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DPIW – SURFACE WATER MODELS

LEVEN & GAWLER CATCHMENT

Leven & Gawler Surface Water Model Hydro Tasmania Version No: 2.1

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 2007/08

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 Mark Willis Dr Fiona

Ling

Crispin

Smythe

April 2007 Final

2.0 Mark Willis Fiona Ling C. Smythe Sept 2007 Final

2.1 Mark Willis Fiona Ling C. Smythe July 2008 Final

Current Document Approval

PREPARED BY Mark Willis

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 is part of a series of reports which present the methodologies and results

from the development and calibration of surface water hydrological models for 26

catchments under both current and natural flow conditions. This report describes the

results of the hydrological model developed for the Leven and Gawler catchment.

A model was developed for the Leven and Gawler catchment that facilitates the

modelling of flow data for 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 from the scenario modelling allow the calculation of indices of hydrological

disturbance. These indices include:

• Index of Mean Annual Flow

• Index of Flow Duration Curve Difference

• Index of Seasonal Amplitude

• Index of Seasonal Periodicity

• Hydrological Disturbance Index

The indices were calculated using the formulas stated in the Natural Resource

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

Murray-Darling Basin (MDBC 08/04).

A user interface is also provided that allows the user to run the model under varying

catchment demand scenarios. It allows the user to add further extractions to catchments

and see what effect these additional extractions have on the available water in the

catchment of concern. The interface provides sub-catchment summary of flow statistics,

duration curves, hydrological indices and water entitlements data. For information on the

use of the user interface refer to the Operating Manual for the NAP Region Hydrological

Models (Hydro Tasmania 2004).


iii

CONTENTS

EXECUTIVE SUMMARY ii

1. INTRODUCTION 6

2. CATCHMENT CHARACTERISTICS 7

3. DATA COMPILATION 9

3.1 Climate data (Rainfall & Evaporation) 9

3.2 Advantages of using climate DRILL data 9

3.3 Transposition of climate DRILL data to local catchment 10

3.4 Comparison of Data Drill rainfall and site gauges 12

3.5 Streamflow data 14

3.6 Irrigation and water usage 14

3.7 Estimation of unlicensed dams 19

3.8 Environmental flows 20

4. MODEL DEVELOPMENT 22

4.1 Sub-catchment delination 22

4.2 Hydstra Model 22

4.2.1 Lake Isandula 24

4.3 AWBM Model 25

4.3.1 Channel Routing 27

4.4 Model Calibrations 28

4.4.1 Factors affecting the reliability of the model calibration. 39

4.4.2 Model Accuracy - Model Fit Statistics 40

4.4.3 Model accuracy across the catchment 44

4.5 Model results 46

4.5.1 Indices of hydrological disturbance 48

4.6 Flood frequency analysis 49

5. REFERENCES 52

5.1 Personal Communications 53

6. GLOSSARY 54

APPENDIX A 56


iv

LIST OF FIGURES

Figure 2-1 Sub-catchment boundaries 8

Figure 3-1 Climate Drill Site Locations 11

Figure 3-2 Rainfall and Data Drill Comparisons 13

Figure 3-3 WIMS Water Allocations 18

Figure 4-1 Hydstra Model Schematic 23

Figure 4-2 Australian Water Balance Model Schematic 27

Figure 4-3 Monthly Variation of CapAve Parameter 31

Figure 4-4 Daily time series comparison (ML/d) – Leven Rv. Good fit. 32

Figure 4-5 Daily time series comparison (ML/d) – Leven Rv. Fair fit. 33

Figure 4-6 Daily time series comparison (ML/d) – Leven Rv. Fair fit. 33

Figure 4-7 Daily time series comparison (ML/d) – Gawler Rv. Good fit. 34

Figure 4-8 Daily time series comparison (ML/d) – Gawler Rv. Fair fit. 34

Figure 4-9 Daily time series comparison (ML/d) – Gawler Rv. Fair fit. 35

Figure 4-10 Time Series of Monthly Volumes – Leven River 36

Figure 4-11 Time Series of Monthly Volumes – Gawler River 36

Figure 4-12 Long term average monthly, seasonal and annual comparison plot – Leven River

37

Figure 4-13 Long term average monthly, seasonal and annual comparison plot – Gawler River

38

Figure 4-14 Duration Curve – Daily flow percentage difference – Leven Rv 42

Figure 4-15 Duration Curve – Monthly volume percentage difference – Leven Rv 43

Figure 4-16 Duration Curve – Daily flow percentage difference – Gawler Rv 43

Figure 4-17 Duration Curve – Monthly volume percentage difference- Gawler Rv 44

Figure 4-18 Time Series of Monthly Volumes- Site 821 45

Figure 4-19 Time Series of Monthly Volumes- Site 14227 46

Figure 4-20 Daily Duration Curve – Leven River 47

Figure 4-21 Daily Duration Curve – Gawler River 47

Figure 4-22 Modelled and Observed Flood Frequency Plot - Leven River at Bannon’s Bridge

51

Figure 4-23 Modelled and Observed Flood Frequency Plot Gawler River at West Gawler51

Figure A-1 Forth catchment – monthly volumes at secondary site. 58

Figure A-2 George catchment – monthly volumes at secondary site. 58

Figure A-3 Leven catchment – monthly volumes at secondary site. 59

Figure A-4 Swan catchment – monthly volumes at secondary site. 59

Figure A-5 Montagu catchment – monthly volumes at secondary site. 60


v

LIST OF TABLES

Table 3.1 Data Drill Site Locations 12

Table 3.2 Assumed Surety of Unassigned Records 15

Table 3.3 Sub Catchment High and Low Priority Entitlements 16

Table 3.4 Average capacity for dams less than 20 ML by Neal et al (2002) 20

Table 3.5 Environmental Flows 21

Table 4.1 Boughton & Chiew, AWBM surface storage parameters 25

Table 4.2 Hydstra/TSM Modelling Parameter Bounds 28

Table 4.3 Adopted Calibration Parameters 31

Table 4.4 Long term average monthly, seasonal and annual comparisons – Leven

River 37

Table 4.5 Long term average monthly, seasonal and annual comparisons – Gawler

River 38

Table 4.6 Model Fit Statistics 41

Table 4.7 R2 Fit Description 41

Table 4.8 Hydrological Disturbance Indices 48

Table A-1 Model performance at secondary sites 61


6

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 required for the development and calibration of the hydrological model (Australian Water Balance Model, AWBM) for the Leven and Gawler catchment;

• To source over 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 catchment demand scenarios;

• Prepare a report summarising the methodology adopted, assumptions made, results of calibration and validation and description relating to the use of the developed hydrologic model and associated software.


