DPIW – SURFACE WATER MODELS MERSEY RIVER ......at intervals of 0.05 o latitude and 0.05 o...

DPIW – SURFACE WATER MODELS

MERSEY RIVER CATCHMENT

Mersey River Surface Water Model Hydro Tasmania Version No: 1.1

i

DOCUMENT INFORMATION

JOB/PROJECT TITLE Surface Water Hydrological Models for DPIW

CLIENT ORGANISATION Department of Primary Industries and Water

CLIENT CONTACT Bryce Graham

DOCUMENT ID NUMBER WR 2007/027

JOB/PROJECT MANAGER Mark Willis

JOB/PROJECT NUMBER E200690/P202167

Document History and Status

Revision Prepared

by

Reviewed

by

Approved

by

Date

approved

Revision

type

1.0 J. Bennett Dr Fiona

Ling

C. Smythe July 2007 Final

1.1 J. Bennett Dr Fiona

Ling

C. Smythe July 2008 Final

Current Document Approval

PREPARED BY James Bennett

Water Resources Mngt Sign Date

REVIEWED BY Dr Fiona Ling


APPROVED FOR

SUBMISSION

Crispin Smythe


Current Document Distribution List

Organisation Date Issued To

DPIW July 2008 Bryce Graham

The concepts and information contained in this document are the property of Hydro Tasmania.

This document may only be used for the purposes of assessing our offer of services and for inclusion in

documentation for the engagement of Hydro Tasmania. Use or copying of this document in whole or in part for any

other purpose without the written permission of Hydro Tasmania constitutes an infringement of copyright.


ii

EXECUTIVE SUMMARY

This report describes the results of the hydrological model developed for the Mersey

River catchment in central-north Tasmania. This report is one of a series of reports that

present the methods and results from the development and calibration of surface water

hydrological models for 26 Tasmanian catchments under both current and natural flow

conditions.

A catchment flow model was developed for the Mersey River, and run under three

scenarios:

• Scenario 1 – No Entitlements (Natural Flow);

• Scenario 2 - With Entitlements (with water entitlements extracted);

• Scenario 3 - Environmental Flows and Entitlements (Water entitlements

extracted, however low priority entitlements are limited by an environmental

flow threshold).

The results of these model runs allowed the calculation of indices of hydrological

disturbance. These indices were:

• Hydrological Disturbance Index

• Index of Mean Annual Flow

• Index of Flow Duration Curve Difference

• Index of Seasonal Amplitude

• Index of Seasonal Periodicity

The indices were calculated using formulas developed for the Natural Resource

Management (NRM) Monitoring and Evaluation Framework developed by SKM for the

Murray-Darling Basin (MDBC 08/04).

A user interface is provided that allows the model to be run under varying scenarios. For

information on the use of the user interface refer to the Operating Manual for the NAP

Region Hydrological Models (Hydro Tasmania 2004a). This allows the user to see what

effect additional extractions can have on the availability of water in the Mersey

catchment. The interface provides summaries of flow statistics, duration curves,

hydrological indices and water entitlements data for each subarea of the catchment. For

information on the use of the user interface refer to the Operating Manual for the NAP

Region Hydrological Models (Hydro Tasmania 2004b).


iii

CONTENTS

EXECUTIVE SUMMARY ii

1. INTRODUCTION 1

2. CATCHMENT CHARACTERISTICS 2

3. DATA COMPILATION 4

3.1 Climate data (Rainfall & Evaporation) 4

3.2 Advantages of using climate DRILL data 4

3.3 Transposition of climate DRILL data to local catchment 5

3.4 Comparison of Data Drill rainfall and site gauges 7

3.5 Streamflow data 9

3.6 Irrigation and water use 9

3.7 Estimation of unlicensed dams 17

3.8 Environmental flows 19

4. MODEL DEVELOPMENT 22

4.1 Catchment Subarea Delineation 22

4.2 Hydstra Model 22

4.2.1 Accounting for Mersey Hydro Electric Scheme 23

4.3 AWBM Model 26

4.3.1 Channel Routing 29

4.4 Model Calibration 29

4.4.1 Accounting for flow diversions on the Mersey River 29

4.4.2 Calibration Method 30

4.4.3 Adopted Model Parameters 31

4.4.4 Model accuracy: Qualitative description 33

4.4.5 Factors affecting the reliability of the model calibration 37

4.4.6 Model Accuracy – Model fit statistics 39

4.4.7 Model Accuracy throughout the Mersey catchment 44

4.5 Model results 45

4.5.1 Indices of hydrological disturbance 46

4.6 Flood frequency analysis 49

5. REFERENCES 50

5.1 Personal Communications 51

6. GLOSSARY 52


iv

LIST OF FIGURES

Figure 2-1 Mersey catchment subarea boundaries 3

Figure 3-1 Climate DRILL Site Locations 6

Figure 3-2 Rainfall and Data DRILL Comparisons 8

Figure 3-3 WIMS (Dec 2006) Water Allocations in the Mersey Catchment 16

Figure 4-1 Hydstra Model Schematic 25

Figure 4-2 Two-tap Australian Water Balance Model Schematic 28

Figure 4-3 Monthly Variation of CapAve Parameter 33

Figure 4-4 Daily time series - typical year (ML/d). Good fit 34

Figure 4-5 Daily time series – low inflow year (ML/d). Good fit. 34

Figure 4-6 Daily time series comparison – high inflow year (ML/d). Good fit. 35

Figure 4-7 Monthly Time Series comparison – Volume (ML) 35

Figure 4-8 Long term average monthly, seasonal and annual flows 36

Figure 4-9 Duration curve – MCF Daily flow proportional difference 41

Figure 4-10 Duration curve - MCF Monthly volume proportional difference 42

Figure 4-11 Duration curve – UIM Daily flow proportional difference 43

Figure 4-12 Duration curve – UIM Monthly volume proportional difference 44

Figure 4-13 Time series of Monthly Volumes – Arm above Mersey (TSM 624.1) (SC9) 45

Figure 4-14 Time series of Monthly Volumes – Don River upstream of Bass Highway (TSM 16200.1) (SC30) 45

Figure 4-15 Daily Duration Curve for Modelled flows 01/01/1900 – 01/01/2006 at the Calibration Site (SC6) 46

Figure B-1 Forth catchment – monthly volumes at secondary site. 59

Figure B-2 George catchment – monthly volumes at secondary site. 59

Figure B-3 Leven catchment – monthly volumes at secondary site. 60

Figure B-4 Swan catchment – monthly volumes at secondary site. 60

Figure B-5 Montagu catchment – monthly volumes at secondary site. 61


v

LIST OF TABLES

Table 3-1 Data DRILL Site Locations 7

Table 3-2 Calibration Site 9

Table 3-3 Assumed Surety of Unassigned Records 10

Table 3-4 Estimated Unlicenced Direct Water Extractions from Mersey and Don River Catchments 11

Table 3-5 Monthly water extractions (ML) from Mersey River by subarea 12

Table 3-6 Average capacity for dams less than 20 ML from Neal et al. (2002) 18

Table 3-7 Environmental Flows 20

Table 4-1 Boughton & Chiew, AWBM surface storage parameters 26

Table 4-2 Hydstra/TSM Modelling Parameter Bounds 29

Table 4-3 Adopted Calibration Parameters 32

Table 4-4 Long term average monthly, seasonal and annual comparisons 37

Table 4-5 Model Fit Statistics – Mersey River 39

Table 4-6 Coefficient of Determination (R2) Fit Categories 40

Table 4-7 Hydrological Disturbance Indices at the Catchment Outflow measuring disturbance between Scenario 1 and Scenario 3 at 3 sites in the Mersey Catchment 48

Table A-1 Hydro Tasmania Sites used for long term mean model inputs (ML/day)55

Table B-2 Tascatch Models’ performance at secondary sites 62


1

1. INTRODUCTION

This report forms part of a larger project commissioned by the Department of Primary

Industries and Water (DPIW) to provide hydrological models for 26 regional catchments.

The main objectives for the individual catchments are:

• To compile relevant data needed to develop and calibrate an Australian Water Balance Model (AWBM) hydrological model for the Mersey River catchment;

• To compile more than 100 years of daily time-step rainfall and streamflow data for input to the hydrologic model;

• To develop and calibrate the hydrologic model under both natural and current catchment conditions;

• To develop a User Interface for running the model under varying scenarios;

• To prepare a report that summarises the methods and assumptions used to develop the model. This report discusses the results of calibration and validation as well as material relating to the use of the hydrologic model (and associated software).


2

2. CATCHMENT CHARACTERISTICS

The Mersey River is fed by a 1680 km2 catchment in central-north Tasmania. It flows

northward and discharges into Bass Strait at the city of Devonport. The south of the

catchment is distinguished by the steep, mountainous terrain and alpine plateaus of the

central highlands of Tasmania, and includes Tasmania’s tallest mountain, Mt Ossa,

which stands at 1617 m ASL. Further north the catchment becomes less mountainous

but remains undulating. Narrow alluvial plains form along the banks of the Mersey in the

north of the catchment.

Land-use in the Mersey catchment is divided between agricultural areas and large tracts

of protected native forest and alpine tundra. The alluvial plains - about one tenth of the

catchment area - are largely dedicated to agriculture. The hills in the catchment (the

remaining catchment area) – particularly the mountains of the south - are covered in

native forests. There are several towns in the Mersey catchment area, but the quantity of

land covered by urban areas is negligible compared to forested and agricultural land.

Annual rainfall varies significantly across the catchment owing to the catchment’s large

size and diverse topography. Average annual rainfall ranges from 2000 mm in the

southern mountains to 800 mm in the catchment’s north.

This model also simulates flows for the adjoining Don River catchment, which is located

to the west of the Mersey and also discharges into Bass Strait. The Don River is fed by a

130 km2 catchment.

For modelling purposes, the Mersey and Don catchments were divided into 41 subareas.

The delineation of these areas is shown in Figure 2-1.

There are 691 registered current entitlements for water extraction. These entitlements

are spread across 31 subareas, all located in the northern half of the catchment. Most

extraction entitlements are for agriculture, but a small number are used for water supply,

recreational, aesthetic and commercial purposes.


3

Figure 2-1 Mersey catchment subarea boundaries


4

3. DATA COMPILATION

3.1 Climate data (Rainfall & Evaporation)

Daily time-step climate data were obtained from the Queensland Department of Natural

Resources & Mines (QDNRM).

QDNRM provides interpolated evaporation and rainfall data (called ‘climate DRILL data’)

at intervals of 0.05 o latitude and 0.05 o longitude (i.e., grid points on a grid of squares

approximately 5 by 5 km in size). These interpolated rainfall and evaporation data are

based on over 6000 rainfall and evaporation stations in Australia (see

www.nrm.qld.gov.au/silo for further details of climate drill data).

3.2 Advantages of using climate DRILL data

These data have a number of benefits over other sources of rainfall data including:

• Continuous data back to 1889. (However, for earlier years there are fewer input

sites available and therefore quality is reduced. The makers of the data-set state

that gauge numbers have been somewhat static since 1957, therefore back to

1957 distribution is considered “good” but prior to 1957 site availability may need

to be checked in the study area.)

• Evaporation data (along with a number of other climatic variables) are also

included for use in the AWBM model. According to the QDNRM web site, all

Data Drill evaporation information combines a mixture of the following data.

1. Observed data from the Commonwealth Bureau of Meteorology (BoM).

2. Interpolated daily climate surfaces from the on-line NR&M climate archive.

3. Observed pre-1957 climate data from the CLIMARC project (LWRRDC QPI-

43). NR&M was a major research collaborator on the CLIMARC project, and

these data have been integrated into the on-line NR&M climate archive.

4. Interpolated pre-1957 climate surfaces. This data-set, derived mainly from the

CLIMARC project data, is available in the on-line NR&M climate archive.

