Low-flow hydrological monitoring and
modelling gaps
D. Barma1 and L.Lowe2
1. Barma Water Resources
2. Sinclair Knight Merz
Low flows report series – June 2012
Low flows report series
This paper is part of a series of works commissioned by the National Water Commission on key water
issues. This work was undertaken by Barma Water Resources and Sinclair Knight Merz Ltd on behalf
of the National Water Commission.
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© Commonwealth of Australia 2012
This work is copyright.
Apart from any use as permitted under the Copyright Act 1968, no part may be reproduced by any
process without prior written permission.
Requests and enquiries concerning reproduction and rights should be addressed to the
Communications Director, National Water Commission, 95 Northbourne Avenue, Canberra ACT 2600
or email bookshop@nwc.gov.au.
Online/print: ISBN: 978-1-921853-86-9
Published by the National Water Commission
95 Northbourne Avenue
Canberra ACT 2600
Tel: 02 6102 6000
Email: enquiries@nwc.gov.au
Date of publication: June 2012
An appropriate citation for this report is: Barma D & Lowe L 2012, Low-flow hydrological monitoring
and modelling gaps, National Water Commission, Canberra.
Disclaimer
This paper is presented by the National Water Commission and does not necessarily reflect the views
or opinions of the Commission.
NATIONAL WATER COMMISSION — Low flows report series
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Contents
Contents ................................................................................................................................................ v
Executive summary ............................................................................................................................. vii
Report context ....................................................................................................................................... x
Introduction........................................................................................................................................... 1
Project scope and approach ...................................................................................................... 1
Report structure ......................................................................................................................... 1
PART I: Identifying gaps and limitations .............................................................................................. 3
1.Low-flow indicators ............................................................................................................................ 4
1.1.Introduction .......................................................................................................................... 4
1.2.Prioritisation of low-flow indicators ....................................................................................... 4
1.3.Deriving time-series streamflow data................................................................................... 7
1.4.Summary.............................................................................................................................. 9
2.Measuring and monitoring low flows ............................................................................................... 10
2.1.Introduction ........................................................................................................................ 10
2.2.Streamflow measurement using a rating curve ................................................................. 10
2.3.Satellite remote sensing .................................................................................................... 11
2.4.Other techniques for streamflow measurement ................................................................. 13
2.5.Monitoring networks ........................................................................................................... 13
2.6.Summary............................................................................................................................ 14
3.Estimating low flows at ungauged sites .......................................................................................... 15
3.1.Introduction ........................................................................................................................ 15
3.2.Streamflow transposition ................................................................................................... 15
3.3.Catchment modelling ......................................................................................................... 16
3.4.Direct estimation of low-flow indicators.............................................................................. 18
3.5.Comparison of techniques ................................................................................................. 19
3.6.Summary............................................................................................................................ 19
4.Estimating low flows in regulated systems...................................................................................... 21
4.1.Introduction ........................................................................................................................ 21
4.2.Water resource system models ......................................................................................... 21
4.3.Summary............................................................................................................................ 23
5.Quantifying anthropogenic influences ............................................................................................. 25
5.1.Introduction ........................................................................................................................ 25
5.2.Direct extractions ............................................................................................................... 25
5.3.Farm dams ......................................................................................................................... 26
5.4.Groundwater extractions .................................................................................................... 26
5.5.Land use change ............................................................................................................... 26
5.6.Wastewater treatment plant discharges ............................................................................ 27
5.7.Summary............................................................................................................................ 27
6.Mechanisms generating low flows .................................................................................................. 29
6.1.Introduction ........................................................................................................................ 29
