Modelling Gaps hydraulic

8/13/2019 Modelling Gaps hydraulic

1/94


2/94

Low-flow hydrological monitoring and

modelling gaps

D. Barma1and L.Lowe

2

1. Barma Water Resources2. Sinclair Knight Mer

Low flows report series ! "une 2#12


3/94

Low flows report series

$his paper is part of a series of wor%s commissioned &y the 'ational Water (ommission on %ey water

issues. $his wor% was underta%en &y Barma Water Resources and Sinclair Knight Mer Ltd on &ehalf

of the 'ational Water (ommission.

')$*+')L W)$,R (+MM*SS*+' Low flows report series iii


4/94

(ommonwealth of )ustralia 2#12

$his wor% is copyright.

)part from any use as permitted under the Copyright Act 1968/ no part may &e reproduced &y anyprocess without prior written permission.

Re0uests and en0uiries concerning reproduction and rights should &e addressed to the(ommunications irector/ 'ational Water (ommission/ 3 'orth&ourne )4enue/ (an&erra )($ 25##or email [email protected].

+nline6print7 *SB'7 89-1-2193:-95-

;u&lished &y the 'ational Water (ommission

3 'orth&ourne )4enue

(an&erra )($ 25##

$el7 #2 51#2 5###

,mail7 [email protected]

ate of pu&lication7 "une 2#12

)n appropriate citation for this report is7 Barma < Lowe L 2#12/ Low-fow hy!roogica "onitoring

an! "o!eing gaps/ 'ational Water (ommission/ (an&erra.

Disclaimer

$his paper is presented &y the 'ational Water (ommission and does not necessarily reflect the 4iews

or opinions of the (ommission.

')$*+')L W)$,R (+MM*SS*+' Low flows report series i4


5/94

(ontents,=ecuti4e summary i=

Being a&le to compare a flow regime at the regional scale is often re0uired. )range-standardised approach has &een adopted in other studies of flow indicators

and the concepts de4eloped in these studies should &e applied to low-flow

indicators to ena&le regional comparisons. =

Streamflow information should &e readily a4aila&le and metadata pro4ided to

allow planners and managers to assess whether streamflows measured or

modelled at a site are suita&le for a particular purpose. ) data&ase of all )ustralian

streamflow gauges that allows users to assess the suita&ility of data for a

particular purpose should &e the result of this proposal. =

'ot all ecologically rele4ant sites are currently metered. $his proposal would

identify ecologically rele4ant sites that are not currently monitored and assess the

&enefit of metering compared with the in4estment re0uired. =

$he outcome of this proposal will &e guidelines that recommend an appropriate

model selection and cali&ration strategy for low flows/ leading to impro4ed

modelling of low flows. =

)t present little information is a4aila&le to help water managers understand the

longe4ity of pools during a cease-to-flow e4ent. $his proposal will map the location

of pools and waterholes and de4elop models to predict the persistence of these

water&odies. =

>uidelines that outline &est practice are re0uired to impro4e the representation of

losses in these models. )doption of a consistent and impro4ed modelling

approach will gi4e planners and managers greater confidence in the estimates of

low flows generated &y water resource supply models. =

) &usiness case for the use of smart meters on pri4ate di4ersions and other

e=tractions could &e used to identify when and where smart meters are

economically ad4antageous to install and use. =i

,stimates of irrigation water use on a daily time-step are poor &ecause they do

not account for irrigator &eha4iour that may &e responding to other dri4ers/ such as

allocation announcements and commodity prices. More sophisticated models arere0uired to reflect the uncertainty in irrigator &eha4iour. =i

$he seasonal impact of land use change on streamflows is not 4ery well

understood/ &ut it is e=pected the impact will &e greater during lows flows than

other parts of the flow regime. $his proposal will in4estigate seasonal 4ariation in

the impact of land use on flows. =i

)n understanding of the mechanisms that generate low flows is re0uired to

predict the impact of climate change scenarios on low flows and to more effecti4ely

address issues of stress during low-flow periods. ) comprehensi4e re4iew of the

e=isting literature is re0uired to summarise the state of %nowledge/ identify %ey

gaps and propose a research agenda to impro4e %nowledge related to the dri4ersof low-flow e4ents. =i

')$*+')L W)$,R (+MM*SS*+' Low flows report series 4


6/94

Report conte=t =ii

*ntroduction 1

;ro?ect scope and approach 1

Report structure 1

;)R$ *7 *dentifying gaps and limitations :

Low-flow indicators @

1.1. *ntroduction @

1.2. ;rioritisation of low-flow indicators @

1.:. eri4ing time-series streamflow data 5

1.@. Summary

Measuring and monitoring low flows 1#

1.3. *ntroduction 1#

1.5. Streamflow measurement using a rating cur4e 1#

1.8. Satellite remote sensing 11

1.9. +ther techni0ues for streamflow measurement 1:

1.. Monitoring networ%s 1:

1.1#. Summary 1@

,stimating low flows at ungauged sites 13

1.11. *ntroduction 13

1.12. Streamflow transposition 13

1.1:. (atchment modelling 15

1.1@. irect estimation of low-flow indicators 19

1.13. (omparison of techni0ues 1

1.15. Summary 1

,stimating low flows in regulated systems 21


1.19. Water resource system models 21

1.1. Summary 2:

Auantifying anthropogenic influences 23

1.2#. *ntroduction 23

')$*+')L W)$,R (+MM*SS*+' Low flows report series 4i


7/94

1.21. irect e=tractions 23

1.22. arm dams 25

1.2:. >roundwater e=tractions 25

1.2@. Land use change 25

1.23. Wastewater treatment plant discharges 28

1.25. Summary 28

Mechanisms generating low flows 2


1.29. *dentifying and monitoring sources of low flow 2

1.2. Modelling 2

1.:#. Summary :#

Cydraulic characteristics :1

1.:1. *ntroduction :1

1.:2. Cydraulic modelling :1

1.::. Summary :2

Summary of issues and gaps ::

;)R$ **7 *dentifying solutions :8

;roposed solutions :9

1.:@. *ntroduction :9

1.:3. ;roposed solutions :9

1.:5. Key proposed solutions @@

)ppendices @

References 8

Tables$a&le 17 Water resource system models 21

$a&le 27 Summary of identified gaps for monitoring and modelling low flows :@

$a&le :7 Summary of solutions to gaps in monitoring and modelling low flows :9

Figures

')$*+')L W)$,R (+MM*SS*+' Low flows report series 4ii


8/94

igure S17 (onte=t of reports produced in the 'ational Water (ommissionDs Low lows

;ro?ect Egroup one/ teal F modelling-related reportsG group two/ green F Waterlines

reportG group three/ orange F ecology-related reportsH. =ii

igure 17 *llustration of difference in impact of a fi=ed reduction in a4erage flows on two

systems of differing 4aria&ility Ethe a4erage flows under natural and current conditions is

the same for &oth cases/ &ut the significance of the impacts is greater for &iota adaptedto a system of low 4aria&ilityH. Source7 SKM E2##3H 5

igure 27 eri4ation of a flow time-series at a gauged and unregulated site 8

igure :7 eri4ation of a flow time-series at an ungauged and unregulated site 9

igure @7 eri4ation of a flow time-series at a regulated site 9

')$*+')L W)$,R (+MM*SS*+' Low flows report series 4iii


9/94

,=ecuti4e summary$he 'ational Water (ommissionIs low flows pro?ect aims to pro4ide water planners and managers

with &etter information and tools to manage low flows. $he first stage of the pro?ect is a scoping study

intended to pro4ide clear direction to the (ommission on priorities for further wor% in two %ey areas7 1H

monitoring and modelling of low flows and/ 2H ecological %nowledge needs with respect to low flows.

$his report co4ers the first area/ summarising gaps and limitations with respect to monitoring and

modelling low flows and proposing possi&le solutions to address these. *t is intended that the solutions

presented will &e refined/ prioritised and impro4ed through consultation with the pro?ect ad4isory

group. $he outcomes will set the direction for further wor% in Stage 2 of the low flows pro?ect.

;art 1 of this report identifies and discusses se4en groups of gaps and limitations associated with

monitoring and modeling low flows/ as highlighted in &old te=t &elow.

Low-flow indicatorspro4ide one means to o&?ecti4ely assess ris%s due to changes in the low-flow

regime. ) plethora of different hydrological indicators has &een de4eloped and used to characterise a

flow regime/ &oth in )ustralia and o4erseas/ and 29 ecologically-rele4ant hydrological indicators ha4e&een identified here that characterise low flow at a site E)ppendi= )H. (alculating low-flow indicators is

relati4ely straightforward if a time-series of daily streamflows is a4aila&le/ howe4er the deri4ation of

daily streamflow datasets presents a challenging practical pro&lem.

