dpiw – surface water models sisters creek catchment

DPIW – SURFACE WATER MODELS

SISTERS CREEK CATCHMENT

Sisters Creek 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 2007/017

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 M. Willis Dr Fiona

Ling

C. Smythe July 2008 Final

Current Document Approval

PREPARED BY James Bennett

Water Resources Mngt Sign Date

REVIEWED BY 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 one of a series of reports that present the methods and results from the

development 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 Sisters Creek catchment

A model was developed for the Sisters Creek 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:

• 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 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 allocation 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 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 usage 9

3.7 Estimation of unlicensed dams 13

3.8 Environmental flows 14

4. MODEL DEVELOPMENT 16

4.1 Subarea delineation 16

4.2 Hydstra Model 16

4.2.1 Lake Llewellyn 18

4.3 AWBM Model 19

4.3.1 Channel Routing 21

4.4 Model Calibration 22

4.4.1 Model Accuracy – Fit Statistics and Visual Assessments 26

4.4.2 Model Accuracy throughout the catchment 27

4.4.3 Model Accuracy: Conclusions 33

4.5 Model results 34

4.5.1 Indices of hydrological disturbance 34

4.6 Flood frequency analysis 36

5. REFERENCES 37

5.1 Personal Communications 38

6. GLOSSARY 39

APPENDIX A 41

APPENDIX B 44


iv

LIST OF FIGURES

Figure 2-1 Subcatchment 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 12

Figure 4-1 Hydstra Model Schematic 17

Figure 4-2 Two Tap Australian Water Balance Model Schematic 21

Figure 4-3 Monthly Variation of CapAve Parameter (adapted from Flowerdale Model

(Willis 2007a)) 24

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

Flowerdale River (from Flowerdale DPIW Surface Water Model (Willis 2007a))

25

Figure 4-5 Long term average monthly, seasonal and annual comparison plot for

Sisters Creek (Modelled from 01/01/1968 – 01/01/2006) 25

Figure 4-6 Time Series of Monthly Volumes- SC4 flows plotted against Area- scaled

Flowerdale Observed flows 29

Figure 4-7 Time Series of Monthly Volumes- SC4 flows plotted against Area – and

Rainfall-Scaled Flowerdale Observed flows 29

Figure 4-8 Time Series of Monthly Volumes- SC3 flows plotted against Area- and




Figure 4-10 Time Series of Daily Volumes- SC6 modelled flows plotted against Sisters

Creek flows Observed during 1991 33

Figure 4-11 Daily Duration Curve 34

Figure B-1 Forth catchment – monthly volumes at secondary site. 46

Figure B-2 George catchment – monthly volumes at secondary site. 46

Figure B-3 Leven catchment – monthly volumes at secondary site. 47

Figure B-4 Swan catchment – monthly volumes at secondary site. 47

Figure B-5 Montagu catchment – monthly volumes at secondary site. 48


v

LIST OF TABLES

Table 3-1 Data Drill Site Locations 7

Table 3-2 Assumed Surety of Unassigned Records 9

Table 3-3 Sub Catchment High and Low Priority Entitlements 11

Table 3-4 Average capacity for dams less than 20 ML by Neal et al (2002) 14

Table 3-5 Environmental Flows 15

Table 4-1 Boughton & Chiew, AWBM surface storage parameters 19

Table 4-2 Hydstra/TSM Modelling Parameter Bounds 22

Table 4-3 Sisters Creek Model Parameters (adopted from Flowerdale Model (Willis

2007a)) 23

Table 4-4 Comparison of Flowerdale Model Parameters used Sisters Creek and model

parameters of other nearby catchments (Adapted from Willis 2007a, Peterson &

Willis 2007, Willis 2007b) 24

Table 4-5 Long term average monthly, seasonal and annual comparisons for Sisters

Creek 26

Table 4-6 Model Fit Statistics – Flowerdale River (adapted from Willis 2007a) 27

Table 4-7 Hydrological Disturbance Indices at the mouth of Sisters Creek 35

Table B-1 Model performance at secondary sites 49


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 required for the development of the hydrological model (Australian Water Balance Model, AWBM) for the Sisters Creek catchment. No data were available to calibrate the model. The model parameters used for Sisters Creek have been taken directly from the DPIW surface water model developed for the adjoining Flowerdale 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 methods adopted, assumptions made, results of calibration and validation and description relating to the use of the developed hydrologic model and associated software.


2

2. CATCHMENT CHARACTERISTICS

Sisters Creek is fed by a small catchment in north-western Tasmania. It flows northward

to Bass Strait where it discharges at the township of Sisters Beach, the only town within

the catchment. The 32.8 km2 Sisters Creek catchment is largely flat with some

topographical undulation in the North West. Elevation change is slight, varying from 300

m ASL in the south of the catchment to sea level at the Creek’s mouth.

Rocky Cape National Park covers about one-tenth of the catchment in the catchment’s

north, and this protected area is covered by native forest. Forested areas in the

catchment are not restricted to the national park, and in sum about a third of the

catchment is covered by native forest (chiefly medium density Eucalypt forest with a

dense understorey). The remainder of the catchment is largely devoted to agriculture. A

small amount of land near the mouth of Sisters Creek is urban (Sisters Beach Township).