7

2. CATCHMENT CHARACTERISTICS

The Leven and Gawler catchment is located in Northern Tasmania and discharges into

Bass Strait at the township of Ulverstone. The catchment boundary provided by DPIW

also includes five small streams that do not flow directly into the Leven or Gawler Rivers

but instead discharge directly into either the Leven estuary or Bass Strait. These

additional streams are known as Masons Creek, Buttons Creek, Skeleton Creek,

Mannings Creek1 and Library Creek 1. For the purpose of this project these have been

considered part of the Leven and Gawler catchment and the combined total area of this

catchment is 684.5 km2.

The headwaters of the catchment start on the slopes of the Black Bluff Range at an

elevation of 1300m. A large proportion of the upper catchment is unpopulated and land

use is a combination of forestry and natural vegetation. The lower part of the catchment

consists of a mixture of agriculture and small (life style) residential allotments. The

catchment includes a number of settlements, the larger ones being Ulverstone, Gunns

Plains, South Riana and North Motton.

Variability in the annual rainfall total across this catchment is significant, mainly due to

the changes in elevation and the varied exposure to the dominant westerly weather

pattern. The lower catchment around Ulverstone, has a typical annual rainfall of 975mm

but the upper catchment around Black Bluff Range has a typical annual rainfall of

1900mm.

Water usage in this catchment is also varied and in total there are 506 registered

(current) entitlements for water extraction on the Water Information Management System

(WIMS Dec 2006). Most of the extractions are concentrated in the lower sub-catchments

and mainly related to agriculture and town water supply. Lake Isandula on the West

Gawler River, which is used as a town water supply, is the largest entitlement. Many of

the upper catchments have few or no registered WIMS entitlements.

For modelling purposes, the Leven and Gawler catchment was divided into 28 sub areas.

The delineation of these areas and the assumed stream routing network is shown in

Figure 2-1.

1 Mannings Creek and Library Creek have been modelled as the one sub-catchment.


8

9

6

7

4

14

17

11

16

10

1

15

20

12

3

19

13

18

5

23

262

22

25

28

8

27

24

21

395000

395000

400000

400000

405000

405000

410000

410000

415000

415000

420000

420000

425000

425000

430000

430000

435000

435000

5395000

5395000

5400000

5400000

5405000

5405000

5410000

5410000

5415000

5415000

5420000

5420000

5425000

5425000

5430000

5430000

5435000

5435000

5440000

5440000

5445000

5445000

5450000

5450000

Legend

Sub-catchment boundary

Stream routing network

0 3 6 9 121.5Kilometers

-

Figure 2-1 Sub-catchment boundaries


9

3. DATA COMPILATION

3.1 Climate data (Rainfall & Evaporation)

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

Resources & Mines (QDNRM).

The Department provides time series climate drill data from 0.05o x 0.05o (about 5 km x 5

km) interpolated gridded rainfall and evaporation data 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

This data has a number of benefits over other sources of rainfall data including:

• Continuous data back to 1889 (however, further back there are less 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) is also

included which can be used for the AWBM model. According to the QNRM 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, are available in the on-line NR&M climate archive.

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

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

measurements.

For the Leven and Gawler catchment the evaporation data was examined and it was


10

found that prior to 1970 the evaporation information is based on the long term daily

averages of the post 1970 data. In the absence of any reliable long term site data this is

considered to be the best available evaporation data set for this catchment.

3.3 Transposition of climate DRILL data to local catchment

Ten climate Data Drill sites were selected to give good coverage of the Leven and

Gawler catchments. Two sites were at the same location as data used for the Claytons

catchment model.

See Figure 3-1 below for a map of the climate Data Drill sites and Table 3.1 for the

location information.


11

_̂

_̂

_̂

_̂ _̂

_̂ _̂

_̂ _̂

_̂

Clayton_07

Clayton_01

LevenGaw_08

LevenGaw_07LevenGaw_06

LevenGaw_05LevenGaw_04

LevenGaw_03

LevenGaw_02

LevenGaw_01

395000

395000

400000

400000

405000

405000

410000

410000

415000

415000

420000

420000

425000

425000

430000

430000

5395000

5395000

5400000

5400000

5405000

5405000

5410000

5410000

5415000

5415000

5420000

5420000

5425000

5425000

5430000

5430000

5435000

5435000

5440000

5440000

5445000

5445000

5450000

5450000

Legend

_̂ Rainfall & Evaporation sitesSub-catchment boundary

0 3 6 9 121.5Kilometers

-

Figure 3-1 Climate Drill site locations


12

Table 3.1 Data Drill site locations

Site Longitude Latitude

LevenGaw_01 146:03:00 -41:09:00

Clayton_01 146:09:00 -41:12:00

LevenGaw_02 146:03:00 -41:15:00

LevenGaw_03 145:57:00 -41:18:00

Clayton_07 146:06:00 -41:18:00

LevenGaw_04 145:54:00 -41:24:00

LevenGaw_05 146:03:00 -41:24:00

LevenGaw_06 145:51:00 -41:27:00

LevenGaw_07 146:00:00 -41:27:00

LevenGaw_08 145:48:00 -41:30:00

3.4 Comparison of Data Drill rainfall and site gauges

As rainfall data is a critical input to the modelling process it is important to have

confidence that the Data Drill long term generated time series does in fact reflect what is

being observed within the catchment. Rainfall sites in closest proximity to the Data Drill

locations were sourced and compared. The visual comparison and the R2 value indicate

that there appears to be good correlation between the two, which is to be expected as

the Data Drill information is derived from site data. The annual rainfall totals of selected

Data Drill sites and neighbouring sites for coincident periods are plotted in Figure 3-2.


13

0

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1910

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1948

Annaul Rainfall (mm)

Data Drill - Claytons_07 Central Castra - Site 1515R2 = 0.98

0

500

1000

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3000

1923

1926

1929

1932

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Data Drill - Leven_Gawler_05 Nietta South - Site 1567R2 = 0.98

0

200

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1969

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1990


Data Drill - Leven_Gawler_01 Penguin - Site 1671R2 = 1.00

Figure 3-2 Rainfall and Data Drill comparisons


14

3.5 Streamflow data

There were two historical streamflow gauge sites identified in the Leven and Gawler

catchment which were potentially suitable as calibration sites.

Site Name

Sub-

catchment

Location

Site No. Period of Record Easting Northing

Gawler River at West Gawler

SC3 14208 24/03/1965 to 01/01/1983

429100 5440800

Leven River at Bannons Bridge

SC4 14207 18/06/1963 to present 423700 5432800

This data was provided by DPIW as a text file in Mega litres per day and both sites were

used for calibration of the model. No significant review of this data has been undertaken

by Hydro Tasmania, as it assumed that DPIW has provided the best available data set.

However, brief investigations of the site rating histories contained on Hydro Tasmania’s

archives indicate the following:

• The Leven River at Bannon’s Bridge site appears to be based on a natural

control with at least 5 ratings covering the 44 years of record. The comments

associated with these ratings suggest that this is a reliable flow record site.