Key issues and gaps associated with generating streamflow datasets are7

Measuringlow flows to assist in achie4ing en4ironmental and other o&?ecti4es that are affected &y

low flows is difficult compared to measuring a4erage flows. or e=ample streamflow gauging using

a rating cur4e is su&?ect to large errors at low flows and alternati4e gauging techni0ues/ such as

ultrasonic meters/ may pro4ide a more accurate alternati4e. )lso the current spatial co4erage and

monitoring fre0uency of streamflows and di4ersions/ and of any management rules associated with

these/ may &e inade0uate to measure and hence safeguard the flow regime pro4ided to meet the

ecological needs descri&ed in water plans. rom an ecological measurement perspecti4e/

streamflow gauges would ideally &e located at ecologically rele4ant locations/ or at least at

locations where the flow characteristics were representati4e of the rele4ant location. Cistorically

this has not &een the case with the location of streamflow gauges typically &eing dri4en &y the

needs of managing a water supply for e=tracti4e users as opposed to the en4ironment.

) su&stantial amount of effort is re0uired to ade0uately estimate a time-series of daily streamflows

at an ungauged site. Rainfall-runoff models are commonly used to estimate streamflows/ &ut the

relati4e a&ility of widely a4aila&le rainfall-runoff models to represent low flows and the &est

approach to cali&rate them for low flows is not widely understood.

$he main limitation of using water resource systemmodels toestimate low flows at aregulated

siteis the poor representation of ri4er losses and daily operating rules in these models. $he focusof model cali&ration is also an important factor in the accuracy of the low flows modelled at the

sites of interest.

$here are difficulties in deri4ing daily time-series of flow that represent historical/ current and natural

conditions. $he main challenge relates to the 0uantification of anthropogenic influenceson

streamflows.

;lanners and managers need to understand the mechanismsthatgenerate low flows. $he

prediction of low flows under possi&le scenarios Ee.g. climate changeH will &e impro4ed if the

processes that produce low flows are &etter understood. Water managers would &e a&le to more

efficiently address issues of stress during low-flow periods if the dri4ers of these e4ents were %nown.

Cowe4er/ the mechanisms that generate low flows are generally not well understood. Recently there

ha4e &een de4elopments in com&ined groundwater and surface water modelling/ &ut there ha4e &een

few studies to monitor surface water6groundwater interactions.

')$*+')L W)$,R (+MM*SS*+' Low flows report series i=


10/94

rom an ecological perspecti4e it is important to consider the magnitude of low flows in con?unction

with the hydraulic characteristicsof the stream. (onsidera&le time and e=pense is re0uired to

understand the hydraulic characteristics of a stream and at present little information is a4aila&le to

help water managers understand the longe4ity of pools during a cease-to-flow e4ent. ue to the

difficulty in o&taining hydraulic information/ low-flow indicators ha4e typically &een used as a surrogate

for hydraulic information.

;art 2 of the report &riefly identifies possi&le solutions to the 3#J gaps identified in ;art 1. *t then

descri&es 11 proposed solutions to address %ey low flows gaps and needs in more detail. $hese were

identified and de4eloped with the assistance of input from a wor%shop in4ol4ing specialists with

%nowledge and e=perience of low-flow hydrology/ water resource supply modelling/ hydraulic

modelling/ hydrography and ecology. $he proposals are7

e4elop low-flow indicators for regional comparison

Being a&le to compare a flow regime at the regional scale is often re0uired. ) range-

standardised approach has &een adopted in other studies of flow indicators and the concepts

de4eloped in these studies should &e applied to low-flow indicators to ena&le regional

comparisons.*mpro4e awareness of the uncertainty associated with low-flow indicators

$he deri4ation of daily streamflow data relies on a series of assumptions/ all of which will

introduce uncertainty and affect the accuracy of the low-flow indicators. While the accuracy will

depend on many site-specific factors/ water managers may &enefit from assistance with li%ely

accuracy and ways to decrease uncertainty. $he outcome of this proposal is clear guidance on

the li%ely magnitude of uncertainty in low-flow indicatorsG methods and tools to 0uantify the

uncertaintyG an understanding of the main factors contri&uting to the uncertaintyG as well as

guidelines for using this information to impro4e decision ma%ing.

*mpro4e the a4aila&ility of streamflow information and metadata

Streamflow information should &e readily a4aila&le and metadata pro4ided to allow plannersand managers to assess whether streamflows measured or modelled at a site are suita&le for a

particular purpose. ) data&ase of all )ustralian streamflow gauges that allows users to assess

the suita&ility of data for a particular purpose should &e the result of this proposal.

*ncrease metering and monitoring of ecologically rele4ant sites

'ot all ecologically rele4ant sites are currently metered. $his proposal would identify

ecologically rele4ant sites that are not currently monitored and assess the &enefit of metering

compared with the in4estment re0uired.

e4elop guidelines for estimating low flows

$he outcome of this proposal will &e guidelines that recommend an appropriate model selection

and cali&ration strategy for low flows/ leading to impro4ed modelling of low flows.

*mpro4e understanding of the location and longe4ity of pools and waterholes

)t present little information is a4aila&le to help water managers understand the longe4ity of

pools during a cease-to-flow e4ent. $his proposal will map the location of pools and waterholes

and de4elop models to predict the persistence of these water&odies.

*mpro4ed representation of losses in water resource supply models

>uidelines that outline &est practice are re0uired to impro4e the representation of losses in

these models. )doption of a consistent and impro4ed modelling approach will gi4e planners

and managers greater confidence in the estimates of low flows generated &y water resource

supply models.

e4elop a &usiness case for smart metering

')$*+')L W)$,R (+MM*SS*+' Low flows report series =


11/94

) &usiness case for the use of smart meters on pri4ate di4ersions and other e=tractions could

&e used to identify when and where smart meters are economically ad4antageous to install and

use.

*mpro4e modelling of daily irrigation water use

,stimates of irrigation water use on a daily time-step are poor &ecause they do not account for

irrigator &eha4iour that may &e responding to other dri4ers/ such as allocation announcements

and commodity prices. More sophisticated models are re0uired to reflect the uncertainty in

irrigator &eha4iour.

*mpro4e understanding of seasonal impacts of land use change on low flows

$he seasonal impact of land use change on streamflows is not 4ery well understood/ &ut it is

e=pected the impact will &e greater during lows flows than other parts of the flow regime. $his

proposal will in4estigate seasonal 4ariation in the impact of land use on flows.

Re4iew mechanisms that generate low flows

)n understanding of the mechanisms that generate low flows is re0uired to predict the impact

of climate change scenarios on low flows and to more effecti4ely address issues of stress

during low-flow periods. ) comprehensi4e re4iew of the e=isting literature is re0uired to

summarise the state of %nowledge/ identify %ey gaps and propose a research agenda to

impro4e %nowledge related to the dri4ers of low-flow e4ents.

')$*+')L W)$,R (+MM*SS*+' Low flows report series =i


12/94

Report conte=t$his report is part of a larger series of reports produced for the 'ational Water (ommissionIs Low

lows ;ro?ect Eigure S1H.

igure S17 (onte=t of reports produced in the 'ational Water (ommissionDs Low lows ;ro?ect Egroupone/ teal F modelling-related reportsG group two/ green F Waterlines reportG group three/ orange Fecology-related reportsH.

')$*+')L W)$,R (+MM*SS*+' Low flows report series =ii

Hydrological modelling practices for estimating low flows guidelines

Hydrological modelling practices for estimating low flows stocktake, review and case studies

Low flow hydrological monitoring and modelling needs

Guidance on ecological responses and hydrological modelling for low-flow water planning

Review of literature quantifying ecological responses to low flows

Low flow hydrological classification of Australia

arly warning, compliance and diagnostic monitoring of ecological responses to low flows

!ynthesis of case studies quantifying ecological responses to low flows

leven case study reports quantifying ecological responses to low flows


13/94

*ntroduction

Project scope and approach

Low flows are critical for sustaining ecosystems during dry periods &y maintaining water a4aila&ility

and 0uality. Knowledge of low-flow &eha4iour is increasingly important as water e=traction grows and

as the fre0uency and6or duration of drought conditions increase.

$he 'ational Water (ommission has initiated a low flows pro?ect to pro4ide water planners and

managers with &etter information and tools to achie4e en4ironmental and related o&?ecti4es affected

&y low flows. $his pro?ectIs first stage is a scoping study intended to pro4ide clear direction to the

(ommission on priorities for further wor% in two %ey areas7

a. monitoring and modelling of low flowsG and

&. ecological %nowledge needs related to low flows.

$his report focuses on the first %ey area. *t summarises the limitations/ issues and gaps with respect

to the monitoring and modelling of low flows to inform the setting and assessment of en4ironmental

flow and related o&?ecti4es across )ustralia. *t then proposes potential ways to address these.

$he initial draft was &ased on a literature re4iew and the com&ined e=perience of the authors. $he

pro?ect then sought the input of specialists with %nowledge and e=perience of low-flow hydrology/

water resource supply modelling/ hydraulic modelling/ hydrography and ecology in order to aH confirm

and6or further identify the %ey issues and gaps in current monitoring and modelling of low flows with a

focus on achie4ing en4ironmental flow o&?ecti4es/ and &H recommend solutions to address issues and

fill gaps.

$he proposals Eand gapsH in this report will &e considered and prioritised &y an ad4isory group of

water planners and managers to assess/ for e=ample/ how readily achie4a&le they are/ and whether

state agencies or other institutions already ha4e actions in place to achie4e them. ;riority solutions

will &e progressed in Stage 2 of the Low lows pro?ect.