Rocky Cape National Park contains a significant water storage: Lake Llewellyn. Lake

Llewellyn was commissioned in 1968 for use in recreation, and is managed by Tasmania

Parks and Wildlife Service. It stores up to 340 ML.

Annual rainfall does not vary significantly across the catchment owing to the catchment’s

small size, varying from 1400 mm in the south to 1200 mm in the catchment’s north.

There are 61 registered (current) entitlements for water extraction. These entitlements

are spread across all subareas except the two nearest the mouth of Sisters Creek

(subareas 1 and 11). Most of the extractions are for agriculture, although the largest

single entitlement is for Llewellyn Dam (340 ML), which is used as a public recreational

facility.

For modelling purposes, the Sisters Creek catchment was divided into 11 sub areas.

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


3

Figure 2-1 Subcatchment boundaries


4

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).

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). This 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 dates 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 from

1957 onward distribution is considered “good” but before 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 and 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

CLIMARC project data, is available from 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 Sisters Creek catchment the evaporation data were examined and it was found


5

that before 1970 the evaporation information is based on the long term daily averages of

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 coverage of the Sisters Creek

catchment. Because the Sisters catchment is small, and data DRILL sites are separated

by at least 5 km, eight of the DRILL sites were located outside (but near to) the

catchment. Three sites used were also used (and originally extracted for) the

Inglis/Flowerdale DPIW surface water model.

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

SISTERS_01 -40°54’00” 145°30’00”

SISTERS_02 -40°57’00” 145°30’00”

SISTERS_03 -40°57’00” 145°33’00”

SISTERS_04 -40°57’00” 145°36’00”

SISTERS_05 -41°00’00” 145°30”00”

SISTERS_06 -41°00’00” 145°33’00”

SISTERS_07 -41°57’00” 145°30’00”

INGFLOW_02 -41°00’00” 145°36’00”

INGFLOW_04 -41°03’00” 145°30’00”

INGFLOW_05 -41°03’00” 145°36’00”

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 being observed within the

catchment. Rainfall sites in close proximity to the Data Drill locations were sourced and

compared. The annual rainfall totals of selected Data Drill sites and neighbouring sites

for coincident periods are plotted Figure 3-2. The visual comparison and the R2 value

indicate that there appears to be good correlation for two sites which is to be expected as

the Data Drill information is derived from site data. However at a third site (TSM site

1543.1), the correlation with the nearest data drill site is poor, particularly for the earlier

part of the record. It is notable that this poor correlation exists for a record that ends in

the 1950s – it is expected that better correlation occurs in more recent years of record

(as it does at the two other sites shown).

Sis

ters

Cre

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urf

ace W

ate

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Hydro

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V

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8

Figure 3-2 Rainfall and Data Drill comparisons

R2 =

0.8

6

R2 =

0.5

8

R2 =

0.9

7


9

3.5 Streamflow data

No streamflow data were available to calibrate the Sisters Creek catchment model.

Model parameters were adopted from the DPIW surface water model for the adjoining

Flowerdale catchment, and this is discussed in section 4.4.

3.6 Irrigation and water usage

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

from DPIW from the Water Information Management System (WIMS Dec 2006). 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 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:

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

In total there were 741.7 ML unassigned entitlements (surety = 0) identified for inclusion

in the surface water model, of which 97 ML were assigned surety 1 and 644.7 ML

assigned surety 6.

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

to remove the following records:

• 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


10

available for Low Priority entitlements after environmental flow requirements have been

met.

DPIW estimated direct extractions in excess of water licenses to be 718 ML per year.

This volume was apportioned to subareas according to the proportions of licensed direct

extractions in each subarea (in lieu of more detailed information to the contrary).

Allowances for unlicensed dam extractions are covered in Section 3.7.

A summary table of monthly entitlement volumes by subarea 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.


11

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 0.0 0.0 0.0 0.0 0.9 0.8 0.9 0.9 0.8 0.0 0.0 0.0 4.2