• Site 14208, Gawler at West Gawler, has only one rating covering the 18 years of

record. Comments such as “poor rating” and “natural control tidal” and the

closure of the site in 1983, suggest this may be a less reliable flow record site.

3.6 Irrigation and water usage

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

from DPIW and is sourced from the Water Information Management System (WIMS Dec

2006). The WIMS 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 contained a

significant number of sites which had a Surety of 0. DPIW staff advised that in these

cases the Surety should be determined by the extraction “Purpose” and assigned as

follows:


15

Table 3.2 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

Fire Fighting 1

Dust Proof 6

In total there were 2459.8 ML unassigned entitlements (surety = 0) identified for inclusion

in the surface water model, of which 1658.7 ML were assigned surety 1 and 802.1 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 by a Purpose name called “fish farm” or “Acquacult”.

There were no fish farms identified in this 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 and Entitlements), water will only be

available for Low Priority entitlements after environmental flow requirements have been

met.

Following communications with DPIW staff, allowances for extractions not yet included in

the WIMS (Dec 2006) were made. DPIW advised that in the Gawler catchment, an

additional 2659ML should be allowed. For the Leven Catchment it was advised that an

allowance based on the Gawler surety5/surety 6 ratio should be used and this was

calculated to be 3786 ML. These allowances were proportioned over the sub-

catchments based on existing WIMS entitlements. It was agreed that for the purpose of

this calculation, the large extractions relating to Lake Isandula should be excluded from


16

this apportionment and sub-catchments 26, 27and 2 deemed to lie within the Gawler

catchment.

Allowances for unlicensed dam extractions are covered in Section 3.7.

A summary table of total entitlement volumes on a monthly basis by sub-catchment is

provided below in Table 3.3 and in the Catchment User Interface. A map of the water

allocations in the catchment is shown in Figure 3-3.

Table 3.3 Sub Catchment high and low priority entitlements

Water Entitlements Summarised - Monthly Demand (ML) for each Subarea & Month

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

High Priority Entitlements

SC1 14.97 13.52 14.97 14.49 0.50 0.48 0.50 0.50 0.48 14.97 14.49 14.97 105

SC2 89.07 80.45 89.07 86.20 11.06 10.71 11.06 11.06 10.71 89.07 86.20 89.07 664

SC3 78.59 70.98 78.59 76.05 21.03 20.36 21.03 21.03 20.36 78.59 76.05 78.59 641

SC4 58.70 53.02 58.70 56.80 11.03 10.68 11.03 11.03 10.68 63.33 61.29 58.70 465

SC5 7.13 6.44 7.13 6.90 3.94 3.81 3.94 3.94 3.81 7.13 6.90 7.13 68

SC6 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC7 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC8 4.29 3.87 4.29 4.15 1.13 1.10 1.13 1.13 1.10 4.29 4.15 4.29 35

SC9 236.67 213.76 236.67 229.03 5.41 5.23 5.41 5.41 5.23 236.67 229.03 236.67 1,645

SC10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC11 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC12 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC14 1.80 1.63 1.80 1.75 0.00 0.00 0.00 0.00 0.00 1.80 1.75 1.80 12

SC15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC16 0.70 0.64 0.70 0.68 0.28 0.27 0.28 0.28 0.27 0.70 0.68 0.70 6

SC17 185.64 167.67 185.64 179.65 6.11 5.91 6.11 6.11 5.91 185.64 179.65 185.64 1,300

SC18 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC20 2.74 2.48 2.74 2.65 0.92 0.89 0.92 0.92 0.89 2.74 2.65 2.74 23

SC21 178.83 161.52 178.83 173.06 174.52 168.89 174.52 174.52 168.89 178.83 173.06 178.83 2,084

SC22 32.07 28.96 32.07 31.03 2.57 2.48 2.57 2.57 2.48 32.07 31.03 32.07 232

SC23 23.06 20.83 23.06 22.32 9.65 9.34 9.65 9.65 9.34 23.06 22.32 23.06 205

SC24 17.59 15.88 17.59 17.02 4.63 4.48 4.63 4.63 4.48 17.59 17.02 17.59 143

SC25 14.52 13.11 14.52 14.05 2.60 2.52 2.60 2.60 2.52 14.52 14.05 14.52 112

SC26 120.81 109.12 120.81 116.91 15.84 15.33 15.84 15.84 15.33 120.81 116.91 120.81 904

SC27 39.72 35.88 39.72 38.44 3.13 3.03 3.13 3.13 3.03 39.72 38.44 39.72 287

SC28 74.78 67.54 74.78 72.36 15.97 15.45 15.97 15.97 15.45 74.78 72.36 74.78 590

Total 1,182 1,067 1,182 1,144 290 281 290 290 281 1,186 1,148 1,182 9,523

Low Priority Entitlements

SC1 14.90 13.45 14.90 14.41 5.54 5.36 5.54 5.54 5.36 5.54 15.31 14.90 121

SC2 5.85 5.28 5.85 5.66 81.61 83.04 85.81 85.81 83.04 85.81 77.74 5.85 611

SC3 26.24 23.70 26.24 25.39 33.77 32.68 33.77 33.77 32.68 33.77 28.68 26.24 357

SC4 42.17 38.09 42.13 38.86 25.00 24.19 25.00 25.00 24.19 25.00 27.88 40.35 378

SC5 0.00 0.00 0.00 0.00 3.40 3.29 3.40 3.40 3.29 3.40 3.29 0.00 24

SC6 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -


17

SC7 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC8 0.00 0.00 0.00 0.00 4.39 4.25 4.39 4.39 4.25 4.39 4.25 0.00 30

SC9 378.91 342.24 375.28 356.80 6.06 5.86 6.06 6.06 5.86 6.06 20.78 372.65 1,883

SC10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC11 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC12 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC14 0.85 4.77 5.28 4.09 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 15

SC15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC16 0.00 0.00 0.00 0.00 0.65 0.63 0.65 0.65 0.63 0.65 0.63 0.00 5

SC17 230.62 208.30 230.62 223.18 48.25 46.69 48.25 48.25 46.69 48.25 84.81 230.53 1,494

SC18 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC20 1.39 1.25 1.39 1.34 0.87 0.84 0.87 0.87 0.84 0.87 0.84 1.39 13