Report structure

$he information presented in this report is di4ided into two parts.

Part I: Identifying gaps and limitations

) comprehensi4e re4iew of the monitoring and modelling of low flows is pro4ided in ;art *. )R*

re4iewed and de4eloped a list of low-flow indicators that are ecologically rele4ant ERolls et al. 2#1#H.

$he a&ility to measure or estimate these low-flow indicators is discussed in (hapter ,rror7 Reference

source not found.Where4er possi&le and appropriate to the scenario of interest/ low-flow indicators

are calculated using measured historical streamflows. $he effecti4eness of current streamflow

monitoring is re4iewed in (hapter .Where streamflow measurements are not a4aila&le other

modelling techni0ues are re0uired to estimate streamflows and these are addressed in (hapter .*n

(hapter the estimation of low flows in regulated systems is addressed. *n many catchments

anthropogenic influences such as di4ersions/ farm dams/ groundwater e=tractions and land use

changes may affect low flows and these are discussed in (hapter .*n (hapter the methods to

monitor and model the mechanisms that generate low flows are discussed. ,cological processes are

influenced &y the water le4els in a ri4er and the use of hydraulic models to represent low-flow

hydraulics is re4iewed &riefly in (hapter .$he re4iew leads to the identification of appro=imately 3#gaps in e=isting %nowledge and these are listed in (hapter .



14/94

Part II: Identifying solutions

;art ** identifies possi&le solutions to the 3#J gaps identified in ;art *. Solutions to address each gap

are proposed in Section 1.:3. $he 11 %ey gaps and associated solutions arising from the wor%shop

are descri&ed in more detail in Section .:.



15/94

;)R$ *7 *dentifying gaps and limitations

')$*+')L W)$,R (+MM*SS*+' Low flows report series :


16/94

Low-flow indicators

1.1. Introduction

Low-flow periods are a natural feature of )ustralian ri4er systems &ut can &e a period of high stress

for a0uatic ecosystems. ecreasing the magnitude of low flows reduces the a4aila&ility of in-stream

ha&itat/ which can lead to a long-term reduction in the 4ia&ility of populations of flora and fauna.

,=tended durations of ero or cease-to-flow periods can also harm a0uatic ecosystems since they

can result in partial or complete drying of the channel. $his may lead to loss of connecti4ity &etween

pools and e4en complete loss of a0uatic ha&itat. *n regulated ri4er systems the magnitude of low flows

may &e increased as ri4ers are used to con4ey water from a reser4oir to users who re0uire supply -

such alteration to a more persistent flow regime can also ha4e an ecological effect.

Low-flow indicators pro4ide one means to o&?ecti4ely assess the relati4e en4ironmental ris% due to

changes in the low-flow regime. $ypically these assessments loo% at changes in a low-flow indicator

o4er time or as a result of increased anthropogenic influences in a catchment. Low-flow indicators canalso &e used to assess the &enefits of alternati4e in4estment strategies. )ccordingly/ any change in

low-flow indicators can &e used in con?unction with an assessment of corresponding en4ironmental

4alues to help weigh up the &enefits and disad4antages of any strategy that in4ol4es changes to the

flow regime.

) plethora of different hydrological indices has &een de4eloped and used to characterise the flow

regime/ &oth in )ustralia and o4erseas. )s part of the Low lows pro?ect 29 low-flow indicators ha4e

&een identified from a re4iew of literature related to low-flow ecology and indicators &y the )ustralian

Ri4ers *nstitute E)ppendi= )H. $his chapter first discusses how to select and prioritise useful low-flow

indictors ESection1.2H. )s the calculation of indicators typically re0uires a time-series of flow/ the

deri4ation of these time-series is introduced in Section 1.:.

1.2. Prioritisation of low-flow indicators

Many low-flow indicators are a4aila&le to characterise a flow regime and prioritisation of indicators is

usually re0uired &ased on criteria such as7

clarity of the relationship &etween the indictor and an ecological response

ease of measurement of the indicator

sensiti4ity of the indicator to changes in flow &eha4iour

a&ility to meaningfully compare the indicator &etween catchments

a&ility to meaningfully compare the indicator o4er time.

,ach of these criteria is discussed &elow.

1.1.1.larity of the relationship between the indicator and anecological response

)n o4er4iew of the lin%s &etween low-flow indicators and ecological response is presented in

)ppendi= ) to ?ustify each indicator. $he importance of each low-flow indicator may 4ary &etween

regions and this is discussed in the ta&le. $he geographical and regional 4ariation in low-flow metric

redundancy across )ustralia should &e esta&lished.

')$*+')L W)$,R (+MM*SS*+' Low flows report series @


17/94

$he statistical redundancy in the )ppendi= ) indicators should also &e determined since many of the

low-flow indicators presented will &e strongly correlated. +ne re4iew of se4eral studies in4estigating

the issue of interdependence ESma%htin 2##1H recommends that only one low-flow indicator is

re0uired/ howe4er the indicators considered in that re4iew differ from those listed here and initial

studies in the Low low ecology pro?ect Eigure S1H indicate that four to si= indicators can generally

characterise a low-flow regime.

$he indicators included in )ppendi= ) relate to ri4er flow howe4er from an ecological perspecti4e it is

important to consider hydraulic characteristics in con?unction with flow. *t would &e useful to identify

further potential low-flow indicators that relate to hydraulic characteristics Esee (hapter H.

!ase of measurement of the indicator

(alculation of the low-flow indicators in )ppendi= ) is relati4ely straightforward if a time-series of daily

streamflows is a4aila&le. Cowe4er/ deri4ation of the re0uired streamflow datasets presents a

challenging practical pro&lem. *t is the main focus of this re4iew and is introduced in Section 1.:.

+nce a daily time-series of streamflows is de4eloped/ software pac%ages are freely a4aila&le that arecapa&le of calculating most of the low-flow indicators from )ppendi= ). $hese pac%ages include the

Ri4er )nalysis ;ac%age ER);H/ which is a4aila&le as part of the eWater tool%it EMarsh 2##:H/ and

)0ua;a%/ which was de4eloped &y r Rory 'athan and is a4aila&le on the SKM we&site E>ordon et

al. 2##@H. Most of the indicators can &e calculated using these pac%ages directly/ with the e=ception of

the indicators related to antecedent and post low-flow e4ent conditions. $hese indicators could &e

included in a software pac%age if re0uired.

$here are se4eral methods a4aila&le to calculate the Baseflow *nde= EB*H. $he Lynn and Colic% filter

is commonly used. $he results can &e sensiti4e to the digital filter parameters selected &y the

practitioner. Wor% is underway to in4estigate appropriate 4alues to adopt for those parameters.

ue to the nature of the data a4aila&le/ monthly flows are generally more accurate than daily flows.Cowe4er/ ecological responses often occur due to flow e4ents lasting only one or two days/ and

hence the flow indices presented in )ppendi= ) are generally &ased on streamflows at a daily time-

step. $here are two possi&le approaches to address this mismatch. $he first and preferred approach

is to further impro4e the accuracy of daily streamflows. Cowe4er/ in some regions it may not &e

practical to o&tain daily streamflows. *n these regions a second approach may &e re0uired in which

ecological indicators are de4eloped to conform to the a4aila&le monthly data. Cowe4er/ there is little in

the way of monthly indicators that are ecologically meaningful. SKM E2##3H addressed this issue &y

comparing daily and monthly flow indices and found the 4aria&ility in 1# daily indices could &e largely

e=plained &y fi4e monthly indices. *n data-poor regions the use of monthly indices that reflect

ecologically meaningful daily indices may &e re0uired.

"ensiti#ity of the indicator to changes in flow beha#iour

$he traditional approach to assessing flow stress in4ol4es identifying the differences &etween

streamflow &eha4iour under current and natural1flow conditions. $he low-flow indices can &e

calculated using data representing &oth these flow conditions. ) large change in a low-flow indicator

&etween natural and current conditions will represent a higher li%elihood of ecological stress than a

small change. ) more meaningful assessment of ecological stress can &e pro4ided if the change

o&ser4ed in the indicator is put into its hydrologic conte=tG that is/ if the current low-flow indicator is

compared with the range e=perienced under the natural flow regime. *n other words/ the ecological

stress is li%ely to &e greater if the current flow regime sits outside the 4aria&ility o&ser4ed in the

natural flow regime. igure 1illustrates the difference in the impact of a fi=ed reduction in a4erage

1$his is sometimes referred to as the unimpactedI or pre-de4elopmentI condition as it represents the streamflow that would

occur if all anthropogenic e=tractions and di4ersions ceased/ under current Eor possi&ly historicH conditions of land use co4er.