SC2 16.7 15.1 16.7 16.1 8.3 8.0 8.3 8.3 8.0 16.7 16.1 16.7 154.9

SC3 0.0 0.0 0.0 0.0 0.3 0.3 0.3 0.3 0.3 0.0 0.0 0.0 1.4

SC4 19.1 17.2 19.1 18.5 1.7 1.6 1.7 1.7 1.6 19.1 18.5 19.1 138.9

SC5 10.7 9.6 10.7 10.3 1.7 1.6 1.7 1.7 1.6 10.7 10.3 10.7 81.3

SC6 57.3 51.7 57.3 55.4 2.6 2.5 2.6 2.6 2.5 57.3 55.4 57.3 404.2

SC7 0.0 0.0 0.0 0.0 1.1 1.1 1.1 1.1 1.1 0.0 0.0 0.0 5.6

SC8 0.0 0.0 0.0 0.0 0.3 0.3 0.3 0.3 0.3 0.0 0.0 0.0 1.4

SC9 0.0 0.0 0.0 0.0 0.6 0.5 0.6 0.6 0.5 0.0 0.0 0.0 2.8

SC10 9.5 8.6 9.5 9.2 0.9 0.8 0.9 0.9 0.8 9.5 9.2 9.5 69.5

SC11 0.0 0.0 0.0 0.0 1.1 1.1 1.1 1.1 1.1 0.0 0.0 0.0 5.6

Total 113.2 102.3 113.2 109.6 19.3 18.7 19.3 19.3 18.7 113.2 109.6 113.2 869.8

Low Priority

Entitlements

SC1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

SC2 5.5 5.0 5.5 5.4 45.9 44.4 45.9 45.9 44.4 45.9 44.4 5.5 344.0

SC3 0.0 0.0 0.0 0.0 2.9 2.8 2.9 2.9 2.8 2.9 2.8 0.0 20.0

SC4 8.3 7.5 8.3 8.0 27.1 26.2 27.1 27.1 26.2 27.1 18.8 8.3 219.9

SC5 4.3 3.9 4.3 4.2 24.0 23.3 24.0 24.0 23.3 24.0 23.3 4.3 187.0

SC6 45.5 41.1 42.4 35.8 28.9 27.9 28.9 28.9 27.9 28.9 27.9 45.2 409.2

SC7 0.0 0.0 0.0 0.0 16.2 15.6 16.2 16.2 15.6 16.2 15.6 0.0 111.5

SC8 28.9 26.1 28.9 27.9 28.9 27.9 28.9 28.9 27.9 28.9 27.9 28.9 340.0

SC9 0.0 0.0 0.0 0.0 1.4 1.3 1.4 1.4 1.3 1.4 1.3 0.0 9.5

SC10 6.5 5.8 6.5 6.3 19.3 18.7 19.3 19.3 18.7 19.3 10.1 6.5 156.0

SC11 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Total 99.1 89.5 96.0 87.6 194.4 188.2 194.4 194.4 188.2 194.4 172.3 98.7 1797.1

All

Entitlements

SC1 0.0 0.0 0.0 0.0 0.9 0.8 0.9 0.9 0.8 0.0 0.0 0.0 4.2

SC2 22.2 20.1 22.2 21.5 54.2 52.4 54.2 54.2 52.4 62.6 60.6 22.2 498.9

SC3 0.0 0.0 0.0 0.0 3.2 3.1 3.2 3.2 3.1 2.9 2.8 0.0 21.4

SC4 27.4 24.8 27.4 26.5 28.8 27.8 28.8 28.8 27.8 46.1 37.3 27.4 358.8

SC5 15.0 13.5 15.0 14.5 25.7 24.9 25.7 25.7 24.9 34.7 33.6 15.0 268.3

SC6 102.8 92.8 99.7 91.2 31.4 30.4 31.4 31.4 30.4 86.1 83.3 102.4 813.4

SC7 0.0 0.0 0.0 0.0 17.3 16.7 17.3 17.3 16.7 16.2 15.6 0.0 117.1

SC8 28.9 26.1 28.9 27.9 29.2 28.2 29.2 29.2 28.2 28.9 27.9 28.9 341.4

SC9 0.0 0.0 0.0 0.0 1.9 1.9 1.9 1.9 1.9 1.4 1.3 0.0 12.3

SC10 16.0 14.5 16.0 15.5 20.1 19.5 20.1 20.1 19.5 28.8 19.3 16.0 225.5

SC11 0.0 0.0 0.0 0.0 1.1 1.1 1.1 1.1 1.1 0.0 0.0 0.0 5.6

Total 212.3 191.8 209.2 197.2 213.8 206.9 213.8 213.8 206.9 307.7 281.9 212.0 2666.9


12

Figure 3-3 WIMS (Dec 2006) Water allocations


13

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 is 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

the following method:

• Aerial photographs (dates unknown) supplied by DPIW were analysed.

These photographs did not cover the entire area of the catchment: only 6 of

11 subareas were completely covered. Farm dams were detected by eye

and counted for every subarea that was totally covered by the photographs.

The number of dams of any size was counted in each of the 6 visible

subareas. The number of unlicensed dams could be determined by

subtracting the licensed dams information: 17 unlicensed storages were

identified in 6 subareas.

• Using this information a ratio of unlicensed to licensed dams was

determined. For the 6 subareas that were counted the ratio of unlicensed :

licensed dams was 0.78. It was assumed that this ratio would be the same

across the catchment. This assumption is validated by the similar

unlicensed:licensed dam ratio of 1.1 calculated for the adjoining

Inglis/Flowerdale catchment, indicating that this ratio is reasonably

consistent across catchments in this region. The Sisters Creek

unlicensed:licensed dam ratio was then used to estimate the number of

unlicensed dams in uncounted sub-catchments: the catchment has a total

of 50 licensed storages, and thus an estimated 39 unlicensed dams (50 *

0.78 = 39).

• 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 the 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 was considered

acceptable.


14

• 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.

• 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 also

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).