5. Incorporation of Automatic Weather Station (AWS) datum records. Typically,

an AWS is placed at a user's site to provide accurate local weather

measurements.

The evaporation data derived for the Mersey catchment were examined. Before 1970 the


5

evaporation information is based on the long-term daily averages of data collected after

1970. In the absence of any reliable long-term site data this evaporation data-set is

considered to be the best available for this catchment.

3.3 Transposition of climate DRILL data to local catchment

Ten climate Data Drill sites were selected to give coverage of the Mersey catchment.

Because the Mersey catchment is large, data DRILL sites were chosen to reflect the

range of annual rainfall: i.e. where rainfall varied greatly across small areas (notably in

the mountainous south of the catchment) more DRILL sites were selected.

See Figure 3-1 below for a map of the climate Data Drill sites and Table 3-1 for the

location information.


6

Figure 3-1 Climate DRILL site locations


7

Table 3-1 Data DRILL Site Locations

Site Latitude Longitude

Mersey_01 -41:15:00 146:27:00

Mersey_02 -41:18:00 146:21:00

Mersey_03 -41:24:00 146:18:00

Mersey_04 -41:24:00 146:27:00

Mersey_05 -41:33:00 146:15:00

Mersey_06 -41:33:00 146:27:00

Mersey_07 -41:39:00 146:24:00

Mersey_08 -41:42:00 146:15:00

Mersey_09 -41:48:00 146:12:00

Mersey_10 -41:54:00 146:09:00

3.4 Comparison of Data Drill rainfall and site gauges

As rainfall data are critical inputs to the model it is important to have confidence that

the Data DRILL long-term generated time series reflect what is observed within the

catchment. There were a number of Hydro Tasmania sites available within the

catchment that provided almost complete daily rainfall records longer than 10 years.

These records were compared to the nearest Data DRILL ‘virtual’ rain gauges (Figure

3-2). Visual inspection and R2 values indicate an acceptable correlation between the

DRILL interpolated annual rainfalls and more recent rainfall records (since c. 1975).

However, upon visual inspection DRILL data showed less fidelity to rainfalls from an

earlier record (1956-1968 - Figure 3-2). As noted earlier, DRILL evaporation data

before 1970 are also based on post-1970 means. As neither evaporation nor rainfall

data are completely reliable before 1970, hindcast flows for periods preceding 1970

should be treated with caution.

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3.5 Streamflow data

The stream flow gauge site at Kimberley was identified as a suitable calibration site. The

site is located low in the catchment (see Figure 2-1) and has a long flow record, detailed

in Table 3-2.

Table 3-2 Calibration Site

Site Name Site No. Sub-catchment Location

Period of

Record

Latitude Longitude

Mersey at Kimberley 22 SC6 08/03/1921

- Present

-41:23:50.2 146:29:40.5

This flow record was retrieved from the Hydro Tasmania database. A brief investigation

of the site rating history on Hydro Tasmania archives revealed that seven ratings applied

to the site between 01/01/1986 and 01/01/2006 (the period used for calibration). The site

has a naturally controlled water body that is regularly monitored for rating changes, and

the record is considered reasonably reliable.

3.6 Irrigation and water use

Information on the current water entitlement allocations in the catchment was obtained

from DPIW from the Water Information Management System (WIMS) December 2006

data-set. The extractions or licenses in the catchment are of a given Surety (from 1 to 8),

with Surety 1-3 representing high priority extractions for modelling purposes and Surety

4-8 representing the lowest priority. The data provided by DPIW include a number of

sites that had a surety of 0. DPIW staff advised that in these cases the surety should be

determined by the extraction “Purpose” and assigned as shown in Table 3-3, below.


10

Table 3-3 Assumed Surety of Unassigned Records

Purpose Surety

Aesthetic 6

Aquaculture 6

Commercial 6

Domestic 1

Industrial 6

Irrigation 6

Storage 6

Other 6

Power Generation 6

Recreation 6

Stock and Domestic S & D 1

Stock 1

Water Supply 1

In total there were 3184 ML unassigned entitlements (surety = 0) identified for inclusion

in the surface water model, of which 1038 ML were assigned Surety 1 and 2146 ML

assigned Surety 6.

DPIW staff also advised that the water extraction information provided should be filtered

to remove the following records:

• Extractions relating to fish farms should be omitted as this water is returned to the

stream. These are identified in the WIMS database by the purpose labels

“acquacult” or “fish farm”. One fish farm was identified in the catchment.

• The extraction data-set includes a “WE_status” field where only “current” and

“existing” should be used for extractions. All other records, for example deleted,

deferred, transferred, suspended and proposed, should be omitted.

When modelling Scenario 3 (Environmental Flows with Entitlements), water will only be

available for Low Priority entitlements after environmental flow requirements have been

met.

DPIW estimated that a total of 8889 ML were extracted in addition to allocations currently

recorded in the WIMS database. Unlicensed direct extractions in the Mersey and Don

River catchments were assigned to individual streams and tributaries (Table 3-4), and

were assigned to subareas in the model user interface accordingly. Where streams

flowed through a number of subareas (e.g. Dasher River, Mersey River), unlicensed

direct extractions were assigned according to the proportions of licensed direct

extractions in these streams, in the absence of data to the contrary. Allowances for

unlicensed dam extractions are discussed in Section 3.7.


11

Table 3-4 Estimated Unlicensed Direct Water Extractions from Mersey and Don

River Catchments

Stream Estimated Extractions

(ML) Subareas Where Extractions Apply

Bella Macargie Creek & Tributaries (Don River) 93

SC30

Bonneys Creek & Tributaries 342 SC15

Cockers Creek & Tributaries 112 SC33

Coiler Creek & Tributaries 691 SC11

Dasher River & Tributaries 1232 SC24, SC10, SC7

Dodder Rivulet 304 SC7

Don River1 464

SC35, SC36, SC37,

SC38, SC39

Figure of Eight Creek 72 SC31

Knights Creek & Tributaries and Greens Creek & Tributaries 271

SC13

Latrobe Creek & Tributaries 133 SC29

Lobster Rivulet & Tributaries 351 SC21, SC19

Mersey River 3187 SC16

Minnow Creek & Tributaries 475 SC23

Mole Creek 540 SC12, SC14

Redwater Creek & Tributaries 493 SC13

Smiths Creek 433 SC10

Stave Creek & Tributaries 159 SC30

Total 9353

A summary table of monthly water extraction volumes by subarea is shown in Table 3-5

and in the Catchment User Interface. A map of the water extraction allocations in the

catchment is shown in Figure 3-3.

1 Don River Direct extractions extrapolated from Bella Macargie Creek Estimate. It was

assumed extractions in each Don River Subarea would be the same as the extraction for Bella

Macargie Creek, which is wholly contained in subarea SC30.


12

Table 3-5 Monthly water extractions (ML) from Mersey River by subarea

Subcatch Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total

High Priority Entitlements

SC1 30.74 27.77 30.74 29.75 0.57 0.55 0.57 0.57 0.55 30.74 29.75 30.74 213

SC2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC3 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC4 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC5 67.10 60.60 67.10 64.93 1.42 1.37 1.42 1.42 1.37 67.10 64.93 67.10 466

SC6 58.68 53.00 58.68 56.79 8.11 7.85 8.11 8.11 7.85 58.68 56.79 58.68 441

SC7 136.44 123.24 136.44 132.04 46.37 44.88 46.37 46.37 44.88 136.44 132.04 136.44 1,162

SC8 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC9 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC10 132.29 119.48 132.29 128.02 33.50 32.42 33.50 33.50 32.42 132.29 128.02 132.29 1,070

SC11 118.00 106.58 118.00 114.19 46.49 44.99 46.49 46.49 44.99 118.00 114.19 118.00 1,036

SC12 74.84 67.60 74.84 72.43 21.72 21.02 21.72 21.72 21.02 74.84 72.43 74.84 619

SC13 103.06 93.09 103.06 99.74 5.11 4.94 5.11 5.11 4.94 103.06 99.74 103.06 730

SC14 0.00 0.00 0.00 0.00 1.42 1.37 1.42 1.42 1.37 0.00 0.00 0.00 7

SC15 50.07 45.22 50.07 48.45 10.50 10.16 10.50 10.50 10.16 50.07 48.45 50.07 394

SC16 70.30 63.50 70.30 68.03 26.45 25.60 26.45 26.45 25.60 70.66 68.38 70.30 612

SC17 61.94 55.95 61.94 59.94 2.23 2.16 2.23 2.23 2.16 61.94 59.94 61.94 435

SC18 1.06 0.96 1.06 1.03 0.00 0.00 0.00 0.00 0.00 1.06 1.03 1.06 7

SC19 40.07 36.19 40.07 38.77 6.32 6.11 6.32 6.32 6.11 40.07 38.77 40.07 305

SC20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC21 13.42 12.12 13.42 12.98 15.41 14.92 15.41 15.41 14.92 13.42 12.98 13.42 168

SC22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC23 85.06 76.86 85.06 82.39 8.08 7.90 8.08 8.08 7.90 85.06 82.39 85.06 622

SC24 0.38 0.35 0.38 0.37 2.37 2.29 2.37 2.37 2.29 0.38 0.37 0.38 14

SC25 248.58 224.52 248.58 240.56 12.15 11.76 12.15 12.15 11.76 248.58 240.56 248.58 1,760

SC26 0.00 0.00 0.00 0.00 9.36 9.06 9.36 9.36 9.06 0.00 0.00 0.00 46

SC27 0.00 0.00 0.00 0.00 0.57 0.55 0.57 0.57 0.55 0.00 0.00 0.00 3

SC28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC29 24.27 21.92 24.27 23.49 14.68 14.21 14.68 14.68 14.21 24.27 23.49 24.27 238

SC30 19.54 17.65 19.54 18.91 31.78 30.76 31.78 31.78 30.76 19.54 18.91 19.54 291

SC31 10.63 9.61 10.63 10.29 15.42 14.93 15.42 15.42 14.93 10.63 10.29 10.63 149

SC32 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC33 16.38 14.79 16.38 15.85 3.40 3.29 3.40 3.40 3.29 16.38 15.85 16.38 129

SC34 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC35 26.90 24.30 26.90 26.04 35.74 34.59 35.74 35.74 34.59 26.90 26.04 26.90 360

SC36 15.60 14.09 15.60 15.10 19.62 18.98 19.62 19.62 18.98 15.60 15.10 15.60 204

SC37 14.67 13.25 14.67 14.20 8.76 8.48 8.76 8.76 8.48 14.67 14.20 14.67 144


13


SC38 32.47 29.33 32.47 31.42 63.72 61.66 63.72 63.72 61.66 32.47 31.42 32.47 537

SC39 17.83 16.11 17.83 17.26 57.59 55.73 57.59 57.59 55.73 17.83 17.26 17.83 406

SC40 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

Total 1,470 1,328 1,470 1,423 509 493 509 509 493 1,471 1,423 1,470 12,568

Low Priority Entitlements

SC1 45.58 41.17 45.58 44.11 1.45 1.40 1.45 1.45 1.40 1.45 1.40 45.58 232

SC2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC3 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC4 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC5 97.34 109.89 121.66 117.74 13.18 12.76 13.18 13.18 12.76 13.18 12.76 37.88 576

SC6 45.19 40.82 45.19 43.73 36.92 35.73 36.92 36.92 35.73 36.92 35.73 45.19 475

SC7 18.42 16.63 18.42 17.82 67.43 65.26 67.43 67.43 65.26 67.43 65.26 18.42 555

SC8 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC9 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC10 17.45 15.76 17.45 16.89 46.31 44.82 46.31 46.31 44.82 46.31 40.34 17.45 400