18/94

flows in two systems of differing 4aria&ility. $he same concept can &e applied to other flow indices/

including indices that reflect the magnitude and fre0uency of low flows. SKM E2##3H de4eloped a non-

parametric approach to compare current and natural flow indices in which the degree of flow stress is

standardised &y reference to the cumulati4e e=ceedence distri&ution of the natural flow regime. $he

approach de4eloped &y SKM E2##3H is referred to as the range-standardisedI approach. *t is

ac%nowledged/ howe4er/ that some non-hydrologic stresses in the same ecosystem/ such as poor

water 0uality/ may result in ecosystems &eing more sensiti4e to changes in low flow than would

otherwise ha4e &een the case under natural flow conditions.

)4erage 4alue

Enatural regimeH)4erage 4alue

Enatural regimeH

Range of natural 4alues Range of natural 4alues

$a% Flows of high #ariability $b% Flows of low #ariability

)4erage 4alue

Ecurrent regimeH

)4erage 4alue

Ecurrent regimeH

1ifference &etween natural

and current regime is outside

range of natural 4ariation

1ifference &etween natural

and current regime is well within

range of natural 4ariation

igure 17 *llustration of difference in impact of a fi=ed reduction in a4erage flows on two systems ofdiffering 4aria&ility Ethe a4erage flows under natural and current conditions is the same for &oth cases/&ut the significance of the impacts is greater for &iota adapted to a system of low 4aria&ilityH. Source7SKM E2##3H

&bility to meaningfully compare the indicator between catchments

) comparison of flow stress at the regional scale is often re0uired. Low-flow hydrology 4aries

significantly across )ustralia and is largely characterised &y the com&ination of hydrogeology and

climate. ,4en in those areas that e=perience a similar climate/ it is common to find streams thate=hi&it 4astly different cease-to-flow properties. $he 4aria&ility of flows is considera&ly different across

)ustralia. $he same change in a low-flow indicator at two sites may not result in the same degree of

ecological stress if the sites differ in the degree of 4aria&ility o&ser4ed in the flow regime Esee igure

1H. $he application of the range-standardisedI approach allows comparison across regions with

different flow regimes ! all other stress-related factors &eing e0ual.

&bility to meaningfully compare the indicator o#er time

Low-flow indices are sensiti4e to the length of streamflow record used in the calculations. SKM E2##3H

analysed this sensiti4ity &y loo%ing at the 4ariation in the indicator 4alues calculated using fi4e/ 1#/ 13/

2# and 23 years of data. $he results generally show a mar%ed reduction in standard error in all indicesonce the length of record reaches a&out 13 years. ) similar analysis was underta%en &y Kennard et

al. E2##H/ which also found that 13 years of streamflow data was re0uired to estimate flow indicators.

Cowe4er/ the length of record re0uired to calculate low-flow indicators associated with less fre0uent

e4ents has not &een in4estigated.

1.:. Deri#ing time-series streamflow data

$he deri4ation of low-flow indicators is &ased on a time-series of streamflows. $ypically the indicators

are calculated to represent historical/ natural or current flow conditions. $he method used to deri4ethese streamflows 4aries &etween sites that are7



19/94

gauged 4ersus ungauged

regulated 4ersus unregulated2.

$he general process to deri4e streamflows for each com&ination of these conditions is descri&ed in

this section.

$he process to deri4e streamflows at a gauged and unregulated site is shown in igure 2. $he

gauged streamflows represent the historical conditions Esee (hapter H. $o deri4e a natural time-series

the historical impacts of anthropogenic acti4ities Esuch as e=tractionsH are added &ac% to the gauged

streamflows. $o estimate a time-series of flows representing current conditions/ the anthropogenic

impacts at the current le4el of de4elopment ElodH are su&tracted from the natural time-series.

,stimation of the reduction in streamflows caused &y anthropogenic acti4ities is discussed in (hapter

.

(ease-to-flow e4ents Ewhere there is no flow recorded at the gauging stationH may &e partially due to

anthropogenic acti4ities. *n these cases the natural time-series should e0ual the anthropogenic

effects. )t other times there may &e no water a4aila&le and under natural conditions a cease-to-flow

e4ent would ha4e occurred. *t is difficult to distinguish &etween these two situations and assumptionsmust &e made &y practitioners. *t should also &e ac%nowledged that su&surface connecti4ity may

remain after surface water has ceased to flow and may maintain recharge of refugia/ and that these

flows are not represented in the time-series of streamflows.

Gauged Streamflow

(Chapter 3)

Add Historical

Anthropogenic Effects

(Chapter 6)

Subtract Anthropogenic

Effects at Current lod

(Chapter 6)

Current

FlowsHistorical

Flows

atural

Flows

igure 27 eri4ation of a flow time-series at a gauged and unregulated site

$he process to deri4e streamflows at an ungauged and unregulated site is shown in igure :. )

method is re0uired to estimate the natural flows in the catchment/ such as the use of streamflow

transposition or the application of a catchment model Esee (hapter H. $he historical and current flows

are then estimated &y ta%ing into account the anthropogenic effects.

Estimate of atural Flow

(Chapter !)

Subtract Historical

Anthropogenic Effects(Chapter 6)

Subtract Anthropogenic

Effects at Current lod(Chapter 6)

Current

Flows

Historical

Flows

atural

Flows

2*n Aueensland/ regulated and unregulated water systems are referred to as supplemented and unsupplemented systems

respecti4ely.



20/94

igure :7 eri4ation of a flow time-series at an ungauged and unregulated site

$he process at a regulated site is a little more comple=. >auged streamflows will represent historical

flows at sites with a gauge. Cowe4er/ at other ungauged sites a water resource system model is

re0uired to model the historical impacts. $hese models capture the effect of water supply

infrastructure and operating rules E(hapter H/ and may also &e used to predict flows under current and

pre-de4elopment conditions. )n e0ui4alent natural flow model is re0uired to deri4e natural flows in

these systems.

"ater #esource S$stem %odel

(Chapter &)

#un model with

historical operatingrules and demands

(Chapter &)

#un model with

current operatingrules and demands

(Chapter &)

Current

Flows

Historical

Flows

atural

Flows

Estimate of atural Flow

(Chapter !)

Gauged Streamflow

(Chapter 3)

igure @7 eri4ation of a flow time-series at a regulated site

$he 4arious components of estimating the time-series of flow are co4ered in more detail in chapters

to .

) common theme throughout this report surrounds the difficulties in4ol4ed in estimating a daily time-

series of flow. )t an ungauged location the time-series is su&?ect to a range of model uncertainties

that include model cali&ration and e=trapolation to an ungauged location Echapters and H. ,4en at a

gauged location there is uncertainty in the streamflow measurements E(hapter H. )ll sites are su&?ect

to the uncertainty in estimating anthropogenic influences E(hapter H. )ll of the different sources of

uncertainty will influence the accuracy of the low-flow indicators. et e4en though the accuracy ofindicators depends on many site-specific factors Ee.g. historical gauging or the nature of

anthropogenic influencesH/ some general guidance on their li%ely accuracy could &enefit water

managers. Se4eral case studies could &e underta%en to demonstrate the possi&le magnitude of these

uncertainties. *t should also &e noted that in tropical systems a daily time-series may not &e re0uired

to identify the persistence of refugia &ecause predicta&le low flows occur for e=tended periods.

$he archi4ing of reference natural and current streamflows is currently poor. $hese datasets are

typically prepared on a ri4er-&y-ri4er &asis at different times and &y different people. While they are

generally a4aila&le/ the effort re0uired to o&tain and understand the assumptions &ehind them is

sometimes more difficult than it should &e. $his situation would &e less challenging if sufficient

detailed documentation a&out the model architecture/ cali&ration process and scenario esta&lishment

were readily a4aila&le. Where re4isions to datasets ha4e occurred/ there is not always ade0uate4ersion control/ which creates duplication and the potential for use of superseded datasets. $hese

datasets are highly 4alua&le and ha4e 4arious uses for multiple sta%eholders. ) repository of these

datasets for %ey en4ironmental flow sites/ either centrally stored or distri&uted &ut maintained in a

consistent manner &y local agencies/ could offer greater ease of access and certainty for users of

these datasets. Resourcing of this data pro4ision and storage will &e essential if the same issues are

not to arise in the future.

When archi4ing these datasets/ consistent notes should accompany them to indicate which

anthropogenic influences ha4e specifically &een considered in the deri4ation of naturalI flows/ as well

as a reference to readily a4aila&le technical reports documenting the flow deri4ation.

*n addition to deri4ing low-flow indicators under natural Eor referenceH and current conditions/ the li%ely

changes to low-flow indicators under future scenarios Esuch as climate changeH may &e useful.



21/94

Cowe4er/ the influence of longer-term climate regime 4aria&ility Eor changeH on the low-flow indicators

is not well understood.

1.@. "ummary

) list of hydrological indicators related to low flows has &een compiled E)ppendi= )H. ,=isting software

pac%ages Ee.g. R);H are a4aila&le to calculate most of these indicators. Cowe4er/ the main challenge

in deri4ing these indicators is the generation of a daily time-series of flow that may represent natural/

current or historical conditions. $he methods a4aila&le to generate these time-series 4ary &etween

sites that are gauged6ungauged and regulated6unregulated.

$he %ey gaps and limitations related to low-flow indicators are7

the indices do not ena&le comparison &etween regions

the uncertainty associated with low-flow indicators is not well understood.

