catchment;

• Recharge occurred in the wetter months from April to August except for one episodic recharge

event in January 2000.

These responses are discussed further in the following sections.

5.4.1 Seasonal Recharge

The downslope bores in the Cuballing catchment showed seasonal fluctuations of increasing and

decreasing water levels. The alternating periods of recharge and discharge in the bores 5B and 5C are

shown in Figure 32 for the 11 year period of record. The other downslope bore 8C also showed a

seasonal response to rainfall (Appendix A), although less pronounced than in the nested bores. The

nested bores begin to recharge at approximately the same time throughout the period of record. This

occurs in around April to June in most years. The water levels peak in around September and October.

The exception is the episodic recharge of January 2000, which is the only recharge event that did not

occur in the wet winter months.

 

Figure 32 Seasonal groundwater fluctuations of Cuballing bores 5B and 5C over the 11 years of

record

‐ 48 ‐ 

Results 

5.4.2 Shallow Aquifer Response

The water table in the nested site shows rapid responses to some rainfall events. Figure 33 shows the

impact of a 5 minute, 10 year ARI event and a 3 hour, <1 year ARI event on bore 5B in 1998. In

response to the first event, the water table shows a sudden jump of 1.3m before quickly receding to its

pre-event level after 2 days. A similar response for this bore can be seen to the second event in May

1998 where the groundwater rises 0.6m within 2 hours before receding to pre-event levels within 1

day. This pattern is common for the aquifer monitored by this bore, with nine rapid rise and equally

rapid decline ‘events’ evident throughout the eleven year period of record. The rapid increases are

also seen in the shallow observation bore 5A, although the time taken for the water table to decrease is

longer than in 5B (Appendix A).

 

Figure 33 Rapid water table response of Cuballing 5B to a 5 min, 10 year ARI event in March

and a 3 hour, <1 year ARI event in May 1998

The length of time the shallow water table experienced recharge varied throughout the study period.

On average, the unconfined aquifer became saturated over a one month period. Within that time, the

water table was very responsive to some rainfall events. Table 8 identifies five rainfall events that

caused large responses in the water table over less than 24 hours. The water table responses can be

seen in Figure 32. The rainfall events tend to be low ARI and high duration except for the January

2000 event. The amount of recharge was substantial, with the maximum rise of 1.29m occurring in

August 2001. For a specific yield of 0.1, the amount of rainfall that fell during the period of

groundwater rise was not sufficient to cause the magnitude of rise observed. A ‘water deficit’ in

millimetres was calculated for each event in Table 8. The large groundwater rise in August 2001

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Results 

required 91.1mm more water than in situ rainfall and the smallest event in July 2000 only required

5.8mm more than rainfall.

Table 8 Rainfall events that caused quick responses in Cuballing 5B

Date Rainfall ARI (years) 

Rainfall Duration (hours) 

Rainfall (mm) 

Water level change (m) 

Duration of Groundwater Response (hours) 

Water Deficit (mm) 

Jan‐2000  10  6  65.8  0.79  5  ‐13.5 

Jul‐2000  <1  48  32.6  0.38  22  ‐5.8 

Aug‐2001  1  24  37.6  1.29  13  ‐91.1 

May‐2005  2  12  41.6  1.09  12  ‐67.7 

Jul‐2007  <1  72  21.0  0.80  14  ‐58.7 

5.4.3 High Intensity Events

High intensity, low duration events had no impact on the piezometric heads of the deep aquifers if the

event occurred during the drier months. Figure 34 shows the response to the 1 hour, 100 year ARI

event in April 2003 in the bores 7C and 8C. The bores in the nested site do not have any data for this

period so the shallow groundwater response to this event is unknown. The upslope bore 7C and

downslope bore 8C both show no significant response to the rainfall event as there is no observable

deviation from the normal fluctuations. High intensity events only caused recharge during the wetter

months from April to August.

   

Figure 34 Groundwater response of Cuballing bores 7C and 8C to a 1 hour, 100 year ARI event

in April 2003

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Results 

5.4.4 Low Intensity Events

Recharge in the Cuballing catchment was more likely to be due to low intensity, long duration events

occurring in the wet winter months. A 72 hour, 5 year ARI event is shown in Figure 35 along with the

hydrographs for bores 5B, 5C and 7C. The intermediate observation bore 5B responds immediately to

the rainfall event with a 0.3m rise in groundwater over two days. The soil profile then becomes

saturated as the groundwater level remains constant for the following month. The deep piezometer 5C

in the nested site shows a delayed response to the rainfall. Before the event, the groundwater head was

already increasing however the rate of rise escalated following the event. The upslope bore 7C also

shows a delayed response to rainfall. About six days after the event commenced, the head in the bore

begins to rise and continues to rise for around a month. The estimated magnitude of this rise was

0.15m after taking into account the general fluctuations within the data. Bores 8C and 10C both

showed evidence of recharge in response to this event with rises of 0.3m and 0.12m respectively

(Appendix A).