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

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

estimated as 54.6 ML (39 * 1.4ML). This equates to 1.66 ML of unlicensed

dams/km2. The total volume of existing permitted extractions for storages

in the study catchment is 1567.3 ML. Therefore the 54.6 ML of unlicensed

dams equates to 3.4% 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

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

that for Sisters Creek 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 scenario 1 and the environmental flow would be

assumed to be:


15

• 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).

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.

Table 3-5 Environmental Flows

Catch-ment area (km

2)

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

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

SC1 1.5 3.5 2.9 3.1 5.9 7.4 18.2 34.9 43.8 31.1 15.1 13.6 7.4 15.6

SC2 4.9 0.6 0.5 0.6 1.2 1.4 3.3 5.9 7.6 5.5 2.6 2.4 1.5 2.8

SC3 1.0 1.9 1.6 1.7 3.2 4.1 10.7 20.3 25.6 18.5 8.8 7.8 4.2 9.0

SC4 7.3 0.7 0.6 0.6 1.2 1.6 4.5 8.3 10.1 7.5 3.3 3.2 1.7 3.6

SC5 3.0 0.4 0.3 0.3 0.7 0.7 1.9 3.4 4.4 3.1 1.5 1.4 0.8 1.6

SC6 5.1 1.4 1.2 1.3 2.3 3.1 8.5 16.0 20.1 14.2 6.8 5.9 3.3 7.0

SC7 2.5 0.2 0.2 0.2 0.4 0.5 1.5 2.8 3.4 2.4 1.1 0.9 0.5 1.2

SC8 0.6 3.3 2.7 3.0 5.6 7.0 17.4 33.4 41.7 29.7 14.4 13.0 7.0 14.9

SC9 1.8 2.8 2.3 2.5 4.8 5.9 15.1 28.0 35.2 25.8 12.3 11.2 6.0 12.6

SC10 5.2 0.4 0.4 0.4 0.7 1.0 2.2 4.7 5.6 3.7 2.0 1.6 0.9 2.0

SC11 1.1 0.1 0.1 0.1 0.2 0.2 0.5 1.0 1.2 0.8 0.4 0.4 0.2 0.4


16

4. MODEL DEVELOPMENT

4.1 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 fully 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

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

lengths between them.

These outputs were manually checked to ensure they accurately represented the

catchment. Any minor modifications 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 Sisters

Creek 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 subarea, through the catchment via a channel routing

function.

The rainfall and evaporation are 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. 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.

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

subarea 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


17

spatially over the catchment.

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

function.

Figure 4-1 Hydstra Model schematic


18

4.2.1 Lake Llewellyn

A significant storage - Lake Llewellyn - was identified during the creation of the Sisters

Creek catchment model in subarea SC8. Lake Llewellyn is managed by Tasmania

Parks and Wildlife and only has an influence on the flow regime of Sisters Creek of one

downstream subarea (SC1). No information relating to historic lake discharges was

identified. Discussions with DPIW staff on the appropriate way to model this lake

resulted in the following decisions:

• Scenario 1 will model the catchment with no dam or lake present for all of record.

• Both Scenarios 2 and 3 will model the catchment with:

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

1967.

o From 1968 onwards, the lake will be modelled using a basic volume

balance rule assuming the following:

� Lake volume will be 340 ML (from DPIW dams database) and at

full supply level at start of model;

� Water entitlements falling within the Lake Llewellyn subarea (SC8)

will be extracted from the lake volume;

� Inflows in excess of the lake volume will be discharged

downstream as spill;

� If Scenario 3 is selected then a flow will be released downstream

equal to the environmental flow specified in the user interface for

the Lake Llewellyn subarea (SC8). However when the modelled

inflow to SC8 is less than the specified environmental flow, the

downstream release will be reduced to equal SC8 inflow. This

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

of low inflow.


19

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

& Chiew, 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 given in Table 4-1.

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

Partial area of smallest store A1=0.134



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

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

Capacity of smallest store C3=(0.66*Ave/ A3)=1.524*Ave


20

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

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. Further information on the 2 tap

variant of the AWBM model is provided in Parkyn & Wilson (1997).


21

Figure 4-2 Two Tap 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


22

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. e.g. αfl where fl is a length factor.

Parameters required by Hydstra/TSM Modelling and their legal 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

No streamflow records of Sisters Creek of sufficient duration were available to calibrate

the Model. Model parameters used to calibrate the Flowerdale River component of the

Inglis/Flowerdale DPIW surface water model were adopted for this model as the

Flowerdale River catchment adjoins Sisters Creek catchment.

Calibration of the Inglis/Flowerdale model was achieved by adjusting model parameters

by comparing the monthly, seasonal and annual volumes. A generalised calibration

method is presented in APPENDIX A. This process is detailed in the Inglis/Flowerdale

DPIW surface model report (Willis, 2007a). The adopted model parameters are shown in

Table 4-3.

