CHOWILLA MODEL 2012

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CHOWILLA MODEL 2012

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Our ref: A191B/R002d Date: 8 May 2012

CHOWILLA MODEL 2012

Document Status

Issue Date Purpose of Document

Revision A 11 November 2011 Draft for Comment

Revision B 11 January 2012 Updated Draft for Comment

Revision C 2 March 2012 Final Draft for Comment

Revision D 8 May 2012 Final Report

Name Position Signature Date

Author Virginia Riches Modeller/Hydrogeologist 8 May 2012

Reviewer Hugh Middlemis Senior Principal 8 May 2012

Disclaimer This document is and shall remain the property of RPS Aquaterra. The document may only be used for the purposes for which it was commissioned and in accordance with the Terms of Engagement for the commission. Unauthorised copying or use of this document in any form whatsoever is prohibited.

A191B/R002d DOCUMENT STATUS / DISCLAIMER

CHOWILLA MODEL 2012

EXECUTIVE SUMMARY

The Chowilla Floodplain (along with the Lindsay-Wallpolla floodplain upstream) forms one of six Icon Sites identified as part of The Living Murray (TLM) initiative for improving environmental flows. The preferred long-term management option for the Chowilla Floodplain is to construct an environmental regulator on lower Chowilla Creek, and smaller ancillary structures on bypass flow routes, for the purpose of environmental watering. As part of salinity accountability obligations under the Basin Salinity Management Strategy (BSMS), the operation of the environmental regulator must be assessed for its salinity impacts. The Chowilla Groundwater Model has been used previously to examine the potential impacts of the environmental regulator (Howe et al 2007). However, reviews of this work identified key uncertainties in the input data (Salient Solutions, 2008). These have been addressed in the Chowilla 2012 upgrade, and include: • Updated LIDAR topography which has resulted in changes to: - Surface topography; - Inundation area; - Stream levels; - Evapotranspiration (depth-dependent discharge from specified surface elevation); • Refinement of groundwater salinity zones based on AEM data; and • Clarification and documentation of the flood inundation recharge rates.

The Chowilla 2012 groundwater model achieved good calibration with the updated data and comparison to measured salt load data also confirmed the suitability of the model for investigating environmental watering scenarios (e.g. analysing the impact of the regulator). The scenario run was designed to assess the impact of regulator operation over the benchmark period (1975-2000). The results from this assessment indicated that: • 10,000 ML/day at 19.25 m AHD regulator events show the greatest increase in salt load to the river, with peak impacts (effect due to regulator) ranging from ~150 to 300 t/day. • The maximum peak impact of ~300 t/day occurs for the event in the year 2000 subsequent to the 10,000 ML/day at 19.25 m AHD regulator operation. • Impact on peak salt load of subsequent flooding events of up to ~100 t/day (most noticeable in the period between the 1987 and 1996 regulator events). • Salt load effects (above base case) due to a regulator event recedes over a period of about one year (roughly same as for Chowilla 2007), but can be interrupted by a natural flood.

There remain acknowledged conceptual uncertainties and knowledge gaps relating to the detailed spatial and/or temporal distribution of floodplain hydrodynamics, stream bed conductance, groundwater salinity, salt washoff processes, salt loads and evapotranspiration complexities. However, the good match that has been achieved to measured groundwater levels and salt loads would indicate that the level of model simplicity that has been adopted is adequate for the purpose of the study.

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TABLE OF CONTENTS

1. INTRODUCTION...... 1 1.1 Project Background...... 1 1.2 Statement of Objectives ...... 1

2. HYDROLOGY AND HYDROGEOLOGY...... 2 2.1 Location...... 2 2.2 Climate ...... 2 2.3 Hydrology and Hydrogeology ...... 2 2.3.1 Previous Investigations ...... 2 2.3.2 Regional Hydrogeological Setting ...... 2 2.3.3 Hydrogeological Units ...... 7 2.3.4 Project Region Hydrology...... 14

3. CONCEPTUAL MODEL ...... 18 3.1 Chowilla Groundwater Model Development ...... 18 3.1.1 Model Documentation ...... 18 3.1.2 Model History ...... 18 3.2 Conceptual Model Key Features ...... 20 3.2.1 Hydrogeology, Interpretations and Assumptions...... 20 3.2.2 Surface Water ...... 20 3.2.3 Simplification of Surface Water Components ...... 22 3.2.4 Groundwater Recharge...... 25 3.2.5 Evapotranspiration Zones and Values...... 26 3.2.6 Groundwater Salinity...... 28 3.2.7 Salt Load Impacts to River Murray Channel due to Raising Lock 6 ...... 32 3.3 Knowledge Gaps and Conceptual Uncertainty...... 32

4. MODEL CONSTRUCTION ...... 34 4.1 Software Package ...... 34 4.2 Domain and Grid Design ...... 34 4.3 Model Layers...... 34 4.3.1 Surface Elevation ...... 34 4.3.2 Layer Structure and Hydrogeology...... 34 4.4 Aquifer and Aquitard Hydraulic Parameters ...... 41 4.5 Model Boundary Conditions ...... 42 4.5.1 Layer 1: Upper Monoman Formation & Pliocene Sands ...... 42 4.5.2 Layer 2: Lower Monoman Formation & Pliocene Sands ...... 44 4.5.3 Layer-3: Lower Pliocene Sands ...... 46 4.5.4 Layer-4: Bookpurnong Formation...... 46 4.5.5 Layer-5: Murray Group Limestone ...... 46 4.6 Recharge...... 46

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4.6.1 Dryland Mallee Recharge and Flushed Zone Floodplain Discharge...... 46 4.6.2 Floodplain Inundation Recharge...... 46 4.7 Model Stress Periods...... 46

5. MODEL CALIBRATION ...... 49 5.1 Steady State Model Calibration ...... 49 5.2 Transient Model Calibration...... 49 5.2.1 Semi-quantitative comparison of modelled potentiometric head distributions (contours) and observed potentiometric point data...... 49 5.2.2 Semi-quantitative comparison of modelled and observed potentiometric heads (hydrographs) ...... 49 5.2.3 Quantitative Assessments of the Scaled Root Mean Square (SRMS)...... 52 5.2.4 Iteration Residual Error...... 52 5.2.5 Mass Balance ...... 59 5.2.6 Salt Load Confirmation ...... 59 5.2.7 Salt Water Balance Model Verification ...... 62

6. PREDICTIVE SCENARIO RUNS ...... 66 6.1 Scenario Assessed...... 66 6.2 Model Inputs for the Scenario...... 66 6.3 Scenario Run Results ...... 66 6.4 Salt Water Balance Run Results ...... 72 6.5 Discussion of Scenario Results ...... 72 6.5.1 Groundwater Salinity ...... 77 6.5.2 Groundwater volumes and Related Salt Loads ...... 77

7. MODEL SENSITIVITY ANALYSIS...... 78 7.1 Variation to Specific Stress...... 78 7.1.1 Evapotranspiration...... 78 7.1.2 Anabranch Bed Conductance...... 83 7.2 Event Based Salt Load Analysis...... 83 7.3 Uncertainty in Measured and Modelled Salt Load data ...... 92 7.4 Conclusion as to the Drivers in the System ...... 92

8. SUMMARY/CONCLUSIONS...... 96 8.1 Model Improvements ...... 96 8.2 Results...... 96 8.3 Model Capability, Assumptions and Limitations...... 96 8.4 Recommendations...... 97

9. REFERENCES...... 98

10. GLOSSARY ...... 100

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TABLES Table 3.1: Chowilla Model Layers and Groundwater Flow System...... 20 Table 3.2: Anabranch Bed Conductance...... 25 Table 3.3: Inundation Recharge rates based on soil types (Overton et al, 2005) ...... 26 Table 3.4: Salinity statistics based on AEM data and Preliminary River reaches in EC (µS/cm)...... 32 Table 4.1: Model layer aquifers and aquitards...... 39 Table 4.2: MODFLOW layer types...... 39 Table 4.3: Calibrated model aquifer and aquitard hydraulic parameters ...... 41 Table 4.4: Water Levels in the Anabranches...... 44 Table 4.5: Inundation Areas Provided ...... 47 Table 5.1: Chowilla 2012 Mass Balance...... 59 Table 6.1: Water Levels in the Anabranch (Regulator Scenario)...... 67 Table 6.2: Changes in Murray River Salinity due to Regulator Events ...... 72

FIGURES Figure 1: Chowilla Floodplain and Model Area Location Plan (Yan et al) Figure 2: Satellite Photograph of Model Domain and Chowilla Floodplain (Yan et al, 2004) Figure 3: Pre River Locking, Creek and Groundwater Interaction (Yan et al, 2004) Figure 4: Post River Locking, Creek and Groundwater Interaction (Yan et al, 2004) Figure 5: Hydrogeological Cross Section (1 July 1995) (Yan et al) Figure 6: Conceptual Hydrogeological Cross Section (Yan et al, 2004) Figure 7: Measured Elevation of Groundwater Table, Monoman Sand and Pliocene Sands (Yan et al, 2004) Figure 8: Groundwater Salinity (mg/L) in the Monoman Formation across the Chowilla Floodplain Figure 9: Measured Potentiometric Head Contour Plan, Murray Group Limestone (Yan et al, 2004) Figure 10: Anabranch Creek with no permanent flow, believed to be common Pre-Locking (Yan et al) Figure 11: Post-Locking constant flow in Monoman Creek (Yan et al, 2004) Figure 12: Tree Death resulting from rising Groundwater Table and Salinisation Figure 13: Observed and Discetised River Murray Flow Hydrograph at Lock 6 (Howe et al) Figure 14: Anabranch Creek Grouping (Howe et al, 2007) Figure 15: Impacts of the Implementation of the River Murray in Chowilla 2011 Figure 16: Observed and Discretised River Murray Flow Hydrograph at Lock 6, Benchmark Period (ML/D) Figure 17: Flood Inundation Recharge Distribution and Rates for Specified Flow Rates Figure 18: Evapotranspiration from Watertable Figure 19: MOdelled Evapotranspiration Distribution Figure 20: Groundwater Salinity and River Reaches Figure 21: Model Domain (55km East to West, 45km North to South) (Yan et al, 2004) Figure 22: Model Grid (76.5m by 62.5m to 305m by 250m) (Yan et al, 2004) Figure 23: Ground Surface Elevation (LiDAR) Figure 24: Topography Specified in Model Figure 25: Chowilla Model Layers (Yan et al, 2004) Figure 26: Layer 1 Boundary Conditions Figure 27: Layers 2 and 3 Boundary Conditions Figure 28: Layer 5 Boundary Conditions Figure 29: Layer 1 Modelled Groundwater Contours Vs Observed Points at 2003 Figure 30: Chowilla Bore Locations Figure 31: Chowilla 2012 Calibration Hydrographs Figure 32: Chowilla 2012 Calibration Hydrographs Figure 33: Chowilla 2012 Calibration Hydrographs Figure 34: Chowilla 2012 Calibration Hydrographs

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Figure 35: Chowilla 2012 Calibration Statistics and Scatterplot - 1/05/2003 Figure 36: Chowilla 2012 Calibration Statistics and Scatterplot - 1/10/2003 Figure 37: Chowilla 2011 Measured and Modelled Saltload Figure 38: Measured Vs Modelled Cumulative Salt Load Figure 39: Comparison of Measured Salt Load to Modelled Salt Load Analysis Figure 40: Salt Water Balance Model Validation for the 1996 Flood Event Figure 41: Salt Water Balance Model Validation for the 2000 Flood Event Figure 42: Simplified Hydrograph with Regulator Events (Howe et al, 2007) Figure 43: Extent of Inundation for Regulator Events Figure 44: Inundation Areas for 10,000 ML/day Regulator Event and 40,000 ML/day Base Event Figure 45: Modelled Salt Loads and Impact for the Regulator Scenario Figure 46: Salt Water Balance Model for the 1980, 10,000 ML/day Regulator Event Figure 47: Salt Water Balance Model for the 1980, 10,000 ML/day Regulator Event Figure 48: Salt Water Balance Model for the 1980, 10,000 ML/day Regulator Event Figure 49: Salt Water Balance Model for the 1980, 10,000 ML/day Regulator Event Figure 50: Modelled Sensitivity Evapotranspiration Distribution - Rate and Extinction Depth Doubled Figure 51: Sensitivity of Salt Load to Evapotranspiration Figure 52: Cumulative Salt Load for Evapotranspiration Sensitivity Figure 53: Modelled Sensitivity Evapotranspiration Distribution - Rate Doubled Figure 54: Sensitivity of Salt Load to Anabranch Bed Conductance Figure 55: Cumulative Salt Load for Anabranch Bed Conuctance Sensitivity Figure 56: Chowilla 2012 Salt Loads for 40,000 ML/day Floods Figure 57: Chowilla 2012 Salt Loads for 60,000 ML/day Floods Figure 58: Chowilla 2012 Salt Loads for 100,000 ML/day Floods Figure 59: Sensitivity Analysis for Chowilla 2012 40,000 ML/day floods Figure 60: Sensitivity Analysis for Chowilla 2012 60,000 ML/day floods Figure 61: Sensitivity Analysis for Chowilla 2012 100,000 ML/day floods Figure 62: Modelled and Measured Salt Loads for 40,000 ML/day Floods Figure 63: Modelled and Measured Salt Loads for 60,000 ML/day Floods Figure 64: Modelled and Measured Salt Loads for 100,000 ML/day Floods

APPENDICES Appendix A: Documentation for LiDAR Appendix B: Surface elevation Contours Appendix C: Hydraulic Parameters Appendix D: Inundation Areas Appendix E: Model Stress Periods Appendix F: Scenario Hydrographs Appendix G: Sensitivity Hydrographs

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CHOWILLA MODEL 2012

1. INTRODUCTION

1.1 PROJECT BACKGROUND The Chowilla Floodplain (along with the Lindsay-Wallpolla floodplain upstream) forms one of six Icon Sites identified as part of The Living Murray (TLM) initiative for improving environmental flows. Chowilla Floodplain is important because it retains much of the area's natural character and attributes. It has a high diversity of terrestrial and aquatic habitats; supports populations of rare, endangered and nationally threatened species; as well as sites of cultural significance that are heritage protected. The area is also important for its recreational and economic values. The Chowilla floodplain is underlain by an aquifer with a shallow watertable and generally highly saline groundwater (except in certain near-River “flushed zones”), and has been well documented as a source of saline groundwater discharge to the River Murray – especially in the periods immediately following large flood events. The preferred long-term management option for the Chowilla Floodplain is to construct an environmental regulator on lower Chowilla Creek, and smaller ancillary structures on bypass flow routes, for the purpose of environmental watering. A draft proposal has been developed by Department for Water (DFW) for investing in detailed design for the Chowilla Creek environmental regulator. It highlights that the proposal represents the only practical way of curbing the rapid and widespread ecological decline currently being experienced on the Chowilla floodplain. DFW wish to investigate the potential local and ‘real time’ (or short term) salinity impacts of the operation of the regulator to inform downstream users of the potential impacts. In addition, as part of salinity accountability obligations under the Basin Salinity Management Strategy (BSMS), the operation of the environmental regulator must be assessed for its long term salinity impacts. In order to meet these requirements and estimate these impacts, a range of fit-for-purpose tools are required, including: • Hydrodynamic model (to identify surface water inundation extent-duration-magnitude); • Recharge/evapotranspiration model (biophysical conceptual model and related parameters); • Groundwater flow model (to integrate inputs/outputs to/from groundwater system); and • Salt and Water Balance (to help quantify real time salinity effects).

1.2 STATEMENT OF OBJECTIVES The objective of this project is to update the Chowilla groundwater flow model, including output from the hydrodynamic model (and recharge/ evapotranspiration model where appropriate), and use this model with the salt and water balance (SWB) tool to estimate potential local ‘real time’ impacts and the (long term) BSMS salinity accountability position. The Chowilla groundwater flow model was initially developed by DfW in 2004 (Yan et al, 2004), and the model history is described in detail in Section 3.

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2. HYDROLOGY AND HYDROGEOLOGY

2.1 LOCATION The Chowilla floodplain is approximately 50 km east of Renmark and is located adjacent to the River Murray in the northwest region of the Murray Basin. The floodplain occurs primarily in South Australia, but extends over the border into New South Wales (Figure 1) (Yan et al, 2004). The Chowilla floodplain was listed as a Riverland Wetland of International Importance in 1987 under the UNESCO Ramsar Convention (Yan et al 2004) as well as being designated a Significant Ecological Asset (or ‘Icon Site’) under the ‘The Living Murray’ (‘TLM’) programme for the Murray- Darling Basin (Overton et al, 2005). The water bodies and vegetation distribution of the floodplain and surrounding area are clearly distinguishable on satellite imagery (Figure 2) (Yan et al 2004).

2.2 CLIMATE The climate in the Chowilla Floodplain is semi arid with an average rainfall of approximately 260 mm/yr and a potential evapotranspiration of 2000 mm/yr (Overton and Jolly, 2004). There is a slight winter dominance in the yearly rainfall and annual rainfall is highly variable (Overton and Jolly, 2004).

2.3 HYDROLOGY AND HYDROGEOLOGY The hydrology that underpins the modelling has remained unchanged from the 2004 Chowilla Groundwater Model Report. The following descriptions (for this Section) are taken from Yan et al 2004, with some modifications.

2.3.1 PREVIOUS INVESTIGATIONS Numerous hydrological and hydrogeological investigations have been conducted in the region since the commencement of investigations in the 1960s related to the proposed Chowilla Dam. Concerns have been raised regarding the hydraulic impacts on the Chowilla floodplain that have occurred in response to the construction and operation of Lock-6 and Lock-7. These impacts are discussed in detail in the Chowilla Resources Management Plan (Sharley and Huggan, 1995). In summary, controlled pool levels above the locks have resulted in the elevation of the groundwater table across the Chowilla floodplain (Figures 3 and 4), and altered flows in the anabranch creek system that occurs on the floodplain. In parts of the floodplain, the elevated groundwater table has resulted in increased salt accumulation and this has resulted in severe consequences for vegetation health. It has generally been accepted that there has been an increase in the flux of saline groundwater entering the anabranch creeks (occurring in response to the elevated groundwater table), and this has resulted in an increased salt load being delivered to the River Murray. On average 130 tonnes/day of salt enters the Chowilla floodplain with regional groundwater inflow but there is a wide range in salt loads due to climate variability. After extended dry periods and low flows in the River Murray, the salt load entering the anabranch creeks from the aquifer system (and thus the river) is 40–60 tonnes/day. The maximum peak of 1,800 tonnes/day occurred in the recession of the 1974 flood.

2.3.2 REGIONAL HYDROGEOLOGICAL SETTING The Pliocene (Loxton – Parilla) Sands forms a regionally extensive unconfined to semi-confined aquifer into which the trench of the ancestral River Murray floodplain is incised. Within this trench, the Monoman Formation and the overlying Coonambidgal Formation were deposited, and it is within this sequence that the channel of the modern River Murray itself is incised (Collingham 1990).

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CHOWILLA FLOODPLAIN AND MODEL AREA LOCATION PLAN (YAN ET AL, 2004) FIGURE 1

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SATELLITE PHOTOGRAPH OF MODEL DOMAIN AND CHOWILLA FLOODPLAIN (YAN ET AL, 2004) FIGURE 2

f:\jobs\a191\600\r002\figures\figure 2_satellite photograph of model domain and chowilla floodplain.doc

PRE RIVER LOCKING, CREEK AND GROUNDWATER INTERACTION (YAN ET AL, 2004) FIGURE 3

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POST RIVER LOCKING, CREEK AND GROUNDWATER INTERACTION (YAN ET AL, 2004) FIGURE 4

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CHOWILLA MODEL 2012

The Pliocene Sands and the Monoman Formation are considered to be in direct hydraulic connection (Figure 5). The Monoman Formation and the Pliocene Sands have a total combined thickness of ~50 m. The surficial sediments of the thin Coonambidgal Formation overlay the Monoman Formation. The groundwater table occurs within the Coonambidgal Formation or in the Monoman Formation in some areas. Saline groundwater enters the Chowilla floodplain by lateral and vertical flow from the Pliocene Sands. This is augmented by slow vertical leakage from the underlying regional confined Murray Group Limestone through the Bookpurnong Formation and into the Pliocene Sands. Saline groundwater (25,000–50,000 mg/L) enters the River Murray by direct inflow, and via the flux of groundwater entering the anabranch creeks that then deliver the salt load to the River. The flux of saline groundwater entering the creeks is determined by the hydraulic conductivity on the sides and bed of the creeks, and the head difference between the water table and the creek stage. Therefore measurements of the groundwater level in the aquifer and the stage of the creeks at a similar time is critical, as this data can then be used to calculate the flux of saline groundwater entering the creeks, and consequently, the total salt load being delivered to the River Murray. A conceptual hydrogeological model of the 200 square kilometre Chowilla floodplain is given in Figure 6 and indicates the hydrogeological units, surface water features, and the flow directions within the floodplain. The cross-section A-A’ is sited upstream of the anabranch creek system on the eastern site of the floodplain. This cross section indicates groundwater flow in the aquifer system including: lateral flow from the highland area, vertical leakage from Murray Group Limestone, discharge to the anabranch creeks, discharge by evapotranspiration from the extensive areas where a shallow groundwater table exists, and lateral flow from the River Murray to the aquifer system. The cross-section B-B’ is located downstream of the anabranch creek system on the western side the floodplain. This cross-section indicates lateral flow from the highland area, vertical leakage from the Murray Group Limestone and direct discharge from the creeks into the river downstream of Lock-6. The creeks can be either losing or gaining.

2.3.3 HYDROGEOLOGICAL UNITS The characteristics of each hydrogeological unit (see Figure 5) are discussed in order of increasing depth below ground surface. In the environmental flow context, the key floodplain processes are mostly shallow hydrodynamic interactions, and while there is a focus on representing these processes in some detail in the Chowilla model, the deeper groundwater units and related regional flow processes are also adequately represented.

Coonambidgal Formation The Coonambidgal Formation consists of a discontinuous clay layer 0 to 2 m thick. This formation determines the unconfined to semi-unconfined nature of the Monoman Formation, recharge to the Monoman Formation during and after flooding, and the rate of evapotranspiration.

Monoman Formation The Monoman Formation unconfined to semi-unconfined aquifer consists of relatively clean fine to coarse alluvial sands overlain by thin silts and clay (Anon, 1989), but may itself contain thin clay layers. The groundwater table within the Chowilla floodplain occurs generally within the Monoman Formation, or within the overlying Coonambidgal Formation. Drilling and pumping tests on the Chowilla floodplain at Gum Flat and Tareena Bong indicated that the Monoman Formation is separated into an upper and lower aquifer by a thin aquitard (Howles and Marsden, 2003). This situation is represented in the model by applying differing hydraulic conductivity values to upper and lower aquifers, as described in detail later. The Monoman Formation is restricted to the River Murray trench and is in direct hydraulic connection with the river, the underlying semi-confined Lower Pliocene Sands, and the laterally adjacent unconfined Upper Pliocene Sands on the highland. The cross-section (Figure 5) indicates that this aquifer is ~30 m thick and is incised into the underlying Pliocene Sands in the Chowilla region. The Monoman Formation has a hydraulic conductivity of 10 to 20 m/day.

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HYDROGEOLOGICAL CROSS SECTION (1 JULY 1995) (YAN ET AL, 2004) FIGURE 5

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Layer 1 & 2

Layer 3

Layer 4

Layer 5

Layer 1 & 2

Layer 3

Layer 4

Layer 5

CONCEPTUAL HYDROGEOLOGICAL CROSS SECTION (YAN ET AL,2004) FIGURE 6

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CHOWILLA MODEL 2012

A potentiometric head contour plan (Figure 7) has been constructed for the Monoman Formation and the regional Pliocene Sands using monitoring data obtained in May 2003 from selected wells completed at the top and middle of the Monoman Formation. This approach minimises differences in groundwater levels that may result from the use of wells of varying depth when groundwater salinities span a wide range. Outside of the Chowilla floodplain the groundwater table occurs within the Pliocene Sands and data from wells in this area has been used to complete the plan. This plan indicates a general pattern of regional groundwater flow towards the River Murray trench. The River Murray pool level above Lock-6 is elevated above the groundwater table of the surrounding Monoman Formation resulting in recharge from the river into the aquifer. A groundwater trough occurs to the north of the river and to the west of Lock-6, through which groundwater discharges either from the Monoman Formation to the west of Lock-6 via an evaporative sink, or directly into the Monoman and Chowilla Creeks. The salinity of Monoman groundwater is 5,000 to 70,000 mg/L. Salinity values and distribution obtained from observation wells is given in Figure 8.