Figure 35 Groundwater response of Cuballing bores 5B, 5C and 7C to a 72 hour, 5 year ARI

event in August 1998

5.4.5 Episodic Recharge

A particularly wet January in 2000 caused episodic recharge for all bores with data available. The

month had 129mm of rainfall compared to a long-term average of 11mm (section 5.3.1). The majority

of this rainfall was due to three events: an 8 hour, <1 year ARI event (20mm); a 10 hour, 10 year ARI

event (51mm) and a 3 hour, 5 year ARI event (22mm) within 16 days of each other. Recharge

occurred in all bores in the nested site and in 7C and 8C (10C and 11C have no data). Figure 36 shows

the response of bores 7C and 8C. The upslope bore 7C shows a neutral trend in the three months

leading up to January with a clear upward trend in the months afterwards. The downslope bore 8C

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Results 

shows an immediate response to the 10 year ARI event during a period of declining groundwater

heads following a seasonal peak in September 1999. The groundwater recharge in January 2000 is the

only occurrence of episodic recharge in the Cuballing catchment for the study record.

 

Figure 36 Groundwater response of Cuballing bores 7C and 8C to 129mm of monthly rainfall in

January 2000

5.5 Groundwater Recharge in East Perenjori

Groundwater response to rainfall in the East Perenjori catchment can be summarised as follows:

• The lower valley and valley floor bores (EPC1, 7C, 8B, 8C and MS5) showed seasonal patterns of

recharge and discharge with a delayed response to rainfall;

• The seasonal pattern of the intermediate (8B) and deep bores (8C) varied temporally;

• High intensity events caused quick recharge responses in the lower valley and valley floor bores;

• A rainfall event in 1999 caused substantial rise in the water table of the shallow bore (8A) and

significant recharge in the upslope bores (9C and 20C).

These responses are discussed further in the remainder of this section.

 

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Results 

5.5.1 Seasonal Response

The valley floor bores in the catchment show a seasonal pattern of increasing and decreasing

groundwater levels. These alternating periods of recharge and discharge for the bores 8B, 8C and 7C

are shown in Figure 37 for the entire period of record. The peaks and troughs of the nested site don’t

show a temporally consistent match between the intermediate and deep groundwater records. In 1998

and 2008 the peaks and trough are out of sync in terms of timing and magnitude. In 2006 to 2007 the

timing of the peaks and troughs correlate well as evident in Figure 37. Downslope deep bore 7C

shows a seasonal pattern of recharge and discharge, the timing of which is consistent with 8C during

the period 1999 to 2007. Water levels for the deeper bores peak in February and March and reach

their lowest points in August and September. A delay between rainfall and groundwater recharge is

evident as the majority of rainfall occurs in winter (Figure 31) but piezometric heads don’t peak until

late summer and early autumn.

 

Figure 37 Seasonal groundwater fluctuations of East Perenjori bores 8B, 8C and 7C over the 11

years of record

5.5.2 High Intensity Events

The 100 year ARI event in 2004 had a varied groundwater response for the different bores in the East

Perenjori catchment. The 1 hour event took place in February 2004 and the corresponding

groundwater levels for that year in bores EPC1, 7C and 20C are shown in Figure 38. The response of

the shallow groundwater to this event is not known as there is no data for the intermediate bore in the

nested site and the shallow observation bore was dry. The midslope bore EPC1 rose approximately

0.1m following this event. The downslope bore 7C showed an increased rate of rise after the rainfall

event and subsequently rose 0.3m. Both EPC1 and 7C had relatively quick responses to this event.

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Results 

The upslope bore 20C showed no significant response to this event, as shown in Figure 38, which is

the same as the response in the other upslope bore 9C (Appendix A). High intensity events caused

quick responses in lower valley and valley floor bores but limited response in the upper slope bores.

 

Figure 38 Groundwater response of East Perenjori bores EPC1, 7C and 20C to a 1 hour, 100

year ARI event in February 2004

5.5.3 Episodic Recharge

Significant groundwater recharge occurred in 1999 and was observed in all the bores throughout the

catchment. As the rain gauge for the catchment did not record any data, the interpolated rainfall data

was used and the intensity of the event is unknown. The interpolated rainfall shows that 125mm fell

over three days in May 1999. The long-term average rainfall for May is only 42mm. The shallow

observation bore 8A went from being dry to rising 0.8m in 2 days. The water table remained at this

level for a month before slowly discharging over the remainder of the year. The deep midslope bore

EPC1 showed a prolonged response to the event, rising around 0.4m over 3 months before the logger

failed. The deep upslope bore 9C showed a continual rise over 12 months with the piezometric head

increasing by 1.3m. Since mid-2000 the bore has slowly discharged over time with no significant

response to rainfall since. The other upslope bore 20C shows a similar response as 9C with a steady

rise over a year followed by a slow discharge (Appendix A).

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Results 

 

Figure 39 Groundwater response of East Perenjori bores 8A, EPC1 and 9C to a 125mm over 3

days in May 1999

A wetter than average January in 2006 had a variable effect on groundwater recharge throughout the

catchment. Of the two upslope bores 9C and 20C, only 20C showed a recharge response to the 63mm

6 hour, 20 year ARI event (Figure 40). Beginning in March, the piezometric head for 20C rises 0.4m

over twelve months. The head in bore 9C does not show any response to the event and continues its

long-term declining trend. Where data was available, the lower valley and valley floor bores showed

increased rates of recharge (Appendix A). The January 2006 event caused episodic recharge in only

one of the upslope bores.