+ther gaps and limitations identified in the re4iew are as follows7

most low-flow indicators can &e calculated using e=isting software/ with the e=ception of indicators

related to antecedent and post low-flow e4ent conditions

there are difficulties in deri4ing daily time-series of flow to calculate the flow indicators in data-poor

areas

it is difficult to prioritise adoption of the 29 low-flow indicators

estimation of a natural time-series of flow re0uires assumptions a&out the role of anthropogenic

effects in cease-to-flow e4ents

the length of data re0uired to calculate low-flow indicators associated with less fre0uent e4ents is not

%nown

the influence of longer-term climate regime 4aria&ility Eor changeH on the low-flow indicators is not well

understood

the li%elihood of low-flow e4ents under future scenarios is not well understood

reference natural Eand currentH flows are poorly archi4ed and are usually not readily a4aila&le from

state agencies for ongoing use.

')$*+')L W)$,R (+MM*SS*+' Low flows report series


22/94

Measuring and monitoring low flows

1.3. Introduction

Where they are a4aila&le/ gauged streamflows pro4ide a time-series of historical streamflows. *n

unregulated catchments gauged streamflows are also the &asis for estimating a time-series of

streamflow representati4e of natural and current conditions. $he time-series of streamflows are used

to generate the re0uired low-flow indicators. *n regulated catchments they form the &asis for the

cali&ration of ri4er system models that are used to assess the impacts of management decisions on

flow and usage regimes.

$he most common method of streamflow gauging across )ustralia is &ased on the measurement of

stream le4el and con4ersion to streamflow using a rating cur4e Eor stage discharge relationshipH. $his

method and %ey %nowledge gaps are descri&ed in Section 1.5. $here are few alternati4e techni0ues

a4aila&le ! these are discussed in Sections 2.: and 1.9. inally/ the current limitations and gaps in

e=isting monitoring networ%s are discussed in Section 1..

1.5. "treamflow measurement using a rating cur#e

)t each streamflow gauging site the water le4el is measured fre0uently. $he water le4el is then

con4erted to a flow rate using the rating cur4e. Water le4els &elow a defined threshold will indicate a

cease-to-flow e4ent. $he rating cur4e is constructed &ased on a sample of streamflows measured

using the 4elocity-area method and their corresponding water le4el Ea concurrent streamflow and

water le4el data sample is termed a gaugingIH. $he rating cur4e can &e fit to the gaugings either using

statistical techni0ues or can include some su&?ecti4e ?udgement that may ta%e into account the

influence of the shape of the ri4er cross-section and downstream o&structions. etails of these

methods can &e found in standard hydrology te=t&oo%s Esuch as ingman 1@G Cerschy 193H.

$he uncertainty associated with streamflow measurements depends on the measurement error

associated with the water le4el and uncertainty in the rating cur4e/ which in turn depends on the

num&er of gaugings used to de4elop the rating cur4e and the 4ariation &etween the indi4idual

gaugings. $here is an )ustralian Standard that specifies a method to 0uantify the uncertainty

associated with streamflow measurements EStandards )ustralia 1#H. Se4eral studies ha4e applied

this standard at sites across )ustralia. )t the 81 sites analysed &y +&ey et al. E2##9H in >ippsland

EictoriaH/ the o4erall uncertainty in the 2##3!#5 annual flow was found to range &etween N2 and N2@

per cent/ with the ma?ority &etween N3 and N13 per cent. $he method was also used to assess 1@

streamflow gauges within the Werri&ee Ri4er catchment EictoriaH and the uncertainty in the annual

streamflows during 2##3!#5 ranged from N@ to N@1 per cent of the reported flow ELowe 2##H.

$he uncertainty in streamflow measurements at low flows will 4ary &etween sites. $he uncertainty in

the water le4el measurement will 4ary &etween instrumentation. $he num&er of historical gaugings

made at low flows will influence the uncertainty in the rating cur4e at low flows. $he nature of the

cross-section of the stream is also influential. or a wide ri4er without an incised channel/ a small

change in the water le4el will result in a large proportional change in the discharge at low flows. )s

such/ uncertainty in water le4el measurements can result in a large uncertainty in discharge at low

flows in percentage terms. $echni0ues are a4aila&le to calculate the uncertainty in streamflow

measurements at low flows and the necessary data can generally &e o&tained. Cowe4er/ these

assessments are rarely underta%en and the general user is often unaware of the potential uncertainty

associated with the streamflow measurements.

or 4ery low water le4els it may &e necessary to estimate the streamflow &y e=trapolating the ratingcur4e &eyond the range of gauged flows. )t e=tremely low flows it can &e difficult to o&tain gaugings if

')$*+')L W)$,R (+MM*SS*+' Low flows report series 1#


23/94

the water depth is too low to allow a current meter or the 4elocity is too slow to spin the propeller of

the current meter EScanlon 2##8H. Auality codes are assigned to each streamflow measurement and

will identify measurements that are &ased on an e=trapolation from the rating cur4e.

) streamflow gauge may not &e capa&le of measuring all of the flow at the site. or e=ample/ if the

streamflow measurements are ta%en at a weir/ the measurements may not include any water that

&ypasses the weir through a fish passage or is released as a passing flow. )dditionally/ streamflow

gauges do not measure su&surface flows.

*t is important that periods where a stream ceases to flow are identified through monitoring. )t many

locations there is a control structure such as a 4-notch weir or a natural roc% &ar that ma%es it easy to

identify when there is a cease-to-flow e4ent. Cowe4er/ there may &e difficulties where there is a

natural cross-section and its shape changes o4er time through geomorphological processes.

$he a&ility to monitor low flows 4aries according to the climate/ access and geomorphology of ri4er

systems. *n ri4ers with multiple flow paths/ unsta&le cross-sections and poor access/ it is difficult to

monitor streamflows accurately. $his is e4ident in the remote car&onate a0uifers of tropical northern

)ustralia/ where features such as naturally forming tufa dams in car&onate a0uifer catchments can

lead to low flows appearing to increase throughout the dry season when this is actually not the case.

$he e=tent to which this issue has &een resol4ed and the a&ility to address it with further in4estment in

research or alternati4e monitoring technologies could &e discussed with hydrographers from the

'orthern $erritory epartment of 'atural Resources/ ,n4ironment/ the )rts and Sport E'R,$)SH who

ha4e pre4iously reported this issue. $he 0uality of monitoring is also time- and e4ent-dependent/ as

was e4ident in the post-&ushfire periods in southern )ustralia/ when the mo4ement of ash and

sediment significantly altered channel cross-sections.

1.8. "atellite remote sensing

Monitoring low flows in remote or ungauged catchments presents a serious challenge to waterresource management due to the limited amount of o&ser4ed information on flow &eha4iour and

patterns. *nstalling gauging stations in remote locations can &e costly as well as pro&lematic in terms

of maintenance and ser4icing. urthermore/ stream gauge data represents &eha4iour at a single

point/ and therefore may not represent the total flow in certain circumstances/ such as ri4er &raiding.

Satellite remote sensing could potentially pro4ide much of the information needed to ma%e decisions

on water resources. Stewardson et al. E2##H note se4eral well-de4eloped practical methods for using

satellite remote sensing information to o&ser4e and characterise inundated areas as well as time-

dependent &eha4iour. ) wide range of options are a4aila&le that 4ary in cost/ accuracy and

applica&ility to the particular re0uirements of a pro?ect.

,ssentially/ each method consists of the analysis and interpretation of multispectral satellite imagedata to esta&lish the condition of a study area at a particular point in time. +ften this re0uires some

%nowledge of the particular conditions on the ground/ such as 4egetation and soil type/ which can

affect how the satellite-&ased information is interpreted EStewardson et al. 2##H.

Mapping areas of inundation during a particular flow or flood e4ent can &e analysed in con?unction

with %nowledge of the study areaIs landscape and hydrology to estimate flows. $he analysis of

satellite remote sensing images o4er time can pro4ide &oth short- and long-term information a&out

inundation e=tents. $his process will re0uire cali&ration o4er a period of time to produce useful results.

Cowe4er/ Stewardson et al. E2##H identified se4eral challenges in estimating total inundated area/

and therefore challenges in using satellite-&ased information in estimating flows7



24/94

$here is generally a trade-off &etween temporal and spatial resolution. Stewardson et al. E2##H

identified two satellites/ Landsat $M3 and M+*S/ which can capture medium-scale imagery useful

for estimating inundated areas o4er )ustraliaIs &road and remote semi-arid region:.M+*S is a&le to

capture daily imagery/ &ut it has a spatial resolution of 23# m. $his resolution is li%ely to &e poor at

o&ser4ing low-flow areas since the inundated areas may not &e distinguisha&le at a pi=el scale of 23#

m. $he imagery captured &y Landsat $M3 has a pi=el sie of :# m/ which is a more appropriate scale

for o&ser4ing low flows and those at a ri4er channel scale EStewardson et al. 2##H. Cowe4er/ the

fre0uency of the Landsat $M3 passing is inter4als of 15 days/ which may &e too coarse to o&ser4e

some infre0uent and &rief e4ents that may still &e important in terms of estimating water resources. *n

addition/ &oth satellite sensors using the 4isi&le range of the spectral data will &e inhi&ited &y cloud

co4er that may &e associated with the rainfall and flow e4ents.