SC11 37.60 33.96 37.60 36.38 47.88 46.33 47.88 47.88 46.33 47.88 46.33 37.60 514

SC12 4.12 3.72 4.12 3.99 170.83 165.32 170.83 170.83 165.32 170.83 45.12 4.12 1,079

SC13 2.31 2.09 2.31 2.24 43.27 41.88 43.27 43.27 41.88 43.27 41.88 2.31 310

SC14 46.33 41.85 46.33 44.84 47.68 46.14 47.68 47.68 46.14 47.68 44.84 46.33 554

SC15 0.08 0.08 0.08 0.08 37.31 36.11 37.31 37.31 36.11 37.31 36.11 0.08 258

SC16 12.88 11.63 12.88 12.46 77.15 74.66 77.15 77.15 74.66 77.15 72.87 12.88 594

SC17 91.46 82.61 91.46 88.51 2.28 2.21 2.28 2.28 2.21 2.28 2.21 91.46 461

SC18 0.65 0.59 0.65 0.63 0.65 0.63 0.65 0.65 0.63 0.65 0.63 0.65 8

SC19 39.39 35.58 39.39 38.12 45.52 44.06 45.52 45.52 44.06 45.52 22.86 29.97 476

SC20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC21 8.58 7.75 8.58 8.30 82.82 80.15 82.82 82.82 80.15 82.82 80.15 8.58 614

SC22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC23 347.10 314.40 354.64 347.52 249.61 241.59 249.61 249.61 241.59 249.61 241.59 337.94 3,425

SC24 0.00 0.00 0.00 0.00 1.30 1.26 1.30 1.30 1.26 1.30 1.26 0.00 9

SC25 364.98 329.66 364.98 353.21 20.99 20.31 20.99 20.99 20.31 20.99 20.31 364.98 1,923

SC26 69.05 62.37 69.05 66.82 99.58 96.37 99.58 99.58 96.37 99.58 96.37 69.05 1,024

SC27 0.00 0.00 0.00 0.00 2.02 1.96 2.02 2.02 1.96 2.02 0.00 0.00 12

SC28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC29 58.87 53.17 58.87 56.97 27.37 26.49 27.37 27.37 26.49 27.37 26.49 58.87 476

SC30 15.80 14.27 15.80 15.29 32.74 31.68 32.74 32.74 31.68 32.74 31.68 15.80 303

SC31 0.21 0.19 0.21 0.21 10.48 10.14 10.48 10.48 10.14 10.48 10.14 0.21 73

SC32 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC33 0.44 0.40 0.44 0.43 4.79 4.63 4.79 4.79 4.63 4.79 4.63 0.44 35


14


SC34 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC35 5.73 5.17 5.73 5.54 33.88 32.79 33.88 33.88 32.79 33.88 32.05 5.73 261

SC36 1.78 1.61 1.78 1.73 21.99 21.28 21.99 21.99 21.28 21.99 21.28 1.78 161

SC37 8.49 7.67 8.49 8.22 17.69 17.12 17.69 17.69 17.12 17.69 10.60 8.49 157

SC38 19.75 19.76 21.88 17.97 76.36 73.90 76.36 76.36 73.90 76.36 66.48 16.37 615

SC39 28.48 25.72 33.12 32.92 95.69 92.60 95.69 95.69 92.60 95.69 78.89 28.48 796

SC40 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

Total 1,388 1,279 1,427 1,383 1,415 1,370 1,415 1,415 1,370 1,415 1,190 1,307 16,373

All Entitlements

SC1 76.32 68.93 76.32 73.86 2.02 1.95 2.02 2.02 1.95 32.19 31.15 76.32 445

SC2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0

SC3 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0

SC4 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0

SC5 164.43 170.49 188.76 182.67 14.60 14.13 14.60 14.60 14.13 80.28 77.69 104.97 1041

SC6 103.87 93.82 103.87 100.52 45.03 43.58 45.03 45.03 43.58 95.60 92.52 103.87 916

SC7 154.86 139.87 154.86 149.86 113.80 110.13 113.80 113.80 110.13 203.87 197.30 154.86 1717

SC8 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0

SC9 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0

SC10 149.74 135.25 149.74 144.91 79.82 77.24 79.82 79.82 77.24 178.60 168.36 149.74 1470

SC11 155.59 140.54 155.59 150.57 94.37 91.32 94.37 94.37 91.32 165.87 160.52 155.59 1550

SC12 78.96 71.32 78.96 76.42 192.55 186.34 192.55 192.55 186.34 245.68 117.55 78.96 1698

SC13 105.37 95.17 105.37 101.97 48.38 46.82 48.38 48.38 46.82 146.33 141.61 105.37 1040

SC14 46.33 41.85 46.33 44.84 49.10 47.52 49.10 49.10 47.52 47.68 44.84 46.33 561

SC15 50.15 45.30 50.15 48.54 47.81 46.27 47.81 47.81 46.27 87.38 84.56 50.15 652

SC16 83.17 75.13 83.17 80.49 103.60 100.26 103.60 103.60 100.26 147.81 141.25 83.17 1206

SC17 153.40 138.56 153.40 148.45 4.51 4.37 4.51 4.51 4.37 64.22 62.15 153.40 896

SC18 1.71 1.54 1.71 1.65 0.65 0.63 0.65 0.65 0.63 1.71 1.65 1.71 15

SC19 79.45 71.76 79.45 76.89 51.84 50.17 51.84 51.84 50.17 85.59 61.63 70.03 781

SC20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0

SC21 22.00 19.87 22.00 21.29 98.23 95.06 98.23 98.23 95.06 96.23 93.13 22.00 781

SC22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0

SC23 432.15 391.26 439.70 429.91 257.69 249.49 257.69 257.69 249.49 334.66 323.98 422.99 4047

SC24 0.38 0.35 0.38 0.37 3.67 3.55 3.67 3.67 3.55 1.69 1.63 0.38 23

SC25 613.56 554.18 613.56 593.77 33.14 32.07 33.14 33.14 32.07 269.56 260.87 613.56 3683

SC26 69.05 62.37 69.05 66.82 108.94 105.42 108.94 108.94 105.42 99.58 96.37 69.05 1070

SC27 0.00 0.00 0.00 0.00 2.59 2.51 2.59 2.59 2.51 2.02 0.00 0.00 15

SC28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0

SC29 83.14 75.10 83.14 80.46 42.05 40.70 42.05 42.05 40.70 51.64 49.98 83.14 714


15


SC30 35.34 31.92 35.34 34.20 64.52 62.44 64.52 64.52 62.44 52.28 50.59 35.34 593

SC31 10.85 9.80 10.85 10.50 25.90 25.06 25.90 25.90 25.06 21.11 20.43 10.85 222

SC32 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0

SC33 16.82 15.19 16.82 16.28 8.19 7.93 8.19 8.19 7.93 21.16 20.48 16.82 164

SC34 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0

SC35 32.63 29.47 32.63 31.58 69.62 67.38 69.62 69.62 67.38 60.78 58.09 32.63 621

SC36 17.38 15.70 17.38 16.82 41.61 40.27 41.61 41.61 40.27 37.59 36.38 17.38 364

SC37 23.17 20.93 23.17 22.42 26.46 25.60 26.46 26.46 25.60 32.37 24.80 23.17 301

SC38 52.21 49.09 54.35 49.39 140.08 135.56 140.08 140.08 135.56 108.83 97.90 48.84 1152

SC39 46.31 41.83 50.96 50.18 153.28 148.33 153.28 153.28 148.33 113.52 96.15 46.31 1,202

SC40 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0

SC41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0

Total 2,858 2,607 2,897 2,806 1,924 1,862 1,924 1,924 1,862 2,886 2,614 2,777 28,940


16

Figure 3-3 WIMS (Dec 2006) Water Allocations in the Mersey catchment


17

3.7 Estimation of unlicensed dams

Under current Tasmanian law a dam permit is not required for a dam if it is not on a

watercourse and holds less than 1ML of water storage (prior to 2000 it was 2.5 ML),

and is used only for stock and domestic purposes. Therefore there are no records for

these storages. The storage volume attributed to unlicensed dams was estimated by

analysis of aerial and satellite photographs by the following method:

• Aerial and Satellite photographs were analysed. Google Earth was

selected as the source for the photographs as other aerial photographs

were not readily available. While Google Earth covers the entire

catchment, the resolution of all but 4 subareas – SC 6, SC13, SC25 and

SC26 (all located in the lower lying north-east of the catchment) - was too

poor to be able identify dams. Mersey is a mountainous catchment and as

a result is frequently in cloud, which may explain the poor resolution of

Google Earth photographs of the catchment. The Google Earth photos

covering this catchment were taken between September 2002 and January

2007. The number of dams of any size was counted by eye in the 4 visible

subareas. The number of unlicensed dams was determined by subtracting

the number of licensed dams. A total of 116 unlicensed dams were

identified in the 4 visible subareas. The ratio of unlicensed: licensed dams

were calculated to be 0.41. This is similar to the nearby Leven & Gawler

(0.49) and Panatana (0.41) catchments. This ratio was used to estimate the

number of unlicensed dams in subareas that were obscured by multiplying

the number of licensed dams by the ratio. This method led to an estimate

of 1431 unlicensed dams over 31 subareas in the catchment;

• It was assumed most of these dams would be legally unlicensed dams

(less than 1 ML and not situated on a water course). However, it was

assumed that there would be a proportion of illegal unlicensed dams up to

20ML in capacity. A frequency distribution of farm dam sizes presented by

Neal et al (2002) for the Marne River Catchment in South Australia showed

that the average dam capacity for dams less than 20 ML was 1.4 ML (Table

3-6), and this dam size was adopted after discussion with DPIW;

• Following discussions with DPIW, the unlicensed dam demand was

assumed to be 100%. The assumption is that all unlicensed dams will be

empty at the start of May and will fill over the winter months, reaching 100%

capacity by the end of September;


18

• Difficulties in detecting farm dams from aerial photography by eye are

compounded when photography is not of suitably high resolution.

Depending on the season and time of day that an aerial photograph is

taken, farm dams can appear clearly or blend into the surrounding

landscape. Vegetation can obscure the presence of a dam, and isolated

stands of vegetation can appear as a farm dam when in fact no such dam

exists. On balance, however, it was assumed that the number of false

detections is countered by the number of missed detections, and in the

absence of another suitably rapid method the approach gives acceptable

results;

• Assuming this dam size distribution is similar to the distribution given in

Neale et al.’s (2002) study catchment in South Australia, the total volume of

unlicensed dams in the Mersey catchment is estimated to be 2003.4 ML

(1431 * 1.4ML). This equates to approximately 2 ML/km2 of unlicensed

dams in the 31 subareas where dams are present, or 1.1 ML/km2 over the

entire catchment. The total volume of existing permitted dam extractions in

the study catchment is 8322 ML. Therefore the volume of unlicensed dams

equates to approximately 24 % of the total dam extractions from the

catchment.

Table 3-6 Average capacity for dams less than 20 ML from Neal et al. (2002)

Size Range (ML)

Average Volume

(ML) Number of

Dams

Total Volume

(ML)

0 - 0.5 0.25 126 31.5

0.5 - 2 1.25 79 98.75

2 - 5 3.5 13 45.5

5 - 10 7.5 7 52.5

10 - 20 15 6 90

27.5 231 318.25

Average Dam Volume: 1.4 ML


19

3.8 Environmental flows

Scenario 3 was to account for environmental flows within the catchment. DPIW advised

that for most of the Mersey catchment they currently do not have environmental flow

requirements defined. The exception is flow from Lake Parangana, which conforms to a

mandated environmental flow release: under usual conditions, a minimum 172.8 ML/day

flows into the Mersey River at Liena through the mini hydro installation or the riparian

valve at the Parangana Dam (this flow may be reduced when natural inflow into Lake

Parangana is less than 172.8 ML/day). After discussions with DPIW, it was assumed the

172.8 ML/day environmental flow would be passed on to all subareas downstream of

Lake Parangana. To account for environmental flows to those subareas not downstream

of Lake Parangana, the calibrated catchment model was run under scenario 1 (Modelled

– no entitlements (Natural)) and the environmental flows in these subareas were

assumed to be:

• The 20th percentile of flows for each sub-catchment during the winter period (01

May to 31st Oct).