Pliocene Sands The Pliocene Sands unconfined to semi-confined aquifer consists of fine to medium sand with some clay and silt layers. This aquifer forms the regional unconfined aquifer in the highland area outside of the Chowilla floodplain but becomes semi-confined below the Monoman Formation within the floodplain (Figure 5). Aquifer parameters applied to the model for this unit are based partly on values adopted from Jolly and Walker (1995), and partly on those commonly used for representing a confined aquifer in this region. This aquifer is ~30 m thick with salinity of 20,000 to 70,000 mg/L, and a hydraulic conductivity of 2 to 5 m/day. The regional groundwater flow occurs laterally and vertically from the Pliocene Sands into the Monoman Formation and from there into the anabranch creeks. This saline groundwater is then conveyed to the River Murray.

Bookpurnong Formation The Bookpurnong Formation occurs between the Pliocene Sands and the underlying Murray Group Limestone. This aquitard consists of poorly consolidated plastic silts and shelly clays, and its low vertical hydraulic conductivity controls vertical leakage from the underlying Murray Group Limestone into the overlying Pliocene Sands. The Bookpurnong Formation is 20 to 40 m thick and has a vertical hydraulic conductivity estimated at 10-7 to 10-6 m/day. Vertical hydraulic conductivity values in the range 10-7–10-6 m/day were applied to the model based on previous technical investigations (Barnett, 1990). Sensitivity tests performed on Chowilla 2004 indicated that varying the vertical hydraulic conductivity of the Bookpurnong Formation significantly affects potentiometric head in both the Monoman Formation and the Pliocene Sands.

Murray Group Limestone The Murray Group Limestone is a regionally extensive confined aquifer underlying the Bookpurnong Formation. This aquifer consists of a consolidated, highly fossiliferous, yellowbrown to grey, fine to coarse, bioclastic limestone. This aquifer is ~100 m thick and has a hydraulic conductivity of 0.03 to 2 m/day. A regional potentiometric head contour plan (Figure 9) has been constructed for the Murray Group Limestone using data obtained in 2003. This plan indicates a general groundwater flow from east to west. The potentiometric head of the Murray Group Limestone is elevated several metres above that of the overlying aquifers. The salinity of groundwater in this aquifer is ~20,000 mg/L (Sharley and Huggan, 1995). This aquifer layer was included in the model to represent the influence of the regional groundwater flow system, notably the effects of vertical leakage from the Murray Group Limestone into the overlying sediments.

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MEASURED ELEVATION OF GROUNDWATER TABLE, MONOMAN SAND AND PLIOCENE SANDS (YAN ET AL, 2004) FIGURE 7

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GROUNDWATER SALINITY (mg/L) IN THE MONOMAN FORMATION ACROSS THE CHOWILLA FLOODPLAIN (YAN ET AL, 2004) FIGURE 8 f:\jobs\a191\600\r002\figures\figure 8_groundwater salinity monoman.doc

MEASURED POTENTIOMETRIC HEAD CONTOUR PLAN, MURRAY GROUP LIMESTONE (YAN ET AL, 2004) FIGURE 9

f:\jobs\a191\600\r002\figures\figure 9_potentiometric head contour plan mgl.doc

CHOWILLA MODEL 2012

2.3.4 PROJECT REGION HYDROLOGY

Floodplain Hydrology The discussion in the following two sections is based on the understanding of the hydrology of the Chowilla floodplain developed from previous investigations (Sharley and Huggan, 1995). There are a number of inter-related factors that control groundwater movement into, and out of, the floodplain, including: • River regulation by locks and weirs. • Depth to groundwater table under the Chowilla floodplain. • The frequency, extent, depth and duration of flood events. • Regional hydraulic gradients towards the Chowilla floodplain. • The presence and depth of incision of anabranch creeks and billabongs. • Evapotranspiration fluxes and salt concentration effects.

Hydrology Prior to River Regulation Prior to construction of the locks and weirs (“pre-locking”) on the River Murray in the 1930s (refer Figure 3): • River pool elevation gradually increased upstream. • There was no permanent flow in the anabranch creeks under median and drought conditions (Figure 10). • Recharge occurred to the aquifer system during regular flooding, mainly in areas where the lower permeability Coonambidgal Formation is absent. • The anabranch creeks were the main groundwater sinks for the aquifer system underlying the floodplain, along with evapotranspiration.

Hydrology Post River Regulation • The River Murray was modified into a series of stepped pools. • Upstream of Lock-6, elevated river pool levels resulted in elevation of the groundwater table (immediately adjacent to the River Murray) and additional recharge to the aquifer system, which in certain places has resulted in the development of a flushed zone of much fresher groundwater than usual. • Immediately downstream of Lock-7 the average river pool level was not significantly altered, however, further downstream the average river pool level was slightly elevated. • Elevated pool levels resulted in constant flow through the anabranch creeks that then delivered a mix of River Murray water and saline groundwater back to the river on a daily basis (Figure 11). • Construction of locks, weirs and storages on, and diversions from, the River Murray resulted in highly modified reduced flows, and less frequent flood events. • Evapotranspiration increased, due to the elevated (by 1–2 m) groundwater table on the Chowilla floodplain. This resulted in the soil salinisation and thus degradation of the native vegetation (Figure 12).

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ANABRANCH CREEK WITH NO PERMANENT FLOW (YAN ET AL, 2004) FIGURE 10

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POST-LOCKING CONSTANT FLOW IN MONOMAN CREEK (YAN ET AL, 2004) FIGURE 11

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TREE DEATH RESULTING FROM RISING GROUNDWATER TABLE AND SALINISATION (YAN ET AL, 2004) FIGURE 12

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CHOWILLA MODEL 2012

3. CONCEPTUAL MODEL

3.1 CHOWILLA GROUNDWATER MODEL DEVELOPMENT This report documents the 2011-12 upgrade of the Chowilla Groundwater Model. The conceptualisation is based on the original Chowilla Model (2004), with updates as identified herein. The model history has been included to document the changes that have occurred prior to this upgrade, notably the three main modelling programmes in 2004, 2007 and 2011-12, which are referred to in the text as: • Chowilla 2004. • Chowilla 2007. • Chowilla 2012.

3.1.1 MODEL DOCUMENTATION The Chowilla 2004 model was documented in Yan et al, 2004, which focused on salt load impact to the River under different groundwater management options. The Chowilla 2004 model report includes a detailed description of model construction as well as the hydrogeology of the area. While this report included a discussion of groundwater recharge due to flooding, the Chowilla 2004 model did not include this feature. The report also documented the calibration of the model and the prediction scenarios run to determine the impact of the groundwater management options. The Chowilla 2007 model was documented in Howe et al, 2007, a scenario simulation set of the Chowilla 2004 model. The significant change between Chowilla 2004 and Chowilla 2007 was the inclusion of recharge due to flooding, with the majority of other model components remaining unchanged from Chowilla 2004. Chowilla 2007 focused on the scenarios run with the additional recharge and was not a stand alone or comprehensive model report. The Chowilla 2012 model is documented herein and also draws together the information from both Chowilla 2004 and Chowilla 2007. This document is designed as a stand alone and comprehensive model report and includes descriptions of the model conceptualisation, construction, calibration and scenario predictions.

3.1.2 MODEL HISTORY The model history below has been taken from Howe et al 2007 and documents the history of the model up to the Chowilla 2007 scenario model. In 2004, DFW (then DWLBC) developed a numerical groundwater flow model capable of simulating the regional aquifer system underlying the Chowilla floodplain (Figure 1). At that time, all model structures and boundaries were defined and hydraulic parameters were estimated during calibration to monitoring data and data from pumping tests. The model is comprehensively documented in Yan et al, (2004). The model was used to simulate the regional aquifer system under low river flow conditions and did not include the impact of any flooding. In 2005–06, the model (Chowilla 2004) was adapted for the first time by DFW to simulate the aquifer hydraulic response to natural flooding and flooding induced by the regulator. During the project it was assumed that the regulator was operated on an annual basis over a ten-year period (Overton et al, 2005). This assessment indicated that operation of the regulator induced an increased salt load accession (above that of the same flood magnitude under natural conditions) of up to ~400 t/d immediately after flooding, and an average increase of ~75 t/d over the ten year period. In 2007, the Chowilla 2004 groundwater model was used to simulate the aquifer hydraulic response to historic flood events and flooding (including flood inundation recharge) induced by the regulator, resulting in the Chowilla 2007 model. This used a simplified version of the River Murray flow hydrograph of the past 30 years (Figure 13). The fundamental model parameters and conditions (in Chowilla 2007) were not changed from model development in 2004, other than to apply the conditions necessary to simulate flooding, including inundation and recharge.

Page 18 A191B/R002d

OBSERVED AND DISCRETISED RIVER MURRAY FLOW HYDROGRAPH AT LOCK 6 (HOWE ET AL 2007) FIGURE 13

f:\jobs\a191\600\r002\figures\figure 13_observed and simplified river murray flow hydrograph at lock 6.doc

CHOWILLA MODEL 2012

3.2 CONCEPTUAL MODEL KEY FEATURES

3.2.1 HYDROGEOLOGY, INTERPRETATIONS AND ASSUMPTIONS The hydrogeology in Chowilla 2012 (and Chowilla 2007) is unchanged from the Chowilla 2004 Groundwater Model. The five layer model includes four aquifers and one aquitard (Yan et al, 2004), representative of the units described in Table 3.1, and with detailed descriptions of the hydrogeological units and their properties provided in Section 2. Table 3.1: Chowilla Model Layers and Groundwater Flow System

Hydrogeology Hydrogeology Layer Regional Lateral Flow Vertical Flow (Floodplain) (Highland)

Upper Monoman Pliocene Sands to 1 Pliocene Sands East to West Formation, Monoman Formation Lower Monoman Pliocene Sands to 2 Pliocene Sands East to West Formation, Monoman Formation Potential for upwards flux 3 Lower Pliocene Sands East to West through underlying Bookpurnong Formation Very small volumes of groundwater Limited by low 4 Bookpurnong Formation move laterally into and out of Layer-4 permeability due to its low permeability. 5 Murray Group Limestone Northeast to Southwest Basal Aquifer in Model

3.2.2 SURFACE WATER

Major Surface Water Components The surface water components of the model fall under three categories: • The anabranches on the Chowilla Floodplain. • The River Murray. • Lake Victoria.

Chowilla Anabranch System In Chowilla 2007 the anabranches were conceptualised as river cells with time varying water levels. This remains unchanged in principle in Chowilla 2012; however the water levels have been updated based on new hydrodynamic modelling results (see below). Anabranches have been simplified into 24 groups consistent with Chowilla 2007 (Figure 14), with an associated stream water level, stream bed level and stream bed conductance parameter. This is consistent with the methodology used in Chowilla 2007, and bed levels were updated where necessary based on changes to the surface elevation from the LIDAR.

River Murray The construction of locks, weirs, storages on the river and diversions from the River Murray has resulted in highly modified reduced flows, and less frequent flood events. The River Murray has been conceptualised as a series of stepped pools, and is considered to be primarily a losing stream upstream of Lock-6, evidenced by the significant low salinity flushed zones within the groundwater system adjacent to the river, but gaining for the reach immediately downstream of Lock-6. Both the River Murray and Lake Victoria have previously been conceptualised in the model as specified head cells. One of the key upgrades for Chowilla 2012 was to change the implementation of the River Murray in the model from constant heads to river cells, to allow for a more realistic representation of the river.

Page 20 A191B/R002d Anabranch Group Number

Anabranch River Cells

River Murray River Cells

ANABRANCH CREEK GROUPING (HOWE ET AL, 2007) FIGURE 14

f:\jobs\a191\600\r002\figures\figure 14_anabranch creek grouping figure 14.doc

CHOWILLA MODEL 2012

Lake Victoria The specified levels for the Lake Victoria river feature remain unchanged from Chowilla 2007 (constant head). Although it was not identified as a key requirement, if required, Lake Victoria could be modelled with variable levels to represent its operational dynamics, but it has been assumed that there would be a low influence on the Chowilla floodplain salt loads due to level changes at Lake Victoria.

3.2.3 SIMPLIFICATION OF SURFACE WATER COMPONENTS Chowilla 2012 is primarily a groundwater model and as such surface water components are simplified. These simplifications include: • A simplified Murray River Flow Hydrograph comprising monthly time steps and 20 000 ML/d flow magnitude divisions with a river flow of 5000 ML/d assumed between flood events. • A flat Murray River weir pool (no backwater curves). • Inundation areas and stream levels for flows of 80,000 and 100,000 ML/day are represented by pre-locking conditions in the hydrodynamic model (Section 3.2.4). • Anabranch bed conductance parameter values that increase as the water level in the anabranches increases (representing increased wetted perimeter).

Simplified River Murray Flow Hydrograph A river flow hydrograph was used in Chowilla 2007 to represent river levels over the period 1977 to 2007, based on the River Murray flow hydrograph from Lock-6. This “QSA flow” was discretised for modelling purposes into a “simplified hydrograph” comprising monthly time steps and 20 000 ML/d flow magnitude divisions (Yan et al, 2004). River flow of 5000 ML/d was assumed as the steady/background flow regime between flood events. An upgrade to Chowilla 2012 involved extending the time frame such that it runs over the benchmark period (1975 to 2000), with the extended (simplified) hydrograph given in Figure 16. The extension simplification (1975 to 1977) was based on visual inspection of the GS4260200 hydrograph over the monthly time steps. This was approximated to the closest 20,000 ML/day consistent the existing simplified hydrograph, again with a steady/background flow assumption of 5,000 ML/day. The hydrodynamic surface water model (WaterTech, 2011) was run at levels consistent with the simplified hydrograph to establish the detailed water level distributions in the anabranches and the inundation areas for groundwater recharge.

River Murray Backwater Curves The Chowilla 2004, 2007 and 2012 models assume a flat weir pool (both spatially and temporally) for the main river channel between Lock-5 and Lock-6, and between Lock-6 and Lock-7. Changes to the weir pool (raising and subsequent lowering) are only applied during operation of the Chowilla regulator, above Lock-6. This methodology of not incorporating water level variations during high flows or any backwater effects is considered conservative for the following reasons: • A flat weir pool will result in lower river levels at the upper end of each reach approaching the next lock compared to the adoption of a backwater curve, maximising the potential for river gaining conditions and therefore larger salt loads. The backwater curve can be significant; for example, the level immediately downstream of Lock-7 is approximately 1.4 m higher than the Lock-6 upstream pool level (19.25 mAHD) for a 10 GL/day flow, and 3.2 m higher for a 30 GL/day flow. • In reality, the backwater curves with and without Lock-6 raising will converge over the length of the reach approaching Lock-7. A flat weir pool during operation of the regulator and raising of Lock-6 (to 19.87 mAHD) to a level lower than the backwater curve again maximises the potential for river gaining conditions and thus salt loads (see Figure 15).

Page 22 A191B/R002d Regulator 19.87m

Flat Weir Pool 19.25m Lock 7 Lock 6

Flat Weir Pool – Chowilla 2011 Model

Regulator 30,000 ML

30,000 ML Regulator 10,000 ML 3.2 m 10,000 ML 1.4 m

~76 km Lock 7 Lock 6

Potential Impact of Backwater Curves Figure not to scale

IMPACTS OF THE IMPLEMENTATION OF THE RIVER MURRAY IN CHOWILLA 2011 FIGURE 15

f:\jobs\a191\600\r002\figures\figure 15_impacts of the implementation of the river murray in chowilla 2011.doc

OBSERVED AND DISCRETISED RIVER MURRAY FLOW HYDROGRAPH AT LOCK 6, BENCHMARK PERIOD (ML/D) FIGURE 16

f:\jobs\a191\600\r002\figures\figure 16_observed and simplified river murray flow hydrograph at lock 6_benchmark.doc

CHOWILLA MODEL 2012

Anabranch Bed Conductance Anabranch bed conductance was updated to reflect the dynamic nature of the anabranches during flood conditions, specifically the increase in the wetted perimeter with increased flow. Table 3.2 gives the bed conductance values of the anabranches for various river flows. In addition to this it was assumed that the stream bed conductance for all regulator events was 10 m2/day. This was considered appropriate as the 10,000 ML/day regulator scenario is similar in size to the 40,000 ML/day base case flood and thus would have a similar conductance. Table 3.2: Anabranch Bed Conductance

Flow Conductance (ML/day) (m2/day)

5,000 2.5 20,000 5 40,000 10 60,000 10 80,000 10 100,000 10

3.2.4 GROUNDWATER RECHARGE

Major Groundwater Recharge Components Groundwater recharge has three main components in the Chowilla model: • Background (Mallee dryland) recharge. • Negative recharge representative of evapotranspiration from dense eucalypt forest in a flushed zone near the river Murray. • Recharge due to flood inundation.

Background recharge is applied to the area outside the floodplain at a rate of 0.1 mm/yr, consistent with other models in the region. Chowilla 2004 contained a zone of negative recharge (-1 mm/day) which has been maintained in the 2011-12 model upgrade. Yan et al, 2004, describes this zone as evapotranspiration from healthy eucalypt forest and the rate is based on an estimate from Thornburn et al, 1993. This zone was confirmed in Chowilla 2004 through calibration to potentiometric head, which could only be matched by implementing this zone (Yan et al, 2004). The scope of this 2011-12 investigation did not extend to analysis of the high rainfall events of 2010-11, but future work programs may wish to review whether there is evidence of a significant recharge event due to the extremely high rainfall events of 2010-11 that could impact on salt load predictions. The following description relates to the recharge due to flood inundation, which has been a key focus of the 2011-12 model upgrade.

Floodplain Inundation Recharge Zones and Values Flood inundation recharge is varying in time and space and requires information on the area to be inundated and the recharge rate applied. These are combined to create recharge zones that vary over time based on the simplified hydrograph. Inundation areas were based on hydrodynamic modelling by WaterTechnology for the flow volumes in the simplified hydrograph (WaterTechnology, 2009). This work used the updated LIDAR and was based on the flood volumes identified in the simplified river hydrograph (Section 3.2.2). Flows at 80 and 100 GL/day are represented by ‘pre-development’ conditions, with no structures.

A191B/R002d Page 25 CHOWILLA MODEL 2012

These conditions closely approximate the inundation extents and water levels of ‘existing’ conditions at these flows (pers. comm. Ben Tate, Water Technology, 29 June 2011), due to the following reasons: • The locks are fully open at flows above 55 to 60 GL/day, therefore their influence becomes negligible. • Flows of 60 GL/day and less are modelled with existing structures to represent current ‘post- development’ conditions.

The flood inundation recharge rates used in Chowilla 2007 (and all subsequent models including Chowilla 2012) were based on the potential groundwater recharge documented in Overton et al, 2005. This recharge was based on different soil types in the Chowilla floodplain and is shown in Figure 17. Overton et al 2005 states: The recharge rates were provided to Yan et al. (2004) to be incorporated into the MODFLOW groundwater model. After testing and calibrating the MODFLOW model the groundwater recharge rates were thought to be too high and were reduced from the maximum soil physical rates to values that resulted in better model calibration, and these are shown in Table 3.4. (reproduced below in Table 3.3). The original values are likely to represent the soil water recharge rates, which would be higher than the groundwater recharge rates after soil water storage and evapo- transpiration. Table 3.3: Inundation Recharge rates based on soil types (Overton et al, 2005)

Final adopted recharge rates applied to Soil Type Comment Chowilla 2007 and 2012 (mm/day)

1a Heavy Clay (Lignum) 0.5 1b Clay (Red Gum/Black Box) 0.5 2a Sandy Clay (Open Plain Swamps) 1 2b Sandy Clay (Red Gum Along Creeks) 1 2c Sandy Clay (Red Gum/Black Box Forest) 1 3 Clay Loam (Black Box Woodland) 2 4a Sandy Clay Loam Salinised (Black Box Woodland) 2 4b Sandy Clay Loam (Black Box Woodland) 2 5 5 Sandy Loam (Dunes) 2

The recharge rates used in the Chowilla 2012 Groundwater Model are consistent with the rates in the WaterTechnology Hydrodynamic model with one exception. One recharge zone has a specified recharge rate of 2 mm/day in Chowilla 2012 (and Overton et al 2005), but was specified as 3 mm/day in the WaterTechnology hydrodynamic model. This was due to a copying/digitising error, however the impact on the model is considered minimal (pers. com. Ben Tate, WaterTechnology, June 2011).

3.2.5 EVAPOTRANSPIRATION ZONES AND VALUES Evapotranspiration (“ET”) is a major sink for groundwater, and occurs in areas of shallow water table (generally considered to be less than 3 to 4 m below ground surface). Evapotranspiration in Chowilla 2012 is split into two components, evapotranspiration from the shallow water table (including transpiration from shallow rooted vegetation) and evapotranspiration from deep-rooted floodplain vegetation in major flushed zones. Evapotranspiration from the water table is modelled using the evaporation function in MODFLOW whereas evapotranspiration from deep-rooted vegetation in major flushed zones has been represented by an area of negative recharge.

Page 26 A191B/R002d 485000 490000 495000 500000 485000 490000 495000 500000 0 0 0 0

0 100 GL/day 0 0 80 GL/day 0 0 0 0 0 3 3 3 3 5 5 5 5 2 2 2 2 6 6 6 6

LAKE LIMBRA LAKE LIMBRA 0 0 0 0

0 COOMBOOL SWAMP 0 0 COOMBOOL SWAMP 0 0 0 0 0 8 8 8 8 4 4 4 4 2 2 2 2

6 OLD COOMBOOL 6 6 OLD COOMBOOL 6

SA SA

NSW NSW LAKE LITTRA LAKE LITTRA PUNKAH ISLAND PUNKAH ISLAND LAKE WERTA WERT LAKE WERTA WERT

0 STANLEY ISLAND 0 0 STANLEY ISLAND 0 0 BOAT CREEK ISLAND 0 0 BOAT CREEK ISLAND 0 0 0 0 0 3 3 3 3 4 4 4 4 2 2 2 2 6 ISLE OF MAN 6 6 ISLE OF MAN 6 MONOMAN ISLAND MONOMAN ISLAND HORSESHOE LAGOON HORSESHOE LAGOON

QUEEN BEND QUEEN BEND

WILPERNA ISLAND WILPERNA ISLAND 0 0 0 0

0 CHOWILLA ISLAND 0 0 CHOWILLA ISLAND 0 0 0 0 0 8 8 8 8 3 3 3 3 2 2 2 2 6 6 6 6

HANCOCK HILL HANCOCK HILL 0 0 0 0 0 0 0 0 0 0 0 0 3 3 3 3 3 3 3 3 2 2 2 2 6 6 6 6 VIC VIC 0 0 0 0 0 0 0 0 0 0 0 0 8 8 8 8 2 2 2 2 2 2 2 2 6 6 6 6 485000 490000 495000 500000 485000 490000 495000 500000

485000 490000 495000 500000 485000 490000 495000 500000 0 0 0 0 0 0 60 GL/day 0 40 GL/day 0 0 0 0 0 3 3 3 3 5 5 5 5 2 2 2 2 6 6 6 6

LAKE LIMBRA LAKE LIMBRA 0 0 0 0

0 COOMBOOL SWAMP 0

0 COOMBOOL SWAMP 0 0 0 0 0 8 8 8 8 4 4 4 4 2 2 2 2 6 6 OLD COOMBOOL 6 OLD COOMBOOL 6

SA SA

NSW NSW LAKE LITTRA LAKE LITTRA PUNKAH ISLAND PUNKAH ISLAND LAKE WERTA WERT LAKE WERTA WERT 0 0 STANLEY ISLAND 0 STANLEY ISLAND 0 0 0 BOAT CREEK ISLAND 0 BOAT CREEK ISLAND 0 0 0 0 0 3 3 3 3 4 4 4 4 2 2 2 2 6 6 ISLE OF MAN 6 6 MONOMAN ISLAND ISLE OF MAN HORSESHOE LAGOON MONOMAN ISLAND HORSESHOE LAGOON

QUEEN BEND QUEEN BEND

WILPERNA ISLAND WILPERNA ISLAND 0 0 0 0 0 0 CHOWILLA ISLAND 0 CHOWILLA ISLAND 0 0 0 0 0 8 8 8 8 3 3 3 3 2 2 2 2 6 6 6 6

HANCOCK HILL HANCOCK HILL 0 0 0 0 0 0 0 0 0 0 0 0 3 3 3 3 3 3 3 3 2 2 2 2 6 6 6 6 VIC VIC 0 0 0 0 0 0 0 0 0 0 0 0 8 8 8 8 2 2 2 2 2 2 2 2 6 6 6 6 485000 490000 495000 500000 485000 490000 495000 500000

BROKEN HILL PORT AUGUSTA LEGEND Localities Recharge Rate (mm/d) 0 1 2 4 Roads -1 (evap discharge) RENMARK MILDURA Kilometres FIGURE 17

ADELAIDE SCALE 1:250,000 @ A4 Watercourses 0.5 GDA 1994 MGA Zone 54 Flood Inundation Recharge Distribution State Boundary 1 Disclaimer: While all reasonable care has been taken to ensure the information and Rates for specified flow ranges ECHUCA contained on this map is up to date and accurate, no guarantee is given that the information portrayed is free from error or omission. Please verify the accuracy River Murray 2 HORSHAM BENDIGO of all information prior to use. Note: Information shown on this map is a copyright of Aquaterra Australia 2011 Waterways MOUNT GAMBIER AUTHOR AL REPORT NO R001

PORTLAND DRAWN AL REVISION 1 Cadastre DATA SOURCES Hydrotech DATE 11/05/11 JOB NO. A191 002 Geoscience Australia CHOWILLA MODEL 2012

Where the evapotranspiration function is used, it is based on the following assumptions (Figure 18): • The maximum evaporation rate occurs when the water table is at the ground surface. • The evaporation rate is reduced to zero when the water table falls below a specified extinction depth. • Between the ground surface and the extinction depth the evaporation rate varies linearly.