$here is also a trade-off &etween spatial resolution and cost. M+*S imagery is a4aila&le freely to

download Ealthough costs associated with the effort re0uired to select and download rele4ant imagery

should &e factored inH. $here is a cost associated with ac0uiring Landsat $M3 imagery and therefore

the num&er of images re0uired needs to &e &alanced against the study area e=tent and &udget

a4aila&le. $he num&er of images re0uired also influences the cost of analysis.

Landsat $M3 imagery is a4aila&le from the mid 19#s through to the present/ with some gaps due todowntime of the satellite operation. *n addition the satellite is well past its intended lifespan and its

future operation is uncertain.

Landsat $M imagery can also &e used to identify water&odies across the landscape. SKM E2##5H

used Landsat $M imagery to identify permanent wetlands in the Wimmera EictoriaH. Se4eral images/

spanning 12!2##3/ were compared to e4aluate their permanency &y monitoring wetland area

changes o4er time. $his data was fed into a geographic information system E>*SH where it was used

to classify wetlands &ased on the presence of water following different meteorological conditions and

at different times of year.

*n semi-arid and arid regions of )ustralia the presence and persistence of water&odies can &e inferred

from the presence of 4egetation. Satellite remote sensing can &e used to detect the location of4egetation o4er time and may pro4e to &e a more efficient way of monitoring the persistence of

water&odies.

*n using satellite remote sensing information to o&ser4e inundation le4els/ the specific re0uirements of

o&ser4ing low flows must &e carefully considered. *t will &e necessary to determine which satellite

data is at an appropriate temporal and spatial resolution to o&ser4e the ri4er channels and inundated

areas/ as well as important changes in flow le4el o4er time. (oarser resolution data such as that of

the M+*S satellite is a4aila&le at daily inter4als. )lthough larger pi=el-sie data is unli%ely to &e a&le

to accurately represent inundated areas/ &y maintaining a continuous se0uence of data and

comparing this with ground o&ser4ations/ a relationship can &e esta&lished &etween spectral

&eha4iour and flow le4els EStewardson et al. 2##H.

$he data-interpretation method must &e considered to ena&le a meaningful result. *t is imperati4e that

sources of error are well understood &efore ma%ing this selection/ such as the effects of cloud co4er/

tur&idity and soil type EStewardson et al. 2##H.

inally/ any remote sensing application must &e 4erified and ground-truthed. Significant effort in

ground-truthing is re0uired for understanding the uncertainty of the data compared with ground-&ased

monitoring. $his would allow the appropriate conte=t to &e placed on information when the resource

manager or sta%eholders are ma%ing decisions that depend on the different data.

:$here are a large num&er of satellites that capture imagery at a range of scales such as Spot/ Auic%&ird and World4iew 2

which capture imagery 1# to 2# m/ 1 to 3 m and O 1 m respecti4ely.



25/94

1.9. 'ther techni(ues for streamflow measurement

Streamflow measurement using a rating cur4e is the most common method/ &ut other techni0ues are

emerging that may pro4ide &etter and more accurate representation of low flows. )lternati4e

techni0ues may &e particularly useful at sites that are influenced &y &ac%water effects/ weeds and

sedimentation/ unsta&le &ed conditions or at which the discharge can 4ary considera&ly with only asmall change in the water le4els.

)coustic Eor ultrasonicH meters are &ased on the measurement of sound signals. $here are two main

types of acoustic meters. $he ultrasonic doppler meter measures the time ta%en for an acoustic signal

sent into the water to &ounce &ac%. $he ultrasonic transit time meter measures the time ta%en for an

acoustic signal to tra4el &etween two transducers. $hese meters measure the 4elocity in the ri4er at a

particular depth. $o measure the flow in a ri4er/ the meter either needs to &e placed at a depth that

represents the a4erage 4elocity/ or meters need to &e placed at se4eral depths EWM+ 2##9H.

,lectromagnetic meters are another alternati4e. $hey pass an electrical current through the meter and

the 4oltage measured is proportional to the 4elocity of the water E)ustralian 'ational (ommittee on

*rrigation and rainage 2##2H. (urrently these technologies do not pro4ide &etter measurements at

low flows than con4entional methods.

*n some cases the water le4el measurement that corresponds to ero or low flows will pro4ide useful

information to assess ecological water re0uirements and estimation of the streamflow is not re0uired.

or e=ample/ monitoring of the water le4els within off-stream water&odies pro4ides information on

their persistence/ &ut these measurements are not widely made.

1.. Monitoring networ)s

,ach state and territory in )ustralia collects streamflow measurements from a networ% of sites

ELadson 2##9H. *t is important that these networ%s are a&le to &e used to measure low flows to

achie4e water plan o&?ecti4es and to set and assess compliance against low-flow di4ersion rules.

Streamflow gauging along a ri4er com&ined with metering of any ma?or off-ta%es should &e

esta&lished at a spatial and temporal scale commensurate with this a&ility. *n the Murray arling

Basin this need has &ecome especially important with the shepherding of water from upstream

tri&utaries such as the arling Ri4er to deli4er ecological outcomes in the lower Murray Ri4er in South

)ustralia. Streamflow gauging &ecomes e4en more important if di4ersions are not monitored during

the e4ent/ so that ri4er operators can assess the 4olume of any losses along the reach. +perators can

then decide whether they fall outside of the range of anticipated losses and thus may &e attri&uta&le

to unauthorised ta%e. *mpro4ing the spatial co4erage and monitoring fre0uency of streamflow gauging

and di4ersions will also help to define low-flow management rules for the en4ironment to a similar

le4el of certainty as those used for supplying consumpti4e users. $his applies &oth to e=isting and

new di4ersions. Seasonal monitoring of low flows and di4ersions would lend much support torecommendations on en4ironmental flows.

rom an ecological measurement perspecti4e/ streamflow gauges Eflow or le4elH would ideally &e

located at ecologically rele4ant locations/ or at least at locations where the flow characteristics were

representati4e of the rele4ant location. *n practice/ factors such as resourcing/ access/ cross sectional

sta&ility and the need for information to manage a water supply system ha4e dri4en the decisions on

the location of streamflow gauges. )n in4entory of important ecological locations that are not currently

gauged could &e assem&led and the practicality and cost6&enefit of monitoring at or near these sites

assessed. $his information could inform future changes to gauging networ%s and encourage

consideration of a0uatic ecosystem management needs.

Real-time information a&out low flows may &e re0uired for management purposes. or e=ample/ anen4ironmental water manager may decide to release water from storage or place a &an on di4erters

')$*+')L W)$,R (+MM*SS*+' Low flows report series 1:


26/94

once the flow in a ri4er falls &elow a particular trigger. Real-time information is a4aila&le at some

locations and is used &y water authorities across )ustralia. Cowe4er/ access to this information is

limited and may not &e a4aila&le to all rele4ant sta%eholders.

ata from e=isting gauging networ%s is a4aila&le 4ia a few different sources/ &ut most states ha4e

made data a4aila&le on the internet ELadson 2##9H. 'ot all of these sites currently pro4ide access to

0uality codes or gauging history/ which would &e useful information for low-flow studies. $he

)ustralian Bureau of Meteorology also plays an important role in data pro4ision and is wor%ing

towards pro4iding an integrated source of information E)ustralian Bureau of Meteorology 2#1#H.

1.1#. "ummary

) networ% of streamflow gauges across )ustralia pro4ides useful information a&out low flows. $he %ey

gaps and limitations related to measuring and monitoring low flows are7

users are unaware of the uncertainty in low-flow streamflow measurements

the streamflows at many important ecological locations are not gauged

real-time flow information is not widely a4aila&le

there are se4eral well-de4eloped practical methods for using satellite remote sensing information to

o&ser4e and characterise inundated areas as well as time-dependent &eha4iour/ &ut ade0uate on-

ground o&ser4ations are re0uired to ground-truth interpretations

the current spatial co4erage and monitoring fre0uency of streamflow gauging and di4ersion metering

may not ade0uately protect water flows to meet ecological needs and o&?ecti4es/ or inform the setting

and compliance of low-flow management rules

the water le4els in off-stream water&odies are important/ &ut not commonly measured.

+ther gaps and limitations identified are7

limited num&er of gaugings a4aila&le during low-flow periods

difficulty measuring 4ery low flows using a current meter

measurement of low flows at unsta&le cross-sections is difficult

the channel is not always well defined and it can &e difficult to determine the low-flow paths

the &enefits of other emerging streamflow measurement technologies in measuring low flows are not

widely understood

the measurement uncertainty associated with water le4els will 4ary &etween different instrumentation

there is flow through fish passages that is not recorded during gauging

current monitoring techni0ues do not pic% up su&surface flow

monitoring needs to &e a&le to identify cease-to-flow e4ents.