• The 30th percentile of flows for each sub-catchment during the summer period (01

Nov – 30 April).

The Modelled – no entitlements (Natural) scenario was run from 01/01/1900 to

01/01/2006.

A summary table of the monthly environmental flows by sub-catchment is provided

below in Table 3-5 and in the Catchment User Interface.


20

Table 3-7 Environmental Flows

Subarea

Sub-area size

(km2)

Environmental Flow (ML/d) Per Month at each subcatchment

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave.

SC12 11.6

172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8

SC22 46.2

172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8

SC3 62.3 200.0 141.6 126.1 188.1 502.8 705.3 922.4 994.7 919.5 690.6 618.0 393.1 533.5

SC4 78.0 26.7 22.5 18.9 24.3 36.0 65.5 151.5 168.9 131.7 59.3 43.7 35.4 65.4

SC52 23.2

172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8

SC62 20.1

172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8

SC7 51.5 36.1 29.6 24.2 29.8 34.1 67.9 157.1 220.5 126.6 66.5 54.7 45.2 74.4

SC82 46.5

172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8

SC9 86.0 38.4 31.7 27.6 37.9 71.9 133.8 224.9 236.6 202.1 136.9 104.8 59.3 108.8

SC10 45.7 23.2 19.3 16.5 19.7 23.5 48.4 123.8 154.3 90.7 45.8 35.3 30.1 52.6

SC11 42.9 8.4 7.0 5.7 5.8 5.9 9.9 18.5 22.8 20.1 15.4 13.3 10.8 12.0

SC12 40.6 8.2 6.8 5.6 5.7 6.1 10.5 20.1 25.6 20.6 15.1 12.7 10.6 12.3

SC13 22.8 7.3 6.1 5.0 5.5 5.2 8.0 18.2 20.5 18.1 13.8 12.0 9.5 10.8

SC14 49.5 10.5 8.6 7.0 7.3 7.8 14.3 28.4 36.0 25.6 19.6 16.3 13.3 16.2

SC15 12.0 2.0 1.6 1.4 1.5 1.5 2.3 4.9 5.2 4.9 3.8 3.3 2.6 2.9

SC16 82.1 19.1 15.8 13.2 14.2 16.2 31.3 61.8 98.3 57.1 34.6 30.2 25.3 34.8

SC172 55.3

172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8

SC182 43.7

172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8

SC19 35.6 33.0 26.9 23.2 30.4 37.7 64.0 158.6 188.8 151.9 60.9 51.2 44.3 72.6

SC20 155.9 94.9 72.8 61.5 84.1 151.5 297.4 578.1 603.9 504.2 271.3 211.2 150.3 256.8

SC21 87.0 24.6 20.7 18.1 23.9 31.1 54.6 135.6 153.2 123.8 47.4 38.1 33.2 58.7

SC222 61.4

172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8

SC23 118.3 35.5 29.7 24.9 31.0 39.5 76.7 198.4 243.3 164.8 76.1 58.9 45.2 85.4

SC24 40.1 11.7 9.7 8.0 9.4 10.7 21.7 62.5 83.8 50.3 22.9 17.8 14.9 27.0

SC252 25.7

172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8

SC26 19.9 3.6 3.0 2.4 2.6 2.5 3.6 8.6 9.8 8.4 6.6 5.9 4.6 5.1

SC272 35.4

172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8 172.8

SC28 198.1 117.9 83.9 73.7 121.6 345.1 493.3 624.8 634.1 587.6 471.2 413.8 241.2 350.7

SC29 22.2 3.8 3.0 2.6 2.8 2.7 4.2 8.6 9.5 9.2 7.0 6.4 4.9 5.4

SC30 16.1 30.1 24.9 19.8 21.5 21.8 42.7 90.6 126.0 82.8 54.2 47.8 37.0 49.9

SC31 9.1 2.0 1.7 1.3 1.4 1.5 2.8 5.2 7.7 5.0 3.7 3.2 2.5 3.2

SC32 5.1 1.0 0.8 0.7 0.7 0.7 1.2 2.3 3.1 2.4 1.8 1.6 1.2 1.5

SC33 3.8 0.8 0.6 0.5 0.5 0.5 0.9 1.7 2.3 1.8 1.4 1.2 0.9 1.1

SC34 3.3 0.6 0.5 0.4 0.5 0.4 0.8 1.5 1.9 1.6 1.2 1.0 0.8 0.9

SC35 19.0 4.0 3.3 2.7 2.8 2.7 5.0 9.8 13.9 9.8 7.5 6.4 5.0 6.1

SC36 12.8 22.2 18.5 14.6 16.1 17.4 32.8 72.2 97.7 67.0 39.6 35.3 27.5 38.4

2 This subarea is downstream of Parangana Dam. The environmental flow requirement in this

subarea was assumed to equal releases mandated for Parangana Dam.


21

Subarea

Sub-area size

(km2)

Environmental Flow (ML/d) Per Month at each subcatchment

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave.

SC37 11.6 2.5 2.0 1.7 1.7 1.8 3.3 6.0 8.7 6.1 4.7 4.0 3.2 3.8

SC38 36.5 16.6 13.8 11.0 12.3 13.9 25.8 60.7 77.3 52.8 29.6 26.2 21.0 30.1

SC39 33.3 8.5 7.1 5.8 6.7 7.9 14.7 37.5 51.1 31.1 15.6 13.1 10.8 17.5

SC40 37.0 17.4 14.3 12.6 17.0 42.0 68.5 103.6 102.2 97.9 67.5 56.5 27.9 52.3

SC41 44.9 19.8 16.2 14.2 19.1 31.8 76.7 116.8 124.9 105.6 68.2 53.9 27.3 56.2


22

4. MODEL DEVELOPMENT

4.1 Catchment Subarea Delineation

Subarea delineation was performed using CatchmentSIM GIS software.

CatchmentSIM is a freely available 3D-GIS topographic parameterisation and hydrologic

analysis model. The model automatically delineates watershed and subarea boundaries,

generalises geophysical parameters and provides in-depth analysis tools to examine and

compare the hydrologic properties of subareas. The model also includes a flexible result

export macro language to allow users to couple CatchmentSIM with any hydrologic

modelling package that is based on subarea networks.

For the purpose of this project, CatchmentSIM was used to delineate the catchment,

break it up into numerous subareas, determine their sizes and provide routing lengths

between them.

These outputs were visually checked to ensure they accurately represented the

catchment. For Mersey catchment several modifications were required. CatchmentSIM

treats lakes differently when calculating routing lengths, and for the three subareas (SC4,

SC3, SC2) containing the major lakes in this catchment (Lake Mackenzie, Lake

Rowallan, Lake Parangana), the routing lengths were not sufficiently accurate. Routing

lengths for these three subareas were estimated by manually tracing routing lengths in

the GIS software package ArcMap, and then entered into the model.

For more detailed information on CatchmentSIM see the CatchmentSIM Homepage

www.toolkit.net.au/catchsim/

4.2 Hydstra Model

A computer simulation model was developed using Hydstra Modelling. The Mersey

River subareas, described in Figure 2-1, were represented by model “nodes” and

connected together by “links”. A schematic of this model is displayed in Figure 4-1.

The flow is routed between each sub-area and through the catchment via a channel

routing function.

Rainfall and evaporation were calculated for each subarea using inverse-distance

gauge weighting. The gauge weights were automatically calculated at the start of each

model run. The weighting is computed for the centroid of the subarea. Subareas were

divided into quadrants separated by four radial lines emanating from the centroid (i.e.,

like slicing a pie into four pieces). A weight for the closest gauge in each quadrant was


23

computed as the inverse of the square of the distance between the gauge and centroid.

For each time step and each node, the gauge weights are applied to the incoming

rainfall and evaporation data.

The AWBM Two Tap rainfall/runoff model was used to calculate the runoff for each

subarea separately. This means the Mersey model is a series of AWBM two tap models,

all using a single set of calibration parameters: one AWBM model for each subarea. The

output of a given subarea AWBM acts as the input for the subarea immediately

downstream, and so on. This series of models was preferred over the usual method of

using a single AWBM model for the whole catchment as it more accurately distributes

runoff and base flow spatially over the catchment. The AWBM two-tap model was

chosen over the more common single tap AWBM model for the whole catchment as it

allows better simulation of base flow recessions.

The flow is routed between each subarea through the catchment via a channel routing

function.

4.2.1 Accounting for Mersey Hydro Electric Scheme

The upper Mersey catchment has undergone extensive modification for the hydro-

electric power generation scheme, which needed to be accounted for in the model.

There are three major dams in the Mersey catchment: Lake Mackenzie Dam (SC4),

Lake Rowallan Dam (SC3), and Lake Parangana Dam (SC2), all built between 1967

and 1972 (see Figure 4-1). Each of the storages significantly alters flow to the

subareas downstream. Of particular note is the Parangana dam, which supplies a

tunnel that diverts substantial flow from the Mersey to the Forth River; flow volumes in

the Mersey River are not conserved at the Parangana subcatchment boundary.

Following discussion with DPIW, these alterations to natural stream flow were

accounted for by effectively splitting the Model at each dam. Mean daily inflows into

subareas downstream of storages were calculated for each month from Hydro

Tasmania records for the period 1997-2007 for Mackenzie and Lake Rowallan dams

and for 2002-2007 for Lake Parangana (Table A-1). A shorter period was used for

Parangana, as mandatory environmental flows have been released downstream since

2002. Before 2002 the Lake Parangana spilled only during large flood events.

Environmental flows from Lake Parangana are mandated for the foreseeable future, so

the shorter record better reflects future flows into the Mersey from Parangana, despite

its brevity. When the model is run under scenarios 2 or 3 (i.e. not under the “natural”

scenario) mean inflows are used as inputs into the subareas directly downstream of the


24

dams. Customised code was entered into the outflow node of the relevant sub-

catchments. The basic rules associated with this code are:

- Scenario 1, “No Entitlements (Defines ‘Natural’ flows)” will model the catchment

with no dam or lake present for all of record.

- Both Scenario 2 “with Entitlements (extraction not limited by Env.Flows)” and

Scenario 3 “Environmental Flows & Entitlements (‘Low Priority Ents. Limited by

Env Flows’)” will model the catchment with:

1. No dam or lake present in the model prior to its construction completion

date.

2. For all years following the completion date, flows downstream of the

dam will be a total of the average long term (10 year) monthly flows

which will include spill, power station discharge (if applicable) and any

known environmental releases.

Because long-term monthly average flows were only calculated from records up to 10

years old, care should be taken if using the model for hindcasting flows before 1997.

The remainder of the model operates as usual, with the modelled outflows from any

given subarea acting as inflows to the subarea immediately downstream. The details

of individual lakes in the scheme and how they are treated in the model is described in

APPENDIX A.


25

Figure 4-1 Hydstra Model schematic


26

4.3 AWBM Model

The AWBM Two Tap model (Parkyn & Wilson 1997) is a relatively simple water balance

model with the following characteristics:

• it has few parameters to fit;

• the model representation is easily understood in terms of the outflow

hydrograph;

• the parameters of the model can largely be determined by analysis of the

outflow hydrograph;

• the model accounts for partial area rainfall-run-off effects;

• runoff volume is relatively insensitive to the model parameters.