As the water table fluctuates with time, so this depth-dependent discharge feature results in variations of the amount of groundwater being removed from the model due to evapotranspiration, even though the maximum evapotranspiration rate applied remains constant over time. Initial evapotranspiration rates and extinction depths from Chowilla 2004 were based on a CSIRO floodplain investigation conducted near Loxton (Holland et al., 2001) and were refined through the model calibration process (i.e. to achieve a good match to measured groundwater levels). The final parameter values were not based on considerations of surface features or vegetation type as such. Evapotranspiration rates range from 150 to 250 mm/yr (much less than 1 mm/day) with extinction depths between 1.5 and 3 m. These are shown in Figure 19. Evapotranspiration values used in Chowilla 2012 (maximum ET rate and extinction depth) are consistent with values used in previous Chowilla floodplain studies. Similarly, the evapotranspiration values used are consistent with similar floodplain modelling studies at other locations (Aquaterra, 2008). There is a zone of negative recharge in the model to represent evapotranspiration from healthy eucalypt forest near the River Murray in the flush zone (as described above in the section on recharge). The feature was implemented in the Chowilla 2004 model (Yan et al, 2004), with the rate based on an estimate from Thornburn et al, 1993. This zone was confirmed in Chowilla 2004 through calibration to potentiometric head, which could only be matched by implementing this zone (Yan et al, 2004).

3.2.6 GROUNDWATER SALINITY The groundwater model is designed to provide an estimate of the flow rate of groundwater to the rivers and creeks, which is then multiplied by the groundwater salinity for that area to obtain an estimate of the salt load. Information on groundwater salinity is required for this purpose. Saline groundwater primarily enters the Chowilla floodplain by flow through the Pliocene Sands. There is additional groundwater entering the floodplain through slow vertical leakage from the underlying regional confined Murray Group Limestone through the Bookpurnong Formation and into the Pliocene Sands. Saline groundwater (25,000–50,000 mg/L) enters the River Murray by direct inflow, and via the flux of groundwater entering the anabranch creeks that then deliver the salt load to the River. Previous modelling efforts (Chowilla 2004 and 2007) have shown that applying a non uniform groundwater salinity distribution based on bore salinity data (presumably during dry periods) tended to overestimate the salt load impacts immediately following weir lowering. However, by applying a nominally lower but spatially uniform salinity across the floodplain (such as 25,000 mg/L), the peak salt loads were matched better to the measured data. This could be related to bank storage freshening during the periods when the regulator is kept at a high level and the river is recharging the surrounding aquifer. Chowilla 2012 has used Airborne Electro-Magnetic (AEM) survey data (CSIRO) to provide more accurate estimates of the near-stream salinity for each reach to apply as the new groundwater salinity distribution in the model. These reaches and the associated AEM data are given in Figure 20.

Page 28 A191B/R002d

Evapotranspiration is at the maximum rate where water table is at or above specified surface (eg. topography)

Ground surface

Extinction depth Simple saturated zone model assumes linear change in evapotranspiration with depth (can be more complex)

Evapotranspiration is zero where water table is below extinction depth

EVAPOTRANSPIRATION FROM WATERTABLE FIGURE 18

f:\jobs\a191\600\r002\figures\figure 18_evapotranspiration from watertable.doc

Max ET Rate: 6250000 Max ET Rate: Extinction Depth: Extinction Depth: Max ET Rate: Extinction Depth:

6248000

Max ET Rate: Max ET Rate:150 mm/y Extinction Depth: 6246000 Extinction Depth:1.5 m

6244000

6242000

6240000

6238000

6236000

Max ET Rate: 6234000 Extinction Depth:

484000 486000 488000 490000 492000 494000 496000 498000 500000 502000 504000

MODELLED EVAPOTRANSPIRATION DISTRIBUTION FIGURE 19

f:\jobs\a191\600\r002\figures\figure 19_modelled evapotranspiration distribution.doc

485000 490000 495000 500000 505000

RENMARK MILDURA GRIFFITH

ADELAIDE

ECHUCA

HORSHAM BENDIGO

MOUNT GAMBIER MELBOURNE PORTLAND 0 0 0 0 0 0 8 8 4 4 2 2 6 NSW 6 OLD COOMBOOL LEGEND Localities

State Boundary

Model Reaches (Adpoted Salinity for Saltload Calculation mg/L)

1 (25,014 mg/L) SA 2 (35,070 mg/L) PUNKAH ISLAND 3 (5,832 mg/L)

STANLEY ISLAND Salinity (EC) 0 0

0 BOAT CREEK ISLAND 0 0 0

3 3 < 10,000 4 4 2 2 6 6 10,000 - 20,000 ISLE OF MAN MONOMAN ISLAND 20,000 - 30,000 30,000 - 40,000 40,000 - 50,000 50,000 - 60,000 60,000 - 70,000 QUEEN BEND > 70,000

WILPERNA ISLAND 0 0

0 CHOWILLA ISLAND 0 0 0 8 8 3 3 2 2 6 6 0 1 2 4

Kilometres SCALE 1:125,000 @ A4

GDA 1994 MGA Zone 54

DATA SOURCES Hydrotech Geoscience Australia CSIRO

HANCOCK HILL Disclaimer: While all reasonable care has been taken to ensure the information contained on HUNCHEE this map is up to date and accurate, no guarantee is given that the information portrayed is free from error or omission. Please verify the accuracy of all information prior to use.

Note: The information shown on this map is a copyright of Aquaterra Australia 2012 0 0 0 0 0 0 3 3 3 3 2 2 6 6 VIC FIGURE 20

Groundwater Salinity and River Reaches

AUTHOR AL REPORT NO R001

DRAWN AL REVISION 1 485000 490000 495000 500000 505000 DATE 18/05/11 JOB NO. A191 008

D:\Work Information\Aquaterra\Template\A4_Landscape.mxt CHOWILLA MODEL 2012

For modelling purposes, a reach was defined using GIS methods in conjunction with AEM data, and the mean salinity in the AEM data for that reach was calculated. Reaches were defined spatially by grouping areas of similar salinity. The mean salinity calculated for each reach (Table 3.4) was then used (with the appropriate groundwater flow data) to calculate the salt loads to the river. In all modelled time series salt load calculations the mean salinity (for each reach) was used with a conversion factor of 0.6 mg/L per EC (µS/cm). For reach 1 (see Figure 20 for location), which represents the zone most influenced by the inundation from the proposed regulator, the average near river salinity based on the AEM survey is 41,690 EC or 25,014 mg/L (based on conversion factor of 0.6). This value is very close to the value of 25,000 mg/L previously applied for calculation of salt fluxes. The AEM study itself involved a regression to measured bore salinity data, with a reported R2 value of about 0.7 (pers com. Ray Evans, February 2012), which indicates a reasonably strong but by no means a perfect relationship. Table 3.4: Salinity statistics based on AEM data and Preliminary River reaches in EC (µS/cm)

Maximum Salinity Model Mean Salinity Standard Minimum Salinity EC Mean Salinity Reach EC (µS/cm) Deviation EC (µS/cm) (mg/L) (µS/cm) 1 41,690 12,770 7,480 82,990 25,014 2 58,450 20,150 7,780 139,740 35,070 3 9,720 7,800 4,240 64,840 5,832

Note: Chowilla 2004 and 2007 assumed a spatially uniform value of 25,000 mg/L

3.2.7 SALT LOAD IMPACTS TO RIVER MURRAY CHANNEL DUE TO RAISING LOCK 6 The salt load impacts to the main river channel due to raising lock 6 were previously excluded from reporting as it was assumed to be a minor component of the total salt load impact. However, recent work has shown that the salt load impact on the main river channel due to raising lock 6 may be greater than previously thought (Aquaterra, 2010). This work utilised the Chowilla 2007 numerical model to predict the salt load impact on the main river channel due to raising Lock-6 by 0.5 m over a period of 92 days for environmental watering purposes, again assuming a flat weir pool. The result was a peak salt load of 86 t/day to the main river channel, reducing to 22 t/day after one month, which continued to reduce to background levels over a period of ~6 months (modified from Aquaterra, 2010, by using near river salinity assessed for Chowilla 2012). Given the similarity between the Aquaterra (2010) work and the raising of Lock-6 for the Chowilla regulator under the 2011-12 scope of works, the results are indicative of the potential salt load impact on the main river channel, and help justify the Chowilla 2011 model upgrade. Note that the weir raising project did not consider the operation of Chowilla regulator itself, which may also have an impact on the main river channel (conveyed through the groundwater system), in addition to the modification of Lock-6. Therefore, the actual impacts on the main river channel may be larger due to the combined raising of Lock-6 and operation of Chowilla regulator. Comparison between the two projects suggests that the impact to the main river channel is likely to result in an additional ~18% salt load impact to that previously reported (i.e. ~86 t/day to the main river channel compared to 450 t/day from the Chowilla floodplain).

3.3 KNOWLEDGE GAPS AND CONCEPTUAL UNCERTAINTY Key uncertainties in the input data have been addressed in this latest work, notably through updates to the LIDAR topography and related hydrodynamic modelling of inundation areas and stream levels. In addition, the results sensitivity to evapotranspiration parameters has also been investigated, as this is a major interceptor of groundwater across the floodplain. Although LIDAR addresses one level of uncertainty for evapotranspiration (surface elevation), complexities with this process suggest a need to benchmark the model-calculate evapotranspiration against remotely sensed data (e.g. Sebal or Modis data). Currently there are no available studies on this for the Chowilla Floodplain (pers.comm. Tanya Doody, March 2012) however; it is possible that this may become available in the future.

Page 32 A191B/R002d CHOWILLA MODEL 2012

As discussed in Section 3.2.2, some surface water processes have been simplified, and thus there is a degree of uncertainty in this model element. These simplifications include the absence of backwater curves and dynamic river levels for the River Murray. Conceptually this implies that local scale processes, such as bank storage (fresh river water being stored in the river bank and groundwater local to the river in periods of high flow) and dynamic flushing may not be represented in the model to a fine level of detail. With the focus of the model on regional scale processes for the Chowilla Flood plain it is reasonable to simplify these local scale processes, however the Chowilla 2012 model may need further refinements if it is required to examine these processes in detail in the future. While the AEM data has improved on previous extrapolation of observation bore salinity, the near- stream salinity is held constant with time. This influences the local scale processes discussed above, as near-stream groundwater may freshen in times of flood and assuming a constant salinity may result in overestimating salt load in the post flood period. The measured data on salt loads that the model is compared to is based on the difference between the upstream and downstream measurements in the River Murray at Chowilla creek. This effectively integrates the salt load effects across the entire floodplain. This is an appropriate data set for examining regional salt load however it does not allow for investigation of local scale processes along the river. Notwithstanding the conceptual uncertainties and knowledge gaps outlined above, the good match to measured groundwater levels and salt loads that has been achieved would indicate that the level of model simplicity that has been adopted is adequate for the purpose of the study.

A191B/R002d Page 33 CHOWILLA MODEL 2012

4. MODEL CONSTRUCTION

4.1 SOFTWARE PACKAGE MODFLOW is a three-dimensional finite difference mathematical code that was developed by the US Geological Survey (McDonald and Harbaugh, 1988), and continues to be updated. Visual MODFLOW Version 4.1 (Waterloo Hydrogeologic Inc) was selected by DFW as the pre- and post-processor software for quick generation and analysis of data files for MODFLOW. Groundwater Vistas Version 5 (ESI Ltd, 2005) was chosen as the pre-processor to develop the recharge inputs for the MODFLOW model.

4.2 DOMAIN AND GRID DESIGN The model domain and grid remain unchanged from the Chowilla 2004 and is shown in Figures 21 and 22. The following description has been taken from Yan et al 2004. The model domain covers an area 55 km (east-west) by 45 km (north-south) and includes the western part of Lake Victoria and the entire Chowilla floodplain (Figure 21). The bounding AMG coordinates are (southwest) E470000 N6220000 and (northeast) E525000 N6265000 (GDA 1994). The selection of a large model domain that incorporates the smaller study area is consistent with good modelling practice. The model domain boundaries are set at a sufficient distance from the study area such that they do not influence the behaviour of the aquifer system in the study area. The rectangular model grid is divided into 393 rows and 390 columns. The minimum grid size is 76.5 x 62.5 m in the Chowilla floodplain. The maximum grid size is 305 x 250 m in the remaining model area and comprises of 312,500 finite difference cells.

4.3 MODEL LAYERS

4.3.1 SURFACE ELEVATION The surface elevation of the model was updated based on the LIDAR data provided. The LIDAR data only covers the Chowilla Floodplain while the model includes both the floodplain and highland areas. Accurate surface elevation data is a critical requirement in areas of shallow water table (i.e. across the floodplain area), to ensure accurate discharge via the depth-dependent evapotranspiration feature.

Chowilla Floodplain Ground Surface The ground surface elevation (Figure 23) of the Chowilla floodplain was based on the 2003 LIDAR provided by DFW and updated to resolve discrepancies between survey points and the LIDAR. A summary of the issues with the original LIDAR and the method used to correct it is given in Appendix A.

Highland Ground Surface The highland ground surface was not updated and is consistent with Chowilla 2004, which is understood to based on SRTM data (accuracy of around ±10m). The elevation of the highland is between 50 and 60 mAHD and is less accurate than the elevation of the Chowilla Floodplain (Yan et al 2004). The change in the Chowilla floodplain surface created artificial high and low points around the edge of the floodplain, between the original ground surface and the updated LIDAR. These locations were smoothed and checked for consistency with aerial imagery of the location. The resulting surface elevation is given in Figure 24.

4.3.2 LAYER STRUCTURE AND HYDROGEOLOGY As indicated previously, the layer structure remains unchanged from Chowilla 2004 (Table 4.1). The description of the layer structure has been taken from Yan et al 2004, with MODFLOW layer options given in Table 4.2.

Page 34 A191B/R002d

MODEL DOMAIN (55 KM EAST TO WEST, 45 KM NORTH TO SOUTH) (YAN ET AL, 2004) FIGURE 21 f:\jobs\a191\600\r002\figures\figure 16_model domain.doc

MODEL GRID (76.5 BY 62.5 M TO 305 BY 250 M) (YAN ET AL, 2004) FIGURE 22 f:\jobs\a191\600\r002\figures\figure 17_model grid.doc

0 0 0 0 0 0 3 3 5 5

2 480000 485000 490000 495000 500000 505000 2 6 6

RENMARK MILDURA GRIFFITH

ADELAIDE

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PORTLAND COOMBOOL SWAMP 0 0 0 0 0 0 8 8 4 4 2 2 6 NSW 6 OLD COOMBOOL LEGEND Localities

Watercourses

LAKE LITTRA SA State Boundary

PUNKAH ISLAND LAKE WERTA WERT Roads

0 STANLEY ISLAND 0

0 BOAT CREEK ISLAND 0 River Murray 0 0 3 3 4 4 2 2

6 6 Waterways ISLE OF MAN MONOMAN ISLAND HORSESHOE LAGOON Cadastre

Lidar Elevation (mAHD) 12 - 20

QUEEN BEND 20 - 25 25 - 30 WILPERNA ISLAND 30 - 40 0 0

0 CHOWILLA ISLAND 0 0 0 40 - 50 8 8 3 3

2 CLOVER LAKE 2 6 6 50 - 60 60 - 70 LAKE MERRETI 70 - 80 80 - 90 90 - 95

HANCOCK HILL HUNCHEE 0 1 2 4 0 0

0 0 Kilometres 0 0 3 3

3 3 SCALE 1:150,000 @ A4 2 CAL LAL 2 6 6 VIC GDA 1994 MGA Zone 54 DATA SOURCES Hydrotech Geoscience Australia

Disclaimer: While all reasonable care has been taken to ensure the information contained on this map is up to date and accurate, no guarantee is given that the information portrayed is free from error or omission. Please verify the accuracy of all information prior to use.

Note: The information shown on this map is a copyright of Aquaterra Australia 2011 0 0 0 0

0 0 FIGURE 23 8 8 2 2

2 HORSESHOE LAGOON 2 6 6 Ground Surface Elevation (LiDAR)

AUTHOR AL REPORT NO R001

DRAWN AL REVISION 1 480000 485000 490000 495000 500000 505000 DATE 12/05/11 JOB NO. A191 004

D:\Work Information\Aquaterra\Template\A4_Landscape.mxt 0 0 0 0 0 0 3 3 5 5

2 480000 485000 490000 495000 500000 505000 2 6 6

RENMARK MILDURA GRIFFITH

ADELAIDE

ECHUCA

HORSHAM BENDIGO

LAKE LIMBRA MOUNT GAMBIER MELBOURNE

PORTLAND COOMBOOL SWAMP 0 0 0 0 0 0 8 8 4 4 2 2 6 NSW 6 OLD COOMBOOL LEGEND Localities

Watercourses

LAKE LITTRA SA State Boundary

PUNKAH ISLAND LAKE WERTA WERT Roads

0 STANLEY ISLAND 0

0 BOAT CREEK ISLAND 0 River Murray 0 0 3 3 4 4 2 2

6 6 Waterways ISLE OF MAN MONOMAN ISLAND HORSESHOE LAGOON Cadastre

Modelled Topography (mAHD) 12 - 20

QUEEN BEND 20 - 25 25 - 30 WILPERNA ISLAND 30 - 40 0 0

0 CHOWILLA ISLAND 0 0 0 40 - 50 8 8 3 3

2 CLOVER LAKE 2 6 6 50 - 60 60 - 70 LAKE MERRETI 70 - 80 80 - 90 90 - 95

HANCOCK HILL HUNCHEE 0 1 2 4

0 0 Kilometres 0 0 0 0

3 3 SCALE 1:150,000 @ A4 3 3

2 CAL LAL 2 6 6 VIC GDA 1994 MGA Zone 54 DATA SOURCES Hydrotech Geoscience Australia

Disclaimer: While all reasonable care has been taken to ensure the information contained on this map is up to date and accurate, no guarantee is given that the information portrayed is free from error or omission. Please verify the accuracy of all information prior to use.

Note: The information shown on this map is a copyright of Aquaterra Australia 2011 0 0 0 0

0 0 FIGURE 24 8 8 2 2

2 HORSESHOE LAGOON 2 6 6 Topography specified in model

AUTHOR AL REPORT NO R001

DRAWN AL REVISION 1 480000 485000 490000 495000 500000 505000 DATE 12/05/11 JOB NO. A191 004

D:\Work Information\Aquaterra\Template\A4_Landscape.mxt CHOWILLA MODEL 2012

Table 4.1: Model layer aquifers and aquitards

Layer Aquifer / MODFLOW Hydrogeological unit (Floodplain) Hydrogeological unit (Highland) No aquitard layer

Upper Monoman Formation Pliocene Sands unconfined aquifer of unconfined to semi-confined aquifer. variable thickness. Type-3 is used for this Type-3 is used for this layer due to layer due to the groundwater table Type-3 1 the groundwater table occurring Aquifer occurring within the Coonambidgal within the Coonambidgal Formation Formation on the floodplain, and the on the floodplain, and the semi- semi-confined nature of the aquifer. confined nature of the aquifer. Lower Monoman Formation – semi- Pliocene Sands – semi-confined aquifer Type-3 2 confined aquifer of variable Aquifer of variable thickness. thickness. 3 Lower Pliocene Sands, semi-confined low permeability aquifer, thickness ~5 m. Aquifer Type-3 4 Bookpurnong Formation - aquitard of variable thickness. Aquitard Type-0 5 Murray Group Limestone - confined aquifer of variable thickness. Aquifer Type-0

Table 4.2: MODFLOW layer types

Layer type Aquifer type Aquifer hydraulic parameters

Type-0 Confined Transmissivity and storage coefficient (specific storage, SS) are constant. Transmissivity varies and is calculated from saturated thickness and hydraulic Type-1 Unconfined conductivity. The storage coefficient (specific yield, SY) is constant. Type-1 is only valid for the uppermost layer of a model.

Type-2 Confined/ Transmissivity is constant - the storage coefficient may alternate between values Unconfined applicable to the confined (SS) or unconfined (SY) states.

Type-3 Confined/ Transmissivity varies and is calculated from the saturated thickness and hydraulic conductivity. The storage coefficient may alternate between values applicable to Unconfined the confined (SS) or unconfined (SY) state.

As introduced in Section 3, the regional aquifer system underlying the Chowilla floodplain was conceptualised as five layers, including four aquifer layers and one aquitard layer, as described in detail below (see also Figure 25 and Table 4.1).

Layer 1: Upper Monoman Formation, Pliocene Sands Layer 1 represents the Upper Monoman Formation as an unconfined to semi-confined aquifer (on the Chowilla floodplain) and the Upper Pliocene Sands as an unconfined aquifer (on the highland). Layer 1 is about 10 m thick on the floodplain and 30 to 60 m thick on the highland. The base elevation of Layer 1 in the floodplain area was determined from drillhole logs (where available) and mapping/extrapolation of these values (Appendix B). The representation of the Upper Monoman Formation in the model Layer 1 as a Modflow Type-3 layer (confined / unconfined) allows the model to simulate the layer as unconfined when the groundwater table occurs below the aquifer top, i.e. is within the aquifer, and confined if the groundwater table occurs above the aquifer top, which assists in representing the semi-confining nature of the Coonambidgal Formation.

Layer 2: Lower Monoman Formation, Upper Pliocene Sands Layer 2 represents the Lower Monoman Formation semi-confined aquifer (on the Chowilla floodplain) and the Upper Pliocene Sands semi-confined aquifer (on the highland). Layer 2 is about 10 m thick on the floodplain and 3 to 10 m thick on the highland. The base elevation of Layer 2 was determined from drillhole logs (where available) and mapping/extrapolation of these values (Appendix B).

A191B/R002d Page 39

CHOWILLA MODEL LAYERS (YAN ET AL, 2004) FIGURE 25 f:\jobs\a191\600\r002\figures\figure 20_model layers.doc

CHOWILLA MODEL 2012

Layer 3: Lower Pliocene Sands Layer 3 represents the Lower Pliocene Sands semi-confined aquifer. Layer 3 is about 20 m thick on Chowilla floodplain and 15 to 30 m thick on the highland. The base elevation of Layer 3 was determined from drillhole logs and cross-sections from previous reports (Anon 1989; Watkins 1992) (Appendix B).