SC21 54.36 49.10 54.36 52.60 59.93 57.99 59.93 59.93 57.99 59.93 57.03 54.36 678

SC22 2.66 2.40 2.66 2.57 35.38 34.24 35.38 35.38 34.24 35.38 28.45 2.66 251

SC23 0.00 0.00 0.00 0.00 5.00 4.84 5.00 5.00 4.84 5.00 4.84 0.00 35

SC24 0.00 0.00 0.00 0.00 10.95 10.60 10.95 10.95 10.60 10.95 10.60 0.00 76

SC25 1.06 0.96 1.06 1.03 15.04 14.55 15.04 15.04 14.55 15.04 10.48 1.06 105

SC26 46.36 42.12 46.63 45.13 88.91 86.04 88.91 88.91 86.04 89.45 82.70 46.30 838

SC27 12.19 11.01 12.19 11.80 36.84 35.65 36.84 36.84 35.65 36.84 35.65 12.19 314

SC28 8.31 7.51 8.31 8.05 43.40 42.00 43.40 43.40 42.00 43.40 37.37 8.31 335

Total 826 750 827 791 505 493 509 509 493 510 531 817 7,560

All Entitlements

SC1 29.87 26.98 29.87 28.90 6.04 5.85 6.04 6.04 5.85 20.51 29.79 29.87 226

SC2 94.92 85.74 94.92 91.86 92.67 93.75 96.87 96.87 93.75 174.88 163.94 94.92 1,275

SC3 104.82 94.68 104.82 101.44 54.80 53.03 54.80 54.80 53.03 112.35 104.73 104.82 998

SC4 100.86 91.10 100.83 95.66 36.03 34.87 36.03 36.03 34.87 88.33 89.17 99.05 843

SC5 7.13 6.44 7.13 6.90 7.34 7.11 7.34 7.34 7.11 10.54 10.20 7.13 92

SC6 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC7 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC8 4.29 3.87 4.29 4.15 5.52 5.35 5.52 5.52 5.35 8.68 8.40 4.29 65

SC9 615.58 556.01 611.95 585.83 11.46 11.09 11.46 11.46 11.09 242.72 249.81 609.32 3,528

SC10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC11 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC12 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC14 2.66 6.40 7.09 5.84 0.00 0.00 0.00 0.00 0.00 1.80 1.75 1.80 27

SC15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC16 0.70 0.64 0.70 0.68 0.93 0.90 0.93 0.93 0.90 1.36 1.31 0.70 11

SC17 416.26 375.98 416.26 402.83 54.35 52.60 54.35 54.35 52.60 233.89 264.46 416.17 2,794

SC18 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

SC20 4.13 3.73 4.13 4.00 1.79 1.73 1.79 1.79 1.73 3.61 3.50 4.13 36

SC21 233.19 210.62 233.19 225.66 234.45 226.89 234.45 234.45 226.89 238.76 230.09 233.19 2,762

SC22 34.73 31.37 34.73 33.61 37.95 36.72 37.95 37.95 36.72 67.45 59.48 34.73 483

SC23 23.06 20.83 23.06 22.32 14.64 14.17 14.64 14.64 14.17 28.06 27.16 23.06 240

SC24 17.59 15.88 17.59 17.02 15.58 15.08 15.58 15.58 15.08 28.54 27.62 17.59 219

SC25 15.58 14.07 15.58 15.08 17.64 17.07 17.64 17.64 17.07 29.56 24.53 15.58 217

SC26 167.17 151.24 167.44 162.04 104.75 101.37 104.75 104.75 101.37 210.26 199.61 167.11 1,742

SC27 51.91 46.88 51.91 50.23 39.97 38.68 39.97 39.97 38.68 76.56 74.09 51.91 601

SC28 83.09 75.05 83.09 80.41 59.37 57.45 59.37 59.37 57.45 118.17 109.73 83.09 926

Total 2,008 1,818 2,009 1,934 795 774 799 799 774 1,696 1,679 1,998 17,084


18

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!( Water Allocations

0 2.5 5 7.5 101.25Kilometers

-

Figure 3-3 WIMS Water allocations


19

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 storages (prior to 2000 it was 2.5 ML),

and only used 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 photographs and the methodology adopted follows:

• Aerial photographs were analysed. GoogleEarth was selected as the

source for the aerial photographs because in this case the majority of the

catchment was covered by high resolution photography. The GoogleEarth

photos covering this catchment were based on 2003 to 2006. The number

of dams of any size in six selected sub-catchments were counted by eye.

Based on these numbers and the DPIW entitlements data a ratio of

unlicensed to licensed dams was calculated for each sub-catchment. The

results were, 0.23, 1.25, 0.33, 0.32, 0.45 and 0.33 unlicensed dams per

licensed dam, with an average of 0.49. This compares favourably with the

Panatana catchment which had an average of 0.41.

• Using the average ratio of 0.49 unlicensed dams per licensed dam an

estimate of the number of unlicensed dams in the uncounted sub-

catchments was determined. In total it is estimated that there are 163

unlicensed dams throughout 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. Some of these were visible on the aerial photographs.

• 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 3.4).

• Following discussions with DPIW staff, 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.

• Assuming this dam size distribution is similar to the distribution of the study

catchment in South Australia, then the total volume of unlicensed dams can

be estimated as 228 ML (163 * 1.4ML). This equates to 0.33 ML of

unlicensed dams/km2, however large portions of the catchment are


20

undeveloped and accordingly this value varies significantly from one sub-

catchment to another. The total volume of existing permitted dams

extractions in the study catchment is 4988 ML. Therefore the 228 ML of

unlicensed dams equates to approximately 4% of the total dam extractions

from the catchment.

Table 3.4 Average capacity for dams less than 20 ML by 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

3.8 Environmental flows

One of the modelling scenarios (Scenario 3) was to account for environmental flows

within the catchment. DPIW advised, that for the Leven and Gawler catchment, they

currently do not have environmental flow requirements defined. In the absence of this

information it was agreed that the calibrated catchment model would be run in the

Modelled – No entitlements (Natural) scenario and the environmental flow would be

assumed to be:

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

31st Oct).

• The 30th percentile 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 environmental flows on a monthly breakdown by sub-catchment

is provided below in Table 3.3 and in the Catchment User Interface.