For these reasons parameters can more easily be transferred to ungauged catchments.

The AWBM routine used in this study is the Boughton Revised AWBM model (Boughton

& Chiew 2003). Boughton & Chiew (2003) showed that when using the AWBM model

the total amount of runoff is mainly affected by the average surface storage capacity and

much less by how that average is spread among the three surface capacities and their

partial areas. Given an average surface storage capacity (CapAve), the three partial

areas and the three surface storage capacities are defined in Table 4-1.

Table 4-1 Boughton & Chiew, AWBM surface storage parameters

Partial area of S1 A1=0.134



Capacity of S1 C1=(0.01*Ave/A1)=0.075*Ave

Capacity of S2 C2=(0.33*Ave/ A2)=0.762*Ave

Capacity of S3 C3=(066*Ave/ A3)=1.524*Ave

The AWBM routine produces two outputs: direct run-off and base-flow. Direct run-off is

produced after the content of any of the soil stores is exceeded; it can be applied to the

stream network directly or by catchment routing across each subarea. Base-flow is


27

usually supplied unrouted directly to the stream network, at a rate proportional to the

water depth in the ground water store. The ground water store is recharged from a

proportion of excess rainfall from the three surface soil storages.

Although the AWBM accounts for base-flow, it is not intended that the AWBM be used to

predict base-flow contribution within catchments. Base-flow in the AWBM routine is used

as a fit parameter to obtain a good recession of surface water hydrographs. The AWBM

does not specifically account for attributes that affect baseflow such as geology and inter-

catchment groundwater transfers.

The AWBM processes are shown below in Figure 4-2.


28

Figure 4-2 Two-tap Australian Water Balance Model schematic


29

4.3.1 Channel Routing

A common method employed in nonlinear routing models is a power function storage

relation.

S = K.Qn

K is a dimensional empirical coefficient, the reach lag (time). In the case of Hydstra/TSM

Modelling:

i.L =K α

where

Li = Channel length (km)

α = Channel Lag Parameter

n = Non-linearity Parameter

Q = Outflow from Channel Reach (ML/day)

A reach length factor may be used in the declaration of α to account for varying reach lag

for individual channel reaches. e.g. α.fl where fl is a length factor.

Parameters required by Hydstra/TSM Modelling and their recommended bounds are

given in Table 4-2.

Table 4-2 Hydstra/TSM Modelling Parameter Bounds

α Channel Lag Parameter Between 0.0 and 5.0

L Channel Length (km) Greater than 0.0 (km)

N Non-linearity Parameter Between 0.0 and 1.0

4.4 Model Calibration

4.4.1 Accounting for flow diversions on the Mersey River

The choice of calibration period was dictated by the reliability of rainfall and evaporation

input data. As noted, these data may not be reliable before 1970 (see Section 3.4).

Thus a more recent calibration period was appropriate for this model. This was


30

complicated by the extensive alterations to the Mersey flow regime by the development

of the Hydro electric power scheme for the Mersey, the first part of which commenced in

June 1967 (see Figure 4-1). Of particular note is the construction of the Parangana Dam

and tunnel, which diverts a large amount of flow from the Mersey River to the Forth

River, meaning flow volume of the Mersey is not conserved after this dam.

In order to calibrate the model, the model was split at the node located at the settlement

of Liena, which is located downstream of Parangana dam. The Mersey at Liena site

(TSM 60.1/100.00/1) was chosen as it is the nearest site downstream from the

Parangana Dam with a continuous and reliable flow record. For calibration purposes the

Mersey at Liena flow record was used as the inflow to the Mersey at Liena node rather

than the inflows generated by the model. There are no major flow diversions on the

Mersey downstream of Liena. Using the Mersey at Liena flow record as an input into the

Model circumvents the need to account for altered flows due to hydropower

infrastructure. The site chosen for calibration was Mersey at Kimberley, which offered a

reliable and lengthy flow record. The pickup between Mersey at Liena and the calibration

site is 676 km2, which is significantly large for the model to simulate stream routing

accurately. Note that this modification to the model was only used during the calibration

process. The final model uses long-term monthly downstream discharges from

Parangana Dam, as detailed in APPENDIX A.

4.4.2 Calibration Method

Calibration was achieved by adjusting catchment parameters so that the modelled flows

best replicated the flows observed at the Mersey at Kimberley gauging station (site 22)

over 20 years of available flow data (01/01/1986 to 01/01/2006). This period was chosen

as there were few interruptions to the flow record in this time, and the rainfall DRILL data

matched observed rainfall records for this period (see Section 3.4).

The fit of parameters were chosen by first comparing the volumes of monthly and annual

flows over the entire calibration period, and second by comparing annual hydrographs.

Regression statistics and engineering judgment were employed when observing daily

and monthly time series comparisons.

The calibration process can best be understood as attempting to match the modeled

calibration flow (MCF) to the observed flow record. The MCF can be described as:


31

MCF = MNEM - (WE x TPRF)

Where:

MCF = Modeled Calibration Flow

MNEM = Modeled - No Entitlements (Modified)

WE = Water Entitlements

TPRF = Time Period Reduction Factor

Water entitlements were included in the calibration model and adjusted to the time period

of calibration by applied a Time Period Reduction Factor (TPRF). The TPRF was

calculated by a method developed in the Tasmanian State of the Environment report:

water demand has increased by an average of 6% annually over the last 4 decades. A

6% annual reduction from 2006 to the middle year of the calibration period, 1996,

resulted in a TPRF of 53.9% of the current extractions was applied to all years in the

calibration period. For the Mersey River the water entitlement extractions at the

calibration site are negligible in relation to the observed flow, thus the model calibration

would be unchanged regardless of the TPRF applied.

The model was calibrated to the observed flow as stated in the formula MCF = MNEM -

(WE x TPRF). Other options of calibration were considered, including adding the water

entitlements to the observed flow. However, the chosen method is considered to be the

better option as it preserves the observed flow and unknown quantities are not added to

the observed record. The chosen method also preserves the low flow end of the

calibration, as it does not assume that all water entitlements can be met at any time.

In the absence of information on daily patterns of extraction, the model assumes that

water entitlements are extracted at a constant daily flow for each month. For each

daily time step of the model if water entitlements cannot be met, the modelled outflows

are restricted to a minimum value of zero and the remaining water required to meet the

entitlement is lost. Therefore the MCF takes account of very low flow periods where

the water entitlements demand can not be met by the flow in the catchment. Table 4-4

shows the total catchment monthly water entitlements (demand) used in the calibration.

4.4.3 Adopted Model Parameters

The adopted calibrated model parameters are shown in Table 4-3. These calibration

parameters are adopted for all three scenarios in the user interface. Although it is

probable that some catchment characteristics such as land use and vegetation will

have changed over time, it is assumed that the rainfall run-off response defined by the

calibration parameters has not changed significantly over time. Therefore it is

appropriate to apply these parameters to all three scenarios.


32

To achieve a better fit of seasonal volumes, the normally constant store parameter

CapAve has been made variable for each month. In order to avoid rapid changes in

catchment characteristics between months, CapAves of consecutive months were

smoothed. A CapAve of a given month was assumed to occur on the middle day of that

month. It was assumed that daily CapAves occurring between consecutive monthly

CapAves would fit to a straight line, and a CapAve for each day was calculated on this

basis. The annual profile of CapAves for the Mersey catchment is shown in Figure 4-3.

Monthly CapAve values followed a generally smooth curve moving from lower values in

summer to higher values in winter. The exception was a dip in CapAve in March. This

may be explained by the effects of consecutive dry summer months, which could cause

the catchment properties to change slightly before the onset of the wetter autumn and

winter period.

Table 4-3 Adopted Calibration Parameters

PARAMETER VALUE

INFBase 0.8

K1 0.99

K2 0.92

GWstoreSat 120

GWstoreMax 130

H_GW 50

EvapScaleF 1

Alpha 3

n 0.8

CapAve Jan 48

CapAve Feb 67

CapAve Mar 42

CapAve Apr 80

CapAve May 80

CapAve June 102

CapAve July 118

CapAve Aug 143

CapAve Sep 152

CapAve Oct 147

CapAve Nov 120

CapAve Dec 95


33

0

20

40

60

80

100

120

140

160

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month

Ca

pA

ve

Figure 4-3 Monthly Variation of CapAve Parameter

4.4.4 Model accuracy: Qualitative description

In all plots the “Modelled Calibration Flow” series - representing the modelled output

under scenario 2 – is compared to the observed flow at the calibration site.

Time series plots have been displayed for three representative years of the observed

and modelled flow: a typical year (Figure 4-4), a low-inflow year (Figure 4-5) and a

high-inflow year (Figure 4-6). The quality of fit for each annual plot is described in the

caption text. The quality of fit was determined initially by visual inspection, and verified

by calculating the coefficient of determination (R2) for the observed and modelled flows

shown in each figure. The catchment’s average precipitation data used in the model

are also plotted to show the relative magnitudes of precipitation through the year. Note

that the precipitation trace is plotted on an independent scale (marked on the right of

each graph). The water extraction entitlements for the subcatchment upstream of the

calibration site are small relative to the Mersey’s flow (Table 4-4).

The time series plots show consistent response to rainfall events and good fidelity

between modelled and observed hydrographs (Figure 4-4 and Figure 4-5). The

calibration method focused on matching flow volumes while matching hydrograph

shapes was given lesser importance, and hence a highly accurate match between

observed and modelled time series plots was not expected. Despite this hydrograph

response was good.

The good fit of the annual time series plots is supported by the excellent match

between observed and modelled average flow volumes. The monthly, seasonal and


34

annual volume balances for the whole period of calibration record are presented in

Table 4-4, Figure 4-7 and Figure 4-8. The demand values shown represent the

estimated monthly demands for the middle year of the calibration period (see section

4.4) for the subareas upstream of the calibration site. The calibration procedure

generally ensures that the seasonal and annual volumes are preserved. In this

instance average demand is much lower than the volume of flow in the river.

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

01/1993 04/1993 07/1993 10/1993 01/1994

Da

ily

Flo

w (

ML

/da

y)

-40

-30

-20

-10

0

10

20

30

40

50

60

Pre

cip

ita

tio

n (

mm

)

Precipitation Modelled Calibration Flow Observed

R2 = 0.84

Figure 4-4 Daily time series - typical year (ML/d). Good fit

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

01/1999 04/1999 07/1999 10/1999 01/2000

Da

ily

Flo

w (

ML

/da

y)

-40

-30

-20

-10

0

10

20

30

40

50

60

Pre

cip

ita

tio

n (

mm

)Precipitation Modelled Calibration Flow Observed

R2 = 0.81

Figure 4-5 Daily time series – low inflow year (ML/d). Good fit.


35

0

5000

10000

15000

20000

25000

01/2003 04/2003 07/2003 10/2003 01/2004

Da

ily

Flo

w (

ML

/da

y)

-40

-30

-20

-10

0

10

20

30

40

50

60

Pre

cip

ita

tio

n (

mm

)

Precipitation Modelled Calibration Flow Observed

R2 = 0.88

Figure 4-6 Daily time series comparison – high inflow year (ML/d). Good fit.