Layer 4: Bookpurnong Formation Layer 4 represents the Bookpurnong Formation aquitard. Layer 4 is about 20 m thick in the north and about 40 m thick in the south of the model domain, and 25 to 30 m thick on the Chowilla floodplain. The base elevation of Layer 4 (Appendix B) was adopted from previous investigations (Waterhouse 1989).

Layer 5: Murray Group Limestone Layer 5 represents the Murray Group Limestone confined aquifer. Layer 5 was assumed to be 100 m thick (Waterhouse 1989). The elevation of the base of the Murray Group Limestone is given in Figure C6 (Appendix B).

4.4 AQUIFER AND AQUITARD HYDRAULIC PARAMETERS The final aquifer and aquitard hydraulic parameters for Chowilla 2012 are given in Table 4.3, with their distribution within each layer given in Appendix C. These values are consistent with values of aquifer and aquitard hydraulic parameters documented in reports, and from drilling programs and pumping tests on the Monoman Formation (Anon, 1989; Waterhouse, 1989; Watkins, 1992; Howles and Marsden, 2003). Table 4.3: Calibrated model aquifer and aquitard hydraulic parameters

Aquifer / aquitard Layer Kh (m/day) Kv (m/day) Sy (-) Ss** (m-1)

Upper Monoman Formation 1 0.1*, 10-15 0.1*, 0.15-1 0.05 1x10-5 Lower Monoman Formation 2 0.1* - 5 0.1*, 0.15 - 1 0.05 1x10-5 Upper Pliocene Sands 1&2 5 5 0.05 1x10-5 Lower Pliocene Sands 3 3 0.05 0.05 1x10-5 Bookpurnong Formation 4 1x10-7 – 8x10-6 1x10-7 – 8x10-6 - 1x10-5 Murray Group Limestone 5 3 0.1 0.05 1x10-5

* Lower permeability material under / near the River Murray. ** Specific storage is confined storativity divided by layer thickness.

Parameter changes for Chowilla 2012 from the values adopted in Chowilla 2004 include the following, which helped to improve the model calibration performance, especially in terms of salt load impacts (some groundwater level matches were also improved): • Specific yield in the Monoman Formation changed from 0.1 to 0.05. • Specific yield in the Pliocene Sands changed from 0.1 to 0.05. • Specific storage in the Monoman Formation changed from values in the range 10-3to 10-4, to a uniform value of 10-5, noting that while Chowilla 2004 identified that the model results were not sensitive to this parameter, the new value is more physically realistic for the specified model layer thicknesses. • Specific storage in the Upper Pliocene Sands changed from 10-3 to 10-5 (see also comment above). • Hydraulic conductivity in the Murray Group Limestone changed from values in the range 0.03 to 0.5 m/day to a uniform value of 3 m/day.

As described in Section 3.2.2, another key parameter change was made to the stream bed conductance, which had a significant effect on predicted salt loads.

A191B/R002d Page 41 CHOWILLA MODEL 2012

4.5 MODEL BOUNDARY CONDITIONS The majority of the model boundary conditions remained unchanged from the Chowilla 2004. The most significant boundary condition change was to the stream bed conductance parameter values, and to converting the constant head cells representing the River Murray to river cells, similar to the representation of the anabranches. Anabranch water levels were also updated to reflect the impact of the new LIDAR on the Hydrodynamic model, and while this had a significant impact on predicted salt loads, it is an input data change not a model parameter change as such. Boundary conditions are described per layer in the following.

4.5.1 LAYER 1: UPPER MONOMAN FORMATION & PLIOCENE SANDS Boundary conditions for Layer 1 are shown in Figure 26. The boundary conditions that are unchanged from Chowilla 2004 (Yan et al, 2004) are described below: • No-flow boundaries where groundwater flow is parallel to the model edge. • General head boundaries on the edges where groundwater flows into and out of the model. • Constant head boundary cells to simulate Lake Victoria pool level. - In the transient (post-locking) model 25 m AHD was applied. • Drainage cells were applied in the model in areas of reduced elevation to simulate some low land areas where groundwater constantly discharges due to evaporation. • Drainage cells (18 m AHD) were applied in the southwest corner to simulate the existing irrigation drainage system in the Renmark Irrigation Area.

The following Layer 1 boundary conditions were updated for Chowilla 2012, based on the updated LIDAR and reviewer comment: • River cells were used to simulate the River Murray stage and pool level. • In the transient (post-locking) model the following stepped pool levels were applied: - 24.25 m AHD upstream of Lock-7. - 19.25 m AHD Lock 6 to Lock-7. - 16.30 m AHD downstream of Lock-6. • River cells were applied to simulate the stage of the anabranch creeks on the Chowilla floodplain. - In the transient (post-locking) model the river stage elevation applied to the river cells (for flows of 5,000 ML) gradually declines from upstream to downstream, consistent with the locking control. - Table 4.4 gives the water levels for each reach for varying river flows. - Table 3.2 (previously) presents the stream bed conductance parameter values, which change for the anabranch creeks when flood conditions are applied (to represent the increased wetted perimeter).

Page 42 A191B/R002d

LAYER 1 BOUNDARY CONDITIONS FIGURE 26

f:\jobs\a191\600\r002\figures\figure 26_layer 01 boundary conditions.doc

CHOWILLA MODEL 2012

Table 4.4: Water Levels in the Anabranches

Anabranch water levels (m AHD) for various river flows

Chowilla 2012 WaterTech Bed 5,000 20,000 40,000 60,000 80,000 100,000 Groundwater Hydrodynamic Elevation ML/day ML/day ML/day Ml/day ML/day ML/day Model ID Model ID* (m AHD)

5 24 18 18.53 18.62 19.64 20.48 21.25 21.73 6 23 18 18.42 18.56 19.84 20.58 21.18 21.71 7 22 18 18.23 18.35 19.51 20.33 21.02 21.56 8 21 17.7 18.23 18.35 19.48 20.29 20.97 21.50 9 20 17 18.06 18.17 19.25 20.10 20.78 21.30 10 19 17.5 17.73 17.82 19.10 19.99 20.69 21.20 11 17 17 17.64 17.75 19.01 19.90 20.59 21.12 12 15 16.5 17.62 17.73 18.97 19.86 20.55 21.08 13 14 16 17.57 17.67 18.92 19.82 20.52 21.06 14 12 16.1 17.56 17.64 18.86 19.77 20.47 21.03 16 10 16 17.15 17.24 18.57 19.57 20.32 20.93 17 8 16 16.75 16.84 18.37 19.44 20.28 20.90 18 6 14.3 16.46 16.62 18.28 19.37 20.24 20.88 19 4 12 16.43 16.60 18.25 19.32 20.17 20.84 20 2 14.5 16.38 16.55 18.16 19.19 19.92 20.74 21 3 13.5 16.40 16.56 18.19 19.23 20.01 20.76 22 1 13.3 16.38 16.54 18.14 19.15 19.86 20.69 25 5 15 17.61 17.62 18.33 19.33 20.15 20.81 26 7 15 16.45 16.61 18.27 19.36 20.30 20.91 27 18 18 19.14 19.19 19.96 20.58 21.08 21.50 28 16 17.4 18.22 18.33 19.57 20.29 20.80 21.25 29 13 17.5 18.01 18.09 19.31 20.11 20.64 21.12 30 11 16.8 17.32 17.39 18.80 19.76 20.53 21.05 31 9 15 17.04 17.13 18.56 19.60 20.39 20.95

* The WaterTech Hydrodynamic model and Chowilla 2012 Groundwater model use different ID’s for each of the river reaches. This report uses the ID’s from the Chowilla 2012 Groundwater Model, however the correlating hydrodynamic model ID has been included here for completeness.

4.5.2 LAYER 2: LOWER MONOMAN FORMATION & PLIOCENE SANDS The following boundary conditions (see Figure 27) were applied in the model and remain unchanged from Chowilla 2004 (Yan et al, 2004): • No-flow boundaries where groundwater flow is parallel to the model edge. • General head boundaries on the model edges where groundwater flows into and out of the model. • Constant head boundaries to simulate hydraulic connectivity between Lake Victoria and aquifers.

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LAYERS 2 AND 3 BOUNDARY CONDITIONS FIGURE 27 f:\jobs\a191\600\r002\figures\figure 22_layers2 and 03 boundary conditions.doc

CHOWILLA MODEL 2012

4.5.3 LAYER-3: LOWER PLIOCENE SANDS Boundary conditions in Layer 3 are the same as Layer 2, as per Chowilla 2004.

4.5.4 LAYER-4: BOOKPURNONG FORMATION The model edges are no flow boundaries in this aquitard layer, as per Chowilla 2004.

4.5.5 LAYER-5: MURRAY GROUP LIMESTONE General head boundaries were used at the model edges to simulate groundwater flow into and out of the model, as per the Chowilla 2004 (see Figure 28).

4.6 RECHARGE As introduced in Section 3, the groundwater recharge for Chowilla 2012 has three components: • Background (Mallee) recharge (highland area). • Negative recharge representative of evapotranspiration from a dense stand of eucalypt forest in a major flushed zone on the floodplain. • Recharge due to flood inundation.

4.6.1 DRYLAND MALLEE RECHARGE AND FLUSHED ZONE FLOODPLAIN DISCHARGE Background dryland rainfall recharge is applied to the area outside the floodplain at a rate of 0.1 mm/yr, consistent with other regional models in the area (and unchanged since the Chowilla 2004 model). To be consistent with Chowilla 2004, background recharge was not applied to the floodplain as recharge to this area may be as low as 0 mm/year (Thornburn et al, 1993). As previously mentioned, an area of negative recharge is specified in the model on the floodplain to represent a constant high rate of evapotranspiration from dense eucalypt forest in a major flushed zone near the River Murray (Figure 19). This zone of negative recharge (-1 mm/day) is unchanged from the Chowilla 2004 model (maintained in the 2011-12 model upgrade).

4.6.2 FLOODPLAIN INUNDATION RECHARGE Flood inundation recharge is time varying and requires data on the area to be inundated and the recharge rate applied. These are combined to create recharge zones that vary over time. Table 4.5 (see below) describes the flood volumes and scenarios of the inundation areas provided. These flood volumes correspond to the volumes specified in the simplified hydrograph (Figure 16). Appendix D contains figures showing these inundation areas. The recharge rates used in Chowilla 2004 (and all subsequent models including Chowilla 2012) were based on the potential groundwater recharge documented in Overton et al, 2005. The recharge rates and related assumptions were presented and discussed in Section 3.2.3, and Table 3.3 summarised the rates applied.

4.7 MODEL STRESS PERIODS The transient history match model starts at the beginning of May, 1975, consistent with the start of the benchmark period (which ends on January 1st 2000). The end of the transient history match model is the end of November 2006, consistent with the previous modelling task reported in Yan et al. 2004 Stress periods in the model are monthly, resulting in 379 stress periods in total for the transient history match model, with an additional stress period added for predictive purposes. Model stress periods are shown in Appendix E. Scenario modelling is carried out over the history match period to assess the effect of implementing the regulator at specified times ( compared to the base case of no regulator). As a result, scenario models use the same stress period set up as used in the transient history match model discussed above.

Page 46 A191B/R002d CHOWILLA MODEL 2012

Table 4.5: Inundation Areas Provided

Flood Volume Hydrodynamic Hydrodynamic Chowilla from Scenario Pre- or Post- Scenario Water Lock-6 (m AHD) Regulator Hydrograph (adopted Development Levels (ML/day) Operational (ML/day) naming)

Scenario 2 – 5,000 5,000 19.25 No Post 5GL/day Scenario 2 – 20,000 20,000 19.25 No Post 10GL/day Scenario 2 – 40,000 40,000 19.25 No Post 40GL/day Scenario 2 – 60,000 60,000 Fully open No Post 60GL/day Scenario 1 – Natural – no 80,000 80,000 No Pre 80GL/day Lock-6 Scenario 1 – Natural – no 100,000 100,000 No Pre 100GL/day Lock-6

10,000 Yes – 19.25 m Scenario 4d 10,000 19.25 Post (with regulator) AHD

40,000 Yes – 19.87 m Scenario 4e-10 10,000 19.87 Post (with regulator) AHD

60,000 Yes – 19.87 m Scenario 4e-30 30,000 19.87 Post (with regulator) AHD

Note: Regulator operational refers to the proposed Chowilla Regulator. Pre- or post- development refers to locking, with pre-development corresponding to “natural”, pre-locking river conditions (Section 3.1.5).

A191B/R002d Page 47 6265000

General Head Boundary 26.5 - 35 m AHD 6260000

6255000

6250000

General Head Boundary 6245000 General Head Boundary 20.5 - 26.5 m AHD 27.5 - 35 m AHD

6240000

6235000

6230000

General Head Boundary 6225000 20.5 - 27.5 m AHD

6220000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000

LAYER 5 BOUNDARY CONDITIONS FIGURE 28 f:\jobs\a191\600\r002\figures\figure 23_layer 05 boundary conditions.doc

CHOWILLA MODEL 2012

5. MODEL CALIBRATION

5.1 STEADY STATE MODEL CALIBRATION As this modelling task is primarily related to refinement of transient recharge stresses on the model, the steady state model has not yet been re-run, and thus the steady state calibration has not been assessed. The steady state calibration of the Chowilla 2004 model is documented in Yan et al 2004.

5.2 TRANSIENT MODEL CALIBRATION Model performance has been assessed by examination of time series water levels and water level trends with time at selected observation bores. As further verification of the calibration performance of the model, time series salt load estimates have been calculated and compared to measured salt loads. As the salt loads are a flux-based criterion, the calibration performance is assessed on a combination of levels and fluxes, which helps address model non-uniqueness issues (Middlemis 2001). Areas identified as having poorer matches to the observed groundwater level data have been subjected to parameter changes in an effort to improve the calibration performance. Final parameterisation has been documented in Section 4, with performance criteria presented in this section. Evapotranspiration parameters have been used in previous modelling of the Chowilla floodplain to achieve calibration. Due to the changes made to the topography in the model, it was considered that modifications to evapotranspiration parameters (primarily extinction depth) were appropriate in Chowilla 2012 to improve calibration. Figure 19 illustrates the final distribution of evapotranspiration used in the calibrated model.

5.2.1 SEMI-QUANTITATIVE COMPARISON OF MODELLED POTENTIOMETRIC HEAD DISTRIBUTIONS (CONTOURS) AND OBSERVED POTENTIOMETRIC POINT DATA Figure 29 shows a plan view of modelled water level contours at 2003, with observed water level point data overlaid. It can be seen from this figure that the modelled water level contours are quite consistent with the observation data.

5.2.2 SEMI-QUANTITATIVE COMPARISON OF MODELLED AND OBSERVED POTENTIOMETRIC HEADS (HYDROGRAPHS) Modelled water levels have been compared to observed data for 27 observation bores in the Chowilla floodplain (Figure 30). While there are significantly more groundwater bores available in the Chowilla floodplain, they were not all suitable for calibration purposes. The 27 bores were chosen based on selection criteria that were applied to previous models. This specified that calibration bores were required to comply with the following: • Reference Height in mAHD provided. • Monitored the Monoman Aquifer. • Includes sufficient data, specifically pre 2000 when the majority of floods occurred.

Bores that complied with the first two points but had insufficient data during the period of flooding were selected as verification bores to be used in the prediction scenarios.

A191B/R002d Page 49 6250000

17.6

17.2 6248000 18.0

17.8 18.0 17.4 17.6 16.8 17.4 17.9 16.8 17.8 6246000 16.8 17.4

17.8

17.8

6244000 17.5 16.5

16.5

16.416.4 17.7

6242000 16.4 16.3

16.3 16.4

6240000

16.0

6238000

6236000

6234000

484000 486000 488000 490000 492000 494000 496000 498000 500000 502000 504000

LAYER 1 MODELLED GROUNDWATER CONTOURS VS OBSERVED POINTS AT 2003 FIGURE 29 f:\jobs\a191\600\r002\figures\figure 26_modelled groundwater contours vs observed points at 2003.doc

485000 490000 495000 500000 0 0 0 0 0 0 3 3 5 5 2 2 6 6

CHW154

LAKE LIMBRA

COOMBOOL SWAMP NSW

0 CHW162 0 0 0

0 SA 0 8 8

4 CHW123 4 2 2 6 6

OLD COOMBOOL CHW138 CHW135 CHW124 CHW159 CHW137 CHW108 CHW141 CHW157 CHW158 CHW110 CHW134 CHW148

LAKE LITTRA CHW046

PUNKAH ISLAND LAKE WERTA WERT CHW115 CHW116 STANLEY ISLAND 0 0

0 BOAT CREEK ISLAND 0 0 0

3 CHW121 3 4 4 2 2 6 6 CHW117 CHW112 CHW037 ISLE OF MAN CHW119 HORSESHOE LAGOON CHW118 MONOMAN ISLAND

CHW120 CHW155

QUEEN BEND

CHW156 WILPERNA ISLAND 0 0

0 CHOWILLA ISLAND 0 0 0 8 8 3 3 2 2 6 6

HANCOCK HILL 0 0 0 0 0 0 3 3 3 3 2 2 6 6

VIC 0 0 0 0 0 0 8 8 2 2 2 2 6 6

485000 490000 495000 500000

BROKEN HILL PORT AUGUSTA LEGEND Chowilla Bores 0 1 2 4 RENMARK Localities MILDURA Kilometres FIGURE 30 Roads ADELAIDE SCALE 1:125,000 @ A4 Chowilla Bore Locations GDA 1994 MGA Zone 54 Watercourses Disclaimer: While all reasonable care has been taken to ensure the information ECHUCA contained on this map is up to date and accurate, no guarantee is given that the information portrayed is free from error or omission. Please verify the accuracy State Boundary HORSHAM BENDIGO of all information prior to use. Note: Information shown on this map is a copyright of Aquaterra Australia 2011 River Murray MOUNT GAMBIER AUTHOR AL REPORT NO R001 Waterways PORTLAND DRAWN AL REVISION 1 DATA SOURCES Hydrotech DATE 11/05/11 JOB NO. A191 002 Cadastre Geoscience Australia CHOWILLA MODEL 2012

Figures 31 to 34 show modelled water levels compared to observed levels. It can be seen that the modelled levels compare well to the observed data, representing both the absolute level and the trends in water level. The only exception to this is bores that are located near Gum Flat, which do not match measured trends post 2005. This is due to a watering event that occurred at Gum Flat that is not included in the model. These bores include: • CHW108. • CHW123. • CHW124. • CHW134. • CHW135. • CHW137. • CHW138. • CHW141.

5.2.3 QUANTITATIVE ASSESSMENTS OF THE SCALED ROOT MEAN SQUARE (SRMS) SRMS has been calculated at two points in time during 2003 (1/5/2003 and 1/10/2003). These dates were chosen based on Yan et al, 2004, which reports a normalised root mean square value of 3.15% at 2003. Figures 35 and 36 show the scatter plots for Chowilla 2012, with SRMS calculated at 7.38% and 6.65% respectively, demonstrating good agreement between the modelled and observed values. While this is more than Chowilla 2004, Chowilla 2012 is significantly more complex, including temporally and spatially variable floodplain recharge which was not included in Chowilla 2004.

5.2.4 ITERATION RESIDUAL ERROR Iteration residual water balance error term ranges between +0.4% and -0.6%, well within the ±1% range of the MDBC 2001 guidelines (Middlemis, 2001).

Page 52 A191B/R002d 22 CHW037/1 22 CHW046/1 Modelled 21 21 Observed 20 Ground Surface 20

19 19

18 18

17 17 Water Level (mAHD Water Level Water Level (mAHD) Water Level 16 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW108/1 22 CHW110/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW112/1 22 CHW115/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW116/1 22 CHW117/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Chowilla 2012 Calibration Hydrographs FIGURE 31

F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Hydrographs_Basecase.xls]Figure_01 22 CHW118/1 22 CHW119/1 Modelled 21 21 Observed 20 Ground Surface 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW120/1 22 CHW121/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW123/1 22 CHW124/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW134/1 22 CHW135/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Chowilla 2012 Calibration Hydrographs FIGURE 32

F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Hydrographs_Basecase.xls]Figure_02 22 CHW137/1 22 CHW138/1 Modelled 21 21 Observed 20 Ground Surface 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW141/1 22 CHW148/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW154/1 22 CHW155/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW156/1 22 CHW157/A

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Chowilla 2012 Calibration Hydrographs FIGURE 33

F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Hydrographs_Basecase.xls]Figure_03 22 CHW158/1 22 CHW159/1 Modelled 21 21 Observed

20 Ground 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW162/1

21

20

19

18

17

Water Level (mAHD) Water Level 16

15 1975 1980 1985 1990 1995 2000 2005 Year

Chowilla 2012 Calibration Hydrographs FIGURE 34

F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Hydrographs_Basecase.xls]Figure_04 CALIBRATION PARAMETERS VALUE

Scaled Mean Sum of Residuals SMSR -3.29 %

Root Mean Square RMS 0.17 m

Scaled RMS SRMS 7.38 %

Root Mean Fraction Square RMFS 0.96 %

Scaled RMFS SRMFS 7.32 %

Coefficient of Determination CD 1.12

SCATTERGRAM 20

19

18

Modelled Head (m) Head Modelled 17

16

15 15 16 17 18 19 20 Measured Head (m)

CHOWILLA 2012 CALIBRATION STATISTICS AND SCATTERPLOT – 1/5/2003 FIGURE 35

f:\jobs\a191\600\r002\figures\figure 35_calibration statistics and scatterplot_05_2003.doc

CALIBRATION PARAMETERS VALUE

Scaled Mean Sum of Residuals SMSR 2.53 %

Root Mean Square RMS 0.14 m

Scaled RMS SRMS 6.65 %

Root Mean Fraction Square RMFS 0.82 %

Scaled RMFS SRMFS 6.53 %

Coefficient of Determination CD 1.11

SCATTERGRAM 20

19

18

Modelled Head (m) Head Modelled 17

16

15 15 16 17 18 19 20 Measured Head (m)

CHOWILLA 2012 CALIBRATION STATISTICS AND SCATTERPLOT – 1/10/2003 FIGURE 36

f:\jobs\a191\600\r002\figures\figure 31_calibration statistics and scatterplot_05_2003.doc

CHOWILLA MODEL 2012

5.2.5 MASS BALANCE The mass balance for the model was calculated for May and October 2003 to be consistent with the SRMS calculations and is given in Table 5.1. The mass balance indicates that the dominant inflow to the groundwater system at these points in time is stream leakage and the dominant outflow is evapotranspiration. The evapotranspiration component of the outflow is represented in the table by both the evapotranspiration column (shallow water table evapotranspiration) and the flush zone evapotranspiration (evapotranspiration by healthy eucalypt forest in the flush zone). These two components remove similar volumes of water from the groundwater at both May and October 2003. Table 5.1: Chowilla 2012 Mass Balance

In (ML/day)

Head Constant River Rainfall Month Storage Dependent Total Head Leakage Recharge Boundaries

May-03 2.8 2.8 24.2 9.8 1.9 41.5

Oct-03 0.9 2.8 24.7 9.8 1.9 40.2

Out (ML/day)

Head Flush Zone Constant River Evapo- Month Storage Dependent Evapo- Drains Total Head Leakage transpiration Boundaries transpiration*

May-03 1.0 0.3 4.9 14.8 5.8 12.6 2.2 41.5

Oct-03 0.9 0.3 4.7 14.3 5.8 12.6 1.9 40.4

* Implemented in the model as negative recharge

In – Out Month (ML/day)

May-03 0

Oct-03 -0.2

5.2.6 SALT LOAD CONFIRMATION The salt load calibration previously undertaken (Chowilla 2007) was against calculated salt loads for the Chowilla floodplain system only, based on monitoring stations on the main river channel located immediately upstream and downstream of the Chowilla Creek tributary with the River Murray. Scenario modelling indicated a peak salt load impact from the operation of Chowilla regulator of up to 450 t/day derived from the Chowilla anabranch system. The time series salt load entering each river reach is shown in Figure 37. It can be seen that the total modelled salt load (dark blue line) compares well to the observed salt loads (red points). Peaks in modelled salt load correspond to simulated inundation events, and compare well with observed data, with respect to amplitude and duration. The modeled cumulative salt load (Figure 38) compares well with the measured cumulative salt load and shows an improvement from the Chowilla 2007 model.