21

Table 3.5 Environmental Flows

Sub-catchment Area (km2)

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

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

SC1 18.9 213.5 122.1 129.5 333.3 594.5 1161.2 1492.1 1486.2 1305.3 815.7 707.2 427.5 732.3

SC2 9.1 0.3 0.3 0.3 0.7 1.0 2.1 6.7 8.6 7.6 3.3 1.8 0.8 2.8

SC3 12.9 6.2 4.7 5.4 9.9 15.0 39.9 96.5 125.6 100.0 56.7 34.4 15.9 42.5

SC4 30.6 202.6 115.1 127.8 331.1 595.6 1146.1 1449.1 1390.9 1264.9 790.7 668.8 418.0 708.4

SC5 10.5 2.4 2.1 2.3 3.9 5.3 17.1 42.8 51.8 41.0 24.7 13.4 6.1 17.8

SC6 37.5 25.7 13.7 16.4 53.1 79.8 126.4 139.7 139.6 127.1 87.0 74.7 54.3 78.1

SC7 32.5 15.4 8.4 8.4 28.6 53.2 95.9 108.0 106.2 95.6 65.1 54.3 35.2 56.2

SC8 6.1 2.1 1.8 2.0 3.5 4.7 14.5 37.0 45.2 34.3 21.7 11.8 5.3 15.3

SC9 52.4 192.5 107.8 126.6 327.8 594.7 1096.5 1348.5 1284.0 1148.4 742.9 607.8 404.0 665.1

SC10 38.6 103.6 59.9 61.6 199.1 338.6 580.5 636.7 641.1 593.9 398.3 335.0 227.4 348.0

SC11 38.7 11.3 6.3 5.9 11.9 29.4 77.8 103.5 104.9 91.2 59.6 44.3 23.9 47.5

SC12 29.0 33.4 18.2 20.0 66.6 106.7 180.4 193.4 191.2 177.9 120.2 103.4 71.3 106.9

SC13 25.1 12.1 6.5 7.3 20.8 37.6 66.0 87.7 86.7 69.9 46.0 37.2 25.7 41.9

SC14 46.7 160.7 94.6 104.3 293.1 489.6 902.3 1088.5 1031.4 904.6 607.4 491.8 334.6 541.9

SC15 36.5 129.2 73.4 76.1 232.8 411.1 765.7 873.1 877.9 763.2 516.9 423.7 278.1 451.8

SC16 39.7 185.8 103.6 122.7 323.7 563.4 1031.2 1256.4 1173.4 1056.6 700.6 567.4 384.8 622.5

SC17 42.5 196.5 112.0 127.1 329.8 595.3 1126.6 1392.5 1375.2 1216.5 781.7 641.8 412.7 692.3

SC18 21.4 39.6 21.1 24.8 79.5 121.5 200.1 218.4 213.6 200.3 135.3 116.0 82.8 121.1

SC19 25.1 17.4 9.2 11.1 36.0 53.6 84.9 93.8 93.9 85.2 58.5 50.2 36.7 52.5

SC20 32.5 209.0 119.9 128.6 332.4 595.8 1165.9 1492.5 1436.3 1296.6 801.6 693.4 422.6 724.6

SC21 2.8 2.6 2.2 2.4 4.2 5.8 18.0 45.6 55.9 44.1 26.3 14.6 6.8 19.0

SC22 15.3 5.7 4.4 4.9 8.7 13.0 37.0 92.5 116.2 92.1 50.7 31.1 14.3 39.2

SC23 19.4 1.6 1.3 1.6 2.7 3.6 12.0 31.1 34.7 27.6 17.3 8.7 4.2 12.2

SC24 5.9 0.5 0.4 0.5 0.8 1.1 3.3 9.1 10.2 8.1 5.0 2.6 1.2 3.6

SC25 14.4 1.2 1.0 1.2 2.0 2.7 8.5 22.9 25.7 20.8 12.9 6.4 3.2 9.0

SC26 19.1 0.6 0.7 0.6 1.4 2.0 3.8 12.3 16.2 14.1 5.6 3.4 1.6 5.2

SC27 7.1 0.2 0.2 0.2 0.5 0.8 1.4 4.5 6.1 5.3 2.1 1.3 0.6 1.9

SC28 14.0 0.9 0.5 0.5 0.9 1.5 3.7 7.9 11.3 9.6 4.5 3.3 1.6 3.9


22

4. MODEL DEVELOPMENT

4.1 Sub-catchment delineation

Sub-catchment 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 sub-catchment

boundaries, generalises geophysical parameters and provides in-depth analysis tools to

examine and compare the hydrologic properties of sub-catchments. The model also

includes a flexible result export macro language to allow users to fully couple

CatchmentSIM with any hydrologic modelling package that is based on sub-catchment

networks.

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

break it up into numerous sub-catchments, determine their areas and provide routing

lengths between them.

These outputs were manually checked to ensure they accurately represented the

catchment. If any minor modifications were required these were made manually to the

resulting 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 sub-

catchments, 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-catchment, through the catchment via a channel

routing function.

The rainfall and evaporation is calculated for each subcatchment 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 sub-

catchment. A quadrant system is drawn, centred on the centroid. A weight for the

closest gauge in each quadrant is computed as the inverse, squared, 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.


23

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

catchment separately. This was chosen over the usual method of a single AWBM model

for the whole catchment as it more accurately distributes the runoff and base flow

spatially over the catchment.

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

routing function.

Figure 4-1 Hydstra Model schematic

As previously mentioned this model includes 4 separate sub-catchments which flow

directly into Bass Strait and therefore are not direct tributaries to the Leven or Gawler

Rivers.


24

4.2.1 Lake Isandula

A significant lake known as Lake Isandula was identified during the creation of the

Gawler catchment model and is located in sub-catchment 21. This dam is owned by

Cradle Coast Water Authority and has an influence on the flow regime in the Gawler

River. No information relating to historic lake discharges was identified. In the absence

of observed lake discharge data, discussions with DPIW staff on the appropriate way to

model this lake resulted in the following decisions:

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

with no dam or lake present for all of record.

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

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

Env Flows’)” scenarios will model the catchment with:

o No dam or lake present in the model prior to and during its construction in

1966.

o From 1967 onwards, the lake will be modelled using a basic volume

balance rule assuming the following:

� Lake volume will be 400 ML (from DPIW dams database) and at

full supply level at start of model.

� Water entitlements falling within the Lake Isandula sub-catchment

(SC21) will be extracted from the lake volume.

� Inflows in excess of the lake volume will be discharged

downstream as spill.

� If the Environmental Flows & Entitlements scenario is selected

then a flow will be released downstream equal to the

environmental flow specified in the user interface, for the Lake

Isandula sub-catchment (SC 21). However when the modelled

inflow to SC21 is less than the specified environmental flow, the

downstream release will be reduced to equal SC21 inflow. This

has been done to stop excessive draw down of the lake in periods

of low inflow.


25

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 actual 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,

2003), which reduces the three partial areas and three surface storage capacities to

relationships based on an average surface storage capacity.

Boughton & Chiew (2003) have shown 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 (Ave), the three partial areas and the

three surface storage capacities are found by;

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=(0.66*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 subcatchment. Base-flow is


26

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.

Whilst the AWBM methodology incorporates an account of base-flow, it is not intended

that the baseflow prediction from the AWBM model be adopted as an accurate estimate

of the baseflow contribution. The base flow in the AWBM routine is based on a simple

model and does not specifically account for attributes that affect baseflow such as

geology and inter-catchment ground water transfers. During the model calibration the

baseflow infiltration and recession parameters are used to ensure a reasonable fit with

the observed surface water information.

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


27

Figure 4-2 Australian Water Balance Model schematic

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:

α


28

and

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. eg. α.fl where fl is a length factor.