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Results 

 

Figure 40 Hydrographs of East Perenjori bores 9C and 20C for 1998 to 2008

5.6 Hydraulic Conductivity

The results of the bail-down tests for the Cuballing bores are shown in Table 9. The results show that

hydraulic conductivity increases along the flow path from 7C to 5C. At the nested site, the hydraulic

conductivity of the deeper aquifer 5C is an order of magnitude greater than the unconfined aquifer 5B.

See Appendix C for plots of relative drawdown versus time for each of the bores tested.

Table 9 Hydraulic conductivities calculated using bail-down tests for selected bores in the

Cuballing catchment

Bore Hydraulic 

Conductivity (m/day) 

5B  0.04 

5C  0.3 

6C  0.1 

7C  0.07 

8C  0.01 

5.7 HARTT

HARTT-XLS was used to determine the lag times between rainfall and groundwater rise. Table 10

shows the results for bores in the Cuballing site. The R2 values for bores 5B and 5C are 0.34 and 0.09

respectively, indicative of low relationships between the predicted monthly delay and groundwater

rise. The R2 values for the remaining bores are equal to or greater than 0.88, demonstrating a strong

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Results 

degree of fit between the monthly lag delay and the groundwater levels. The delay between rainfall

and groundwater response varied from 2 months for the downslope bore 8C to 3 or 4 months for the

upslope bores 7C, 10C and 11C.

Table 10 Results of HARTT analysis for Cuballing bores

Bore Residual Rainfall Type

Best Fit Delay

(months) R2

CUB 5B  AARR  1  0.34 

CUB 5C  AARR  0  0.09 

CUB 7C  AMRR  4  0.96 

CUB 8C  AARR  2  0.88 

CUB 10C  AMRR  4  0.90 

CUB 11C  AARR  3  1.00 

The results of the HARTT statistical analysis for the bores in the East Perenjori catchment are shown

in Table 11. The R2 values for all the bores are less than 0.7, indicative of weak relationships between

rainfall and groundwater response. Downslope bores EPC1 and 7C had higher R2 values (0.65 and

0.55, respectively) than the remaining five bores, however the general relationship is weak.

Table 11 Results of HARTT analysis for East Perenjori bores

Bore Residual Rainfall Type

Best Fit Delay

(months)R2

EPRJ EPC1  AMRR  2  0.65 

EPRJ MS5  AMRR  1  0.39 

EPRJ 7C  AMRR  1  0.55 

EPRJ 8B  AMRR  2  0.18 

EPRJ 8C  AMRR  2  0.37 

EPRJ 9C  AARR  2  0.12 

EPRJ 20C  AMRR  6  0.07 

 

5.8 Water Balance

The results of the water balance for the unconfined aquifer in Cuballing is shown in Table 12. The

results show that the recharge periods range from 24 to 101 days. All terms in the water balance have

been normalised to a per day value to account for the different length of recharge period. The change

in storage for each recharge period is highly variable with recharge varying from a low of less than

400m3/day in 2005 to a high of 8000m3/day in 2001. The leakage terms vary from negative (water is

being discharged upwards adding to the storage of the unconfined aquifer) to positive. The unknown

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Results 

‐ 58 ‐ 

terms in the water balance (throughflow and runoff) are lumped together in the final column of the

table and vary from 456m3/day to 6976m3/day.

Table 12 Results of water balance for unconfined aquifer in Cuballing

Start Date End Date No. Of Days

Change in Storage (∆QS,B)

[m3/day]

Rainfall (R) –

Evaporation (E) [m3/day]

Leakage out of

Aquifer (QL)

[m3/day]

Throughflow (QT,Bin - QT,Bout) and Runoff (Ro)

Required [m3/day]

15/06/1998 5/09/1998 82 2,197 1,163 -4.7 1,029 15/06/2000 10/08/2000 56 2,617 1,372 0.3 1,245 1/08/2001 25/08/2001 24 8,337 1,358 0.5 6,979 20/07/2004 10/09/2004 52 2,790 574 0.6 2,217 5/05/2005 23/06/2005 49 395 1,229 3.8 1,866 6/07/2006 15/10/2006 101 830 374 -0.4 456 20/06/2007 31/08/2007 72 2,529 868 9.8 1,671

The water balance for the semi-confined aquifer in the Cuballing nested bore site is shown in Table

13. The recharge periods for the deeper aquifer all exceed 80 days, which is longer than the recharge

periods of the shallow aquifer, where only two periods exceed 80 days. The throughflow into the

system (17 to 18 m3/day) does not vary greatly during the recharge periods. The leakage term for the

deep system displays the same fluctuations as illustrated in Table 12 for the unconfined aquifer. In

this case, the negative leakage removes water from the deeper aquifer as it is discharged upwards.