6.2.Identifying and monitoring sources of low flow .................................................................. 29
6.3.Modelling ............................................................................................................................ 29
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6.4.Summary............................................................................................................................ 30
7.Hydraulic characteristics ................................................................................................................. 31
7.1.Introduction ........................................................................................................................ 31
7.2.Hydraulic modelling............................................................................................................ 31
7.3.Summary............................................................................................................................ 32
8.Summary of issues and gaps .......................................................................................................... 33
PART II: Identifying solutions ............................................................................................................. 37
9.Proposed solutions .......................................................................................................................... 38
9.1.Introduction ........................................................................................................................ 38
9.2.Proposed solutions ............................................................................................................ 38
9.3.Key proposed solutions ..................................................................................................... 44
Appendices ........................................................................................................................................ 49
References ......................................................................................................................................... 79
Tables
Table 1: Water resource system models ............................................................................................ 21
Table 2: Summary of identified gaps for monitoring and modelling low flows .................................... 34
Table 3: Summary of solutions to gaps in monitoring and modelling low flows .................................. 39
Figures
Figure S1: Context of reports produced for the National Water Commission's Low Flows Project. ......x
Figure 1: Illustration of difference in impact of a fixed reduction in average flows on two systems
of differing variability (the average flows under natural and current conditions is the same for
both cases, but the significance of the impacts is greater for biota adapted to a system of low
variability). Source: SKM (2005) .................................................................................................... 6
Figure 2: Derivation of a flow time-series at a gauged and unregulated site ........................................ 7
Figure 3: Derivation of a flow time-series at an ungauged and unregulated site.................................. 8
Figure 4: Derivation of a flow time-series at a regulated site ................................................................ 8
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Executive summary
The National Water Commission’s low flows project aims to provide water planners and managers
with better information and tools to manage low flows. The first stage of the project is a scoping study
intended to provide clear direction to the Commission on priorities for further work in two key areas: 1)
monitoring and modelling of low flows and, 2) ecological knowledge needs with respect to low flows.
This report covers the first area, summarising gaps and limitations with respect to monitoring and
modelling low flows and proposing possible solutions to address these. It is intended that the
solutions presented will be refined, prioritised and improved through consultation with the project
advisory group. The outcomes will set the direction for further work in Stage 2 of the low flows project.
Part 1 of this report identifies and discusses seven groups of gaps and limitations associated with
monitoring and modeling low flows, as highlighted in bold text below.
Low-flow indicators provide one means to objectively assess risks due to changes in the low-flow
regime. A plethora of different hydrological indicators has been developed and used to characterise a
flow regime, both in Australia and overseas, and 28 ecologically-relevant hydrological indicators have
been identified here that characterise low flow at a site (Appendix A). Calculating low-flow indicators is
relatively straightforward if a time-series of daily streamflows is available, however the derivation of
daily streamflow datasets presents a challenging practical problem.
Key issues and gaps associated with generating streamflow datasets are:
 Measuring low flows to assist in achieving environmental and other objectives that are affected by
low flows is difficult compared to measuring average flows. For example streamflow gauging using
a rating curve is subject to large errors at low flows and alternative gauging techniques, such as
ultrasonic meters, may provide a more accurate alternative. Also the current spatial coverage and
monitoring frequency of streamflows and diversions, and of any management rules associated with
these, may be inadequate to measure and hence safeguard the flow regime provided to meet the
ecological needs described in water plans. From an ecological measurement perspective,
streamflow gauges would ideally be located at ecologically relevant locations, or at least at
locations where the flow characteristics were representative of the relevant location. Historically
this has not been the case with the location of streamflow gauges typically being driven by the
needs of managing a water supply for extractive users as opposed to the environment.
 A substantial amount of effort is required to adequately estimate a time-series of daily
streamflows at an ungauged site. Rainfall-runoff models are commonly used to estimate
streamflows, but the relative ability of widely available rainfall-runoff models to represent low flows
and the best approach to calibrate them for low flows is not widely understood.
 The main limitation of using water resource system models to estimate low flows at a
regulated site is the poor representation of river losses and daily operating rules in these models.
The focus of model calibration is also an important factor in the accuracy of the low flows modelled
at the sites of interest.
 There are difficulties in deriving daily time-series of flow that represent historical, current and
natural conditions. The main challenge relates to the quantification of anthropogenic influences
on streamflows.