Parameters required by Hydstra/TSM Modelling and their legal bounds are:

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 Calibrations

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

best replicates the record at the two sites selected for calibration (for information on

these sites, refer to Section 3.5). The best fit of parameters was achieved by comparing

the monthly, seasonal and annual volumes over the entire calibration period, using

regression statistics and using practitioner judgment when observing daily and monthly

time series comparisons. It should be noted that during the calibration process matching

of average long term monthly volumes (flows) was given the highest priority and

matching of peak flood events and daily flows was given lower priority. Further

discussion of the model calibration fit is given in Section 4.4.2

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

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

MCF = MNEM - (WE x TPRF)

Where:


29

MCF = Modelled Calibration Flow

MNEM = Modelled - No Entitlements (Modified). *

WE = Water Entitlements

TPRF = Time Period Reduction Factor

* Refer to Glossary for additional explanation of these terms

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

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

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

(1996). This states that water demand has increased by an average of 6% annually over

the last 4 decades. 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.

In the Leven catchment, data from the period 01/01/1987 to 01/09/2006 was selected at

Leven at Bannon’s Bridge (site 14207) for calibration. A water entitlements reduction

factor of 56% was applied to all extractions as the mid year of this period was deemed to

be 1996.

In the Gawler catchment, data from the period 25/03/1965 to 01/01/1983 was selected at

Gawler at West Gawler (site 14208) for calibration. A water entitlements reduction factor

of 50% was applied to all extractions as the mid year of this period was deemed to be

1973.

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 extractions 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 and Table

4.5 show the monthly water entitlements (demand) used in the calibration upstream of


30

the calibration sites.

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

acknowledged 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 these

calibration parameters has not changed significantly over time and therefore it is

appropriate to apply these parameters to all three scenarios.

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

CapAve has been made variable and assigned a seasonal profile as shown in Figure

4-3. Two sets of CapAve profiles were applied across the catchment to achieve an

optimum volume balance at both calibration locations. The adopted name and extent of

each CapAve parameter is itemised below.

• CapAve: All of the Leven River and individual (separate) streams included in

subcatchment 28

• CapAve_G: All of the Gawler River and individual (separate) streams included in

subcatchments 26, 27 and 2.

It was found that the calibration fit parameters derived for the Leven catchment generally

translated well to the Gawler catchment. However, to achieve the best fit at both

calibration locations, it was also necessary to vary the calibration parameter K1 between

catchments. The adopted name of K1 and the specific location assignment is itemised

below.

• K1: All of the Leven River catchment and individual (separate) streams

included in sub-catchment 28.

• K1_G: All of the Gawler River and individual (separate) streams included in

sub-catchments 26, 27 and 2.


31

Table 4.3 Adopted Calibration Parameters

PARAMETER Leven VALUE

PARAMETER Gawler VALUE

INFBase 0.75 INFBase 0.75

K1 0.97 K1_G 0.95

K2 0.98 K2 0.98

GWstoreSat 70 GWstoreSat 70

GWstoreMax 100 GWstoreMax 100

H_GW 90 H_GW 90

EvapScaleF 1 EvapScaleF 1

Alpha 3 Alpha 3

n 0.8 n 0.8

CapAve Variable CapAve_G Variable

0

50

100

150

200

250

1 2 3 4 5 6 7 8 9 10 11 12Month

CapeAve

Gawler CapAve

Leven CapAve

Figure 4-3 Monthly Variation of CapAve Parameter

Results of the calibration are shown in the plots and tables that follow in this section. In

all comparisons the “Modelled Calibration Flow” (refer to previous description) has

been compared against the observed flow at the calibration location.

Daily time series plots of three discrete calendar years (Figure 4-4 to Figure 4-9) have

been displayed for the calibration location, showing a range of relatively low to high

inflow years and a range of calibration fits. The general fit for each annual plot is

described in the caption text. This indication is a visual judgement of the relative model

performance for that given year compared to the entire observed record. There is also

a goodness of fit statistic (R2) shown on each plot to assist in the judgement of the

model performance.


32

The catchment average precipitation as input to the model is also displayed to provide

a representation of the relative size of precipitation events through the year. Note that

the precipitation trace is plotted on an offset, secondary scale. Overall the daily time

series plots show a good to fair response to rainfall events and a good to fair

agreement with hydrograph shape. The water entitlements for both calibration

locations are relatively small and for the Leven River, for plotting purposes, the water

entitlements have been multiplied by a factor of 10.

The monthly time series, over the whole period of observed record, are plotted in

Figure 4-10 to Figure 4-11 and overall shows a good comparison between modelled

and observed totals for both calibration locations.

The monthly, seasonal and annual volume balances for the whole period of calibration

record are presented in Figure 4-12 to Figure 4-13 and Table 4.4 to Table 4.5. The

demand values shown represent the adopted total water entitlements upstream of the

gauging site. It has been included to provide a general indication of the relative

amount of water being extracted from the river.

0

2000

4000

6000

8000

10000

12000

14000

16000

01/1994 03/1994 05/1994 07/1994 09/1994 11/1994 01/1995

-100

-80

-60

-40

-20

0

20

40

60Precipitation Modelled Calibration Flow Observed

R2 = 0.82

Figure 4-4 Daily time series comparison (ML/d) – Leven Rv. Good fit.


33

0

5000

10000

15000

20000

25000

01/2000 03/2000 05/2000 07/2000 09/2000 11/2000 01/2001

-100

-80

-60

-40

-20

0

20

40


R2 = 0.66

Figure 4-5 Daily time series comparison (ML/d) – Leven Rv. Fair fit.

0

2000

4000

6000

8000

10000

12000

14000

01/1996 03/1996 05/1996 07/1996 09/1996 11/1996 01/1997

-100

-80

-60

-40

-20

0

20

40


R2 = 0.69

Figure 4-6 Daily time series comparison (ML/d) – Leven Rv. Fair fit.


34

0

200

400

600

800

1000

1200

1400

1600

1800

01/1968 03/1968 05/1968 07/1968 09/1968 11/1968 01/1969

-100

-80

-60

-40

-20

0

20

40


R2 = 0.85

Figure 4-7 Daily time series comparison (ML/d) – Gawler Rv. Good fit.

0

500

1000

1500

2000

2500

01/1975 03/1975 05/1975 07/1975 09/1975 11/1975 01/1976

-100

-80

-60

-40

-20

0

20

40


R2 = 0.66

Figure 4-8 Daily time series comparison (ML/d) – Gawler Rv. Fair fit.


35

0

200

400

600

800

1000

1200

01/1971 03/1971 05/1971 07/1971 09/1971 11/1971 01/1972

-100

-80

-60

-40

-20

0

20

40


R2 = 0.77

Figure 4-9 Daily time series comparison (ML/d) – Gawler Rv. Fair fit.