Table 13 Results of water balance for semi-confined aquifer in Cuballing

Start Date End Date No. Of Days

Change in Storage (∆QS,C)

[m3/day]

Leakage into

Aquifer (QL)

[m3/day]

Throughflow into Aquifer

(QT,Cin) [m3/day]

Throughflow out of

Aquifer Required (QT,Cout) [m3/day]

14/06/1998 15/10/1998 123 18 -2.4 17 -3 30/05/1999 7/10/1999 130 23 -3.4 17 -9 12/06/2000 5/09/2000 85 24 -0.3 17 -7 31/07/2001 21/10/2001 82 18 18.8 18 18 30/05/2004 10/11/2004 164 12 0.3 17 5 23/04/2005 25/10/2005 185 16 4.9 17 6 6/07/2006 11/10/2006 97 6 13.0 17 24 10/07/2007 9/10/2007 91 24 13.5 17 6

Discussion 

6 DISCUSSION

6.1 Barometric Pressure Correction

Two alternative methods of correcting piezometer levels for barometric pressure fluctuations were

applied with varying degrees of success. Calculated BE’s for the nested bores in Cuballing (Table 5)

indicated that BE increases as the level of confinement in the bore increases, in agreement with the

results of Salama et al. (1993b). For the unconfined aquifer (5A), Salama et al. (1993b) found that

there was a minimal response to barometric pressure but the intermediate (5B) and deep semi-

confined (5C) aquifers had BE’s within the range of 0.42 to 0.65 and 0.59 to 0.70, respectively. In

comparison, the average BE’s calculated for the intermediate and deep aquifers were 0.10 and 0.23,

respectively (section 5.2).

The significant difference in the magnitude of the calculated BE’s in Table 5 and the published values

of Salama et al. (1993b) can be attributed to the barometric pressure data being taken from a weather

station 107km away from the catchment whereas Salama et al. (1993b) used barometric pressure

measurements from within the catchment itself. It is likely the spatial and temporal variation in

pressure within the catchment and that at the nearest weather station is significant enough to reduce

the accuracy in calculating BE.

The temporal variation of BE evident in Table 5 complicated attempts to use the BE method to correct

piezometric heads. As the BE of a well was not constant, attempts to use the BE as a correction factor

for piezometer levels may not reflect the true barometric pressure independent groundwater level due

to averaging of the BE over time. If the BE for 5C was calculated over the years 1998 and 1999, an

average result of 0.12 would be attained however if the period used was 2003 and 2004, the BE would

be 0.29. The wide variation in these two results would significantly affect the corrected piezometric

heads when using equation 7. Due to the variability of the BE of a well, the BE method is not suitable

for correcting long-term piezometer levels (M Smith, DAFWA, pers. comm.). Toll & Rasmussen

(2007) acknowledge the transient nature of the BE of a well and Spane (2002) has shown that the

multiple regression method removes more noise than the BE method. Consequently, the BE method

was not used to correct piezometer levels for pressure fluctuations in favour of the multiple regression

method.

The water levels in the shallow and intermediate observation bores responded differently to changes

in barometric pressure. The shallow observation bores showed limited response to barometric pressure

as determined by its low BE (Table 5) and by visual observation of the hydrograph (Figure 22). Water

levels in the intermediate observation bores did respond to variations in barometric pressure for both

catchments. As these bores are screened across their entire length, changes in atmospheric pressure

should have no influence on the groundwater levels as the pressures are in equilibrium (Hiscock 2005;

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Discussion 

Gonthier 2007). The response of the intermediate aquifer to barometric pressure can either be

attributed to air bubbles in the aquifer responding to pressure variations (Brassington 2007) or a low

pneumatic diffusivity of the vadose zone (Spane 2002). Salama et al. (1993b) suggests that the 0.6m

“grey gritty clay” layer described in the bore logs for Cuballing (Salama et al. 1992), is acting as a

semi-confining layer. This is not believed to be the case as the hydrographs for the two observation

bores 5A and 5B react identically when the water table rises high enough to flow into 5A (Appendix

A). This is as expected due to the two bores being screened across their entire length. For this reason,

5A and 5B both monitor the water table at the site and the response to barometric pressure in 5B is

due to air bubbles or the properties of the vadose zone.

The multiple regression method did not completely remove the influence of barometric pressure on

piezometric heads but did diminish the magnitude of the variability that could be attributed to

barometric fluctuations (Figure 25 and Figure 27). Previous research by Rasmussen & Crawford

(1997), Spane (2002) and Toll & Rasmussen (2007) has shown that the multiple regression method is

capable of removing most of the noise attributed to barometric pressure from piezometric head

measurements. These studies all used piezometer levels monitored using pressure transducers and

barometric pressure measured in the same catchment as the groundwater bores.

The limited success of the multiple regression method can be partly attributed to the use of

capacitance probes to monitor piezometric head. Although the probes claim to have an accuracy of

±0.8mm (Dataflow Systems 2009), investigations by DAFWA field technicians have shown that the

accuracy is substantially reduced due to factors such as silt and condensation build up on the probes

(B. Cohen, DAFWA, pers. comm.). The probes therefore require frequent cleaning and calibration to

ensure their accuracy. The need to calibrate groundwater levels measured by capacitance probes to

field measurements as described in section 4.2.2, highlights the inaccuracies inherent with these

instruments.