In the absence of other data, the model parameters used for the Flowerdale catchment

model are assumed to be valid for the Sisters Catchment model. The geographical

proximity of the two catchments implies similar climatic and environmental regimes


23

(notably soil and vegetation types). A visual inspection of maps shows that the Sisters

Creek and Flowerdale catchments have similar topography. Land use in both

catchments is also similar: both catchments are dominated by agriculture and natural

forested areas, with only small proportions of both catchments dedicated to urban use.

Further, the calibration parameters for two other nearby surface water models, Leven &

Gawler and Claytons, are very similar to that of Flowerdale (Table 4-4). The

consistency of model parameters in models for Catchments surrounding Sisters Creek

further validates the assumption that adopting the Flowerdale model parameters for the

Sisters Creek model will result in a reasonable approximation of actual flows in Sisters

Creek. Thus the assumption that both catchments will share hydrological

characteristics (and hence model parameters) is justified.

Modelled flow volumes at the mouth of Sisters Creek (subarea SC1) under two

scenarios are shown in Table 4-5 and Figure 4-5: 1) flow volumes accounting for all

licensed and unlicensed water extractions but not for environmental flows (labelled

Modelled – with entitlements), and 2) flow volumes that do not account for any water

extractions or environmental flows (labelled Modelled – natural). There is considerable

discrepancy in monthly volumes between the two scenarios. This reflects the high

level of demand for water relative to flow volumes in Sisters Creek.

Table 4-3 Sisters Creek Model Parameters (adopted from Flowerdale Model

(Willis 2007a))

PARAMETER Flowerdale VALUE

INFBase 0.75

K1 0.96

K2 0.98

GWstoreSat 70

GWstoreMax 100

H_GW 90

EvapScale 1

Alpha 3

n 0.8

CapAve Variable


24

0

50

100

150

200

250

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

Month

CapAve

Figure 4-3 Monthly Variation of CapAve Parameter (adapted from Flowerdale

Model (Willis 2007a))

Table 4-4 Comparison of Flowerdale Model Parameters used Sisters Creek and

model parameters of other nearby catchments (Adapted from Willis 2007a,

Peterson & Willis 2007, Willis 2007b)

PARAMETER Flowerdale

value Claytons Value

Leven Value

Gawler Value

INFBase 0.75 0.8 0.75 0.75

K1 0.96 0.96 0.97 0.95

K2 0.98 0.995 0.98 0.98

GWstoreSat 70 160 70 70

GWstoreMax 100 200 100 100

H_GW 90 80 90 90

EvapScale 1 1 1 1

Alpha 3 3 3 3

n 0.8 0.8 0.8 0.8


25

0

100

200

300

400

500

600

700

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

Average Flow (ML/Day)

Observed

Modelled Calibration Flow

Scenario 1 (Natural)

Demand

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

Flowerdale River (from Flowerdale DPIW Surface Water Model (Willis 2007a))

0

10

20

30

40

50

60

70

80

90

100

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

Average Flow (ML/Day)

Modelled Calibration Flow

Scenario 1 (Natural)

Demand

Figure 4-5 Long term average monthly, seasonal and annual comparison plot for

Sisters Creek (Modelled from 01/01/1968 – 01/01/2006)


26

Table 4-5 Long term average monthly, seasonal and annual comparisons for

Sisters Creek

Long term Averages (ML/Day)

MONTH Modelled-Calibration

Flow (MCF)1

Scenario 1 “Modelled -- No Entitlements (Natural)” Demand

January 7.47 12.02 6.85

February 6.45 10.64 6.85

March 7.33 11.48 6.75

April 19.41 24.54 6.57

May 27.86 33.93 6.90

June 41.90 48.61 6.90

July 62.60 69.50 6.90

August 80.31 87.16 6.90

September 60.70 67.53 6.90

October 42.47 51.78 9.93

November 24.35 32.50 9.40

December 13.96 19.66 6.84

WINTER 52.64 59.75 7.40

SUMMER 13.16 18.47 7.21

ANNUAL 32.90 39.11 7.30

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

4.4.1 Model Accuracy – Fit Statistics and Visual Assessments

It is an assumption of the Sisters model that the calibration parameters of the adjacent

Inglis/Flowerdale catchment model are appropriate for the Sisters catchment. The

calibration for the Inglis/Flowerdale River catchment model resulted in good replication

of observed streamflows, as evidenced by high coefficients of determination (R2

values) (Table 4-6) and low proportional differences between observed and modelled

flows (Willis 2007a). Annual hydrographs were judged to have fair-to good replication

of observed flows, and modelled flow volumes showed excellent fidelity to observed

flow volumes (Figure 4-4). Calibration of the Inglis/Flowerdale catchment is discussed

in detail by Willis (2007a).

However, the accuracy of the Inglis/Flowerdale surface water model does not

necessarily give an indication of the performance of the Sisters Creek model. While

Sisters Creek lies in close proximity to the Flowerdale River, differences in catchment

characteristics (not least the considerable discrepancy in size) mean that the use of

Flowerdale model parameters in the Sisters Creek model may not be appropriate.

Without the verification of a lengthy, reliable flow record, it is simply not possible to

make this judgment.