36

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Monthly Volume (ML)

Observed - Leven River - site 14207 Modelled Calibration Flow

R2 = 0.95

Figure 4-10 Time Series of Monthly Volumes – Leven River

0

5000

10000

15000

20000

1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982

Monthly Volume (ML)

Observed - Gawler at WG - site 14208Modelled Calibration Flow R

2 = 0.92

Figure 4-11 Time Series of Monthly Volumes – Gawler River


37

0

500

1000

1500

2000

2500

3000

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

WINTER

SUMMER

ANNUAL

Average Flow (ML/Day)

Observed

Modelled Calibration Flow

Modelled -

Modelled No Entitlements (Natural)Demand x10

Figure 4-12 Long term average monthly, seasonal and annual comparison plot –

Leven River

MONTH Observed

Modelled Calibration

Flow

Scenario 1 Modelled –No Entitlements (Natural) Demand

2

Jan 430.93 434.53 455.02 20.52

Feb 301.71 301.68 322.24 20.60

Mar 278.91 288.58 309.09 20.54

Apr 601.19 605.58 626.03 20.36

May 1053.03 1064.16 1066.29 1.86

Jun 1861.99 1894.49 1896.35 1.86

Jul 2486.62 2477.47 2479.33 1.86

Aug 2569.81 2569.05 2570.91 1.86

Sep 2188.37 2182.69 2184.54 1.86

Oct 1540.84 1528.46 1538.63 10.26

Nov 1032.81 1004.18 1015.48 11.32

Dec 580.19 575.25 595.46 20.36

WINTER 1950.11 1952.72 1956.01 3.26

SUMMER 537.62 534.97 553.89 18.95

ANNUAL 1243.87 1243.84 1254.95 11.10

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

Table 4.4 Long term average monthly, seasonal and annual comparisons –

Leven River

2 The demand value includes all extraction potential upstream of calibration site with a 56% time period reduction factor

applied.


38

0

50

100

150

200

250

300

350

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

WINTER

SUMMER

ANNUAL

Average Flow (ML/Day)

Observed

Modelled Calibration Flow

Modelled No Entiltlements

(Natural)

Demand

Figure 4-13 Long term average monthly, seasonal and annual comparison plot –

Gawler River

Table 4.5 Long term average monthly, seasonal and annual comparisons –

Gawler River

MONTH Observed Modelled-Calibration

Flow

Scenario 1 Modelled –No Entitlements (Natural)

Demand 3

Jan 27.35 27.14 33.13 7.10

Feb 17.84 18.03 24.22 7.10

Mar 19.53 19.85 25.95 7.10

Apr 34.21 34.71 42.23 7.10

May 92.60 92.03 98.07 6.26

Jun 130.69 130.63 136.67 6.26

Jul 229.63 229.20 236.35 6.26

Aug 282.62 282.44 288.69 6.26

Sep 213.54 215.26 221.51 6.26

Oct 137.78 135.03 143.41 8.45

Nov 70.70 70.93 78.56 8.20

Dec 42.99 41.85 48.76 7.10

WINTER 181.14 180.76 187.45 6.62

SUMMER 35.43 35.42 42.14 7.29

ANNUAL 108.29 108.09 114.80 6.95

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

3 The demand value includes all extraction potential upstream of calibration site with a 50% time period reduction factor

applied.


39

4.4.1 Factors affecting the reliability of the model calibration.

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

factors which will limit the accuracy of the output. In preparation of this model the most

significant limitations identified that will affect the calibration accuracy are:

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

month. Historically the actual extraction from the river would be much more

variable than this and possess too many levels of complexity to be accurately

represented in a model.

2. The current quantity of water extracted from the catchment is unknown. Although

DPIW have provided water licence information (WIMS Dec 2006) and estimates of

extractions in excess of these licences, these may not represent the true quantity of

water extracted. No comprehensive continuous water use data is currently

available.

3. The quality of the observed flow data (ratings and water level readings) used in the

calibration may not be reliable for all periods. Even for sites where reliable data

and ratings has been established the actual flow may still be significantly different

to the observed (recorded) data, due to the inherent difficulties in recording

accurate height data and rating it to flow. These errors typically increase in periods

of low and high flows.

4. Misrepresentation of the catchment precipitation. 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 would still rely

considerably on the availability of measured rainfall information in the region. This

would also be the case with the evaporation data, which will have a smaller impact

on the calibration.

5. Catchment freezing and snowmelt in the upper catchment, during the winter

months, may affect the flow regime and this has not been specifically handled

within this model.

6. The daily average timestep of the model may smooth out rainfall temporal patterns

and have an effect on the peak flows. For example, intense rainfall events falling in

a few hours will be represented as a daily average rainfall, accordingly reducing the

peak flow.


40

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

individual sub-cathments. Effects due to vegetation and terrain are accounted for

on catchment average basis, using the global AWBM fit parameters. Therefore

individual sub-catchment run-off may not be accurately represented by the model’s

global fit parameters. To account for this a much more detailed and complex model

would be required.

8. The simple operating rules and assumptions used to model the catchment

modification (Lake Isandula) cannot capture the complexities of operation that

occur in reality

4.4.2 Model Accuracy - Model Fit Statistics

The following section is an additional assessment of how reliably the model predicts

flow at the calibration site.

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. In this case x and y

are observed flow and modelled calibration flow. So for the catchment model, R2

indicates how much the modelled calibration flow changes as observed flow changes.

Table 4.6 shows the R2 values between observed and modelled daily and monthly

flows, as well as the proportional difference (%) between the long-term observed and

modelled calibration flows.


41

Table 4.6 Model Fit Statistics

Measure of Fit Leven River at

Bannon’s Bridge

(Site 14207)

Gawler River at

West Gawler

(Site 14208)4

Daily coefficient of determination (R2 Value)

0.69 0.75

Monthly coefficient of determination (R2 Value)

0.95 0.92

Difference in observed and estimated long term annual average flow

+0.0% -0.2%

As previously mentioned the focus of the calibration process was to obtain a good

correlation between monthly long term volumes (and flows) and lesser priority was

given to daily correlations. However without a good simulation of daily flows, a good

simulation of monthly flows would be difficult to achieve. A target R2 of 0.70 (or

greater) was set for the daily flows and a target of R2 of 0.85 (or greater) was set for

monthly flows. It was deemed that these were acceptable targets considering the

model limitations and potential sources of error (refer to 4.4.1). A summary of

comparative qualitative and statistical fit descriptions are provided in the following

Table.

Table 4.7 R2 Fit Description

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 the R2 value is a good indicator of correlation fit it was

only used as a tool, to assist in visually fitting the hydrographs. One of the major

4 The calibration fit for the Gawler River will be influenced by the basic modelling of the operation of Lake Isandula

(refer to section 4.2).


42

limitations is that minor differences in the timing of hydrograph events can significantly

affect the R2 value, although in practice a good calibration has been achieved.