6.2 Groundwater Recharge in Cuballing

6.2.1 Shallow Aquifer

The intermediate observation bore in Cuballing showed a seasonal pattern of recharge and discharge

(Figure 32). In a typical year, the bore showed four phases of groundwater response, as shown in

Figure 41 for a representative ‘cycle’ in 1998. Rainfall during the initial ‘wetting up’ phase does not

contribute to any groundwater rise but adds to soil pore water. In the recharge phase, groundwater

responds rapidly to rainfall inputs until the profile becomes saturated. Once saturated, the

groundwater levels remain saturated for a period of 1 to 2 months, even in the absence of subsequent

rainfall. As rainfall begins to decrease in the drier months beginning in October, the water table

begins to fall as groundwater is discharged via throughflow and evaporative loss.

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Discussion 

 

Figure 41 Phases of groundwater response in the intermediate observation bore Cuballing 5B

from April 1998 to March 1999

The recharge dynamics of the shallow groundwater system can be attributed to upslope saturation and

hillside seepage. The soil profile in the nested bore site remains saturated during the winter period,

irrespective of continuing rainfall. This is due to runoff from hillside seeps upslope contributing water

downslope. This maintains saturation in the lower slopes. Bedrock at bore 6C (see Figure 8 for

location) is only 3.7m below ground surface compared to over 20m in 5C and 7C (Salama et al.

1992). This basement high forces the water table to the surface and in wet periods contributes to

hillside seepage. Although there are no shallow monitoring bores upslope to verify the saturation

dynamics, a site visit in September 2009 confirmed the occurrence of upslope hillside seepage

contributing runoff into the site of the nested bores as shown in Figure 42.

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Discussion 

 

Figure 42 Hillside seepage in Cuballing occurring upslope of the nested bore site (September

2009)

Two types of quick water table responses were evident in the observation bore 5B throughout the

study period. The first type of quick response is a rapid and significant rise within hours of a rainfall

event followed by an equally rapid decline in groundwater level (Figure 33). This response can be

attributed to the reverse Wieringermeer effect, where water in the capillary fringe is converted into

phreatic water in response to a very small amount of rainfall (Gillham 1984). This occurs when the

capillary fringe extends almost to the ground surface. The addition of a very small amount of water is

able to fill the menisci of soil pores and convert water that is normally held in place by surface tension

forces into phreatic water (Heliotis & DeWitt 1987). The rapid rise in the water table is followed by

an equally rapid decline (O'Brien 1982). As the water table in the nested site in Cuballing is normally

within 2m of the land surface, it is likely that the capillary fringe extends to the ground surface. The

reverse Wieringermeer effect explains the rapid rises and declines in water table in the Cuballing

nested site.

The second form of rapid water table response occurred when the water level increased by up to 1.2m

in 24 hours and remained high for months after the rise. As the soil profile remained saturated

following the rapid rise, the reverse Wieringermeer effect does not explain this rapid response. The

‘water deficits’ shown in Table 8 shows that in situ rainfall alone is not sufficient to cause these

sudden rises. A combination of hillside seepage and run-off from upslope parts of the catchment must

be contributing to recharge downslope.

The rainfall events were likely to cause saturation upslope, which then contributed to a rapid rise

downslope. If the January 2000 event is ignored, the rainfall events are all low intensity (<1 to 2 year

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Discussion 

ARI) and long duration (12 to 72 hours). These events also occurred during winter where antecedent

moisture conditions are high. The low intensity events in combination with high initial moisture

contents saturated the subsurface and recharged the shallow groundwater via matrix flow. High

intensity events exceed the infiltration capacity of the soil and most of the rainfall will runoff via

overland flow into the ephemeral stream. The low intensity events saturated the upslope areas causing

saturation excess run-off and hillside seepage due to the basement high. The surface runoff then flows

downhill towards the nested site contributing to the initial rapid recharge and continuing saturation

when rainfall ceases.

The rapid response of the water table is likely to be due to preferential flow paths rather than matrix

flow. The nested site is surrounded by riparian vegetation bounding the ephemeral stream. It is likely

that infiltrating water is following vegetation roots which cause the quick rises. Similar rapid water

table rises were attributed to a combination of matrix flow and preferential pathways by Lewis &

McConnell (1998) in a similar wheatbelt catchment. Johnston (1987) used chloride tracers to show

that observed groundwater recharge was orders of magnitude higher than calculated vertical soil water

flux in rejuvenated zone catchments. This difference was attributed to preferential flow paths and

textural heterogeneities in the regolith. As there were no shallow monitoring bores upslope in the

catchment, it is unknown whether these rapid responses were only experienced in the downslope

observation bores.

6.2.2 Deep Aquifers

Recharge in the semi-confined downslope aquifers (5C) was mostly event driven rather than episodic.

Groundwater recharge occurred during the wet winters and discharge occurred during the dry

summers. The similar recharge response times in the shallow and semi-confined bores show the

strong hydraulic connectivity between the two (Figure 32). The head difference between the two

suggests that the deeper aquifer discharges upwards into the shallow aquifer for most of the year.