A191B/R002d Page 59

Modelled Salt Loads

1,000 Anabranch West (Zone 1) Anabranch East (Zone 2)

800 River Murray (Zone 3)

600

400 Saltload (t/d)

200

0 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005

Measured and Modelled Salt Loads

1,000 Total Saltload Total Anabranch Saltload

800 Observed Salt Loads

600

400 Saltload (t/d)

200

0 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005

MEASURED AND MODELLED SALTLOAD FIGURE 37

f:\jobs\a191\600\r002\figures\figure 37_modelled saltload to river vs observed data.doc

1,600,000 Cumulative Measured vs Modelled Salt Loads

1,400,000

Operational Data Salt Load 1,200,000 Chowilla 2012 Modelled Salt Load

Chowilla 2007 Modelled Salt Load

1,000,000

800,000 Saltload (t) Saltload

600,000

400,000

200,000

0 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005

Measured vs Modelled Cumulative Salt Load FIGURE 38

F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Landscape figures.xls]Fig 03 CHOWILLA MODEL 2012

In addition to the time series salt load, an analysis was performed on the modeled salt load data comparing the total modelled salt load over 12 months with the maximum flow for a flood, similar to an analysis performed on measured data in Overton et al (Figure 39). This analysis was based on the simplified hydrograph and a flood period was defined as: • The time period where the flow went above the steady/background flow of 5,000 ML/day. • The duration of the high flow was longer than for more than 1 month (more than one model stress period).

This provided 19 flood events for analysis. The correlation between flood magnitude and salt load for the modelled data is slightly less than for measured data (Figure 39), however the trend in the data (indicating increased salt loads for larger flood events) is similar. In addition, both analysis show a similar quantitative relationship (based on the line of best fit) where floods with a maximum flow of 100,000 ML/day will give a salt load of approximately 100,000 tonnes over a 12 month period following the flood. This analysis increases the confidence in the modelled salt load results.

5.2.7 SALT WATER BALANCE MODEL VERIFICATION Previously a salt and water balance (SWB) model developed by SKM (SKM 2011) has been used to model the salinity in the river based on (in part) groundwater input from Chowilla 2007. This has been documented in SKM 2011 and details will not be repeated here, however it has been updated with output from the Chowilla 2012 model. Figures 40 and 41 show a comparison between the modeled and measured salinity for parts of the 1996 and 2000 flood events. Good correlation is shown between modelled and measured data for these two flood events.

Page 62 A191B/R002d Linear relationship between salt load and peak river flow for Chowilla for 18 flood events (Overton, 2005)

Total Modelled Salt Load for 12 months following Flood

250,000

200,000

150,000

2 100,000 R = 0.7744

Total Salt Load (tones) Load Salt Total 50,000

0 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 Maximum Flow (ML/day)

Linear relationship between total modelled salt load and peak modelled river flow for Chowilla for 19 flood events (Chowilla 2011)

COMPARISON OF MEASURED SALT LOAD TO MODELLED SALT LOAD ANALYSIS FIGURE 39

f:\jobs\a191\600\r002\figures\figure 39_salt load analysis.doc

SALT WATER BALANCE MODEL VALIDATION FOR THE 1996 FLOOD EVENT FIGURE 40

f:\jobs\a191\600\r002\figures\figure 40_salt water balance model validation for the 1996 flood event.doc

SALT WATER BALANCE MODEL VALIDATION FOR THE 2000 FLOOD EVENT FIGURE 41

f:\jobs\a191\600\r002\figures\figure 41_salt water balance model validation for the 2000 flood event.doc

CHOWILLA MODEL 2012

6. PREDICTIVE SCENARIO RUNS

6.1 SCENARIO ASSESSED The scenario assessed with the Chowilla 2012 model was designed to represent the use of the regulator at various points in time over the benchmark period (Figure 42). The implementation of the regulator scenario included: • 4 x 10,000 ML/day at 19.25 m AHD regulator events (“10,000 ML/day regulator event” in Figure 42). • 4 x 10,000 ML/day at 19.87 m AHD regulator events (“40,000 ML/day regulator event” in Figure 42). • 1 x 30,000 ML/day at 19.87 m AHD regulator events (“60,000 ML/day regulator event” in Figure 42).

Chowilla 2007 used regulator scenarios based on the simplified hydrograph (Figure 42), however it is unclear what hydrodynamic model input was used. This makes a direct, quantitative comparison between the two models inadvisable as differences between the two may be due to different data inputs.

6.2 MODEL INPUTS FOR THE SCENARIO As the scenario model was similar to the base model the inputs required for the scenario were limited to inundation areas (Figure 43) and anabranch creek levels (Table 6.1 – see next page) for each of the regulator flows described above. In addition to this it was assumed that the stream bed conductance for all regulator events was 10 m2/day, as discussed in Section 3.2.2. This was considered appropriate as the 10,000 ML/day at 19.25 m AHD regulator scenario is similar in inundation area to the 40,000 ML/day base case (non-regulator) flood (Figure 44).

6.3 SCENARIO RUN RESULTS The results from the scenario model were compared with output from the Chowilla 2012 base case model to determine the impact of the regulator based on the updated model. Hydrographs from the Chowilla 2012 Regulator Scenario are given in Appendix F. Comparison with Chowilla 2012 base case model output: • 10,000 ML/day at 19.87 m AHD regulator events show the greatest increase in salt load to the river, with peak impacts (effect due to regulator) ranging from ~150 to 300 t/day (Figure 45). • The maximum peak impact (effect due to regulator calculated as difference above base case) of ~300t/day occurs for the event in 2000 subsequent to the 10,000 ML/day at 19.87 m AHD regulator operation. • Impact on peak salt load of subsequent flooding events of up to ~100t/day (most noticeable in the period between the 1987 and 1996 regulator events). • Salt load effect (above base case) due to regulator event recedes over a period of about one year (roughly same as for Chowilla 2007), but can be interrupted by a natural flood.

Page 66 A191B/R002d CHOWILLA MODEL 2012

Table 6.1: Water Levels in the Anabranch (Regulator Scenario)

Anabranch water levels (m AHD) for various river flows

Chowilla 2011 WaterTech Bed Elevation 10,000 ML/day 10,000 ML/day 30,000 ML/day Groundwater Hydrodynamic (m AHD) Model ID Model ID* at 19.25 m AHD at 19.87 m AHD At 19.87 m AHD 5 24 18 19.31 19.89 20.07 6 23 18 19.31 19.90 20.13 7 22 18 19.31 19.89 20.05 8 21 17.7 19.31 19.89 20.04 9 20 17 19.31 19.89 20.01 10 19 17.5 19.31 19.89 19.99 11 17 17 19.31 19.89 19.98 12 15 16.5 19.31 19.89 19.98 13 14 16 19.31 19.89 19.97 14 12 16.1 19.31 19.88 19.96 16 10 16 19.30 19.88 19.93 17 8 16 19.30 19.88 19.92 18 6 14.3 19.30 19.88 19.91 19 4 12 19.30 19.88 19.91 20 2 14.5 19.29 19.87 19.89 21 3 13.5 19.30 19.88 19.89 22 1 13.3 19.29 19.87 19.88 25 5 15 19.30 19.88 19.90 26 7 15 19.30 19.88 19.91 27 18 18 19.32 19.90 20.16 28 16 17.4 19.31 19.89 20.06 29 13 17.5 19.31 19.89 20.02 30 11 16.8 19.31 19.89 19.97 31 9 15 19.31 19.88 19.94

* The WaterTech Hydrodynamic model and Chowilla 2011 Groundwater model use different ID’s for each of the river reaches. This report uses the ID’s from the Chowilla 2011 Groundwater Model, however the correlating hydrodynamic model ID has been included here for completeness.

A191B/R002d Page 67

SIMPLIFIED HYDROGRAPH WITH REGULATOR EVENTS (HOWE ET AL 2007) FIGURE 42

f:\jobs\a191\600\r002\figures\figure 42_simplified hydrograph with regulator events.doc

465000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000

10 GL @ 19.25 mAHD

LAKE LIMBRA 0 0

0 COOMBOOL SWAMP 0 0 0 8 8 4 4

2 OLD COOMBOOL 2 6 6

SA

NSW LAKE LITTRA

LAKE WERTA WERT 0 STANLEY ISLAND 0 0 0

0 PUNKAH ISLAND 0 3 3 4 4 2 2

6 ISLE OF MAN 6 MONOMAN ISLAND HORSESHOE LAGOON

QUEEN BEND

ROTTEN LAKE WILPERNA ISLAND 0 0

0 CHOWILLA ISLAND 0 0 0 8 8 3 3

2 CLOVER LAKE 2 6 6

LAKE MERRETI

LAKE WOOLPOLOOL HUNCHEE HANCOCK HILL 0 0 0 0 0 0 3 3

3 CAL LAL 3 2 2 6 RENY ISLAND VIC 6

HORSESHOE LAGOON 465000 47000C0HAFFEY IRRIGA4T75I0O0N0 AREA 480000 485000 490000 495000 500000 505000 510000 515000 520000

465000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000 0 0 0 0 0 0 3 3 5 5 2 2

6 10 GL @ 19.87 mAHD 6

LAKE LIMBRA 0 0

0 COOMBOOL SWAMP 0 0 0 8 8 4 4

2 OLD COOMBOOL 2 6 6

SA

NSW LAKE LITTRA PUNKAH ISLAND

0 LAKE WERTA WERT 0

0 STANLEY ISLAND 0 0 0 3 3 4 4

2 ISLE OF MAN 2 6 MONOMAN ISLAND HORSESHOE LAGOON 6

QUEEN BEND

ROTTEN LAKE WILPERNA ISLAND 0 0

0 CHOWILLA ISLAND 0 0 0 8 8

3 CLOVER LAKE 3 2 2 6 6

LAKE MERRETI

LAKE WOOLPOLOOL HUNCHEE HANCOCK HILL 0 0 0 0 0 0

3 CAL LAL 3 3 3 2 2

6 RENY ISLAND VIC 6

CHAFFEY IRRIGATION AREA HORSESHOE LAGOON 465000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000

465000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000 0 0 0 0 0 0 3 3 5 5 2 2

6 30 GL @ 19.87 mAHD 6

LAKE LIMBRA 0 0

0 COOMBOOL SWAMP 0 0 0 8 8 4 4

2 OLD COOMBOOL 2 6 6

SA

NSW LAKE LITTRA PUNKAH ISLAND

0 LAKE WERTA WERT 0

0 STANLEY ISLAND 0 0 0 3 3 4 4

2 ISLE OF MAN 2 6 MONOMAN ISLAND HORSESHOE LAGOON 6

QUEEN BEND

ROTTEN LAKE WILPERNA ISLAND 0 0

0 CHOWILLA ISLAND 0 0 0 8 8 3 3

2 CLOVER LAKE 2 6 6

LAKE MERRETI

LAKE WOOLPOLOOL HUNCHEE HANCOCK HILL 0 0 0 0 0 0

3 CAL LAL 3 3 3 2 2

6 RENY ISLAND VIC 6

CHAFFEY IRRIGATION AREA HORSESHOE LAGOON 465000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000

LEGEND Localities

0 2.5 5 10 RENMARK MILDURA Roads FIGURE 43 Kilometres WatercourseLines ADELAIDE SCALE 1:350,000 @ A4 Extent of Inundation GDA 1994 MGA Zone 54 State Boundary for Regulator Events Disclaimer: While all reasonable care has been taken to ensure the information ECHUCA contained on this map is up to date and accurate, no guarantee is given that the information portrayed is free from error or omission. Please verify the accuracy River Murray of all information prior to use. HORSHAM BENDIGO Note: Information shown on this map is a copyright of Aquaterra Australia 2011 Lakes

AUTHOR AL REPORT NO R001 MOUNT GAMBIER Inundation Extents DRAWN AL REVISION 1 DATA SOURCES PORTLAND Hydrotech DATE 11/05/11 JOB NO. A191 002 Cadastre Geoscience Australia

D:\Work Information\Aquaterra\Template\A4_Landscape.mxt 485000 490000 495000 500000 505000 0 0 0 0 0 0

0 0 RENMARK MILDURA

5 5 GRIFFITH 2 2 6 6 LAKE LIMBRA ADELAIDE

ECHUCA

COOMBOOL SWAMP HORSHAM BENDIGO

MOUNT GAMBIER MELBOURNE NSW PORTLAND OLD COOMBOOL

LEGEND

Localities 0 0 0 0

0 0 State Boundary LAKE LITTRA 5 5 4 4

2 SA 2 6 6 Watercourses

PUNKAH ISLAND LAKE WERTA WERT Roads

Cadastre BOAT CREEK ISLAND STANLEY ISLAND Waterways

Inundation for 40,000 ML/day Base Scenario HORSESHOE LAGOON MONOMAN ISLAND Inundation for 10,000 ML/day @ 19.25m (Regulator Scenario)

River Murray 0 0 0 0 0 0

0 QUEEN BEND 0 4 4 2 2 6 6

WILPERNA ISLAND

0 1 2 4

Kilometres SCALE 1:115,000 @ A4 0 0

0 0 GDA 1994 MGA Zone 54 0 0 5 5 3 3 DATA SOURCES 2 2

6 6 Hydrotech Geoscience Australia

HANCOCK HILL Disclaimer: While all reasonable care has been taken to ensure the information contained on this map is up to date and accurate, no guarantee is given that the information portrayed is free from error or omission. Please verify the accuracy of all information prior to use.

Note: The information shown on this map is a copyright of Aquaterra Australia 2011

VIC FIGURE 44 Inundation areas for 10,000 ML/day Regulator Event and 40,000 ML/day Base Event

AUTHOR AL REPORT NO R001

DRAWN AL REVISION 1 485000 490000 495000 500000 505000 DATE 12/05/11 JOB NO. A191 004

D:\Work Information\Aquaterra\Template\A4_Landscape.mxt 1,200 Modelled Salt Load for Regulator Scenario (Chowilla 2012 and 2007) 80,000 Chowilla 2012 Modelled Salt Load 1,000 Chowilla 2007 Modelled Salt Load Regulator Scenarios 60,000 800

600 40,000 Flow (ML/day) Salt Load (t/d) Load Salt 400 20,000 200

0 0 1975 1976 1979 1980 1983 1984 1987 1988 1991 1992 1995 1996 1999 2000 2003 2004

500 Regulator Impact - Regulator minus Base Model (Chowilla 2012 and 2007) 80,000 Chowilla 2012 Impact 400 Chowilla 2007 Impact Regulator Scenarios 60,000 300

200 40,000 100 Flow (ML/day) Salt Load (t/d) Load Salt 0 20,000

-100 1975 1976 1979 1980 1983 1984 1987 1988 1991 1992 1995 1996 1999 2000 2003 2004

-200 0

Modelled Salt Loads and Impact for the Regulator Scenario FIGURE 45

F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Landscape figures.xls]Fig 05 CHOWILLA MODEL 2012

6.4 SALT WATER BALANCE RUN RESULTS The salt and water balance (SWB) model developed by SKM (SKM 2011) was used to estimate the “real time” EC impact in the Murray River, downstream of the Chowilla confluence. This was only available for the four 10,000 ML/day at 19.25 m AHD regulator scenarios (1980, 1998, 2002 and 2004) as the SWB model was not designed for either the 10,000 ML/day and 30,000 ML/day at 19.87 m AHD scenarios. The regulator scenario version of the salt water balance model is based on surface water salinity data from 2008 to 2010. Essentially it represents a hypothetical situation (i.e. input data other than groundwater is based on a theoretical regulator scenario) however the groundwater input data was from each implementation of the 10,000 ML/day at 19.25 m AHD regulator event in Chowilla 2012. The results from the model (Figures 46 to 49) all show a short term (less than 5 days) spike in salinity of approximately 410 µS/cm at about 25 days after regulator operation. This is due to salt wash off and is consistent with the results presented in SKM 2010. After the regulator ceases operation (approximately day 90) and the river levels return to 5,000 ML/day (assumed flow between floods, approximately day 110) there is a small spike in the salinity (Table 6.2), which is predominantly groundwater related (SKM, 2010). For the 1980, 2002 and 2004 regulator events this spike is approximately 315 µS/cm and for the 1998 regulator event it is approximately 330 µS/cm (an increase on Murray River input salinity of approximately 50 and 65 µS/cm respectively). The difference for the 1998 regulator event is most likely due to antecedent conditions, specifically the 60,000 ML/day regulator event that occurred approximately 18 months prior to the 1998 event. While the SWB model does not cover this time period, the groundwater model (Chowilla 2012) does and it is the effect of the antecedent conditions on the groundwater input (from Chowilla 2012) to the SWB model that may impact on the results. While it was initially envisaged that a simple approach could be derived to pro-rata the salt washoff effect for a range of floods (i.e. for floods where the SWB model results are not available), the above discussion demonstrates that there is a wide range of factors influencing salinity effects. This is confirmed by the uncertainty analysis presented later, which shows a wide range of salt load effects, of which the salt washoff could be considered a minor component. In summary, the approaches applied to this study are consistent with the BSMS principle of applying a level of effort consistent with the magnitude of the salinity impact, while identifying the level of uncertainty relating to the salt load estimates. Table 6.2: Changes in Murray River Salinity due to Regulator Events

SWB Regulator Events Groundwater Salt Spike (µS/cm) Increase on Murray River Salinity (µS/cm)

1980 317 51 1998 331 66 2002 315 50 2004 316 51

Long term salinity impacts of the regulator event generally show a slow decrease, with the impact reducing to 40 µS/cm above Murray River input salinity 300 days after the regulator was first operated. This is consistent for all regulator events.

6.5 DISCUSSION OF SCENARIO RESULTS The salt load results presented may appear to be counter-intuitive in some cases, so it is worth reviewing some of the main inter-dependencies. The salt loads are basically dependent on the salinity and the volume of groundwater entering the river. It is assumed that the salinity value does not change with time. The volume of groundwater entering the river is dependent on the hydraulic gradient (difference between groundwater level and stream level) and the conductance of the stream beds. To explain the results, it is necessary to unpack each of these components and understand the impact of changes made to the Chowilla 2012 model.

Page 72 A191B/R002d

SALT WATER BALANCE MODEL FOR THE 1980 10,000 ML/DAY REGULATOR EVENT FIGURE 46 f:\jobs\a191\600\r002\figures\figure 48_salt water balance model for the 1980 regulator event.doc

SALT WATER BALANCE MODEL FOR THE 1998 10,000 ML/DAY REGULATOR EVENT FIGURE 47 f:\jobs\a191\600\r002\figures\figure 49_salt water balance model for the 1998 regulator event.doc

SALT WATER BALANCE MODEL FOR THE 2002 10,000 ML/DAY REGULATOR EVENT FIGURE 48 f:\jobs\a191\600\r002\figures\figure 50_salt water balance model for the 2002 regulator event.doc

SALT WATER BALANCE MODEL FOR THE 2004 10,000 ML/DAY REGULATOR EVENT FIGURE 49 f:\jobs\a191\600\r002\figures\figure 51_salt water balance model for the 2004 regulator event.doc

CHOWILLA MODEL 2012

6.5.1 GROUNDWATER SALINITY The mean groundwater salinity in both the Chowilla 2007 and Chowilla 2012 models is similar (~25,000 mg/L), however Chowilla 2007 has a single value applied to the entire model whereas Chowilla 2012 has a spatially variable salinity (~25,000 mg/L on the western half of the Chowilla floodplain and ~35,000 mg/L on the eastern half – see Table 3.4).

6.5.2 GROUNDWATER VOLUMES AND RELATED SALT LOADS

Hydraulic Gradient The driving head for groundwater flux entering the anabranches, and ultimately the River Murray, is the difference between the groundwater levels and the anabranch levels. The topography and stream levels in Chowilla 2012 have updated LIDAR data which has significantly changed the hydraulic gradient between the streams and groundwater from Chowilla 2007. In general, the stream levels have been reduced from 2007 and there were also some changes to the inundation areas resulting from the LIDAR changes (i.e. these are not a model parameter change but changes to the input data). As the groundwater levels are very similar between the Chowilla 2012 and 2007 models, then the reduction in the stream level input data would result in an increased hydraulic gradient, with the potential to generally increase salt loads. In terms of changes to model parameters, the anabranch stream bed conductance was changed for the Chowilla 2012 model (see next section), and this parameter has a noted impact on the salt load predictions.

Anabranch Bed Conductance Anabranch bed conductance values in Chowilla 2012 have been updated to reflect the dynamic nature of the anabranches during flood conditions, specifically the increase in the wetted perimeter with increased flow. The bed conductance values used in Chowilla 2012 do not vary spatially but do change with time, dependent on river levels (Table 3.2), whereas the bed conductance values used in Chowilla 2007 varied spatially but remained constant over time (Howe et al, 2007). This is particularly relevant to the 10,000 ML/day at 19.25 m AHD regulator scenario where there is a significant difference between Chowilla 2012 and Chowilla 2007. In Chowilla 2007, river zones 13, 14, 18 and 19 (mainly in the north-central part of the floodplain) had a significantly larger conductance value than for Chowilla 2012, allowing large volumes of groundwater to enter the system quickly, mobilising large salt loads (Figure 14). The decrease in conductance for Chowilla 2012 decreases the flux of groundwater able to enter streams at these locations, and thus also reduces the peak and total cumulative salt load mobilised back to the anabranch streams (despite the generally increase hydraulic gradient due to the lower stream levels, as described in the previous section).

A191B/R002d Page 77 CHOWILLA MODEL 2012

7. MODEL SENSITIVITY ANALYSIS

7.1 VARIATION TO SPECIFIC STRESS The sensitivity investigation undertaken looked at two components of the model, evapotranspiration and stream bed conductance. These two parameters were chosen due to uncertainty associated with them (lack of empirical evidence) and the identified model sensitivity from the calibration process.

7.1.1 EVAPOTRANSPIRATION Evapotranspiration is a key floodplain process that can impact groundwater levels and hence salt load to the river. As discussed in Section 3.2.4, evapotranspiration has two components, a maximum rate and an extinction depth. These components interact with the groundwater differently, with evaporation rate affecting peak groundwater levels and recession rates, while extinction depth affects the base groundwater level. For these reasons sensitivity to evapotranspiration was investigated through two model runs, one with doubled evapotranspiration rate and extinction depth and the other with doubled evapotranspiration rate only.

Evapotranspiration Rate and Extinction Depth Doubled A sensitivity run was conducted where both the evapotranspiration rate and extinction depth were doubled over the entire model (Figure 50). This did not include any changes to the evapotranspiration due to healthy eucalypt forest near the River Murray in the flush zone, which was represented in the model as negative recharge (Section 3.2.3). The effect of the increased rate and depth was: • A reduction in groundwater hydrographs by ~2m (Appendix G1 to G4). • A reduction in groundwater hydrograph peaks (Appendix G1 to G4). • A reduction in peak salt load by ~50% (Figure 51). • A reduction in the cumulative salt load by ~80% (Figure 52). • An increase in the duration of salt load impact

This response indicated that the model was fairly sensitive to evapotranspiration and the combination of rate and extinction depth. The output from this sensitivity run gave a very poor calibration match to groundwater level and salt load data and would need substantial adjustments in other parameters to achieve calibration.

Evapotranspiration Rate Doubled A sensitivity run was conducted where only the evapotranspiration rate was doubled over the entire model, with the extinction depth remaining the same as it was in the base model (Figure 53). This did not include any changes to the evapotranspiration due to healthy eucalypt forest near the River Murray in the flush zone, which was represented in the model as negative recharge (Section 3.2.3). The effect of the increased rate was: • Some reduction in groundwater hydrographs (~0.2m) (Appendix G5-G8). • Some reduction in groundwater hydrograph peaks (Figure G5-G8). • Reduced peak salt load by ~10% (Figure 51). • Reduced cumulative salt load by ~20% (Figure 52).

This response was consistent with the conceptual understanding of the effect of the evaporation rate on groundwater. The output from this sensitivity run gave reasonable calibration match to groundwater levels, which for some groundwater bores appears to be a slightly better match than the base model. However the calibration to the salt load data was worse than the base model, and would probably need minor adjustments in other parameters to achieve acceptable calibration performance. In a model uncertainty sense, this scenario provides a good indication of uncertainty, as the model calibration is not seriously affected.