0

50000

100000

150000

200000

250000

300000

1986 1987 1988 1988 1990 1991 1992 1992 1994 1995 1996 1996 1998 1999 2000 2000 2002 2003 2004 2004 2006

Mo

nth

ly V

olu

me

(M

L)

Observed

Modelled Calibration Flow R2 = 0.95

Figure 4-7 Monthly Time Series comparison – Volume (ML)


36

0

500

1000

1500

2000

2500

3000

Ja

n

Fe

b

Ma

r

Ap

r

Ma

y

Ju

n

Ju

l

Au

g

Se

p

Oct

No

v

De

c

WIN

TE

R

SU

MM

ER

AN

NU

AL

Av

era

ge

Flo

w (

ML

/Da

y)

Observed

Modelled Calibration Flow

Modelled - No Entitlements

(natural)Demand x 10

Figure 4-8 Long term average monthly, seasonal and annual flows


37

Table 4-4 Long term average monthly, seasonal and annual comparisons

Long term Averages (ML/Day)

MONTH Observed

Demand4

January 461.06 466.55 487.05 20.53

February 350.23 359.27 379.47 20.55

March 267.06 258.14 278.04 20.66

April 421.60 425.85 446.62 20.74

May 748.65 735.61 749.30 13.24

June 1308.36 1309.79 1322.58 13.24

July 2343.74 2346.37 2358.92 13.24

August 2719.99 2705.29 2718.50 13.24

September 2632.28 2632.12 2645.25 13.24

October 2092.18 2098.69 2119.14 21.07

November 1096.43 1083.38 1103.80 20.55

December 563.62 552.03 572.18 20.21

WINTER 1974.20 1971.31 1985.62 14.55

SUMMER 526.66 524.20 544.53 20.54

ANNUAL 1250.43 1247.76 1265.07 17.54

WINTER from May to Oct, SUMMER from Nov - Apr.

4.4.5 Factors affecting the reliability of the model calibration

Regardless of the effort undertaken to prepare and calibrate a model, there are always

factors that will limit the accuracy of the output. Significant limitations inherent in the

method of calibration were:

• The assumption that water entitlements are taken as a constant rate for each

month is unlikely to be correct. Historical monthly extraction rates are probably far

more variable. Factors affecting water extraction rates and quantities are too

complex to be accurately represented in the model. Further, the Time Period

3 Refer to Section 4.4.2 for explanation of this modelling scenario.

4 A TPRF was calculated for the middle year of calibration period (1996) to be 53.9% of WIMS

(Dec 2006) demand. Demand is defined as total extractions upstream of the calibration site.


38

Reduction Factor applied to extraction entitlements is merely an estimate, and its

accuracy is unknown;

• The quantity of water currently extracted from the catchment is not accurately

known. Although DPIW has provided water extraction licence information (WIMS

Dec 2006) and estimates of extractions in excess of these licenses, these may not

represent the true quantity of water extracted. The method of estimating the

volume of unlicensed dams, while the best available to this project, is crude. No

comprehensive continuous water use data are currently available;

• Catchment precipitation and especially evaporation data used in the models may

not always be accurate. This is due to insufficient rainfall gauge information in and

around the catchment. Despite the Data DRILL’s good coverage of grid locations,

the development of this grid information still relies considerably on the availability of

measured rainfall information in the region. This is also the case with evaporation

data, which will have a smaller impact on the calibration;

• Catchment freezing and snowmelt affect the upper Mersey catchment, especially

during winter months. This may affect the flow regime. Snowmelt has not been

specifically accounted for within this model;

• The daily timestep on which the model operates is likely to smooth out rainfall

temporal patterns and affect peak flows. For example, an intense rainfall event in

which significant rain falls in an hour is treated as if the same quantity of rain had

fallen over 24 hours. Such intense rains can generate substantially more runoff

than events where the same quantity of rain falls evenly over 24 hours. Thus

extreme caution is advised in interpreting modelled flood peaks. The model is

designed to predict longer term flow volumes, and not to accurately predict peak

flows;

• The model does not explicitly account for changes in vegetation and terrain within

individual subareas. Hydrologic effects due to vegetation and terrain are averaged

across the whole catchment using the global AWBM fit parameters. Runoff in

individual subareas may not be accurately represented by this model. To account

for such variation a more complex model is required, the development of which is

outside the scope of this project;


39

• The simple operating rules and assumptions used to model the catchment

modifications (the Hydro-Electric Power generation scheme) cannot capture the

complexities of operation that occur in reality.

4.4.6 Model Accuracy – Model fit statistics

Coefficients of Determination (R2)

One of the most common measures of comparison between two sets of data is the

coefficient of determination (R2). If two data sets are defined as x and y, R2 is the

variance in y attributable to the variance in x. A high R2 value indicates that x and y

vary together – that is, as one data set changes, the other changes too. In this case x

and y are observed flows and modelled flows. So for the Mersey catchment model, R2

indicates how much modelled flows change as observed flows change. Table 4-5

shows the R2 values between observed and modelled daily and monthly flows, as well

as the proportional difference (%) between long-term (20 year) observed and modelled

volumes. The high daily and monthly R2 values returned in conjunction with the small

proportional difference between flow volumes show that the Mersey model is effective

at simulating observed flows.

Table 4-5 Model Fit Statistics – Mersey River

Measure of Fit Value

Daily coefficient of determination (R2 value) 0.82

Monthly coefficient of determination (R2 value) 0.95

Difference in observed and estimated long term

annual average flows - 0.21 %

As noted, the focus of the calibration process was to accurately simulate monthly flow

volumes over a long period (20 years). Matching daily flows was given less priority.

However, without a reasonable simulation of daily flows, a good monthly match would

be difficult to achieve. A target of R2 ≥ 0.7 was set for daily flows, while a target of R2 ≥

0.85 was set for monthly flows. The lower target for daily flows was deemed

acceptable due to model limitations and potential sources of error (see Section 4.4.7).


40

Qualitative descriptions of fit were more formally defined by R2 values as shown in

Table 4-6.

Table 4-6 Coefficient of Determination (R2) Fit Categories

Qualitative Fit Description Daily R2 Monthly R2

Poor R2 < 0.65 R2 < 0.8

Fair 0.65 ≥ R2 > 0.70 0.8 ≥ R2 > 0.85

Good R2 ≥ 0.70 R2 ≥ 0.85

It should be noted that although R2 is a useful objective indicator of fit, it has limitations.

One of the major limitations in using R2 is that minor differences in the timing of

hydrograph events can significantly affect the R2 value. That is, even though the good

visual fit achieved with the Mersey model was reflected in high R2 values, this will not

always be the case. Thus R2 values are an aid to the more subjective practice of

visually calibrating models, but not a substitute.

Proportional difference (%)

An alternative indicator of the reliability of a calibration is the proportional difference

between observed data and the modelled flow measured by percent (%).

Undertaking this analysis for the Mersey at Kimberley calibration site and producing

meaningful proportional difference results was problematic. The reasons are

discussed below:

• The modelled calibration flow (MCF) data includes observed data from the

Mersey at Liena site (refer to section 4.4.1). Therefore the MCF will contain a

percentage of “actual” observed flow, thus influencing the proportional

difference results.

• The model used in the user interface utilises monthly long term averages (refer

to section 4.2.1) as an input of flow downstream of lake Parangana, so again

this will influence the proportional difference results.

In the absence of a viable alternative methodology for comparing the proportional

difference the results from both models have been included below for comparison.


41

Modelled Calibration Flow (MCF) Results.

The proportional differences for the daily flows and monthly volumes were calculated

for the calibration period and are presented as duration curves in Figure 4-9 and Figure

4-10. The graphs show the proportion of time for which the difference between

observed and MCF flows is less than a given value. For example, the All Record trace

in Figure 4-9 shows that for 50 % of the calibration period the difference between

observed and MCF daily flows is 21 % or less. Similarly the All Record trace in Figure

4-10 shows that the difference between observed and MCF monthly flows is less than

17.5 % for 60 % of the 20 year calibration period. The duration curves show three

traces, Summer5, Winter6 and All of Record. The lower values of the Summer trace are

an artefact of the proportionally higher influence of the Mersey at Liena “observed”

flows in the modelled data. In winter the influence of the Mersey at Liena “observed”

data in the MCF is reduced as there is a higher contribution of modelled flow from the

catchments downstream of Lake Parangana.

0

20

40

60

80

100

120

140

160

180

200

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Proportion of Calibration period

Difference

(%

) -

Ob

serv

ed

vs M

od

ell

ed

All record Winter Summer

Figure 4-9 Duration curve – MCF Daily flow proportional difference

5 Summer period = Nov – April, inclusive

6 Winter period = May – Oct, inclusive


42

0

10

20

30

40

50

60

70

80

90

100

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Proportion of Calibration Period

Difference

(%

) -

Ob

serv

ed

vs M

od

elled


Figure 4-10 Duration curve - MCF Monthly volume proportional difference

Overall the MCF model results show a very good result and this is because

approximately half of the model is being replaced with observed “actual” flow from the

Mersey at Liena site.

User Interface Model (UIM) Results.

The proportional differences for the daily flows and monthly volumes were calculated

for the calibration period and are presented as duration curves in Figure 4-9 and Figure

4-10. The graphs show the proportion of time for which the difference between

observed and User Interface Model (UIM) flow is less than a given value. For example,

the All Record trace in Figure 4-11 shows that for 50 % of the calibration period the

difference between observed and UIM daily flows is 40 % or less. Similarly the All

Record trace in Figure 4-12 shows that the difference between observed and UIM

monthly flows is less than 40 % for 60 % of the 20 year calibration period. The duration

curves show three traces, Summer, Winter and All of Record. The higher values of the

Winter trace are an artefact of monthly long-term means used as inputs to account for

hydro-electric power generation infrastructure (see APPENDIX A). Essentially, the

flows downstream of hydro-power infrastructure (Lake Parangana) are treated by the

model as constant for each month, while actual flows would be far more variable.


43

Because the long-term mean flows are proportionally much higher in winter, the

differences between actual flows and modelled flows will be greater, causing the higher

differences in Winter.

0

20

40

60

80

100

120

140

160

180

200

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Proportion of Calibration period

Difference

(%

) -

Ob

serv

ed

vs M

od

ell

ed


Figure 4-11 Duration curve – UIM Daily flow proportional difference


44

0

20

40

60

80

100

120

140

160

180

200

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Proportion of Calibration Period

Difference

(%

) -

Ob

se

rve

d v

s M

od

elled


Figure 4-12 Duration curve – UIM Monthly volume proportional difference

Overall the UIM model results show a poorer result than the MCF model and this is

because approximately half of the model is being replaced with a coarser long term

monthly average.

4.4.7 Model Accuracy throughout the Mersey catchment

The model has been calibrated to provide a good simulation of monthly and seasonal

flow volumes at the calibration site. Calibration sites are typically selected low in the

catchment to encompass as much of the catchment as possible. It is difficult to assess

how reliably the model performs throughout the catchment, although it is assumed that

the model operates satisfactorily at other sites in the catchments. The ability of five

other Tascatch models (developed by the same method as the Mersey Model) to

simulate flows throughout these catchments was assessed. These assessments are

detailed in APPENDIX B. These analyses suggest that on average the models predict

volumes well throughout their catchments (see APPENDIX B).

The fit of the hydrograph shape (which plots daily flows) is expected to vary between

sites within the catchment. Therefore it is expected that hydrograph fit will deteriorate

as the catchment area decreases.


45

In the Mersey Catchment there are two gauging sites that can be used to assess the

calibration fit at alternative locations: the Arm River before it flows into the Mersey (Arm

above Mersey – TSM 624.1), and the outflow of the Don River (Don River upstream of

Bass Highway – TSM 16200.1). Plots of the monthly time series volumes and

corresponding R2 values are shown in Figure 4-13 and Figure 4-14. The model

performed very well at these sites, and thus it is assumed the model will perform with

reasonable accuracy throughout the Mersey catchment.