')$*+')L W)$,R (+MM*SS*+' Low flows report series 1@


27/94

,stimating low flows at ungauged sites

1.11. Introduction

Low-flow indicators may &e re0uired at ungauged sites. or the purposes of this discussion ungauged

sites may include those with no streamflow data/ or those with some streamflow data that re0uires

infilling or e=trapolation &efore it can &e used for its intended purpose. $here are two main

approaches to de4eloping a time-series of flow at ungauged sites7 streamflow transposition and

catchment modelling EWM+ 2##9H. ) description of streamflow transposition is gi4en in Section 1.12/

followed &y a re4iew of rainfall-runoff models in Section 1.1:. >i4en the uncertainties in estimating a

time-series of daily flows/ an appropriate alternati4e is to estimate the low-flow indicators directly from

catchment characteristics ESection 1.1@H.

)ll of these methods pro4ide results that are notionally representati4e of natural conditions. $o

estimate flows representati4e of historical or current conditions/ the influence of anthropogenic

influences must &e ta%en into account Eigure :H. $he 0uantification of anthropogenic influences isdiscussed in (hapter .

1.12. "treamflow transposition

$he transposition method uses the streamflows recorded at a gauged catchment to estimate the

streamflow at an ungauged site. $he recorded streamflows are factored up or down using a

transposition relationship. *n applying this approach two steps are ta%en. irstly/ the most appropriate

gauged catchment must &e selected and secondly/ a transposition relationship needs to &e

determined.

$he &est results are o&tained when the site selected for transposition is either directly upstream ordownstream of the site of interest EWM+ 2##9H. *f such a site is not a4aila&le/ site selection should &e

&ased on the gauged catchmentIs pro=imity and its hydrological similarity EWM+ 2##9H. Lowe and

'athan E2##5H de4eloped a method for selecting appropriate sites across ictoria. )s it is not possi&le

to measure the hydrological similarity of ungauged catchments/ the similarity of catchments with

regard to characteristics influencing the hydrological regime Esuch as rainfall/ soil permea&ility/ stream

fre0uency/ forest co4erH was used as a surrogate for hydrological similarity. $he selection of these

characteristics was &ased on an analysis of 153 gauged catchments in ictoria ELowe < 'athan/

2##5H.

$he transposition relationship is used to factor the gauged streamflow to represent the ungauged

catchment. *f a short period of gauged data is a4aila&le at the ungauged site/ this should &e used to

calculate the transposition relationship. $he transposition factor can &e &ased on the relati4ecatchment area/ or may also ta%e into account differences in rainfall EWM+ 2##9H. >an/ McMahon

and +I'eil E11H &ased it on the catchment area/ mean annual rainfall and the coefficient of 4ariation

of the annual rainfall. +ther studies ha4e &ased the transposition factor on the ratio of the recorded

mean annual flow at the gauged catchment and an estimate of mean annual flow at the ungauged

catchment ELowe < 'athan 2##5G WM+ 2##9H. Spot flow measurements at the otherwise ungauged

site may &e used to 4erify transposition relationships using other parameters if the spot flow data is

insufficient to de4elop such a relationship.

)s descri&ed a&o4e/ the streamflows at the ungauged location are estimated &y multiplying the

streamflows in the gauged catchment &y a transposition factor. Psing this method/ any cease-to-flow

e4ent Ei.e. ero flowH o&ser4ed at the gauged location will &e assumed at the ungauged location.

$herefore it is important that the gauged and ungauged sites ha4e similar cease-to-flowcharacteristics.



28/94

$he streamflow transposition methods descri&ed a&o4e can &e tailored to low flows. or e=ample/

oorwinde et al. E2##:H allocated gauging stations to more than 15## ictorian catchments for the

purpose of monitoring low flows/ while SKM E1H in4estigated low-flow homogeneity in the

Caw%es&ury-'epean Basin in 'ew South Wales. Cowe4er/ the geologic units that control low-flow

&eha4iour are much more difficult to characterise than the topographic and climatic dri4ers that control

a4erage and high flows. actors that influence low flows ! which are not as important for a4erage or

high flows ! include the distri&ution and infiltration characteristics of soils/ the hydraulic

characteristics and e=tent to the a0uifers/ the rate/ fre0uency and amount of rechargeI ESma%htin

2##1H. $he 0uantification of these factors is an intrinsic difficulty when using streamflow transposition

to estimate low flows. ,4en if the characteristics that determine low flows were understood/ the

adoption of these techni0ues may &e hampered &y limited access to information on catchment

characteristics. ) national co4erage of catchment characteristics may &ecome a4aila&le from the

)ustralian Bureau of Meteorology/ which would resol4e this issue. )nother impediment is the time and

effort re0uired to de4elop procedures to select catchments that ha4e similar low-flow &eha4iour and

transposition factors appropriate for low flows.

1.1:. atchment modelling

*n a rainfall-runoff model a time-series of rainfall and e4aporation is used to estimate streamflows. $o

apply a rainfall-runoff model in an ungauged catchment/ the following steps are underta%en7

1. ) rainfall-runoff model is selected

2. Model parameters are determined for a selection of gauged catchments 4ia cali&ration

:. Model parameters are applied to the ungauged catchment with or without ad?ustment

$he conceptual rainfall-runoff model is used to predict streamflows with the transposed model

parameters and climate data. Cydrologists ha4e focused their attention on refining and impro4ing this

approach for se4eral decades. ) &rief summary of these steps and the remaining gaps in %nowledge

are pro4ided &elow.

Model selection

Many different rainfall-runoff models ha4e &een de4eloped o4er the years. Some of the more

commonly used models ha4e &een compiled into the online Rainfall Runoff Li&rary ERRLH/

http#$$www.tookit.net.au$%oos$&&L'which is maintained &y the eWater (R(/ although the num&er of

models used &y industry and academia e=tends &eyond this list and other models are used outside of

)ustralia.

Rainfall-runoff models 4ary in their structure and the num&er of parameters included in the model. $he

low-flow &eha4iour of these models is commonly controlled &y simplistic conceptual &uc%etsI that arepoorly suited to modelling low-flow &eha4iour at the daily time-step. Low flows/ particularly o4er

e=tended dry periods/ arise from multiple su&surface units that &ecome depleted at different stages.

More comple= models are &etter a&le to model low flows/ howe4er the difficulty in cali&ration is

increased/ as is transposition of the model parameters to ungauged catchments Eas discussed in the

ne=t sectionH. Some of these rainfall-runoff models pro4ide a &etter representation of low flows. or

e=ample/ there are two 4ersions of the )WBM rainfall-runoff model. +ne 4ersion is &etter suited to

estimating low flows and the other high flows and floods EBoughton 2##@H.

$he processes go4erning runoff also 4ary and are different in dry/ arid regions EWei et al. 19H.

,stimation of streamflows in these regions is difficult ELadson 2##9H. $he *C)(R,S model is

considered to &e one appropriate for use in ephemeral catchments ELadson 2##9H. (ostelloe et al.

E2##3H found that a lumped conceptual rainfall-runoff model did not ade0uately represent large arid

http://www.toolkit.net.au/Tools/RRLhttp://www.toolkit.net.au/Tools/RRL


29/94

catchments due to the heterogeneity in characteristics across the catchment. *mpro4ed results were

o&tained using a semi-distri&uted grid-&ased conceptual model.

Specialised models are re0uired to ade0uately model low flows in some specific en4ironments. *n

alpine areas/ for e=ample/ snowmelt affects low-flow &eha4iour and hence rainfall-runoff models

should ideally ha4e a snowmelt module when &eing applied there. Snowmelt algorithms for use in

rainfall-runoff models are widely a4aila&le in &oth ,urope and 'orth )merica. Similarly in catchments

with mi=ed geology/ the a&ility to accurately model low flows with many rainfall-runoff models can &e

poor. $he a4aila&ility of only a single groundwater discharge parameter in S*MC was noted as a

potential limitation in modelling car&onate a0uifer catchments in northern )ustralia/ for e=ample/

where groundwater discharge can operate at two speeds ! depending on the storage content of

car&onate and non-car&onate a0uifers during the dry season ESKM 2##8H.

(om&ined hydrologic and hydrogeologic models ha4e &een de4eloped and applied in isolated cases

in recent years. $hese models present the opportunity to &etter model surface water6groundwater

interaction processes at low flows/ &ut are currently highly parameterised and are not supported &y

ade0uate input data. *nput data re0uirements can &e significantly greater for these models than

traditional rainfall-runoff models. (omputing speed and storage has traditionally also &een a pro&lemwith these models/ &ut this has impro4ed mar%edly in recent times.

) few studies ha4e in4estigated the relati4e performance of models in estimating low flows and in

ephemeral catchments Ee et al. 18H. While there appears to &e an understanding of the relati4e

strengths and wea%ness of the common rainfall-runoff models among e=perienced hydrologists/ the

pro4ision of clear guidance in the RRL would go a long way to fostering a wider appreciation.

Model calibration

uring model cali&ration the parameter 4alues are selected to find the &est fit &etween the estimated

and o&ser4ed streamflows. +&?ecti4e functions measure model performance and can &e used to

select model parameters. $he following o&?ecti4e functions are commonly used for a cali&ration thatfocuses on fitting to low flows ELadson 2##9H7

sum of s0uare roots

sum of s0uares of differences of s0uare roots

sum of s0uares of differences of 4alues raised to the power of #.2

sum of a&solute differences of logs.