1 Refer to page 41 for explanation of this modelling scenario.


27

Table 4-6 Model Fit Statistics – Flowerdale River (adapted from Willis 2007a)

Measure of Fit Flowerdale River at

Moorleah

Daily coefficient of determination (R2 value) 0.74

Monthly coefficient of determination (R2 value) 0.91

Difference in observed and estimated long term

annual average flows +0.45%

4.4.2 Model Accuracy throughout the catchment

The Sisters Creek model uses the Flowerdale calibration fit and this model was

calibrated to provide a good simulation of monthly and seasonal flow volumes at the

calibration site. Calibration sites were low in the Flowerdale 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 DPIW Surface

Water models (developed by the same method as the Sisters Creek 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 Inglis and Flowerdale model

performed consistently throughout the catchment (Willis 2007a). A detailed description

of the Inglis and Flowerdale surface flow model’s performance throughout its

catchment is available in Willis (2007a).

As there was only a very limited observed flow record available for Sisters Creek, the

reliability of the model throughout the catchment could not be tested directly. As the

Sisters Creek model adopted the parameters of the Inglis and Flowerdale model, the

record used to calibrate the Flowerdale Catchment (Flowerdale at Moorleah, TSM site

14215) was used to derive a proxy ‘observed’ record with which to test the Sisters

model. The Flowerdale calibration record scaled by a factor of 0.8 to account for

differences in rainfall between the two catchments, calculated from the ratio of the

catchment centroid mean annual rainfall obtained from a mean annual rainfall isohyetal

map. The Flowerdale calibration record was also scaled by area to approximate

‘observed records at 3 subcatchments in the Sisters catchment. These proxy records


28

were compared to modelled calibration flows (MCFs)2 for three subcatchments, SC4,

SC2, and SC1, located high, mid and low in the Sisters catchment, respectively.

Comparison of Flowerdale scaled observed record and subcatchment 4

The area ratio of SC4 to the observed data was calculated to be 5 %. The observed

monthly volumes at the calibration site were multiplied by this ratio in order to calculate

a proxy ‘observed’ record at the catchment outflow. The results are shown in Figure

4-6. Considering the uncertainties and difficulty in generating a scaled observed trace,

the results appear reasonable, although the MCF is noticeably lower than the scaled

observed flow. This is unsurprising, as Sisters Creek catchment is not exposed to the

high rainfalls of Tasmania’s northern highlands that feed the Flowerdale catchment. To

account for differences in rainfall between the Flowerdale and Sisters catchments a

rainfall scaling factor of 0.8 was calculated from the ratio of the catchment centroid

mean annual rainfall obtained from a mean annual rainfall isohyetal map. When the

observed data are scaled for area and rainfall, the traces appear noticeably closer

(Figure 4-7), and the comparison is more useful (the remaining plots show only proxy

records that have been scaled for area and rainfall). However, the MCF trace is still

lower than the scaled observed trace. This difference may be attributable to the fact

that water extractions in the Sisters Creek catchment are proportionally much higher

than those of the Flowerdale catchment. These proportionally higher extractions will

not be present in the scaled Flowerdale observed record.

2 A time period reduction factor (TPRF) of 0.5 was applied to water entitlements to generate the

MCF - see Glossary, and 0 for an explanations of MCF and TPRF


29

0

500

1000

1500

2000

2500

1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989

Monthly Volume (ML)

Area-scaled Observed

SC4 MCF (TPRF = 0.5)

R2 = 0.59

Figure 4-6 Time Series of Monthly Volumes- SC4 flows plotted against Area-

scaled Flowerdale Observed flows

0

200

400

600

800

1000

1200

1400

1600

1800

2000

1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989

Monthly Volume (ML)

Area- and rain-scaled Observed


R2 = 0.59

Figure 4-7 Time Series of Monthly Volumes- SC4 flows plotted against Area –

and Rainfall-Scaled Flowerdale Observed flows


30



monthly volumes at the calibration site were multiplied by this ratio and the rainfall

scaling factor of 0.8 in order to calculate a proxy ‘observed’ record at the catchment

outflow. The results are shown in Figure 4-8. Again, the Sisters Creek MCF is lower

than the scaled Flowerdale flow, which is attributable to the higher water extractions in

the Sisters catchment.

This highlights the dangers of using scaled observed data as a guide for determining

flows at alternate locations or assessing model performance. The model allows for the

spatial variability of rainfall over the catchment, as well as accounting for water

extractions for each catchment, thus the modelled flow prediction will not be

disadvantaged by rainfall spatial variation.

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989

Monthly Volume (ML)



R2 = 0.61


Rainfall-Scaled Flowerdale Observed flows


31



monthly volumes at the calibration site were multiplied by this ratio and the rainfall

scaling factor of 0.8 in order to calculate a proxy ‘observed’ record at the catchment

outflow. The results are shown in Figure 4-9. Again, the Sisters Creek MCF is lower

than the scaled Flowerdale flow, which is attributable to higher water extractions in the

Sisters catchment.