When the soil profile is saturated, the head in the shallow bore exceeds that in the deep aquifer and

leakage across the semi-confining layer causes recharge. The two aquifers begin to recharge at similar

times irrespective of the head difference between the two. This suggests that either the bentonite seal

around the bore casing of 5C is leaking or that recharge is occurring via preferential pathways through

the semi-confining layer. Leakage through the bentonite seal is unlikely as the pressure head in 5C has

caused the water in the bore to rise to ground surface, which would not be possible if the seal was

leaking (see Figure 32). The quick response to rainfall events in the winter supports the idea that

preferential flow is the dominant recharge mechanism in the nested bores as matrix flow would cause

a delayed groundwater response.

The seasonal groundwater response for the nested bores caused the HARTT analysis to show a weak

correlation (R2) between the rainfall delay and groundwater changes (Table 10). This is due to the

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Discussion 

bores not being responsive to wetter than average months due to the soil profile becoming saturated

and any further rainfall becoming runoff. If the bores did not show a seasonal pattern of recharge and

saturation, the piezometric heads would follow the accumulative residual rainfall and rise during

wetter than average periods and fall in drier periods. Only in drier years are variations in levels

evident as the magnitude of the winter rise is subdued. This prevented HARTT from accurately

predicting lag times between rainfall and groundwater rise.

The four deep piezometers 7C, 8C, 10C and 11C showed strong HARTT correlations between rainfall

and groundwater changes (Table 10). The upslope bores (7C, 10C and 11C) showed 3 and 4 month

delays between rainfall and groundwater changes whereas the downslope bore 8C showed a 2 month

delay. The longer delays in the upslope bores suggest that matrix flow is the dominant recharge

process for these bores. As these aquifers are around 20m below the ground surface, matrix flow

through the regolith profile would cause delayed effects of rainfall. The quicker response in 8C is

likely due to a combination of matrix and macropore flow. As the bore is downslope, the shallow

water table is likely to become saturated due to run-on from hillside seepage and rainfall excess as

shown for 5B. The increased head in the shallow aquifer leads to higher vertical hydraulic gradients

and quicker groundwater response times.

6.3 Groundwater Recharge in East Perenjori

6.3.1 Upslope Bores

The dominant recharge mechanism for the upslope bores was direct recharge via matrix flow after the

surface became saturated. The upslope bores 9C and 20C only experienced recharged in response to

large rainfall events. The event in May 1999 was sufficient to saturate the entire catchment and cause

episodic recharge. This is shown by the development of the perched water table monitored by 8A in

the valley floor (Figure 39). The prolonged recharge seen in 9C and 20C can be attributed to matrix

flow in the coarse textured soils of this part of the catchment, as described by Henschke (1989). A

quicker response would have been observed if preferential flow was occurring. As these bores are

upslope in the catchment there is limited opportunity for run-on or throughflow to contribute indirect

recharge into these areas. Consequently, direct recharge occurred with in situ rainfall from the event

percolating through the regolith. The slow decline of piezometric head over several years after the

event demonstrates the low gradients of the system and its reduced ability to discharge water.

The rainfall event in January 2006 was not sufficient to saturate the entire catchment. Only bore 20C

showed evidence of recharge and the shallow water table in 8A remained dry. Recharge did not occur

in bore 9C as it is located higher in the catchment than 20C (Figure 21). Accordingly, it is inferred

that only the lower part of the catchment was saturated by this event. The valley floor bores did show

evidence of recharge in response to this event (Appendix A). The occurrence of episodic recharge in

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Discussion 

the upslope bores of the East Perenjori catchment is dependent on the type of rainfall event and

whether the topsoil is saturated.

6.3.2 Lower Valley Bores

The variable response times to rainfall in the lower valley and valley floor bores demonstrates two

components of recharge to the deep aquifer. The delayed response to rainfall in the seasonal recharge-

discharge patterns (Figure 37) show that recharge in the deep aquifer is occurring upslope in the sandy

textured soils (Henschke 1989). The low gradients of the system result in the delayed groundwater

rise in the valley floor. The second recharge component is a quick response to large rainfall events

(Figure 38). This is attributed to preferential flow of direct recharge from rainfall and indirect

recharge from surface runoff. Rhodamine dye tests by Henschke (1989) showed that most of the water

flow in the fine textured soils of the catchment was due to fractures and fine root channels. The lower

valley and valley floor bores show differing recharge responses depending on the type of rainfall

event.

The HARTT analyses did not show any significant relationship between the delayed effects of rainfall

and groundwater rise with very low correlation coefficients for all bores (Table 11). This is due to the

two recharge components having variable response times to rainfall inputs. The slow response to

upslope recharge is in direct contrast to the quick response of event-based recharge. Additionally,

Ferdowsian et al. (2001) hypothesise that variations in hydraulic conductivity could explain low

correlation coefficients as the rate of water movement is dependent on the level of saturation in the

regolith profile.

The degree of hydraulic connectivity between the shallow aquifer (8B) and the deep aquifer (8C) is

also dependent on the level of saturation in the regolith profile. As shown in Figure 37 the

connectivity between 8B and 8C varies temporally. This is related to rainfall with significant rainfall

events causing the topsoil to become saturated. In response, the shallow and deep aquifer become

hydraulically connected as surface water leaks downwards via macropores (Henschke 1989). The

occurrence of episodic recharge in the upslope bores corresponds to the times of hydraulic connection

between the shallow and regional aquifers (1999 and 2006). This shows that saturation of the surface

is required for macropore flow to become established.