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F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Salt Load Sensitivity.xls]Fig 02 1,000 Evapotranspiration Rate and Extinction Depth Doubled Chowilla 2012 Modelled Salt Load Sensitivity (ET Rate and Depth) 800 Operational Data Salt Load

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CHOWILLA MODEL 2012

7.1.2 ANABRANCH BED CONDUCTANCE Stream bed conductance controls the rate at which water can traverse between the stream and the surrounding area, both to and from the stream. In the Chowilla 2012 model this has significant impact on the salt load by controlling the amount of groundwater that can enter the anabranches and hence contribute to the salt load in the river. Sensitivity to bed conductance was investigated through two model runs, where the base case conductance for the anabranches was firstly multiplied by 10 and then by 100. The effects on the model were similar for both runs, just increased slightly for the bed conductance multiplied by 100. As such, the results from the two models can be considered together and these results indicate that an increase in bed conductance results in: • Increased groundwater hydrograph peaks (little difference between x10 and x100) (Appendix G9-G16). • Increased peak salt load (~200%, slightly more for x100) (Figure 54). • Increased cumulative salt load (~250% for x10 and ~400% for x100) (Figure 55).

This response indicates that the model is highly sensitive to changes in stream bed conductance. The output from these sensitivity runs gave a very poor calibration match to groundwater levels and salt load data that would need substantial adjustments in other parameters to achieve calibration.

7.2 EVENT BASED SALT LOAD ANALYSIS While the above sensitivity analysis involved some focus on individual flood events it was essentially an examination of the sensitive parameters over the period that the model was run. Additional analysis of modelled responses was required to investigate the impact of the parameter changes on specific groups of flood events leading to an event based salt load analysis. The purpose of this analysis was as follows: • To examine the salt load from similar sized floods from the base case model. • To determine a “typical flood” for each group of floods (based on maximum flood rate). • To determine the range around the “typical flood”. • To examine how the flood events from the sensitivity runs compared with the “typical flood”. • Floods were selected based on the peak flow from the simplified hydrograph (Figure 16). These included floods with peak flows of: - 40,000 ML/day. - 60,000 ML/day. - 100,000 ML/day. Floods with peaks of 20,000 and 80,000 ML/day were excluded as there were too few floods to perform the analysis. The analysis was performed by examining the salt load from the beginning of the flood (defined as the first time the flow was greater than 5,000 ML/day) and finding the peak salt load. Each flood event was then aligned at the peak of the salt load and plotted over one another (Figures 56 to 58). From this a “typical flood” for each peak flow rate was determined as well as a range for each flood, based on plus/minus one standard deviation (Figure 56 to 58). The same analysis was performed on the sensitivity runs, except the “typical flood” from the base model was plotted against the range of floods for each peak flood category (Figure 59 to 61). This was used to illustrate the sensitivity flood events in the model to the sensitivity parameters. From this analysis it was determined that: • Doubling the evapotranspiration rate and depth caused significant reduction in the salt load for all floods. • Both the 10x and 100x bed conductance runs significantly increased salt loads for all floods. • The sensitivity run where ET rate was doubled showed similarities to the “typical” flood for all flood events – example of model non-uniqueness issue.

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F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Salt Load Sensitivity.xls]Fig 04 300 Salt Loads for Modelled 40,000 ML/day Floods

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F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Salt Load Sensitivity Figures.xls]40000 Graph 500 ET Rate Doubled 2,500 Anabranch Stream Conductance x10 Typical Flood 1/08/1978 400 2,000 1/07/1983 1/08/1984

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F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Salt Load Sensitivity Figures.xls]60000 Graph 900 ET Rate Doubled 4,000 Anabranch Stream Conductance x10 Typical Flood 800 3,500 1/06/1975 700 1/07/1981 3,000 1/05/1990 600 1/04/1993 2,500 500 2,000 t/d t/d 400 1,500 300

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7.3 UNCERTAINTY IN MEASURED AND MODELLED SALT LOAD DATA The above event based salt load analysis highlighted the range of salt loads may be expected for a “typical flood” based on modelled salt load data. The same analysis was performed on measured salt load data to determine the salt load of a “typical flood” as well as the range of salt loads that could be expected. This analysis was undertaken for the same floods used in the analysis of modelled salt loads (above), however there were some differences, specifically: • Peak salt load (modelled and measured) for the flood did not occur at the same time for some floods. - This meant that while the methodology for analysing the floods remained the same, the time period over which they were analysed was different for some floods • Measured data was incomplete for some floods. This affected: - The 40,000 ML/day flood approximately 30 days prior to the peak of the flood - The 60,000 ML/day flood approximately 30 days prior to the peak of the flood - The 60,000 ML/day flood analysis as the 1983 flood included in the modelled flood analysis had insufficient measured data for analysis. To examine the level of uncertainty for the modelled salt load during flood events a comparison between the event based analysis of measured and modelled was undertaken (Figure 62 to 64). This comparison indicated that for floods of 40,000 ML/day and 100,000 ML/day, modelled salt loads were of a similar shape and magnitude to measured salt loads, however significant differences between modelled and measured salt loads for a “typical flood” were seen for a 60,000 ML/day event. This may be due to a combination of the low number of floods analysed for the 60,000 ML/day floods (3 floods) compared to the 40,000 and 100,000 ML/day floods (6 and 4 floods respectively) as well as the varability of the floods analysed (Figure 63).

7.4 CONCLUSION AS TO THE DRIVERS IN THE SYSTEM The sensitivity analysis conclusively demonstrated that the Chowilla 2012 model is sensitive to both evapotranspiration and stream bed conductance. Stream bed conductance values appeared to have the greater impact on the model, however this was increased by an order or magnitude unlike evapotranspiration, which was doubled. As Chowilla 2012 has demonstrated sensitivity to evapotranspiration it is recommended that any future work on the model include reconciliation between model evapotranspiration and any available data, including remotely sensed evapotranspiration data. Bed conductance should also be reviewed in any future work, however no relevant data sets have identified at this point in time.

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8. SUMMARY/CONCLUSIONS

8.1 MODEL IMPROVEMENTS The primary improvement to the Chowilla 2012 model was the inclusion of the corrected LIDAR data, which resulted in changes to the following model parameters: • Inundation area. • Stream levels. • Model topography. • Evapotranspiration (a depth-dependent process related to the specified topographic level).

In addition, the representation of the Murray River in the model was changed from constant head cells to river cells. Anabranch bed conductance values were also updated to reflect the dynamic nature of the anabranches during flood conditions, specifically the increase in the wetted perimeter with increased flow.

8.2 RESULTS The base case model was assessed using a multiple lines of evidence approach including: • Match to measured groundwater levels. • Scaled root mean squared analysis at specific times. • Comparison to time series measured salt load data. • Comparison to cumulative measured salt load data. • Comparison to measured 12 month post flood salt loads.

For all assessments the base case model was determined to be acceptable. Chowilla 2012 showed similar calibration/confirmation as Chowilla 2007, however a significant improvement was observed in the match to cumulative measured salt load. The scenario run was designed to assess the impact of regulator operation over the benchmark period (1975-2000). The results from this assessment indicated that: • 10,000 ML/day at 19.87 m AHD regulator events show the greatest increase in salt load to the river, with peak impacts (effect due to regulator) ranging from ~150 to 300 t/day. • The maximum peak impact of ~300 t/day occurs for the event in the year 2000 subsequent to the 10,000 ML/day at 19.87 m AHD regulator operation. • Impact on peak salt load of subsequent flooding events of up to ~100 t/day (most noticeable in the period between the 1987 and 1996 regulator events). • Salt load effect (above base case) due to regulator event recedes over a period of about one year (roughly same as for Chowilla 2007), but can be interrupted by a natural flood.

The salt water balance model was used to determined real time impact of 10,000 at 19.27 m AHD ML/day regulator scenarios. This indicated that the groundwater impact of the regulator events would occur approximately 110 days after regulator operation and would be an increase of about 50 to 70 µS/cm. This decreases to 40 µS/cm above Murray River input salinity 300 days after the regulator was first operated.

8.3 MODEL CAPABILITY, ASSUMPTIONS AND LIMITATIONS Chowilla 2012 is a calibrated and documented groundwater model designed to predict the groundwater flux, and hence salt loads, to the Murray River over the benchmark period, both for existing flow events and proposed regulator events. In principle, the model is suitable for simulating any form of environmental watering, similar to the EM4 model developed by Aquaterra for the Lindsay River area (Aquaterra, 2008).

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Assumptions and simplifications were required to develop the Chowilla 2012 model and they are described in depth in Section 3.2.2. However, key assumptions and simplifications include: • A flat Murray River weir pool (no backwater curves). • A simplified Murray River Flow Hydrograph comprising monthly time steps and 20,000 ML/d flow magnitude divisions with a river flow of 5000 ML/d assumed between flood events. • Inundation areas and stream levels for flows of 80,000 and 100,000 ML/day are represented by pre-locking conditions in the hydrodynamic model. • Anabranch bed conductance parameter values that increase as the water level in the anabranches increases (representing increased wetted perimeter). • Evapotranspiration from deep-rooted floodplain vegetation in the flush zone represented by an area of negative recharge. • Salinity zones based on AEM data.

Many of these assumptions are based on the concept that they are conservative, i.e. that the assumption would cause the model to over predict rather than under predict salt load. In addition the time steps dictated by the simplified hydrograph means that short term (less than monthly) events are not able to be represented by this model. The model was evaluated for sensitivity to key parameters, specifically evapotranspiration and stream bed conductance values. It demonstrated sensitivity to both parameters, however evapotranspiration was identified as a parameter that could require more benchmarking to properly constrain the parameter and reduce any potential model non-uniqueness effects.

8.4 RECOMMENDATIONS The Chowilla 2012 model configuration produces acceptable results, however, if future modelling work is undertaken with this model the following changes may need to be considered: • Benchmarking evapotranspiration in the model against existing remotely sensed data (or any other data available). • Dynamic river levels in the Murray River. • Implementation of backwater curves in the Murray River.

In addition to the groundwater model, this upgrade used the salt water balance developed by SKM to examine real time salinity. The original design of SWB model meant that only part of the original scope of work was able to be achieved and any future work involving this model may require action to address the following, which may require additional input from the hydrodynamic model: • Redesigning the SWB model to allow it represent 40,000 and 60,000 ML/day regulator events (or other regulator events required in future work). • Further validate the model against existing floods, including flood recession. • Review whether there is evidence of a significant recharge event due to the extremely high rainfall events of 2010-11 that could impact on salt load predictions. • Change the model such that it can be unpacked to identify what is the contribution from groundwater and what is the contribution from salt wash off. • The model is currently locked so that no interrogation can be made of the relative contributions.

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9. REFERENCES

Anon (1989) The hydrogeology of the Chowilla floodplain. Status report. Aquaterra. (2008). Lock 10 to SA Border Groundwater Model (EM4). Report to SKM. December 2008. Aquaterra (2010) Salinity and Water Use Impacts of River Murray Weir Pool Manipulations, prepared for SA Murray-Darling Basin Natural Resource Management Board Barnett SR (1990) Murray basin hydrogeological investigation - Mallee region groundwater modelling exercise. South Australian Department of Mines and Energy. Report book 90/36. Collingham EB (1990) The basic hydrogeology of the Chowilla Area. Engineering and Water Supply Department of Adelaide. For Murray Darling Basin Commission, 1990. Holland K, Jolly ID, Tyerman S, Mensforth L, Telfer A and Walker GR (2001) Interception of groundwater discharge by floodplain in the lower River Murray: Implications for river salinity. 8th Murray Darling Basin Groundwater Workshop 2001. Howe B, Yan W and Stadter M (2007) Groundwater impact assessment of the proposed Chowilla regulator using the Chowilla numerical model: Report 1, Knowledge and Information Division, Department of Water, Land and Biodiversity Conservation, South Australia Report 2007/28. Howles SR and Marsden ZE (2003) Pump testing on the Chowilla floodplain at Gum Flat in South Australia and Tareena Bong in New South Wales. Department of Water, Land and Biodiversity Conservation. Report 2003/10. Jolly ID and Walker GR (1995) A sketch of salt and water movement in the Chowilla floodplain. CSIRO Division of Water Resources. Adelaide South Australia. November 1995. McDonald MG and Harbaugh AW (1988) A modular three-dimensional finite-difference ground- water flow model: U.S. Geological Survey Techniques of Water-Resources Investigations, book 6, chap. A1, 586 pp. Middlemis H (2001) Groundwater Flow Modelling Guideline. Report by Aquaterra to Murray-Darling Basin Commission. January 2001.

Overton IC, Rutherford JC and Jolly ID (2005) Flood extent, groundwater recharge and vegetation response from operation of a potential weir in Chowilla Creek, South Australia, Report to SA Department of Water, Land and Biodiversity Conservation CSIRO Land and Water Client Report. Salient Solutions (2008) Chowilla Salinity Methodology Peer Review MD1118, Murray Darling Basin Commission, Australia Sharley T and Huggan H (1995) Chowilla resources management plan. Prepared by the Murray- Darling Basin Commission Chowilla Working Group in consultation with the Chowilla Reference Group. Final Report. Thornburn PJ, Thomas JH and Walker GR (1993) Combining measurements of transpiration and stable isotopes of water to determine groundwater discharge from forests. Journal of Hydrology. 150 (1993) p563-587. Water Technology (2009) Chowilla Hydraulic Model Redevelopment and Calibration, prepared for South Australian Murray Darling Basin Natural Resource Management Board Waterhouse JD (1989) The hydrogeology of the Chowilla floodplain. Status report for MDBC. MDBC, Canberra. Waterloo Hydrogeologic Inc. (2004) Visual MODFLOW v.4.0 User’s Manual – The Industry Standard for 3D Groundwater Flow and Contaminant Transport Modelling. Waterloo, Ontario, Canada. Watkins NC (1992) Chowilla resource management plan hydrogeological data report 3. Interpretation of aquifer pump test. Engineering and Water Supply Department of Adelaide. For Murray Darling Basin Commission. EWS 92/8.

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Yan W, Howles S and Marsden Z (2004) Chowilla floodplain numerical groundwater model, DWLBC Report 2004/65, Knowledge and Information Division, Department of Water, Land and Biodiversity Conservation, South Australia.

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10. GLOSSARY

Anabranch — A branch of a river that leaves the main channel. Aquifer — An underground layer of rock or sediment that holds water and allows water to percolate through. Aquifer, confined — Aquifer in which the upper surface is impervious and the water is held at greater than atmospheric pressure. Water in a penetrating well will rise above the surface of the aquifer. Aquifer, unconfined — Aquifer in which the upper surface has free connection to the ground surface and the water surface is at atmospheric pressure. Aquitard — A layer in the geological profile that separates two aquifers and restricts the flow between them. Basin — The area drained by a major river and its tributaries. Benchmark condition — Points of reference from which change can be measured. Biota — All of the organisms at a particular locality. CSIRO — Commonwealth Scientific and Industrial Research Organisation. DEH — Department for Environment and Heritage (Government of South Australia). DFW – Department for Water (Government of South Australia, previously DWLBC). DWLBC — Department of Water, Land and Biodiversity Conservation (Government of South Australia). EC — Electrical conductivity. 1 EC unit = 1 micro-Siemen per centimetre (μS/cm) measured at 25°C. Commonly used to indicate the salinity of water. Evapotranspiration — The total loss of water as a result of transpiration from plants and evaporation from land, and surface water bodies. Floodplain — Of a watercourse means: (a) the floodplain (if any) of the watercourse identified in a catchment water management plan or a local water management plan; adopted under Part 7 of the Water Resources Act 1997; or (b) where paragraph (a) does not apply — the floodplain (if any) of the watercourse identified in a development plan under the Development Act 1993, or (c) where neither paragraph (a) nor paragraph (b) applies — the land adjoining the watercourse that is periodically subject to flooding from the watercourse. GMS — Groundwater Management Scheme. A well field designed and operated to lower the groundwater table. Groundwater — Water occurring naturally below ground level or water pumped, diverted or released into a well for storage underground. Hydrogeology — The study of groundwater, which includes its occurrence, recharge and discharge processes, and the properties of aquifers. (See hydrology.) Impact — A change in the chemical, physical, or biological quality or condition of a water body caused by external sources. Infrastructure — Artificial lakes; dams or reservoirs; embankments, walls, channels or other works; buildings or structures; or pipes, machinery or other equipment. Model — A conceptual or mathematical means of understanding elements of the real world which allows for predictions of outcomes given certain conditions. Examples include estimating storm runoff, assessing the impacts of dams or predicting ecological response to environmental change. Monitoring — (1) The repeated measurement of parameters to assess the current status and changes over time of the parameters measured. (2) Periodic or continuous surveillance or testing to determine the level of compliance with statutory requirements and/or pollutant levels in various media or in humans, animals, and other living things.

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Natural resources — Soil; water resources; geological features and landscapes; native vegetation, native animals and other native organisms; ecosystems. Obswell — Observation Well Network. Permeability — A measure of the ease with which water flows through an aquifer or aquitard. The unit is m2/d. Potentiometric head — The potentiometric head or surface is the level to which water rises in a well due to water pressure in the aquifer; the unit is metres (m). QSA Flow — Flow to South Australia. Real Time — Real time water management can be defined as the process of making decisions to achieve the optimal short term operation of the water management system in response to hydrological conditions ranging from local scale environmental flow events (time frames of hours, weeks or months) to major floods and subsequent recessions (time frames of months to several years) in order to achieve water quality/quantity targets and maintain/improve ecological values. Recharge — The infiltration of water into an aquifer from the surface (rainfall, streamflow, irrigation etc.). Recharge area — The area of land from which water from the surface (rainfall, streamflow, irrigation, etc.) infiltrates into an aquifer. (See artificial recharge, natural recharge.) Regulator — A permanent in stream structure that can be used to control surface water flow. Shuttle Radar Topography Mission (SRTM) – This mission obtained elevation data on a near- global scale to generate the most complete high-resolution digital topographic database of Earth. With respect to this project it refers to the elevation data produced which has an accuracy of ±10m.

Specific storage (Ss) — The amount of water per unit volume of a saturated formation that is expelled from storage due to compression of the mineral skeleton and the pore water.

Specific yield (Sy) — The ratio of the volume of water that a given mass of saturated soil or rock will yield by gravity to the volume of that mass. Surface water — (a) water flowing over land (except in a watercourse), (i) after having fallen as rain or hail or having precipitated in any another manner, (ii) or after rising to the surface naturally from underground; (b) water of the kind referred to in paragraph (a) that has been collected in a dam or reservoir. TDS —Total Dissolved Solids; the unit is milligrams per litre (mg/L). UNESCO — United Nations Educational, Scientific and Cultural Organization. Well — (a) an opening in the ground excavated for the purpose of obtaining access to underground water; (b) an opening in the ground excavated for some other purpose but that gives access to underground water; (c) a natural opening in the ground that gives access to underground water.

A191B/R002d Page 101

APPENDIX A: DOCUMENTATION FOR LIDAR

ABN: 60 093 377 283 ACN: 093 377 283

4th August 2008

Brad Hollis SA MDB NRM Board 28 Vaughan Tce PO Box 240 Berri, South Australia, 5343

Our Ref: J947_L01_BT File No: J7947.01

Dear Brad

Chowilla LiDAR Analysis

Overview The following letter summarises the Chowilla floodplain LiDAR revision. In an email dated 14th of March 2008 Water Technology outlined the discrepancies found between the LiDAR and nine surveyed creek cross-sections. The LiDAR seemed to be approximately 0.3 m higher than the field survey. Subsequent to that finding, the benchmark that the LiDAR was based upon was found to be in error. The benchmark datum was resurveyed in June 2008 and was revised from 60.438 m AHD to 60.232 m AHD (Geoff Sandford – Department for Transport Energy and Infrastructure).

LiDAR The LiDAR laser scanning was undertaken by AAM Hatch with the base station and test points carried out by LICS (now SKM). A metadata report (June 2003), and a Powerpoint presentation of the final LiDAR, provides details regarding the Chowilla LiDAR survey. Only one survey control point was used for the LiDAR, benchmark 7030/1128 with a stated relative level of 60.438 m AHD. The report also states that 241 test points were checked against the interpolated terrain model with a standard error of 0.062 m. This is taken to mean that the interpolated terrain model (that is created from raw laser scanned points), was checked against the raw laser scanned points, to ensure that the algorithm used to create the terrain model was providing accurate results.

The report states that “this data has not been field tested for completeness”. It is difficult to determine exactly what ground truthing was undertaken from the LiDAR documentation, but it is presumed that the lack of has led to the now discovered error in the LiDAR.

A 2m Vertical Mapper grid was developed for the existing LiDAR dataset. S:\J947_CHOWILLA HYDRAULICM 0809\DOCS\REPORT\L01_J947_LIDAR_UPDATE_V2.DOCL01_J947_LIDAR_UPDATE _V2.DOC

Field Survey Extensive field survey of the Chowilla Anabranch system was undertaken by Todd Alexander and is documented in a survey report (June, 2005). The control for this survey used a Leica System 530 RTK GPS, with 15 known control points surveyed. This control set the height at the 7030/1128 benchmark at 60.217 m AHD (0.221 m lower than the LiDAR).

The 7030/1128 benchmark was resurveyed in June 2008 in an attempt to resolve this issue, the revised level was set at 60.232 m AHD (this is only 0.015 m higher than the level used in the cross-section field survey).

The majority of the cross-sections were just bank to bank, with only nine cross-sections extending out onto the floodplain. These cross-sections were used to compare to the LiDAR, as outlined below.

Survey Comparison Nine cross-sections from the field survey were compared with the LiDAR Vertical Mapper grid. The locations of these cross-sections are shown in Figure 1, with the comparison plots shown in Figures 2 to 10. A summary of the average differences for these cross-sections is also shown in Table 1.

The original LiDAR grid was lowered so that the elevation at the resurveyed benchmark 7030/1128 was equal to the resurveyed benchmark datum 60.232 m AHD. It was found that the LiDAR grid was still consistently higher than the surveyed cross-sections, on average 0.152 m. This may be due to the benchmark not being representative of the ground surface for the particular 2x2 m grid cell that the benchmark falls within. Benchmarks are not necessarily at ground level, they may be partially buried or sit slightly above the ground, it may also be on sloping ground.

The original LiDAR Vertical Mapper grid was lowered to reduce the vertical discrepancy with the cross-section survey. Only the points on the floodplain were used from the cross- section survey to compare with the LiDAR as the points in the channel from the LiDAR are not accurate due to the presence of water during the LiDAR survey. After a number of iterations it was found that in order to best eliminate the vertical discrepancy between the LiDAR and the cross-section survey, the LiDAR was required to be lowered by 0.326 m. The surveyed cross-sections and the lowered LiDAR grid are compared in Figures 2 to 10 and Table 1. This shows that lowering the LiDAR by 0.326 m provides a good fit with the cross-section field survey.

A comparison of the surveyed heights and lowered LiDAR for the available 4th order benchmarks at Chowilla is provided in Table 2. The location of the benchmarks is displayed in Figure 1. As discussed above the benchmarks may not be representative of the ground level as they may be partially buried, slightly above ground or be on sloping ground. This shows that for four of the five benchmarks the lowered LiDAR is lower than the surveyed benchmark level, however the average difference is only -0.09 m.