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989

Monthly Volume (ML)



R2 = 0.64


Rainfall-Scaled Flowerdale Observed flows


32

Comparison of Sisters observed record and subcatchment 6

A short term flow record is available for Sisters Creek (TSM site 14241) for the first 6

months of 1991. This record is neither long nor reliable enough for calibration

purposes, but serves to help assess the reliability of the model. The flow record was

recorded near at the outflow of SC6, and hence modelled flows from this subarea were

compared to the observed flow (Figure 4-10). There is poor agreement between

observed and the MCF (TPRF = 0.5) modelled under scenario 2 (with entitlements

extracted), where the MCF volumes are notably lower than observed flows. There is a

better match between observed flow volumes and MCF (TPRF = 0.5) under scenario 1

(natural flows), although even under this scenario MCF flow volumes are substantially

lower than observed volumes. Without a longer and more reliable flow record it is

impossible to confidently explain these discrepancies. However, these differences are

likely due to one or more of the following:

• Water extractions in Sisters catchment are a substantial proportion of total flow

(up to 50 % in some months). As noted, a number of assumptions were made

to calculate water entitlements. If any of these assumptions used to estimate

water extractions from the catchment are inaccurate (e.g. estimate of average

dam size, the temporal distribution of extractions), this will have a large impact

on the modelled flows of Sisters Creek;

• There is the possibility that the observed flows are higher than modelled

because they are being augmented by groundwater flows. The hydrograph

recession periods in the observed record indicate there is a steady baseflow in

Sisters Creek;

• The coarse nature of the rainfall spatial distribution information may lead to a

misrepresentation of the rainfall on the Sisters Creek catchment. The data

DRILL sites used as rainfall input into the model cover a much larger area than

the size of the catchment itself. Discrepancies due to temporal differences in

rainfall are evident in Figure 4-10, notably in the modelled peak flow in

February, which presents a significantly different temporal response in the

observed flow;

• Some of this disagreement may be due to inaccuracies in the flow record at site

14241. As previously stated there are serious doubts about both the reliability of

the observed data and the associated flow rating at site 14241;


33

• It is possible that the Flowerdale calibration parameters are not appropriate for

use on the Sisters Creek catchment. The Flowerdale catchment is much larger,

and is on average a slightly steeper catchment. This may lead to the model

yielding faster response times (i.e. being ‘peakier’) than may occur in reality.

0

5

10

15

20

25

30

35

40

45

Jan Feb Mar Apr May Jun

1991

Monthly Volume (ML)

Sisters Creek observed flow record (TSM site 14241)

SC6 Under Scenaro 1

SC6 Scenario 2 MCF (TPRF = 0.5)

Figure 4-10 Time Series of Daily Volumes- SC6 modelled flows plotted against

Sisters Creek flows observed during 1991

4.4.3 Model Accuracy: Conclusions

The inaccuracy of the model during the only period of record available indicates that

this model should be used with caution. Modelled flows are, in all cases, lower than

comparable observed or proxy records. The transfer of model parameters from the

Flowerdale model may not be suitable for the Sisters Catchment, but have been

applied as a necessity in the absence of better information. Further, in the Sisters

catchment water entitlements are a substantial proportion of flow (as much as 50 % for

some months). Possible inaccuracies in the calculation of water entitlements (e.g. the

assumption of 1.4 ML average dam size may not hold) can lead to large differences in

modelled flows. In the absence of a lengthy, reliable flow record, any conclusions

drawn about the suitability and accuracy of the model are necessarily uncertain. It is

recommended that DPIW consider the installation of a flow measurement site in the

Sisters Creek catchment in order to provide greater surety in the availability of water in

this catchment. This would be a prudent course of action in light of the substantial

water entitlements in the Sisters Creek catchments (as much as 50 % of available


34

volume in some months). Additionally, the collection of such information will allow the

Sisters Creek model to be more reliably calibrated.

4.5 Model results

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

scenarios to be generated;

• Scenario 1 - Natural Flow

• Scenario 2 - Entitlements (river flows with water entitlements extracted)

• Scenario 3 - Entitlements and Environmental Flows (a scenario modelling

environmental flows with all extractions included)

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.

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

of Sisters Creek (SC1) are presented below and in the following section. The outputs

are a comparison of scenario 1 (natural) and scenario 3 (environmental flows with all

extractions included) for period 01/01/1900 to 01/01/2006.

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)

Natural

Entitlements Extracted

Figure 4-11 Daily Duration curve

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:


35

• 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 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 the mouth of Sister

Creek (subarea SC1), comparing scenario 1 (natural) and scenario 3 (environmental

flows with all extractions included) for period 01/01/1900 to 01/01/2006.

Table 4-7 Hydrological Disturbance Indices at the mouth of Sisters Creek

Disturbance Indices Values

undisturbed

(natural flow)

SC4 (High

in

Catchment)

SC3 (Mid

Catchment)

SC1

(Catchment

Outflow)

Index of Mean Annual Flow, A 1.00 0.92 0.88 0.88

Index of Flow Duration Curve

Difference, M 1.00 0.70 0.60 0.66

Index of Seasonal Amplitude, SA 1.00 0.86 0.77 0.81

Index of Seasonal Periodicity, SP 1.00 1.00 0.92 0.92

Hydrological Disturbance Index, HDI 1.00 0.83 0.76 0.79

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.