6.4 Quantifying Recharge via a Simple Water Balance

The water balance approach to quantifying recharge fluxes did not adequately model the dynamics of

the Cuballing system. The water balance for the deep aquifer attempted to show that recharge into the

lower aquifer was either by leakage across the semi-confining layer or by throughflow from upslope.

QT,Cin (Table 13, column 6) was constant over time as the changes in piezometric head in the upslope

bore 7C was negligible compared to the difference in elevation head between 5C and 7C.

‐ 65 ‐ 

Discussion 

‐ 66 ‐ 

Accordingly, the seasonal variations in head for the semi-confined aquifer 5C cannot be attributed to

increased throughflow into the system. QL was determined by the vertical hydraulic gradient between

5B and 5C. As discussed in section 6.2.2 the head difference suggests alternating periods of discharge

upwards and leakage downwards across the semi-confining layer. Some periods of recharge in the

deep aquifer coincided with discharge upwards, resulting in negative leakage as shown in Table 13,

column 5. The unknown component QT,Cout varied depending on the magnitude and direction of the

leakage component. The simplified model of recharge via either leakage or throughflow was not able

to quantify the dominant process in the deep aquifer.

The water balance for the shallow aquifer was not able to quantify the contribution of runoff or

throughflow to recharge. The unknowns of QT,Bin, QT,Bout and Ro were combined due to no data

available for any of these terms. Consequently, the water balance only shows that in situ rainfall was

not sufficient to cause the observed rises in groundwater level during each recharge period. The

relative contributions of indirect recharge via throughflow and runoff could not be determined.

Monitoring of streamflow in the ephemeral stream in the centre of the catchment (Figure 8) would

allow the runoff component of the water balance to be more accurately represented in equation 14.

Estimates of subsurface throughflow in the shallow aquifer required monitoring of the shallow

upslope bores to calculate hydraulic gradients. Due to limitations in the data available, accurate

quantification of the impact of surface runoff on groundwater recharge was not realised.

A significant issue in estimating recharge to the two aquifers is the assumed values for storage

coefficient. Both the shallow and deep water balance equations calculated ΔQS using estimated

storage coefficients for the two systems (equation 16). The storage coefficient for each aquifer was

determined based on order of magnitude estimates by Salama et al. (1994), as described in section

4.7.1. Accurate calculations of recharge rates are very sensitive to variations in the storage parameter

(Healy & Cook 2002). Consequently, the ΔQS term in the water balances did not accurately reflect the

volume of water required to cause the observed changes in piezometric head. In addition the storage

coefficient in unconfined aquifers is not constant and can vary depending on the speed of water table

fluctuations (Vukovic & Soro 1992). The dynamic nature of the storage coefficient was not modelled

by the static water balance.

The water balance approach to quantifying the effect of surface runoff on episodic recharge was a

simplified attempt to model the recharge dynamics. The static equations calculated on a daily timestep

were not able to capture the dynamic processes of water movement in the catchment. Insufficient data

to quantify shallow throughflow, surface runoff and storage coefficients led to assumptions being

made that were not

 

Conclusions 

7 CONCLUSIONS An understanding of groundwater recharge dynamics is critical to managing groundwater rise and

preventing land salinisation. This study has shown that groundwater recharge in the Cuballing and

East Perenjori catchments are both event driven but governed by different processes. The Cuballing

catchment experienced seasonal downslope saturation due to hillside seepage and surface runoff. This

increased rates of recharge to deep aquifer in the downslope areas. The downslope bores in the East

Perenjori also exhibited seasonal patterns but saturation occurred irregularly. When saturation did

occur, recharge rates in the valley floors increased due to macropore flow and significant recharge in

the upper slope bores occurred via matrix flow.

Predictions for changed rainfall regimes in the future will alter the recharge dynamics for these sites.

Predicted reductions in mean annual rainfall will reduce the likelihood of antecedent conditions being

sufficient to cause surface saturation in both catchments. Consequently, episodic recharge is likely to

be less significant in the future. Current trends show that groundwater tables across the wheatbelt are

falling (George et al. 2008). If these trends continue, previous predictions of 4.4 million hectares of

land becoming saline are unlikely to eventuate. Future management strategies should incorporate

predictions for less recharge than that observed in the past.

This study qualitatively described the recharge mechanisms observed in these two catchments.

Attempts to quantify the proportion of episodic recharge attributable to surface runoff were limited by

data availability. Future research should be aimed at better understanding the hydrological dynamics

of wheatbelt catchments. This will enable more accurate conceptual models to be developed and

predictions can be made according to reduced rainfall in the future.

‐ 67 ‐ 

Recommendations 

8 RECOMMENDATIONS This study has highlighted the need for appropriate monitoring and instrumentation when

investigating groundwater recharge processes. A complete understanding of interactions between the

shallow and deep aquifers throughout the catchment was limited by the availability of shallow

groundwater data at only one nested site in each catchment. This is a result of the monitoring program

of the site being designed to investigate regional groundwater trends. Monitoring of shallow water

tables throughout the catchment is recommended to further determine the role of vertical hydraulic

gradients and surface saturation in recharge to the deep aquifers.