S:\J947_CHOWILLA HYDRAULICM 0809\DOCS\REPORT\L01_J947_LIDAR_UPDATE_V2.DOC 2 QFORM-AD-10 REV4

Cross-Section Benchmark Point

Figure 1 – Chowilla LiDAR Validation Points

Figure 2 – Chowilla Creek Cross-Section 1

S:\J947_CHOWILLA HYDRAULICM 0809\DOCS\REPORT\L01_J947_LIDAR_UPDATE_V2.DOC 3 QFORM-AD-10 REV4

Figure 3 – Chowilla Creek Cross-Section 2

Figure 4 – Chowilla Creek Cross-Section 3

S:\J947_CHOWILLA HYDRAULICM 0809\DOCS\REPORT\L01_J947_LIDAR_UPDATE_V2.DOC 4 QFORM-AD-10 REV4

Figure 5 – Monoman Creek Cross-Section

Figure 6 – Punkah Creek Cross-Section 1

S:\J947_CHOWILLA HYDRAULICM 0809\DOCS\REPORT\L01_J947_LIDAR_UPDATE_V2.DOC 5 QFORM-AD-10 REV4

Figure 7 – Punkah Creek Cross-Section 2

Figure 8 – Punkah Creek Cross-Section 3

S:\J947_CHOWILLA HYDRAULICM 0809\DOCS\REPORT\L01_J947_LIDAR_UPDATE_V2.DOC 6 QFORM-AD-10 REV4

Figure 9 – Salt Creek Cross-Section 1

Figure 10 – Salt Creek Cross-Section 2

S:\J947_CHOWILLA HYDRAULICM 0809\DOCS\REPORT\L01_J947_LIDAR_UPDATE_V2.DOC 7 QFORM-AD-10 REV4

Table 1 – Summary of Lowered LiDAR Validation for Cross-Sections Validation Cross‐Section Average Difference (m) Chowilla Creek 0.095 Chowilla Creek 2 ‐0.050 Chowilla Creek 3 0.017 Monoman Creek ‐0.012 Punkah Creek ‐0.064 Punkah Creek 2 ‐0.067 Punkah Creek 3 ‐0.011 Salt Creek 0.035 Salt Creek 2 0.057

Table 2 – Summary of Lowered LiDAR Validation for Benchmarks Validation Benchmark Survey Elevation LiDAR Elevation Difference (m) (m AHD) (m AHD) 70301232 21.456 21.371 ‐0.085 70301254 34.326 34.269 ‐0.057 70304029 44.481 44.298 ‐0.184 70301128 60.232 60.080 ‐0.152 71301052 20.712 20.724 0.012

S:\J947_CHOWILLA HYDRAULICM 0809\DOCS\REPORT\L01_J947_LIDAR_UPDATE_V2.DOC 8 QFORM-AD-10 REV4

Conclusions It has been demonstrated that the LiDAR data for the Chowilla floodplain is inaccurate due to the accuracy of the benchmark of which the LiDAR was based on. This benchmark has been resurveyed and the LiDAR has been lowered to best eliminate the vertical discrepancy between the LiDAR and the cross-section field survey. It has been found that lowering the LiDAR by 0.326 m achieves the best fit overall between the LiDAR and the cross-section field survey. This lowered LiDAR was checked against five benchmarks and it was found that on average the Lowered LiDAR was 0.09 m lower than the surveyed benchmark heights.

It is suggested that before we sign off on this change to the LiDAR that we get an independent review, possibly from Geoff Sandford, as he conducted the revision of the 7030/1128 benchmark datum. It is also advised that MDBC be made aware of this change and its implications.

If it is thought that additional survey is required to validate this LiDAR change, then it is suggested that a number of transect lines be surveyed along relatively flat road surfaces across the floodplain. For previous studies Water Technology has found that a 100 m long transect with points surveyed every 10 m provides a good basis for validating LiDAR. If this is required Water Technology can provide georeferenced shapefiles indicating the best location for survey to be undertaken.

Water Technology will forward a CD with the lowered LiDAR, it is suggested that all old versions of the LiDAR be deleted/archived and clearly marked “superseded”, and replaced with the lowered version. All consultants using this LiDAR should be notified of the change.

If you have any questions regarding this document please contact Ben Tate or Warwick Bishop on (03) 9558 9366.

Yours sincerely Water Technology Pty Ltd

Ben Tate Project Manager ISO 9001 QEC22878 Ph. (03) 9558 9366 SAI Global [email protected]

S:\J947_CHOWILLA HYDRAULICM 0809\DOCS\REPORT\L01_J947_LIDAR_UPDATE_V2.DOC 9 QFORM-AD-10 REV4

APPENDIX B: SURFACE ELEVATION CONTOURS

Anabranches, backwaters and water bodies

Surface elevation contours (m AHD)

­

03.57 km Lock6 Produced By: Water Information Group Knowledge and Information Division Department of Water, Land and Biodiversity Conservation Coordinates: Northing, Easting Datum: GDA_1994_UTM_Zone_54 Date: May 2005

DISCLAIMER The Department of Water, Land and Biodiversity Conservation, its employees and servants do not warrant or make any representation regarding the use, or results of use of the information contained herein as to its correctness, accuracy, currency or otherwise. The Department of Water, Land and Biodiversity Conservation, its Lock7 employees and servants expressly disclaim all liability or responsibility to any person using the information or advice contained herein. COPYRIGHT © Department of Water, Land and Biodiversity Conservation 2004. This work is Copyright. Apart from any use permitted under the Copyright Act 1968 (Cwlth), no part may be reproduced by any process without prior written permission obtained from the Department of Water, Land and Biodiversity Conservation. Requests and enquiries concerning reproduction and rights should be directed to the Chief Executive, Department of Water, Land and Biodiversity Conservation, GPO Box 2834, Adelaide SA 5001.

Figure B1. Ground surface elevation Chowilla floodplain (Yan et al, 2004) Anabranches, backwaters and water bodies

Surface elevation contours (m AHD)

­

03.57 km

Lock6 Produced By: Water Information Group Knowledge and Information Division Department of Water, Land and Biodiversity Conservation Coordinates: Northing, Easting Datum: GDA_1994_UTM_Zone_54 Date: May 2005

DISCLAIMER The Department of Water, Land and Biodiversity Conservation, its employees and servants do not warrant or make any representation regarding the use, or results of use of the information contained herein as to its correctness, accuracy, currency or otherwise. The Department of Water, Land and Biodiversity Conservation, its Lock7 employees and servants expressly disclaim all liability or responsibility to any person using the information or advice contained herein. COPYRIGHT © Department of Water, Land and Biodiversity Conservation 2004. This work is Copyright. Apart from any use permitted under the Copyright Act 1968 (Cwlth), no part may be reproduced by any process without prior written permission obtained from the Department of Water, Land and Biodiversity Conservation. Requests and enquiries concerning reproduction and rights should be directed to the Chief Executive, Department of Water, Land and Biodiversity Conservation, GPO Box 2834, Adelaide SA 5001.

Figure B2. Base elevation Upper Monoman Formation and Upper Pliocene Sands (Yan et al, 2004) Anabranches, backwaters and water bodies

Surface elevation contours (m AHD)

­

03.57 km Lock6 Produced By: Water Information Group Knowledge and Information Division Department of Water, Land and Biodiversity Conservation Coordinates: Northing, Easting Datum: GDA_1994_UTM_Zone_54 Date: May 2005

DISCLAIMER The Department of Water, Land and Biodiversity Conservation, its employees and servants do not warrant or make any representation regarding the use, or results of use of the information contained herein as to its correctness, accuracy, currency or otherwise. The Department of Water, Land and Biodiversity Conservation, its Lock7 employees and servants expressly disclaim all liability or responsibility to any person using the information or advice contained herein. COPYRIGHT © Department of Water, Land and Biodiversity Conservation 2004. This work is Copyright. Apart from any use permitted under the Copyright Act 1968 (Cwlth), no part may be reproduced by any process without prior written permission obtained from the Department of Water, Land and Biodiversity Conservation. Requests and enquiries concerning reproduction and rights should be directed to the Chief Executive, Department of Water, Land and Biodiversity Conservation, GPO Box 2834, Adelaide SA 5001.

Figure B3. Base elevation Lower Monoman Formation and Upper Pliocene Sands (Yan et al, 2004) Anabranches, backwaters and water bodies

Surface elevation contours (m AHD)

­

03.57 km

Lock6 Produced By: Water Information Group Knowledge and Information Division Department of Water, Land and Biodiversity Conservation Coordinates: Northing, Easting Datum: GDA_1994_UTM_Zone_54 Date: May 2005

DISCLAIMER The Department of Water, Land and Biodiversity Conservation, its employees and servants do not warrant or make any representation regarding the use, or results of use of the information contained herein as to its correctness, accuracy, currency or otherwise. The Department of Water, Land and Biodiversity Conservation, its Lock7 employees and servants expressly disclaim all liability or responsibility to any person using the information or advice contained herein. COPYRIGHT © Department of Water, Land and Biodiversity Conservation 2004. This work is Copyright. Apart from any use permitted under the Copyright Act 1968 (Cwlth), no part may be reproduced by any process without prior written permission obtained from the Department of Water, Land and Biodiversity Conservation. Requests and enquiries concerning reproduction and rights should be directed to the Chief Executive, Department of Water, Land and Biodiversity Conservation, GPO Box 2834, Adelaide SA 5001.

Figure B4. Base elevation Lower Pliocene Sands (Yan et al, 2004) Anabranches, backwaters and water bodies

Surface elevation contours (m AHD)

­

03.57 km Lock6 Produced By: Water Information Group Knowledge and Information Division Department of Water, Land and Biodiversity Conservation Coordinates: Northing, Easting Datum: GDA_1994_UTM_Zone_54 Date: May 2005

DISCLAIMER The Department of Water, Land and Biodiversity Conservation, its employees and servants do not warrant or make any representation regarding the use, or results of use of the information contained herein as to its correctness, accuracy, currency or otherwise. The Department of Water, Land and Biodiversity Conservation, its Lock7 employees and servants expressly disclaim all liability or responsibility to any person using the information or advice contained herein. COPYRIGHT © Department of Water, Land and Biodiversity Conservation 2004. This work is Copyright. Apart from any use permitted under the Copyright Act 1968 (Cwlth), no part may be reproduced by any process without prior written permission obtained from the Department of Water, Land and Biodiversity Conservation. Requests and enquiries concerning reproduction and rights should be directed to the Chief Executive, Department of Water, Land and Biodiversity Conservation, GPO Box 2834, Adelaide SA 5001.

Figure B5. Base elevation Bookpurnong Formation (Yan et al, 2004) Anabranches, backwaters and water bodies

Surface elevation contours (m AHD)

­

03.57 km Lock6 Produced By: Water Information Group Knowledge and Information Division Department of Water, Land and Biodiversity Conservation Coordinates: Northing, Easting Datum: GDA_1994_UTM_Zone_54 Date: May 2005

DISCLAIMER The Department of Water, Land and Biodiversity Conservation, its employees and servants do not warrant or make any representation regarding the use, or results of use of the information contained herein as to its correctness, accuracy, currency or otherwise. The Department of Water, Land and Biodiversity Conservation, its Lock7 employees and servants expressly disclaim all liability or responsibility to any person using the information or advice contained herein. COPYRIGHT © Department of Water, Land and Biodiversity Conservation 2004. This work is Copyright. Apart from any use permitted under the Copyright Act 1968 (Cwlth), no part may be reproduced by any process without prior written permission obtained from the Department of Water, Land and Biodiversity Conservation. Requests and enquiries concerning reproduction and rights should be directed to the Chief Executive, Department of Water, Land and Biodiversity Conservation, GPO Box 2834, Adelaide SA 5001.

Figure B6. Base elevation Murray Group Limestone (Yan et al, 2004)

APPENDIX C: HYDRAULIC PARAMETERS

6265000

6260000 Kx = 5 m/d Kz = 5 m/d

6255000

Kx = 15 m/d Kz = 0.15 m/d

6250000 Kx = 15 m/d Kz = 0.1 m/d

Kx = 10 m/d 6245000 Kz = 0.1 m/d

Kx = 15 m/d 6240000 Kz = 1 m/d

6235000

Kx = 0.1 m/d 6230000 Kz = 0.1 m/d

6225000

6220000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000

LAYER 1 HYDRAULIC CONDUCTIVITY DISTRIBUTION FIGURE C.01

\\rpsadldc02\at1\jobs\a191\600\r002\appendicies\appendix_d\figure_d01_layer 1 hydraulic conductivity distribution.doc

6265000

6260000 Kx = 5 m/d Kz = 5 m/d

6255000

Kx = 5 m/d Kz = 0.15 m/d

6250000 Kx = 5 m/d Kz = 0.15 m/d

6245000 Kx = 5 m/d Kz = 0.15 m/d

6240000 Kx = 5 m/d Kz = 1 m/d

6235000

Kx = 0.1 m/d 6230000 Kz = 0.1 m/d

6225000

6220000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000

LAYER 2 HYDRAULIC CONDUCTIVITY DISTRIBUTION FIGURE C.02

\\rpsadldc02\at1\jobs\a191\600\r002\appendicies\appendix_d\figure_d02_layer 2 hydraulic conductivity distribution.doc

6265000

6260000

6255000

6250000

6245000 Kx = 3 m/d Kz = 0.05 m/d

6240000

6235000

6230000

6225000

6220000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000

LAYER 3 HYDRAULIC CONDUCTIVITY DISTRIBUTION FIGURE C.03

\\rpsadldc02\at1\jobs\a191\600\r002\appendicies\appendix_d\figure_d03_layer 3 hydraulic conductivity distribution.doc

6265000

6260000

6255000

6250000

6245000 Kx = 1e-7 m/d Kz = 1e-7 m/d

6240000 Kx = 8e-6 m/d Kz = 8e-6 m/d

6235000

6230000

6225000

6220000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000

LAYER 4 HYDRAULIC CONDUCTIVITY DISTRIBUTION FIGURE C.04

\\rpsadldc02\at1\jobs\a191\600\r002\appendicies\appendix_d\figure_d04_layer 4 hydraulic conductivity distribution.doc

6265000

6260000

6255000

6250000

Kx = 3 m/d 6245000 Kz = 0.1 m/d

6240000

6235000

6230000

6225000

6220000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000

LAYER 5 HYDRAULIC CONDUCTIVITY DISTRIBUTION FIGURE C.05

\\rpsadldc02\at1\jobs\a191\600\r002\appendicies\appendix_d\figure_d05_layer 5 hydraulic conductivity distribution.doc

6265000

6260000 Sy = 0.005 Ss = 0.001

6255000

6250000

Sy = 0.05 Ss = 0.0001 6245000

6240000

6235000

6230000

6225000

6220000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000

LAYER 1 STORAGE DISTRIBUTION FIGURE C.06

\\rpsadldc02\at1\jobs\a191\600\r002\appendicies\appendix_d\figure_d06_layer 1 storage distribution.doc

6265000

6260000

Sy = 0.05 Ss = 0.0001 6255000

6250000 Sy = 0.05 Ss = 0.0001

6245000

6240000

6235000

6230000

6225000

6220000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000

LAYER 2 STORAGE DISTRIBUTION FIGURE C.07

\\rpsadldc02\at1\jobs\a191\600\r002\appendicies\appendix_d\figure_d07_layer 2 storage distribution.doc

6265000

6260000

6255000

6250000

6245000 Sy = 0.05 Ss = 1e-5

6240000

6235000

6230000

6225000

6220000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000

LAYERS 3 - 5 STORAGE DISTRIBUTION FIGURE C.08

\\rpsadldc02\at1\jobs\a191\600\r002\appendicies\appendix_d\figure_d08_layer 3_5 storage distribution.doc

APPENDIX D: INUNDATION AREAS

485000 490000 495000 500000 485000 490000 495000 500000 0 0 0 0

0 100 GL 0 0 80 GL 0 0 0 0 0 3 3 3 3 5 5 5 5 2 2 2 2 6 6 6 6

LAKE LIMBRA LAKE LIMBRA 0 0 0 0

0 COOMBOOL SWAMP 0 0 COOMBOOL SWAMP 0 0 0 0 0 8 8 8 8 4 4 4 4 2 2 2 2

6 OLD COOMBOOL 6 6 OLD COOMBOOL 6

SA SA

NSW NSW LAKE LITTRA LAKE LITTRA PUNKAH ISLAND PUNKAH ISLAND LAKE WERTA WERT LAKE WERTA WERT

0 STANLEY ISLAND 0 0 STANLEY ISLAND 0 0 BOAT CREEK ISLAND 0 0 BOAT CREEK ISLAND 0 0 0 0 0 3 3 3 3 4 4 4 4 2 2 2 2 6 ISLE OF MAN 6 6 ISLE OF MAN 6 MONOMAN ISLAND MONOMAN ISLAND HORSESHOE LAGOON HORSESHOE LAGOON

QUEEN BEND QUEEN BEND

WILPERNA ISLAND WILPERNA ISLAND 0 0 0 0

0 CHOWILLA ISLAND 0 0 CHOWILLA ISLAND 0 0 0 0 0 8 8 8 8 3 3 3 3 2 2 2 2 6 6 6 6

HANCOCK HILL HANCOCK HILL 0 0 0 0 0 0 0 0 0 0 0 0 3 3 3 3 3 3 3 3 2 2 2 2 6 6 6 6 VIC VIC 0 0 0 0 0 0 0 0 0 0 0 0 8 8 8 8 2 2 2 2 2 2 2 2 6 6 6 6 485000 490000 495000 500000 485000 490000 495000 500000

485000 490000 495000 500000 485000 490000 495000 500000 0 0 0 0 0 0 60 GL 0 40 GL 0 0 0 0 0 3 3 3 3 5 5 5 5 2 2 2 2 6 6 6 6

LAKE LIMBRA LAKE LIMBRA 0 0 0 0

0 COOMBOOL SWAMP 0 COOMBOOL SWAMP 0 0 0 0 0 0 8 8 8 8 4 4 4 4 2 2 2 2 6 6 OLD COOMBOOL 6 OLD COOMBOOL 6

SA SA

NSW NSW LAKE LITTRA LAKE LITTRA

PUNKAH ISLAND PUNKAH ISLAND LAKE WERTA WERT LAKE WERTA WERT

0 STANLEY ISLAND 0 0 STANLEY ISLAND 0 0 BOAT CREEK ISLAND 0 0 BOAT CREEK ISLAND 0 0 0 0 0 3 3 3 3 4 4 4 4 2 2 2 2 6 ISLE OF MAN 6 6 ISLE OF MAN 6 MONOMAN ISLAND HORSESHOE LAGOON MONOMAN ISLAND HORSESHOE LAGOON

QUEEN BEND QUEEN BEND

WILPERNA ISLAND WILPERNA ISLAND 0 0 0 0 0 0 CHOWILLA ISLAND 0 CHOWILLA ISLAND 0 0 0 0 0 8 8 8 8 3 3 3 3 2 2 2 2 6 6 6 6

HANCOCK HILL HANCOCK HILL 0 0 0 0 0 0 0 0 0 0 0 0 3 3 3 3 3 3 3 3 2 2 2 2 6 6 6 6 VIC VIC 0 0 0 0 0 0 0 0 0 0 0 0 8 8 8 8 2 2 2 2 2 2 2 2 6 6 6 6 485000 490000 495000 500000 485000 490000 495000 500000

LEGEND Localities

0 1 2 4 RENMARK MILDURA Roads FIGURE D1 Kilometres Watercourses ADELAIDE SCALE 1:250,000 @ A4 Extent of Inundation GDA 1994 MGA Zone 54 State Boundary Natural Flow Disclaimer: While all reasonable care has been taken to ensure the information ECHUCA contained on this map is up to date and accurate, no guarantee is given that the information portrayed is free from error or omission. Please verify the accuracy River Murray of all information prior to use. HORSHAM BENDIGO Note: Information shown on this map is a copyright of Aquaterra Australia 2011 Lakes

AUTHOR AL REPORT NO R001 MOUNT GAMBIER Inundation Extent DRAWN AL REVISION 1 DATA SOURCES PORTLAND Hydrotech DATE 11/05/11 JOB NO. A191 002 Cadastre Geoscience Australia

D:\Work Information\Aquaterra\Template\A4_Landscape.mxt 465000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000

10 GL @ 19.25 mAHD

LAKE LIMBRA 0 0

0 COOMBOOL SWAMP 0 0 0 8 8 4 4

2 OLD COOMBOOL 2 6 6

SA

NSW LAKE LITTRA

LAKE WERTA WERT 0 STANLEY ISLAND 0 0 0

0 PUNKAH ISLAND 0 3 3 4 4 2 2

6 ISLE OF MAN 6 MONOMAN ISLAND HORSESHOE LAGOON

QUEEN BEND

ROTTEN LAKE WILPERNA ISLAND 0 0

0 CHOWILLA ISLAND 0 0 0 8 8 3 3

2 CLOVER LAKE 2 6 6

LAKE MERRETI

LAKE WOOLPOLOOL HUNCHEE HANCOCK HILL 0 0 0 0 0 0 3 3

3 CAL LAL 3 2 2 6 RENY ISLAND VIC 6

HORSESHOE LAGOON 465000 47000C0HAFFEY IRRIGA4T75I0O0N0 AREA 480000 485000 490000 495000 500000 505000 510000 515000 520000

465000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000 0 0 0 0 0 0 3 3 5 5 2 2

6 10 GL @ 19.87 mAHD 6

LAKE LIMBRA 0 0

0 COOMBOOL SWAMP 0 0 0 8 8 4 4

2 OLD COOMBOOL 2 6 6

SA

NSW LAKE LITTRA PUNKAH ISLAND

0 LAKE WERTA WERT 0

0 STANLEY ISLAND 0 0 0 3 3 4 4

2 ISLE OF MAN 2 6 MONOMAN ISLAND HORSESHOE LAGOON 6

QUEEN BEND

ROTTEN LAKE WILPERNA ISLAND 0 0

0 CHOWILLA ISLAND 0 0 0 8 8

3 CLOVER LAKE 3 2 2 6 6

LAKE MERRETI

LAKE WOOLPOLOOL HUNCHEE HANCOCK HILL 0 0 0 0 0 0

3 CAL LAL 3 3 3 2 2

6 RENY ISLAND VIC 6

CHAFFEY IRRIGATION AREA HORSESHOE LAGOON 465000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000

465000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000 0 0 0 0 0 0 3 3 5 5 2 2

6 30 GL @ 19.87 mAHD 6

LAKE LIMBRA 0 0

0 COOMBOOL SWAMP 0 0 0 8 8 4 4

2 OLD COOMBOOL 2 6 6

SA

NSW LAKE LITTRA PUNKAH ISLAND

0 LAKE WERTA WERT 0

0 STANLEY ISLAND 0 0 0 3 3 4 4

2 ISLE OF MAN 2 6 MONOMAN ISLAND HORSESHOE LAGOON 6

QUEEN BEND

ROTTEN LAKE WILPERNA ISLAND 0 0

0 CHOWILLA ISLAND 0 0 0 8 8 3 3

2 CLOVER LAKE 2 6 6

LAKE MERRETI

LAKE WOOLPOLOOL HUNCHEE HANCOCK HILL 0 0 0 0 0 0

3 CAL LAL 3 3 3 2 2

6 RENY ISLAND VIC 6

CHAFFEY IRRIGATION AREA HORSESHOE LAGOON 465000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000 520000 525000

LEGEND Localities

0 2.5 5 10 RENMARK MILDURA Roads FIGURE D2 Kilometres WatercourseLines ADELAIDE SCALE 1:350,000 @ A4 Extent of Inundation GDA 1994 MGA Zone 54 State Boundary for Regulator Events Disclaimer: While all reasonable care has been taken to ensure the information ECHUCA contained on this map is up to date and accurate, no guarantee is given that the information portrayed is free from error or omission. Please verify the accuracy River Murray of all information prior to use. HORSHAM BENDIGO Note: Information shown on this map is a copyright of Aquaterra Australia 2011 Lakes

AUTHOR AL REPORT NO R001 MOUNT GAMBIER Inundation Extents DRAWN AL REVISION 1 DATA SOURCES PORTLAND Hydrotech DATE 11/05/11 JOB NO. A191 002 Cadastre Geoscience Australia