0

5000

10000

15000

20000

25000

30000

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Mo

nth

ly V

olu

me

(M

L)

Observed


Figure 4-13 Time series of Monthly Volumes – Arm above Mersey (TSM 624.1)

(SC9)

0

5000

10000

15000

20000

25000

1980 1980 1981 1982 1984 1984 1985 1986 1988 1988 1989 1990

Mo

nth

ly V

olu

me

(M

L)

Observed


Figure 4-14 Time series of Monthly Volumes – Don River upstream of Bass

Highway (TSM 16200.1) (SC30)

4.5 Model results

The completed model and user interface allows data for three catchment demand


46

scenarios to be generated:

• Scenario 1 – No Entitlements (Natural Flow);

• Scenario 2 - With Entitlements (with water entitlements extracted);

• Scenario 3 - Environmental Flows and Entitlements (Water entitlements

extracted, however low priority entitlements are limited by an environmental

flow threshold).

For each of the three scenarios, daily flow sequence, daily flow duration curves, and

indices of hydrological disturbance can be produced for any subarea.

For information on the use of the user interface refer to the Operating Manual for the

NAP Region Hydrological Models (Hydro Tasmania 2004b).

Outputs of daily flow duration curves and indices of hydrological disturbance at the model

calibration site are presented in Figure 4-15, Table 4-7 and in Section 4.5.1 below. The

outputs are a comparison of scenario 1 with scenario 3 over the period 01/01/1900 to

01/01/2006. Note that this catchment has been extensively modified by the hydro-

electric power generation scheme, and the influence of these modifications may

overwhelm any effects that water extraction entitlements may have on these results.

0.10

1.00

10.00

100.00

1000.00

10000.00

100000.00

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percent Of Time Exceeded

Flo

w (

ML

/d)

Natural

Entitlements

Extracted

Figure 4-15 Daily Duration Curve for Modelled flows 01/01/1900 – 01/01/2006 at

the Calibration Site (SC6)

4.5.1 Indices of hydrological disturbance

The calculation of the estimates of natural flow (scenario 1) and flow less water

extractions but including environmental flows (scenario 3) were used to calculate indices

of hydrological disturbance. These indices include:


47

• Hydrological Disturbance Index

• Index of Mean Annual Flow

• Index of Flow Duration Curve Difference

• Index of Seasonal Periodicity

• Index of Seasonal Amplitude

The indices were calculated using the formulas developed for the Natural Resource

Management (NRM) Monitoring and Evaluation Framework by SKM for the Murray-

Darling Basin (MDBC 08/04).

Table 4-7 shows the Hydrological Disturbance Indices (HDIs) at the Catchment outflow

(SC1), comparing scenario 1 (natural) and scenario 3 (environmental flows with all

extractions included) for period 01/01/1900 to 01/01/2006. Two sites in addition to the

calibration site have been selected to give an indication of the variability of the indices of

hydrological disturbance across the catchment. Note that hydrological disturbance is

evident in the hydrological indices presented in Table 4-7. This is due to the difference in

flow regime between natural flows and flows affected by the hydro-electric power

generation scheme in the upper Mersey catchment.


48

Table 4-7 Hydrological Disturbance Indices at the Catchment Outflow measuring

disturbance between Scenario 1 and Scenario 3 at 3 sites in the Mersey

Catchment

Disturbance Indices Undisturbed

(natural

flow)

SC3 (High

in the

catchment)

SC6

(Calibration

site)

SC1

(catchment

outflow)

Index of Mean Annual Flow, A 1.00 1.00 0.81 0.81

Index of Flow Duration Curve

Difference, M 1.00 1.00 0.78 0.78

Index of Seasonal Amplitude,

SA 1.00 1.00 0.82 0.82

Index of Seasonal Periodicity,

SP 1.00 1.00 0.92 0.92

Hydrological Disturbance

Index, HDI 1.00 1.00 0.82 0.82

Hydrological Disturbance Index (HDI): This provides an indication of the hydrological

disturbance to the river’s natural flow regime. A value of 1 represents no hydrological

disturbance, while a value approaching 0 represents extreme hydrological disturbance.

Index of Mean Annual Flow: This provides a measure of the difference in total flow

volume between current and natural conditions. It is calculated as the ratio of the current

and natural mean annual flow volumes and assumes that increases and reductions in

mean annual flow have equivalent impacts on habitat condition.

Index of Flow Duration Curve Difference: The difference from 1 of the proportional

flow deviation. Annual flow duration curves are derived from monthly data, with the index

being calculated over 100 percentile points. A measure of the overall difference between

current and natural monthly flow duration curves. All flow diverted would give a score of

0.

Index of Seasonal Amplitude: This index compares the difference in magnitude

between the yearly high and low flow events under current and natural conditions. It is


49

defined as the average of two current to natural ratios. Firstly, that of the highest monthly

flows, and secondly, that of the lowest monthly flows based on calendar month means.

Index of Seasonal Periodicity: This is a measure of the shift in the maximum flow

month and the minimum flow month between natural and current conditions. The flows

of the month with the highest mean monthly flow and the flows of the month with the

lowest mean monthly flow are calculated for both current and natural conditions. Then

the absolute difference between the maximum flow months and the minimum flow

months are calculated. The sum of these two values is then divided by the number of

months in a year to get a monthly proportion (measured in %). This proportion is then

subtracted from 1 to give a value range between 0 and 1. For example a shift of 12

months would have an index of zero, a shift of 6 months would have an index of 0.5 and

no shift would have an index of 1.

4.6 Flood frequency analysis

No flood frequency plot has been developed for this model as the river is highly

regulated by the hydro–electric generation scheme, which affects the calibration site

and the lower catchment where the majority of water entitlements are located.


50

5. REFERENCES

Boughton, W.C. and Chiew, F., (2003) Calibrations of the AWBM for use on Ungauged

Catchments

CatchmentSIM Homepage www.toolkit.net.au/catchsim/ , December 2006

QNRM Silo (Drill Data) Homepage www.nrm.qld.gov.au/silo , January 2005

SKM (2003) Estimating Available Water in Catchments in Catchments Using Sustainable

Diversion Limits. Farm Dam Surface Area and Volume relationship, report to DSE, Draft

B October 2003

Hydrology Theme Summary of Pilot Audit Technical Report – Sustainable Rivers Audit.

MDBC Publication 08/04.

National Land and Water Resources Audit (NLWRA) www.audit.ea.gov.au/anra/water/;

January 2005.

Hydro Tasmania (2004a) South Esk River Catchment Above Macquarie River, Impact of

Water Entitlements on Water and Hydro Power Yield.

Hydro Tasmania (2004b). Operating Manual for the NAP region Hydrological Models.

Hydro Report 118783 – Report -015, 17 September 2004.

Hydro Tasmania, (2005), NAP Region Hydrological Model, North Esk Catchment.

Neal B, Nathan RJ, Schreider S, & Jakeman AJ. 2002, Identifying the separate impact of

farm dams and land use changes on catchment yield. Aust J of Water Resources,

IEAust, 5(2):165-176.

Parkyn R, Wilson D, (1997) Paper: Real-Time Modelling of the Tributary Inflows to

ECNZ's Waikato Storages. Published in 24th Hydrology & Water Resources

Symposium Proceedings Auckland NZ 1997.

State of the Environment Report, Tasmania, Volume 1 Conditions & Trends 1996. State

of Environment Unit, Lands Information Services, DELM.

SKM (2005) Development and Application of a Flow Stress Ranking Procedure, report

to Department of Sustainability and Environment, Victoria.


51

5.1 Personal Communications

DPIW (2007) Bryce Graham, Section Head, Ecohydrology, Water Assessment. March-

May 2007.


52

6. GLOSSARY

Coefficient of determination (R2): One of the most common measures of comparison

between two sets of data is the coefficient of determination (R2). If two data sets are

defined as x and y, R2 is the variance in y attributable to the variance in x. A high R2

value indicates that x and y vary together – that is, the two data sets have a good

correlation

High priority entitlements: Water entitlements with an assigned Surety 1 to 3.

Low priority entitlements: Water entitlements with an assigned Surety 4 to 8.

Modelled – No entitlements (Natural): The TimeStudio surface water model run in a

natural state. That is, all references to water entitlements have been set to zero.

Additionally any man made structures such as dams, power stations and diversions

have been omitted and the modelled flow is routed, uncontrolled through the

catchment. This is also referred to as Scenario 1.

Modelled – No entitlements (Modified): The TimeStudio surface water model run

with no water entitlements extracted. That is, all references to water entitlements have

been set to zero. Where human structures are identified that significantly affect the flow

regime, such as large dams, power stations and diversions, the TimeStudio model

contains custom code to estimate the flow effect on the downstream subareas. This

custom code takes effect from the completion date of the structure. Where there are no

significant human structures in the catchment or the model is run before the completion

of these structures this model will produce the same output as “Modelled – No

entitlements (Natural)”. This option is not available within the user interface and is one

of several inputs used to derive a modelled flow specifically for calibration purposes. It

is also referred to as MNEM in Section 4.4.

Modelled – with entitlements (extracted): The TimeStudio surface water model with

water entitlements removed from the catchment flow. Where human structures are

identified within a catchment that significantly affect the flow regime, such as large

dams, power stations and diversions, the TimeStudio model contains custom code to

estimate the flow effect on the downstream sub-catchments. This custom code takes

effect from the completion date of the structure. This is also referred to as Scenario 2.


53

Modelled – environmental flows and entitlements (extracted): The TimeStudio

surface water model with water entitlements removed. However, low priority

entitlements are only removed when sub-catchment flow exceeds a specified

environmental threshold. Where man made structures are identified within a

catchment, such as dams, power stations and diversions the TimeStudio model

contains code to estimate the flow effect on the downstream subcatchments,

commencing on the completion date of the structure. This is also referred to as

Scenario 3.

Time Period Reduction Factor (TPRF): A reduction factor applied to current levels of

water extracted from a catchment. The TPRF was applied to satisfy the assumption

that the amount of water extracted from Tasmanian catchments (e.g. for agriculture)

has increased over time. The TPRF was calculated by a method developed in the

Tasmanian State of the Environment report. This states that water demand has

increased by an average of 6% annually over the last 4 decades. This factor is applied

to current water entitlements to provide a simple estimate of water entitlements

historically. However, following discussions with DPIW the TPRF was capped at 50%

of the current extractions if the mid year of the calibration period was earlier than 1994.

Water entitlements: This refers generally to the potential water extraction from the

catchment. Included are licensed extractions documented in WIMS (Dec 2006),

estimates of additional unlicensed extractions and estimates of unlicensed farm dams.

Unless specified otherwise, Hydro Tasmania dams and diversions are not included.

WIMS (Dec 2006): The Department Primary Industries and Water, Water Information

Management System, updated to December 2006.


54

APPENDIX A

Accounting for the Mersey Hydro Scheme in the Model

Lake Mackenzie

Lake Mackenzie and the Fisher Power station were deemed to have commenced

operation in January 1973. The dam diverts the Fisher River through a canal and then

through Fisher Power Station, discharging into Lake Parangana. Fisher Canal picks up

a small (but unknown) fraction of runoff from SC20, aided by a number of artificial

diversions. The only flows into Fisher River below the dam are from spill events and

from pickup within subarea 20 (less any pickup diverted into Fisher Canal). Mean daily

spill was calculated by month from the Lake Mackenzie Dam record (TSM

629.1/130.00/10) on the Hydro Tasmania data base (Table A-1). When the model is

running either scenario 2 or 3 (i.e., not the natural flow scenario), the model uses these

mean monthly spills as inflow to subarea 20 from January 1973 onward. A good flow

record for Fisher Canal below Lake Mackenzie (TSM 630.1/100.00/1) was available

from the Hydro Tasmania database. Daily Mean flows were calculated by month for

the period 01/04/1997 – 01/07/2007. In the model these mean flows were fed directly

into Lake Parangana (SC2) when running either scenario 2 or 3. This is likely to

understate flow through Fisher Power Station as it neglects the small amount of pickup

flowing into Fisher canal from SC20, but this was considered preferable to using the

less reliable Fisher power station record. Conversely, the model directs pickup that

would flow into Fisher Canal into Fisher River. This means that modelled flows into the

Fisher River are likely to be slightly greater than observed flows. As the pickup diverted

into Fisher Canal is small relative to the pickup from the remainder of the subarea,

modelled flows are not likely to exceed actual flows greatly (notwithstanding the

accuracy of the model calibration). When run in scenario 1 (natural flow), the model

does not account for the existence of Lake Mackenzie or any other artificial diversions.