To accurately quantify the impact of surface water runoff on recharge, monitoring of streamflow and

surface water is required. This would elucidate the rainfall-runoff relationship of each catchment and

could be used to determine what kind of rainfall events result in mostly infiltration and which events

are more likely to cause runoff. The streamflow data could be used to determine baseflow due to

groundwater seepage and surface water loggers could identify periods and depths of ponding. This

information is essential to water balance modelling of the components of groundwater recharge.

It is recommended that continuous monitoring of piezometric heads be undertaken with pressure

transducers. The data used in this study was provided by capacitance probes which are prone to

inaccuracy due to the build up of residue and silt during normal operations. These probes require

frequent calibration to maintain accuracy. Pressure transducers are less susceptible to errors and

require less frequent calibration. Some instruments can also be used to monitor barometric pressure

variations within the catchment. This is essential to effectively removing the effect of barometric

pressure on piezometric heads.

Future studies into groundwater recharge processes should include dynamic modelling of infiltration

and subsurface water flow. The static water balance approach used in this study did not simulate the

dynamic nature of recharge and water movement between aquifers. The use of 3D finite element

models such as MODFLOW or HYDRUS 3D is recommended to simulate the variable nature of

water movement between saturated and unsaturated flow.

‐ 68 ‐ 

References 

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Appendix A – Groundwater Hydrographs  

APPENDIX A

GROUNDWATER HYDROGRAPHS

‐ A1 ‐ 

Appendix A – Groundwater Hydrographs  

 

Figure A1 Cuballing bores 5A, 5B and 5C

‐ A2 ‐ 

Appendix A – Groundwater Hydrographs  

 

Figure A2 Cuballing bores 7C and 8C

‐ A3 ‐ 

Appendix A – Groundwater Hydrographs  

 

Figure A3 Cuballing bores 10C and 11C

‐ A4 ‐ 

Appendix A – Groundwater Hydrographs  

 

Figure A4 East Perenjori bores 8A, 8B and 8C

‐ A5 ‐ 

Appendix A – Groundwater Hydrographs  

 

Figure A5 East Perenjori bores EPC1, MS5, 7C

‐ A6 ‐ 

 

Appendix A – Groundwater Hydrographs  

‐ A7 ‐ 

Figure A6 East Perenjori bores 9C and 20C

Appendix B – Maximum Response Times 

APPENDIX B

MAXIMUM RESPONSE TIMES

‐ B1 ‐ 

Appendix B – Maximum Response Times 

‐ B2 ‐ 

Table B1 Selected maximum response times for barometric pressure correction

Bore  MRT (hours) 

5A  N/A 

5B  10 

5C  12 

7C  6 

8C  6 

10C  15 

11C  18 

Table B2 Selected maximum response times for barometric pressure correction

Bore  MRT (hours) 

1C  18 

MS5  12 

7C  15 

8A  N/A 

8B  18 

8C  12 

9C  6 

20C  12 

Appendix C – Bail‐Down Plots  

APPENDIX C

BAIL-DOWN PLOTS

‐ C1 ‐ 

Appendix C – Bail‐Down Plots  

 

y = 1.0317e‐0.002x

R² = 0.9951

0.1

1

0 100 200 300 400 500 600 700

Head Ra

tio (H

/H0)

Time (s)

Figure C1 Relative drawdown over time for Cuballing bore 5B

 

Figure C2 Relative drawdown over time for Cuballing bore 5C

y = 0.9867e‐0.008x

R² = 0.997

0.01

0.1

1

0 50 100 150 200 250 300 350 400

Head Ra

tio (H

/H0)

Time (s)

‐ C2 ‐ 

Appendix C – Bail‐Down Plots  

 

y = 0.9251e‐0.004x

R² = 0.98

0.1

1

0 50 100 150 200 250 300 350

Head Ra

tio (H

/H0)

Time (s)

Figure C3 Relative drawdown over time for Cuballing bore 6C with the tailing effect

 

Figure C4 Relative drawdown over time for Cuballing bore 6C without the tailing effect

y = 0.9911e‐0.005x

R² = 0.9989

0.1

1

0 20 40 60 80 100 120 140 160

Head Ra

tio (H

/H0)

Time (s)

‐ C3 ‐ 

Appendix C – Bail‐Down Plots  

‐ C4 ‐ 

y = 0.9601e‐0.002x

R² = 0.9978

0.1

1

0 100 200 300 400 500 600 700

Head Ra

tio (H

/H0)

Time (s)

Figure C5 Relative drawdown over time for Cuballing bore 7C

Figure C6 Relative drawdown over time for Cuballing bore 8C

y = 0.9982e‐3E‐04x

R² = 0.9976

0.1

1

0 500 1000 1500 2000 2500 3000 3500

Head Ra

tio (H

/H0)

Time (s)

Appendix D – IFD Curves 

APPENDIX D

IFD CURVES

‐ D1 ‐ 

Appendix D – IFD Curves 

 

Figure D1 IFD Curve for Cuballing

‐ D2 ‐ 

Appendix D – IFD Curves 

‐ D3 ‐ 

 

Figure D2 IFD Curve for East Perenjori