Another indicator on the reliability of the calibration fit is the proportional difference

between observed data and the modelled calibration flow (MCF), measured by percent

(%). The proportional difference for the daily flows and monthly volumes were

calculated and are presented in Figure 4-14 to Figure 4-17 in the form of a duration

curve. These graphs show the percentage of time that a value is less than a specified

bound. For example in Figure 4-14, 40% of the time the difference between the MCF

and observed flow is less than 23%. Similarly in Figure 4-15, for the All of Record

trace, 50% of the time the difference between the MCF monthly volume and observed

volume is less than 17%.

0

10

20

30

40

50

60

70

80

90

100

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

Percentage of time Difference is less than

Difference (%) - Observed vs Modelled

All record Winter Summer

Figure 4-14 Duration Curve – Daily flow percentage difference – Leven River


43

0

10

20

30

40

50

60

70

80

90

100

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




Figure 4-15 Duration Curve–Monthly volume percentage difference – Leven River

0

10

20

30

40

50

60

70

80

90

100

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




Figure 4-16 Duration Curve – Daily flow percentage difference – Gawler River


44

0

10

20

30

40

50

60

70

80

90

100

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




Figure 4-17 Duration Curve –Monthly volume percentage difference-Gawler River

Although these duration curves are an indicator of the reliability of the modelled data,

they also have their limitations and should be used in conjunction with a visual

assessment of the hydrograph fit in determining calibration reliability. One of the major

limitations is that in periods of low flow, the percentage difference between observed

and modelled can be large although the value is not significant. For example, a

1ML/day difference, would show as a 200% difference if the observed flow was 0.5

ML/day. The duration curve graphs shows three traces, the Summer5, the Winter6 and

All of Record. The higher values, caused by the larger proportion of low flows, can be

clearly seen in the Summer trace.

4.4.3 Model accuracy across the catchment

The model has been calibrated to provide a good simulation 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. How the reliability of

this calibration translates to other specific locations within the catchment is difficult to

5 Summer period = Nov to April.

6 Winter period = May to Oct.


45

accurately assess, however on average it would be expected that the model calibration

would translate well to other locations within the catchment. The accuracy of the model

in predicting monthly volumes at other locations has been analysed for five river

catchments modelled as part of this project. The results of this assessment are

summarised in Appendix A. These analyses suggest that on average the models

predict volumes well across the catchment.

The fit of the hydrograph shape (daily flows) is expected to be more site specific and

therefore it is predicted that the calibration fit of these will deteriorate as the catchment

area decreases.

In the Leven and Gawler catchment there are two gauging sites which can be used to

assess the calibration fit at alternative locations. Plots of the monthly time series

volumes and the corresponding R2 values are shown in Figure 4-18 and Figure 4-19.

The results show that the correlation between modelled and observed volumes at

these two sites compares favourably with that of the calibration site. Comparison of

site 14227 gives a poorer fit during the winter periods (high flows), however a brief

check of associated flow ratings shows that there is only one high stage gauging and

multiple rating curves so the poorer fit may be due to poor high stage ratings at this

site.

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

1983 1984 1987 1989 1991 1993

Monthly Volume (ML)

Observed - Leven at Mayday Rd - Site 821SC6 Modelled - with entitlements extracted (Scenario 2)

R2 = 0.92

Figure 4-18 Time Series of Monthly Volumes- Site 821


46

0

1000

2000

3000

4000

5000

6000

06/1987 05/1988 05/1989 05/1990 06/1991 05/1992 05/1993 05/1994

Monthly Volume (ML)

Observed - West Gawler u/s Isandula Res - Site 14227

SC5 Modelled - with entitlements extracted (Scenario 2)

R2= 0.92

Figure 4-19 Time Series of Monthly Volumes- Site 14227

4.5 Model results

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

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 at any sub-catchment location.

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

NAP Region Hydrological Models (Hydro Tasmania 2004).

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

calibration sites are presented below and in the following section. The outputs are a

comparison of scenario 1 (No entitlements - Natural) and scenario 3 (environmental

flows and entitlements) for period 01/01/1900 to 01/01/2007. Results have been

produced at two locations:


47

• Site 14207- Leven Rivar at Bannon’s Bridge at sub-catchment 4.

• Site 14208- Gawler River at West Gawler at sub-catchment 3.

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

Flow (ML/d)

Scenario1 (Natural)

Entitlements Extracted

Figure 4-20 Daily Duration Curve – Leven River

0.10

1.00

10.00

100.00

1000.00

10000.00

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

Percent Of Time Exceeded

Flow (ML/d)

Scenario1 (Natural)

Entitlements Extracted

Figure 4-21 Daily Duration Curve – Gawler River


48

4.5.1 Indices of hydrological disturbance

The calculation of the estimates of natural flows and current flows (farm dams and

irrigation) were used to calculate indices of hydrological disturbance. These indices

include:

• Index of Mean Annual Flow

• Index of Flow Duration Curve Difference

• Index of Seasonal Amplitude

• Index of Seasonal Periodicity

• Hydrological Disturbance Index

The indices were calculated using the formulas stated in the Natural Resource

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

Murray-Darling Basin (MDBC 08/04).

The following table shows the Hydrological Disturbance Indices at 6 locations within the

catchment, comparing scenario 1 (No entitlements - Natural) and scenario 3

(environmental flows and entitlements) for period 01/01/1900 to 01/01/2007. Four sites

in addition to the calibration sites have been selected to give an indication of the

variability of the indices of hydrological disturbance across the catchment.

Table 4.8 Hydrological Disturbance Indices

Disturbance Indices

Values

undisturbed (natural flow)

SC4

Leven River site 14207

SC9

Leven River

SC10

Leven River

SC3

Gawler River site 14208

SC8

Gawler River

SC23

Gawler River

Index of Mean Annual Flow, A 1.00 0.99 0.99 1.00 0.91 0.97 0.98

Index of Flow Duration Curve Difference, M 1.00 0.94 0.97 1.00 0.60 0.79 0.80

Index of Seasonal Amplitude, SA 1.00 0.95 0.97 1.00 0.80 0.93 0.94

Index of Seasonal Periodicity, SP 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Hydrological Disturbance Index, HDI 1.00 0.96 0.98 1.00 0.77 0.89 0.90

Hydrological Disturbance Index: 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.


49

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

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

numerical value of the month with the highest mean monthly flow and the numerical

value 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 percentage of a year. This percentage 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

A flood frequency plot has been developed at both the Leven at Bannon’s Bridge (site

14207) and Gawler at West Gawler (site 14208) gauging sites. The plot shown below

in Figure 4-22 and Figure 4-23 consists of three traces:

1. Observed

dpiw – surface water models leven & gawler catchment · 2014. 8. 6. · gawler river, which is...

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