D:\Work Information\Aquaterra\Template\A4_Landscape.mxt

APPENDIX E: MODEL STRESS PERIODS

Start Date Stop Date Stress Period Start Date Stop Date Stress Period 30/04/1975 31/05/1975 1 30/11/1979 31/12/1979 56 31/05/1975 30/06/1975 2 31/12/1979 31/01/1980 57 30/06/1975 31/07/1975 3 31/01/1980 29/02/1980 58 31/07/1975 31/08/1975 4 29/02/1980 31/03/1980 59 31/08/1975 30/09/1975 5 31/03/1980 30/04/1980 60 30/09/1975 31/10/1975 6 30/04/1980 31/05/1980 61 31/10/1975 30/11/1975 7 31/05/1980 30/06/1980 62 30/11/1975 31/12/1975 8 30/06/1980 31/07/1980 63 31/12/1975 31/01/1976 9 31/07/1980 31/08/1980 64 31/01/1976 29/02/1976 10 31/08/1980 30/09/1980 65 29/02/1976 31/03/1976 11 30/09/1980 31/10/1980 66 31/03/1976 30/04/1976 12 31/10/1980 30/11/1980 67 30/04/1976 31/05/1976 13 30/11/1980 31/12/1980 68 31/05/1976 30/06/1976 14 31/12/1980 31/01/1981 69 30/06/1976 31/07/1976 15 31/01/1981 28/02/1981 70 31/07/1976 31/08/1976 16 28/02/1981 31/03/1981 71 31/08/1976 30/09/1976 17 31/03/1981 30/04/1981 72 30/09/1976 31/10/1976 18 30/04/1981 31/05/1981 73 31/10/1976 30/11/1976 19 31/05/1981 30/06/1981 74 30/11/1976 31/12/1976 20 30/06/1981 31/07/1981 75 31/12/1976 31/01/1977 21 31/07/1981 31/08/1981 76 31/01/1977 28/02/1977 22 31/08/1981 30/09/1981 77 28/02/1977 31/03/1977 23 30/09/1981 31/10/1981 78 31/03/1977 30/04/1977 24 31/10/1981 30/11/1981 79 30/04/1977 31/05/1977 25 30/11/1981 31/12/1981 80 31/05/1977 30/06/1977 26 31/12/1981 31/01/1982 81 30/06/1977 31/07/1977 27 31/01/1982 28/02/1982 82 31/07/1977 31/08/1977 28 28/02/1982 31/03/1982 83 31/08/1977 30/09/1977 29 31/03/1982 30/04/1982 84 30/09/1977 31/10/1977 30 30/04/1982 31/05/1982 85 31/10/1977 30/11/1977 31 31/05/1982 30/06/1982 86 30/11/1977 31/12/1977 32 30/06/1982 31/07/1982 87 31/12/1977 31/01/1978 33 31/07/1982 31/08/1982 88 31/01/1978 28/02/1978 34 31/08/1982 30/09/1982 89 28/02/1978 31/03/1978 35 30/09/1982 31/10/1982 90 31/03/1978 30/04/1978 36 31/10/1982 30/11/1982 91 30/04/1978 31/05/1978 37 30/11/1982 31/12/1982 92 31/05/1978 30/06/1978 38 31/12/1982 31/01/1983 93 30/06/1978 31/07/1978 39 31/01/1983 28/02/1983 94 31/07/1978 31/08/1978 40 28/02/1983 31/03/1983 95 31/08/1978 30/09/1978 41 31/03/1983 30/04/1983 96 30/09/1978 31/10/1978 42 30/04/1983 31/05/1983 97 31/10/1978 30/11/1978 43 31/05/1983 30/06/1983 98 30/11/1978 31/12/1978 44 30/06/1983 31/07/1983 99 31/12/1978 31/01/1979 45 31/07/1983 31/08/1983 100 31/01/1979 28/02/1979 46 31/08/1983 30/09/1983 101 28/02/1979 31/03/1979 47 30/09/1983 31/10/1983 102 31/03/1979 30/04/1979 48 31/10/1983 30/11/1983 103 30/04/1979 31/05/1979 49 30/11/1983 31/12/1983 104 31/05/1979 30/06/1979 50 31/12/1983 31/01/1984 105 30/06/1979 31/07/1979 51 31/01/1984 29/02/1984 106 31/07/1979 31/08/1979 52 29/02/1984 31/03/1984 107 31/08/1979 30/09/1979 53 31/03/1984 30/04/1984 108 30/09/1979 31/10/1979 54 30/04/1984 31/05/1984 109 31/10/1979 30/11/1979 55 31/05/1984 30/06/1984 110 Start Date Stop Date Stress Period Start Date Stop Date Stress Period 30/06/1984 31/07/1984 111 31/01/1989 28/02/1989 166 31/07/1984 31/08/1984 112 28/02/1989 31/03/1989 167 31/08/1984 30/09/1984 113 31/03/1989 30/04/1989 168 30/09/1984 31/10/1984 114 30/04/1989 31/05/1989 169 31/10/1984 30/11/1984 115 31/05/1989 30/06/1989 170 30/11/1984 31/12/1984 116 30/06/1989 31/07/1989 171 31/12/1984 31/01/1985 117 31/07/1989 31/08/1989 172 31/01/1985 28/02/1985 118 31/08/1989 30/09/1989 173 28/02/1985 31/03/1985 119 30/09/1989 31/10/1989 174 31/03/1985 30/04/1985 120 31/10/1989 30/11/1989 175 30/04/1985 31/05/1985 121 30/11/1989 31/12/1989 176 31/05/1985 30/06/1985 122 31/12/1989 31/01/1990 177 30/06/1985 31/07/1985 123 31/01/1990 28/02/1990 178 31/07/1985 31/08/1985 124 28/02/1990 31/03/1990 179 31/08/1985 30/09/1985 125 31/03/1990 30/04/1990 180 30/09/1985 31/10/1985 126 30/04/1990 31/05/1990 181 31/10/1985 30/11/1985 127 31/05/1990 30/06/1990 182 30/11/1985 31/12/1985 128 30/06/1990 31/07/1990 183 31/12/1985 31/01/1986 129 31/07/1990 31/08/1990 184 31/01/1986 28/02/1986 130 31/08/1990 30/09/1990 185 28/02/1986 31/03/1986 131 30/09/1990 31/10/1990 186 31/03/1986 30/04/1986 132 31/10/1990 30/11/1990 187 30/04/1986 31/05/1986 133 30/11/1990 31/12/1990 188 31/05/1986 30/06/1986 134 31/12/1990 31/01/1991 189 30/06/1986 31/07/1986 135 31/01/1991 28/02/1991 190 31/07/1986 31/08/1986 136 28/02/1991 31/03/1991 191 31/08/1986 30/09/1986 137 31/03/1991 30/04/1991 192 30/09/1986 31/10/1986 138 30/04/1991 31/05/1991 193 31/10/1986 30/11/1986 139 31/05/1991 30/06/1991 194 30/11/1986 31/12/1986 140 30/06/1991 31/07/1991 195 31/12/1986 31/01/1987 141 31/07/1991 31/08/1991 196 31/01/1987 28/02/1987 142 31/08/1991 30/09/1991 197 28/02/1987 31/03/1987 143 30/09/1991 31/10/1991 198 31/03/1987 30/04/1987 144 31/10/1991 30/11/1991 199 30/04/1987 31/05/1987 145 30/11/1991 31/12/1991 200 31/05/1987 30/06/1987 146 31/12/1991 31/01/1992 201 30/06/1987 31/07/1987 147 31/01/1992 29/02/1992 202 31/07/1987 31/08/1987 148 29/02/1992 31/03/1992 203 31/08/1987 30/09/1987 149 31/03/1992 30/04/1992 204 30/09/1987 31/10/1987 150 30/04/1992 31/05/1992 205 31/10/1987 30/11/1987 151 31/05/1992 30/06/1992 206 30/11/1987 31/12/1987 152 30/06/1992 31/07/1992 207 31/12/1987 31/01/1988 153 31/07/1992 31/08/1992 208 31/01/1988 29/02/1988 154 31/08/1992 30/09/1992 209 29/02/1988 31/03/1988 155 30/09/1992 31/10/1992 210 31/03/1988 30/04/1988 156 31/10/1992 30/11/1992 211 30/04/1988 31/05/1988 157 30/11/1992 31/12/1992 212 31/05/1988 30/06/1988 158 31/12/1992 31/01/1993 213 30/06/1988 31/07/1988 159 31/01/1993 28/02/1993 214 31/07/1988 31/08/1988 160 28/02/1993 31/03/1993 215 31/08/1988 30/09/1988 161 31/03/1993 30/04/1993 216 30/09/1988 31/10/1988 162 30/04/1993 31/05/1993 217 31/10/1988 30/11/1988 163 31/05/1993 30/06/1993 218 30/11/1988 31/12/1988 164 30/06/1993 31/07/1993 219 31/12/1988 31/01/1989 165 31/07/1993 31/08/1993 220 Start Date Stop Date Stress Period Start Date Stop Date Stress Period 31/08/1993 30/09/1993 221 31/03/1998 30/04/1998 276 30/09/1993 31/10/1993 222 30/04/1998 31/05/1998 277 31/10/1993 30/11/1993 223 31/05/1998 30/06/1998 278 30/11/1993 31/12/1993 224 30/06/1998 31/07/1998 279 31/12/1993 31/01/1994 225 31/07/1998 31/08/1998 280 31/01/1994 28/02/1994 226 31/08/1998 30/09/1998 281 28/02/1994 31/03/1994 227 30/09/1998 31/10/1998 282 31/03/1994 30/04/1994 228 31/10/1998 30/11/1998 283 30/04/1994 31/05/1994 229 30/11/1998 31/12/1998 284 31/05/1994 30/06/1994 230 31/12/1998 31/01/1999 285 30/06/1994 31/07/1994 231 31/01/1999 28/02/1999 286 31/07/1994 31/08/1994 232 28/02/1999 31/03/1999 287 31/08/1994 30/09/1994 233 31/03/1999 30/04/1999 288 30/09/1994 31/10/1994 234 30/04/1999 31/05/1999 289 31/10/1994 30/11/1994 235 31/05/1999 30/06/1999 290 30/11/1994 31/12/1994 236 30/06/1999 31/07/1999 291 31/12/1994 31/01/1995 237 31/07/1999 31/08/1999 292 31/01/1995 28/02/1995 238 31/08/1999 30/09/1999 293 28/02/1995 31/03/1995 239 30/09/1999 31/10/1999 294 31/03/1995 30/04/1995 240 31/10/1999 30/11/1999 295 30/04/1995 31/05/1995 241 30/11/1999 31/12/1999 296 31/05/1995 30/06/1995 242 31/12/1999 31/01/2000 297 30/06/1995 31/07/1995 243 31/01/2000 29/02/2000 298 31/07/1995 31/08/1995 244 29/02/2000 31/03/2000 299 31/08/1995 30/09/1995 245 31/03/2000 30/04/2000 300 30/09/1995 31/10/1995 246 30/04/2000 31/05/2000 301 31/10/1995 30/11/1995 247 31/05/2000 30/06/2000 302 30/11/1995 31/12/1995 248 30/06/2000 31/07/2000 303 31/12/1995 31/01/1996 249 31/07/2000 31/08/2000 304 31/01/1996 29/02/1996 250 31/08/2000 30/09/2000 305 29/02/1996 31/03/1996 251 30/09/2000 31/10/2000 306 31/03/1996 30/04/1996 252 31/10/2000 30/11/2000 307 30/04/1996 31/05/1996 253 30/11/2000 31/12/2000 308 31/05/1996 30/06/1996 254 31/12/2000 31/01/2001 309 30/06/1996 31/07/1996 255 31/01/2001 28/02/2001 310 31/07/1996 31/08/1996 256 28/02/2001 31/03/2001 311 31/08/1996 30/09/1996 257 31/03/2001 30/04/2001 312 30/09/1996 31/10/1996 258 30/04/2001 31/05/2001 313 31/10/1996 30/11/1996 259 31/05/2001 30/06/2001 314 30/11/1996 31/12/1996 260 30/06/2001 31/07/2001 315 31/12/1996 31/01/1997 261 31/07/2001 31/08/2001 316 31/01/1997 28/02/1997 262 31/08/2001 30/09/2001 317 28/02/1997 31/03/1997 263 30/09/2001 31/10/2001 318 31/03/1997 30/04/1997 264 31/10/2001 30/11/2001 319 30/04/1997 31/05/1997 265 30/11/2001 31/12/2001 320 31/05/1997 30/06/1997 266 31/12/2001 31/01/2002 321 30/06/1997 31/07/1997 267 31/01/2002 28/02/2002 322 31/07/1997 31/08/1997 268 28/02/2002 31/03/2002 323 31/08/1997 30/09/1997 269 31/03/2002 30/04/2002 324 30/09/1997 31/10/1997 270 30/04/2002 31/05/2002 325 31/10/1997 30/11/1997 271 31/05/2002 30/06/2002 326 30/11/1997 31/12/1997 272 30/06/2002 31/07/2002 327 31/12/1997 31/01/1998 273 31/07/2002 31/08/2002 328 31/01/1998 28/02/1998 274 31/08/2002 30/09/2002 329 28/02/1998 31/03/1998 275 30/09/2002 31/10/2002 330 Start Date Stop Date Stress Period 31/10/2002 30/11/2002 331 30/11/2002 31/12/2002 332 31/12/2002 31/01/2003 333 31/01/2003 28/02/2003 334 28/02/2003 31/03/2003 335 31/03/2003 30/04/2003 336 30/04/2003 31/05/2003 337 31/05/2003 30/06/2003 338 30/06/2003 31/07/2003 339 31/07/2003 31/08/2003 340 31/08/2003 30/09/2003 341 30/09/2003 31/10/2003 342 31/10/2003 30/11/2003 343 30/11/2003 31/12/2003 344 31/12/2003 31/01/2004 345 31/01/2004 29/02/2004 346 29/02/2004 31/03/2004 347 31/03/2004 30/04/2004 348 30/04/2004 31/05/2004 349 31/05/2004 30/06/2004 350 30/06/2004 31/07/2004 351 31/07/2004 31/08/2004 352 31/08/2004 30/09/2004 353 30/09/2004 31/10/2004 354 31/10/2004 30/11/2004 355 30/11/2004 31/12/2004 356 31/12/2004 31/01/2005 357 31/01/2005 28/02/2005 358 28/02/2005 31/03/2005 359 31/03/2005 30/04/2005 360 30/04/2005 31/05/2005 361 31/05/2005 30/06/2005 362 30/06/2005 31/07/2005 363 31/07/2005 31/08/2005 364 31/08/2005 30/09/2005 365 30/09/2005 31/10/2005 366 31/10/2005 30/11/2005 367 30/11/2005 31/12/2005 368 31/12/2005 31/01/2006 369 31/01/2006 28/02/2006 370 28/02/2006 31/03/2006 371 31/03/2006 30/04/2006 372 30/04/2006 31/05/2006 373 31/05/2006 30/06/2006 374 30/06/2006 31/07/2006 375 31/07/2006 31/08/2006 376 31/08/2006 30/09/2006 377 30/09/2006 31/10/2006 378 31/10/2006 30/11/2006 379 30/11/2006 6/12/2076 380

APPENDIX F: SCENARIO HYDROGRAPHS

22 CHW037/1 22 CHW046/1 Modelled 21 21 Observed 20 Ground Surface 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW108/1 22 CHW110/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW112/1 22 CHW115/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW116/1 22 CHW117/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Chowilla 2012 Regulator Scenario Hydrographs - FIGURE F1

F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Hydrographs_Regulator.xls]Figure_01 22 CHW118/1 22 CHW119/1 Modelled 21 Observed 21 20 Ground Surface 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW120/1 22 CHW121/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW123/1 22 CHW124/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW134/1 22 CHW135/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Chowilla 2012 Regulator Scenario Hydrographs - FIGURE F2

F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Hydrographs_Regulator.xls]Figure_02 22 CHW137/1 22 CHW138/1 Modelled 21 21 Observed 20 Ground Surface 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW141/1 22 CHW148/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW154/1 22 CHW155/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW156/1 22 CHW157/A

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Chowilla 2012 Regulator Scenario Hydrographs - FIGURE F3

F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Hydrographs_Regulator.xls]Figure_03 22 CHW158/1 22 CHW159/1 Modelled 21 Observed 21

20 Ground Surface 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW162/1

21

20

19

18

17

Water Level (mAHD) Water Level 16

15 1975 1980 1985 1990 1995 2000 2005 Year

Chowilla 2012 Regulator Scenario Hydrographs - FIGURE F4

F:\Jobs\A191\200\260_external meetings\Meeting_160212\Handout\[Hydrographs_Regulator.xls]Figure_04

APPENDIX G: SENSITIVITY HYDROGRAPHS

22 CHW037/1 22 CHW046/1 Modelled Observed 20 20 Ground Surface

18 18

16 16

14 14 Water Level (mAHD) Water Level (mAHD) Water Level

12 12 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW108/1 22 CHW110/1

20 20

18 18

16 16

14 14 Water Level (mAHD) Water Level (mAHD) Water Level

12 12 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW112/1 22 CHW115/1

20 20

18 18

16 16

14 14 Water Level (mAHD) Water Level (mAHD) Water Level

12 12 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW116/1 22 CHW117/1

20 20

18 18

16 16

14 14 Water Level (mAHD) Water Level (mAHD) Water Level

12 12 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Sensitivity Hydrographs - ET Rate and Extinction Depth doubled - FIGURE G1

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_01.xls]Figure_01 22 CHW118/1 22 CHW119/1 Modelled

20 Observed 20 Ground Surface

18 18

16 16

14 14 Water Level (mAHD) Water Level (mAHD) Water Level

12 12 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW120/1 22 CHW121/1

20 20

18 18

16 16

14 14 Water Level (mAHD) Water Level (mAHD) Water Level

12 12 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW123/1 22 CHW124/1

20 20

18 18

16 16

14 14 Water Level (mAHD) Water Level (mAHD) Water Level

12 12 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW134/1 22 CHW135/1

20 20

18 18

16 16

14 14 Water Level (mAHD) Water Level (mAHD) Water Level

12 12 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Sensitivity Hydrographs - ET Rate and Extinction Depth doubled - FIGURE G2

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_01.xls]Figure_02 22 CHW137/1 22 CHW138/1 Modelled Observed 20 20 Ground Surface

18 18

16 16

14 14 Water Level (mAHD) Water Level (mAHD) Water Level

12 12 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW141/1 22 CHW148/1

20 20

18 18

16 16

14 14 Water Level (mAHD) Water Level (mAHD) Water Level

12 12 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW154/1 22 CHW155/1

20 20

18 18

16 16

14 14 Water Level (mAHD) Water Level (mAHD) Water Level

12 12 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW156/1 22 CHW157/A

20 20

18 18

16 16

14 14 Water Level (mAHD) Water Level (mAHD) Water Level

12 12 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Sensitivity Hydrographs - ET Rate and Extinction Depth doubled - FIGURE G3

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_01.xls]Figure_03 22 CHW158/1 22 CHW159/1 Modelled Observed 20 20 Ground Surface

18 18

16 16

14 14 Water Level (mAHD) Water Level (mAHD) Water Level

12 12 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW162/1

20

18

16

14 Water Level (mAHD) Water Level

12 1975 1980 1985 1990 1995 2000 2005 Year

Sensitivity Hydrographs - ET Rate and Extinction Depth doubled - FIGURE G4

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_01.xls]Figure_04 22 CHW037/1 22 CHW046/1 Modelled 21 Observed 21

20 Ground Surface 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW108/1 22 CHW110/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW112/1 22 CHW115/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW116/1 22 CHW117/1

21 21

20 20

19 19

18 18

17 17 Water Level (mAHD Water Level Water Level (mAHD) Water Level 16 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Sensitivity Hydrographs - ET Rate doubled - FIGURE G5

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_04.xls]Figure_01 22 CHW118/1 22 CHW119/1 Modelled 21 21 Observed 20 Ground Surface 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW120/1 22 CHW121/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW123/1 22 CHW124/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW134/1 22 CHW135/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Sensitivity Hydrographs - ET Rate doubled - FIGURE G6

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_04.xls]Figure_02 22 CHW137/1 22 CHW138/1 Modelled 21 Observed 21

20 Ground Surface 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW141/1 22 CHW148/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW154/1 22 CHW155/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW156/1 22 CHW157/A

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Sensitivity Hydrographs - ET Rate doubled - FIGURE G7

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_04.xls]Figure_03 22 CHW158/1 22 CHW159/1 Modelled 21 21 Observed

20 Ground 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW162/1

21

20

19

18

17

Water Level (mAHD) Water Level 16

15 1975 1980 1985 1990 1995 2000 2005 Year

Sensitivity Hydrographs - ET Rate doubled - FIGURE G8

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_04.xls]Figure_04 22 CHW037/1 22 CHW046/1 Modelled 21 Observed 21 Ground Surface 20 20

19 19

18 18

17 17 Water Level (mAHD) Water Level (mAHD) Water Level

16 16 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW108/1 22 CHW110/1

21 21

20 20

19 19

18 18

17 17 Water Level (mAHD) Water Level (mAHD) Water Level

16 16 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW112/1 22 CHW115/1

21 21

20 20

19 19

18 18

17 17 Water Level (mAHD) Water Level (mAHD) Water Level

16 16 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW116/1 22 CHW117/1

21 21

20 20

19 19

18 18

17 17 Water Level (mAHD) Water Level (mAHD) Water Level

16 16 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Sensitivity Hydrographs - Anabranch Conductance x 10 - FIGURE G9

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_02.xls]Figure_01 22 CHW118/1 22 CHW119/1 Modelled 21 Observed 21 Ground Surface 20 20

19 19

18 18

17 17 Water Level (mAHD) Water Level (mAHD) Water Level

16 16 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW120/1 22 CHW121/1

21 21

20 20

19 19

18 18

17 17 Water Level (mAHD) Water Level (mAHD) Water Level

16 16 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW123/1 22 CHW124/1

21 21

20 20

19 19

18 18

17 17 Water Level (mAHD) Water Level (mAHD) Water Level

16 16 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW134/1 22 CHW135/1

21 21

20 20

19 19

18 18

17 17 Water Level (mAHD) Water Level (mAHD) Water Level

16 16 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Sensitivity Hydrographs - Anabranch Conductance x 10 - FIGURE G10

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_02.xls]Figure_02 22 CHW137/1 22 CHW138/1 Modelled 21 Observed 21 Ground Surface 20 20

19 19

18 18

17 17 Water Level (mAHD) Water Level (mAHD) Water Level

16 16 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW141/1 22 CHW148/1

21 21

20 20

19 19

18 18

17 17 Water Level (mAHD) Water Level (mAHD) Water Level

16 16 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW154/1 22 CHW155/1

21 21

20 20

19 19

18 18

17 17 Water Level (mAHD) Water Level (mAHD) Water Level

16 16 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW156/1 22 CHW157/A

21 21

20 20

19 19

18 18

17 17 Water Level (mAHD) Water Level (mAHD) Water Level

16 16 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Sensitivity Hydrographs - Anabranch Conductance x 10 - FIGURE G11

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_02.xls]Figure_03 22 CHW158/1 22 CHW159/1 Modelled 21 Observed 21 Ground Surface 20 20

19 19

18 18

17 17 Water Level (mAHD) Water Level (mAHD) Water Level

16 16 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW162/1

21

20

19

18

17 Water Level (mAHD) Water Level

16 1975 1980 1985 1990 1995 2000 2005 Year

Sensitivity Hydrographs - Anabranch Conductance x 10 - FIGURE G12

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_02.xls]Figure_04 22 CHW037/1 22 CHW046/1 Modelled 21 Observed 21

20 Ground Surface 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW108/1 22 CHW110/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW112/1 22 CHW115/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW116/1 22 CHW117/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Sensitivity Hydrographs - Anabranch Conductance x 100 - FIGURE G13

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_03.xls]Figure_01 22 CHW118/1 22 CHW119/1 Modelled 21 21 Observed 20 Ground Surface 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW120/1 22 CHW121/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW123/1 22 CHW124/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW134/1 22 CHW135/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Sensitivity Hydrographs - Anabranch Conductance x 100 - FIGURE G14

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_03.xls]Figure_02 22 CHW137/1 22 CHW138/1 Modelled 21 Observed 21

20 Ground Surface 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW141/1 22 CHW148/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW154/1 22 CHW155/1

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW156/1 22 CHW157/A

21 21

20 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

Sensitivity Hydrographs - Anabranch Conductance x 100 - FIGURE G15

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_03.xls]Figure_03 22 CHW158/1 22 CHW159/1 Modelled 21 Observed 21 20 Ground Surface 20

19 19

18 18

17 17

Water Level (mAHD) Water Level 16 (mAHD) Water Level 16

15 15 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 Year Year

22 CHW162/1

21

20

19

18

17

Water Level (mAHD) Water Level 16

15 1975 1980 1985 1990 1995 2000 2005 Year

Sensitivity Hydrographs - Anabranch Conductance x 100 - FIGURE G16

F:\Jobs\A191\300\320_Model_Output\323_Sensitivity\[Hydrographs_run11_corrected River Levels_Sens_03.xls]Figure_04