55

Table A-1 Hydro Tasmania Sites used for long term mean model inputs (ML/day)

Hydro Infrastructure

accounted for in model

Fisher Canal/ Powerstation

Lake Mackenzie Lake Rowallan Lake Parangana

Commencement date in model

Jan 1973 Jan 1973 June 1967 April 1969

Site Record FISHER CANAL

[B/L L.MACKENZIE]

LAKE MACKENZIE [AT DAM]

MERSEY RIVER [A/B ARM]

MERSEY RIVER [AT LIENA]

Data Source TSM

(630.1/100.00/1) TSM

(629.1/130.00/10) TSM

(153.1/100.00/1) TSM(60.1/100.00/1)

Period 01/04/1997 to

01/04/2007 01/04/1997 to 01/04/2007

01/04/1997 to 01/04/2007

01/04/2002 to 01/04/2007

Subarea No. Affected

SC2 SC20 SC2

SC8

Site record Area scaled model input

January 124.6 0.0 779.3 182.5 155.7

February 110.9 0.0 777.6 169.8 139.0

March 59.6 0.0 493.9 119.4 107.6

April 84.4 0.0 723.7 148.2 131.1

May 251.2 64.4 927.7 185.0 136.2

June 353.2 57.1 1338.5 265.0 162.1

July 473.6 95.1 1828.8 1246.2 1061.9

August 435.8 122.1 1658.3 1086.2 916.5

September 493.8 207.8 2045.6 1810.9 1635.2

October 467.5 84.9 2034.6 603.8 487.5

November 340.7 12.0 1637.5 250.9 180.4

December 187.3 12.4 1004.0 170.5 130.3

Lake Rowallan

Lake Rowallan was deemed to commence in June 1967. A good flow record is

available from Mersey above Arm (TSM 153.1/100.00/1). Mean Daily flows were

calculated for each month from the period 01/04/1997 – 01/04/2007 (Table A-1). The

model uses these means as inflows into SC2 from June 1967 onward when the model

is run under scenario 2 or 3.

Lake Parangana

Lake Parangana dam and diversion were deemed to have commenced in April 1969.

Mean daily inflows into the subarea downstream of Lake Parangana were calculated

for each month over the period 01/04/2002 – 01/04/2007 from the Mersey at Liena

(TSM 60.1/100.00/1) flow record on the Hydro Tasmania data base. The period 2002-

2007 was chosen for Parangana, as mandatory environmental flows have been

released downstream since 2002. Before 2002 the Mersey only spilled over


56

Parangana dam during large flood events. As environmental flows from Lake

Parangana are mandated for the foreseeable future, the shorter record better reflects

future flows into the Mersey from Parangana, despite its brevity. Mersey at Liena flows

into SC22, rather than the subarea immediately downstream of Lake Parangana (SC8).

Thus the pickup from SC8 had to be accounted for. The mean daily pickup was

calculated by month for the period 01/04/2002 – 01/04/2007 and these values were

subtracted from the inflows calculated from the Mersey at Liena record (Table A-1).

The adjusted inflows were then used as inputs into SC8 when the model is run under

scenario 2 or 3.


57

APPENDIX B

This appendix investigates the reliability of Tascatch catchment models in predicting

river flow throughout these catchments. One of the difficulties in assessing model

reliability is the lack of observed data: there is often only one reliable gauging site

within the catchment. Five Tascatch catchment models developed for catchments that

have more than one gauging site were selected and investigated with the results

presented in Table B-2. The analysis undertaken is outlined below.

• The relationship between catchment area of the calibration site (primary site)

and the secondary site was determined. Good variability is represented within

this selection, with the secondary site catchment area ranging between 6.6%

and 41.5% of the calibration site.

• The catchment area relationship was used to derive a time series at the

secondary site based on scaled observed data from the calibration site. This

was used in subsequent analysis to assess the suggestion that an area scaled

time series derived from a primary site was a good representation of sub-

catchment flow in the absence of a secondary gauging site.

• For concurrent periods, estimated monthly volumes (ML) were extracted at both

the calibration site and the secondary site.

• R2 values were calculated on the following data sets for concurrent periods:

o Correlation A: The correlation between the calibration site observed

data and calibration site modelled data. This provides a baseline value

at the calibration site for comparison against the other correlations.

o Correlation B: The correlation between the calibration site observed

data (which has been reduced by area) and secondary site observed

data. This shows the relationship of area scaled estimates as a

predictor of sub-catchment flows, in this case by comparison with a

secondary gauge.

o Correlation C: The correlation between the calibration site observed

data (which has been reduced by area) and secondary site modelled

data. This compares modelled data with an area scaled data set

derived from observed data. This has been done because in the

absence of a gauging site, observed data from another site is often


58

assumed as a good indication of flow within the sub-catchment

(Correlation B addresses this assumption). Where this assumption is

applied, this correlation provides a statistical comparison of the models

ability to predict comparable volumes to that of an area scaled estimate.

o Correlation D: The correlation between the secondary site observed

data and secondary site modelled data. This has been done to assess

how well the calibration undertaken at the primary site directly translates

to other subcatchments within the model.

The catchment model has been calibrated to provide a good fit for monthly and

seasonal volumes at the calibration site. Calibration sites are typically selected low

in the catchment to represent as much of the catchment as possible. Therefore the

calibration fit parameters on average are expected to translate well to other sub-

catchments. However, where subcatchments vary significantly in terrain or

vegetation or rainfall compared to the catchment average, errors are expected to be

greater. The analyses undertaken in this section appears to confirm that the

models perform acceptably and the conclusions drawn from these analyses are

summarised below:

1. Four of the five catchments studied showed fair to good R2 values between

observed and modelled data at the secondary site. (Correlation D).

2. The George secondary site was the worst performing in the study with a fair

R2 value of 0.83. It is expected that this is due to localised changes in

terrain, vegetation and/or rainfall. This is a known limitation of the model

and is therefore expected in some cases.

3. Scaling the calibration site observed data by area to derive a data set at

another location is not recommended. Area scaled data does not

consistently out perform the model at predicting flow/volumes within

catchment. It is demonstrated that the model does (in the majority of cases)

a good job of directly predicting the flow/volumes within catchment.

Time Series plots of the monthly volumes in Megalitres for the five catchments studied

in this section are shown in Figure B-1 to Figure B-4. These plots show that generally

the calibration fit at the primary site translates well as a direct model output at other

locations within the catchment, when modelling monthly volumes.


59

0

20000

40000

60000

80000

100000

120000

140000

1963 1964 1964 1965 1966 1967 1968

Mo

nth

ly V

olu

me (

ML

)

Observed - Forth a/b Lemonthyme Site 450

Site 450 - Modelled - with entitlements

Observed- Scaled Forth at Paloona Bdg - site 386

Figure B-1 Forth catchment – monthly volumes at secondary site.

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

1983 1984 1987 1989

Mo

nth

ly V

olu

me (

ML

)

Observed - Ransom Rv Site 2217

Site 2217 Modelled - with entitlements

Observed - Scaled George at WS site 2205

Figure B-2 George catchment – monthly volumes at secondary site.


60

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

1983 1984 1987 1989 1991 1993

Mo

nth

ly V

olu

me

(M

L)

Observed - Leven at Mayday Rd - Site 821


Observed- Scaled Leven at Bannons site 14207

Figure B-3 Leven catchment – monthly volumes at secondary site.

0

2000

4000

6000

8000

10000

12000

14000

16000

1983 1984 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994

Mo

nth

ly V

olu

me

(M

L)

Observed - Swan u/s Hardings F - Site 2219


Observed - Scaled Swan at Grange site 2200

Figure B-4 Swan catchment – monthly volumes at secondary site.


61

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

1985 1986 1987 1988 1988 1989 1990

Mo

nth

ly V

olu

me

(M

L)

Observed - Montagu at Togari - Site 14216


Observed- Scaled Monatgu at Montagu Rd Brg - Site 14200

Figure B-5 Montagu catchment – monthly volumes at secondary site.

Mers

ey R

iver

Surf

ace W

ate

r M

odel

Hydro

Tasm

ania

V

ers

ion N

o: 1.1

62

Tab

le B

-2

Tascatc

h M

od

els

’ p

erf

orm

an

ce a

t seco

nd

ary

sit

es

Catc

h-

men

t C

ali

bra

tio

n S

ite

Pri

mary

Sit

e

Seco

nd

ary

Sit

e

Co

rrela

tio

n A

C

orr

ela

tio

n B

C

orr

ela

tio

n C

C

orr

ela

tio

n D

Nam

e

Sit

e N

am

e

& N

o.

Su

b-

Catc

hm

en

t L

ocati

on

Catc

hm

en

t A

rea

Km

2

Co

ncu

rren

t d

ata

peri

od

s

use

d in

th

is

an

aly

sis

Sit

e N

am

e

& N

o.

Su

b-

Catc

hm

en

t L

ocati

on

Catc

hm

en

t A

rea

Km

2

Catc

hm

en

t are

a f

acto

r (c

om

pare

d

wit

h

calib

rati

on

sit

e)

Mo

nth

ly M

L

R2 V

alu

e

Cali

bra

tio

n s

ite

ob

serv

ed

vs

Cali

bra

tio

n s

ite

mo

delled

Mo

nth

ly M

L

R2

Valu

e

Seco

nd

ary

sit

e

ob

serv

ed

vs

Calib

rati

on

sit

e

ob

serv

ed

(s

cale

d)

Mo

nth

ly M

L

R2 V

alu

e

Cali

bra

tio

n s

ite

ob

serv

ed

(scale

d)

vs M

od

elled

Mo

nth

ly M

L

R2

Valu

e

Seco

nd

ary

sit

e o

bserv

ed

vs M

od

ell

ed

Fort

h

Fort

h a

t P

alo

ona

Bridge –

S

ite 3

86

SC

33

1079.6

01/0

1/1

963 t

o

01/0

3/1

969

Fort

h R

iver

above

Lem

onth

ym

e –

site 4

50

SC

31

310.2

0.2

873

0.9

7

0.9

5

0.9

5

0.9

7

Georg

e

Georg

e

Riv

er

at S

H

WS

– S

ite

2205

SC

2

397.9

01/0

3/1

983 t

o

01/1

0/1

990

Ransom

Rv

at S

weet

Hill

– S

ite

2217

SC

3

26.1

0.0

656

0.9

1

0.9

6

0.8

6

0.8

3

Leven

Leven a

t B

annons

Bridge –

S

ite14207

SC

4

496.4

01/0

4/1

983 t

o

01/0

9/1

994

Leven a

t M

ayday R

d

– s

ite 8

21

SC

6

37.5

0.0

755

0.9

3

0.8

7

0.8

8

0.9

2

Sw

an

Sw

an R

iver

at

Gra

nge –

S

ite 2

200

SC

20

465.9

01/0

7/1

983 t

o

01/1

0/1

996

Sw

an R

iver

u/s

H

ard

ings

Falls

– s

ite

2219

SC

4

35.6

0.0

764

0.9

2

0.9

5

0.8

2

0.8

5

Monta

gu

Monta

gu a

t M

onta

gu

Rd B

rdge –

S

ite 1

4200

SC

3

325.9

01/0

1/1

985 t

o

01/0

1/1

990

Monta

gu a

t T

ogari –

S

ite 1

4216

SC

2

135.4

0.4

155

0.9

8

0.9

8

0.9

5

0.9

4

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