$hese o&?ecti4e functions are included in a4aila&le rainfall-runoff pac%ages Esuch as those in the RRLH

and are easily adopted. While these o&?ecti4e functions are commonly used/ there has &een no formal

testing of their ade0uacy.

(ali&ration also relies on the s%ill of the modeller to specifically match the proportion of time with

cease-to-flow/ the flow duration cur4e and &aseflow recession cur4e. )utomated procedures for

cali&ration that use o&?ecti4e functions ha4e significantly reduced processing times for cali&ration/ &ut

at present are generally una&le to achie4e the same le4el of accuracy as manual cali&rations.

)s with any model/ the relia&ility of the results will depend on the length of data a4aila&le for

cali&ration and how well the cali&ration data represents the conditions that the model is &eing used to

predict. ) model cali&rated o4er a period of low flows will pro4ide a &etter estimate of low flows than a

model cali&rated o4er a period of high flows. $he transparency of the model cali&ration approach and

how the results are reported can 4ary.

$he shift in climate in south-eastern and south-western )ustralia during the past 1# to :# years has

created some uncertainties in the accuracy of pre4iously cali&rated rainfall-runoff models. Models that



30/94

were cali&rated to data collected &efore the climate shift often o4er-estimate low flows in more recent

periods. $his is possi&ly due to a shift in the relationship &etween rainfall and runoff as a result of

changes in soil moisture and plant upta%e and use of water. $he inter-annual rainfall conditions that

affect soil moisture and groundwater stores are outside of the historical conditions of the cali&ration

period. ) re4iew of the cali&ration period of rainfall-runoff models across southern )ustralia and a

recali&ration of those models to more recent data should &e underta%en where this has not already

occurred. Pnderstanding the relationship &etween e4apotranspiration and temperature/ which is still

&eing de&ated in )ustralia/ will ha4e important implications for &oth the parameterisation and

cali&ration of rainfall-runoff models under climate change conditions.

Transposition of model parameters

*f a period of gauged streamflow record is a4aila&le at the site/ the model parameters are deri4ed

thorough cali&ration of the model to the a4aila&le data. *n locations where no streamflow record e=ists/

the model parameters need to &e transposed from a gauged catchment. Se4eral approaches ha4e

&een trialled and used to transpose model parameters from a gauged to an ungauged catchment.

$hese include adopting model parameters from near&y gauged catchments Ee.g. Mer < Bloschl

2##@G ;ost et al. 2##8H or de4eloping prediction e0uations that lin% indi4idual model parameters tophysical catchment characteristics EMc*ntyre et al. 2##3G Sei&ert 1G Wagener < Wheater 2##5H.

Rather than estimate model parameters indi4idually/ more recently attempts ha4e &een made to

transfer entire sets of model parameters &ased on the similarity of the gauged and ungauged

catchments Ee.g. Bardossy 2##8G Mc*ntyre et al. 2##3G Reichl et al. 2##5/ 2##8H.

Se4eral attempts ha4e &een made to reduce the influence of parameter uncertainty on the prediction

of runoff. Simple rainfall-runoff models ha4e &een de4eloped with few parameters to eliminate any

inter-dependencies Ee.g. "ayasuriya et al. 11/ 1@H. )ttempts at parameter regression using these

models ha4e reported impro4ements Ee.g. Boughton 19@G "ayasuriya et al. 1@G 'athan et al. 15G

;ara?%a et al. 2##8H. $he approach de4eloped &y 'athan et al. E15H was used to estimate flows

across ictoria as an input to determining &ul% water entitlements and pro4ides a practical e=ample of

model parameter transposition.

espite the considera&le effort de4oted to this area/ there are still su&stantial uncertainties associated

with ungauged runoff estimated using rainfall-runoff models ESi4apalan 2##:H. $he difficulties in

predicting runoff in ungauged &asins has &een attri&uted to the uncertainty in the cali&rated model

predictions EBardossy 2##8G Reichl et al. 2##8H/ the heterogeneity of runoff processes and catchment

characteristics ESi4apalan 2##:H/ the use of non-representati4e physical catchment characteristics

E;ara?%a et al. 2##8H/ uncertainty in the catchment characteristics/ and uncertainty in the input data

and model structure EReichl et al. 2##8H.

1.1@. Direct estimation of low-flow indicators

>i4en the uncertainties associated with estimating a time-series of natural daily flows at an ungauged

location/ it may &e more appropriate to directly estimate the low-flow indicators in these catchments

&ased on catchment characteristics such as climate/ hydrogeology/ soils/ topography and land use.

$his approach could &e applied across )ustralia and applied to a range of low-flow indicators. $he

Low fow "anuaEWM+ 2##9H pro4ides a comprehensi4e description of the methodology and

e=amples of its application. irect estimation of low-flow indicators was most recently underta%en for

the 'orthern )ustralia Sustaina&le ields E')SH pro?ect and has also &een underta%en for south-

eastern and south-western )ustralia.

irect estimation of low-flow indicators is helped &y %nowledge of cease-to-flow conditions in any

gi4en ri4er. $his can &e informed &y spot measurements during e=treme droughts or in some cases

&y anecdotal e4idence from water utility operators and ri4er managers. Ca4ing access to this

information would also &e useful to indicate li%ely refuges for ecosystems during low-flow periods and



31/94

could &e coupled with remote sensing information to indicate the presence or a&sence of permanent

pools during e=treme droughts. $he 2##5!#8 drought in south-eastern )ustralia e4ent could &e

analysed.

1.13. omparison of techni(ues

) comparison &y (S*R+ and SKM of direct estimation of low-flow indicators through regional

regression 4ersus estimation &y transposition of rainfall-runoff models &y nearest neigh&our/ indicated

that while &oth methods were similarly accurate for medium to high flows/ direct estimation performed

&etter for low flow indicators. $he disad4antage of this approach is that it does not pro4ide a time-

series of data/ &ut can &e useful to condition rainfall-runoff modelling results/ as demonstrated in the

')S pro?ect.

irect transposition of streamflow data and rainfall-runoff models &oth suffer from pro&lems

associated with the spatial representation of rainfall. )ny research into &etter spatial representation of

time-series rainfall data/ such as the use of radar or other technologies/ will ser4e to impro4e rainfall-

runoff modelling/ including in low-flow periods Ee.g. low-flow fresh e4entsH.

irect transposition also suffers from potential differences in &aseflow recession &eha4iour. or short

periods of missing data/ alternati4e techni0ues for infilling data may &e warranted/ &ut at present there

are no readily a4aila&le tools to help with this. or e=ample/ in a period of no rainfall/ using an

e=ponential &aseflow recession cur4e from the last gauged reading to the ne=t a4aila&le one will

perform significantly &etter than either transposition or rainfall-runoff modelling.

$he techni0ues presented are not useful for modelling in-stream storage &eha4iour after flows ha4e

ceased. or e=ample/ a rainfall-runoff model does not identify low-flow refuges and is not suita&le for

modelling the persistence of a waterhole. *n these instances other types of models are re0uired.

1.15. "ummary

$wo methods to estimate a time-series of natural flow at an ungauged location are presented a&o4e.

Both approaches rely on a series of assumptions/ including the selection of a representati4e gauged

catchment. >i4en the uncertainties associated with these methods/ it may &e more appropriate to

estimate the low-flow indicators directly from catchment characteristics.

$he %ey gaps and limitations related to estimating flows at ungauged locations are7

the relati4e a&ility of commonly a4aila&le rainfall-runoff models to represent low flows is not widely

understood

no study has &een conducted to determine which o&?ecti4e functions should &e used to cali&rate tolow flows.

+ther gaps and limitations identified in the re4iew are as follows7

the catchment characteristics that control low-flow &eha4iour are difficult to identify and characterise

a method to rapidly determine the hydrological similarity of catchments with respect to low flows is not

a4aila&le

transposition methods tend to &e &ased on transposition factors related to the a4erage flow

the shift in climate in south-eastern and south-western )ustralia during the past 1# to :# years has

created some uncertainties in the accuracy of pre4iously cali&rated rainfall-runoff models

the selection of catchment model parameters for ungauged catchments introduces uncertainty



32/94

a su&stantial amount of effort is re0uired to ade0uately estimate a time-series of daily streamflows at

an ungauged site

the location of perennial stream reaches and low-flow refuges for in-stream &iota are not always

%nown

rainfall-runoff models are not useful for modelling processes at a small scale Ee.g. waterholeH.

')$*+')L W)$,R (+MM*SS*+' Low flows report series 2#


33/94

,stimating low flows in regulated systems

1.18. Introduction

$he method adopted to estimate low flows in a regulated water supply system can 4ary &etween flows

re0uired to represent historical/ current and natural scenarios Eigure @H. ue to the need to capture

the comple= management arrangements that e=ist in regulated systems/ a hydrologic ri4er system

model is often re0uired to represent flows under pre- and current de4elopment.

) comprehensi4e re4iew of the limitations of water

Documents

Modelling Gaps hydraulic