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.


36

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

As no observed data were available for Sisters Creek, a comparison plot of modelled

and observed flood frequencies was not possible.


37

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

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

Hydro Tasmania internal report, (2004) South Esk River Catchment Above Macquarie

River, Impact of Water Entitlements on Water and Hydro Power Yield.

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.

Peterson, J and Willis, M (2007) DPIW – Surface Water Models: Claytons Catchment.

Report to DPIW. Hydro Tasmania Consulting Document Number WR 2007/003.

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

of Environment Unit, Lands Information Services, DELM.


38

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

to Department of Sustainability and Environment, Victoria.

Willis, M (2007a) DPIW – Surface Water Models: Inglis and Flowerdale Catchment.


Willis, M (2007b). DPIW – Surface Water Models: Leven and Gawler Catchment.


5.1 Personal Communications

Graham, B. Section Head, Ecohydrology, Water Assessment, DPIW. March-April 2007.


39

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.


40

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.


41

APPENDIX A

Generalised Model Calibration Method

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

best replicates the record at the site selected for calibration. 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.

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:

MCF = Modeled Calibration Flow

MNEM = Modeled - No Entitlements (Modified). *

WE = Water Entitlements

TPRF = Time Period Reduction Factor

* Refer to Glossary for additional explanation of these terms

No streamflow records of Sisters Creek of sufficient duration were available to calibrate

the Model. Model parameters used to calibrate the Flowerdale River component of the

Inglis/Flowerdale DPIW surface water model were adopted for this model as the

Flowerdale River catchment adjoins Sisters Creek catchment.

The Flowerdale catchment calibration used observed records from Flowerdale at

Moorleah (TSM site 14215) from 23/03/1966 to 28/01/2007. The Inglis catchment

calibration used observed records from Inglis above Flowerdale (TSM site 14210) from

08/06/1967 to 07/02/1989.

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


42

50% of the current extractions if the mid year of the calibration period was earlier than

1994. A TPRF of 50% was applied to both the Inglis River above Flowerdale and

Flowerdale River at Moorleah calibration sites as the mid years of the calibration periods

were 1978 and 1987, respectively.

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.

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. 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.

Two sets of CapAve profiles were applied across the catchment to achieve an optimum

volume balance at each calibration location. The adopted name and extent of each

CapAve parameter is itemized below.

• CapAve: All of the Inglis River catchment and individual (separate) streams

to the east of the Inglis River.


43

• CapAve_F: All of the Flowerdale River catchment

To achieve a good fit at both the calibration locations, it was also necessary to vary some

of the other calibration parameters from one location to the next. The adopted name and

extent of each location specific parameter is itemized below.

• INFbase, K1, K2, GWstoreSat & GWstoreMax: All of the Inglis River catchment and

individual (separate) streams to the east of the Inglis River.

• INFbase_F, K1_F, K2_F, GWstoreSat_F & GWstoreMax_F: All of the Flowerdale

River catchment.


44

APPENDIX B

This appendix investigates the reliability of the catchment models at predicting river

flow throughout the catchment. One of the difficulties in assessing model reliability is

the lack of observed data, as there is often only one reliable gauging site within the

catchment. Five catchments that do have more than one gauging site and concurrent

periods of record were selected and investigated with the results presented in Table

Table B -1. 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


45

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 sub-catchments 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 individual sub-catchments vary significantly in terrain

or vegetation or rainfall compared to the catchment average, errors are expected to

be greater. The analysis undertaken in this section appears to that the confirm

models perform acceptably and the conclusions of this analysis 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-5. 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.


46

0

20000

40000

60000

80000

100000

120000

140000

1963 1964 1964 1965 1966 1967 1968

Monthly Volume (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

Monthly Volume (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.


47

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

1983 1984 1987 1989 1991 1993

Monthly Volume (ML)

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

Monthly Volume (ML)

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.


48

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

1985 1986 1987 1988 1988 1989 1990

Monthly Volume (ML)

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.

Sis

ters

Cre

ek S

urf

ace W

ate

r M

od

el

Hydro

Tasm

ania

V

ers

ion N

o: 1.1

49

Table B -1 Model perform

ance at secondary sites

Catch-

ment

Calibration Site

Primary Site

Secondary Site

Correlation A

Correlation B

Correlation C

Correlation D

Name

Site Name

& No.

Sub-

Catchment

Location

Catchment

Area

Km

2

Concurrent

data periods

used in this

analysis

Site Name

& No.

Sub-

Catchment

Location

Catchment

Area

Km2

Catchment

area factor

(compared

with

calibration

site)

Monthly ML

R2 Value

Calibration site

observed vs

Calibration site

modelled

Monthly ML

R2 Value

Secondary site

observed vs

Calibration site

observed

(scaled)

Monthly ML

R2 Value

Calibration site

observed(scale

d) vs Modelled

Monthly ML

R2 Value

Secondary

site observed

vs Modelled

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

dpiw – surface water models sisters creek catchment

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