Planners and managers need to understand the mechanisms that generate low flows. The
prediction of low flows under possible scenarios (e.g. climate change) will be improved if the
processes that produce low flows are better understood. Water managers would be able to more
efficiently address issues of stress during low-flow periods if the drivers of these events were known.
However, the mechanisms that generate low flows are generally not well understood. Recently there
have been developments in combined groundwater and surface water modelling, but there have been
few studies to monitor surface water/groundwater interactions.
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From an ecological perspective it is important to consider the magnitude of low flows in conjunction
with the hydraulic characteristics of the stream. Considerable time and expense is required to
understand the hydraulic characteristics of a stream and at present little information is available to
help water managers understand the longevity of pools during a cease-to-flow event. Due to the
difficulty in obtaining hydraulic information, low-flow indicators have typically been used as a surrogate
for hydraulic information.
Part 2 of the report briefly identifies possible solutions to the 50+ gaps identified in Part 1. It then
describes 11 proposed solutions to address key low flows gaps and needs in more detail. These were
identified and developed with the assistance of input from a workshop involving specialists with
knowledge and experience of low-flow hydrology, water resource supply modelling, hydraulic
modelling, hydrography and ecology. The proposals are:
 Develop low-flow indicators for regional comparison
Being able to compare a flow regime at the regional scale is often required. A rangestandardised approach has been adopted in other studies of flow indicators and the concepts
developed in these studies should be applied to low-flow indicators to enable regional
comparisons.
 Improve awareness of the uncertainty associated with low-flow indicators
The derivation 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 benefit from assistance with likely
accuracy and ways to decrease uncertainty. The outcome of this proposal is clear guidance on
the likely magnitude of uncertainty in low-flow indicators; methods and tools to quantify the
uncertainty; an understanding of the main factors contributing to the uncertainty; as well as
guidelines for using this information to improve decision making.
 Improve the availability of streamflow information and metadata
Streamflow information should be readily available and metadata provided to allow planners
and managers to assess whether streamflows measured or modelled at a site are suitable for a
particular purpose. A database of all Australian streamflow gauges that allows users to assess
the suitability of data for a particular purpose should be the result of this proposal.
 Increase metering and monitoring of ecologically relevant sites
Not all ecologically relevant sites are currently metered. This proposal would identify
ecologically relevant sites that are not currently monitored and assess the benefit of metering
compared with the investment required.
 Develop guidelines for estimating low flows
The outcome of this proposal will be guidelines that recommend an appropriate model selection
and calibration strategy for low flows, leading to improved modelling of low flows.
 Improve understanding of the location and longevity of pools and waterholes
At present little information is available to help water managers understand the longevity of
pools during a cease-to-flow event. This proposal will map the location of pools and waterholes
and develop models to predict the persistence of these waterbodies.
 Improved representation of losses in water resource supply models
Guidelines that outline best practice are required to improve the representation of losses in
these models. Adoption of a consistent and improved modelling approach will give planners
and managers greater confidence in the estimates of low flows generated by water resource
supply models.
 Develop a business case for smart metering
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A business case for the use of smart meters on private diversions and other extractions could
be used to identify when and where smart meters are economically advantageous to install and
use.
 Improve modelling of daily irrigation water use
Estimates of irrigation water use on a daily time-step are poor because they do not account for
irrigator behaviour that may be responding to other drivers, such as allocation announcements
and commodity prices. More sophisticated models are required to reflect the uncertainty in
irrigator behaviour.
 Improve understanding of seasonal impacts of land use change on low flows
The seasonal impact of land use change on streamflows is not very well understood, but it is
expected the impact will be greater during lows flows than other parts of the flow regime. This
proposal will investigate seasonal variation in the impact of land use on flows.
 Review mechanisms that generate low flows
An understanding of the mechanisms that generate low flows is required to predict the impact
of climate change scenarios on low flows and to more effectively address issues of stress
during low-flow periods. A comprehensive review of the existing literature is required to
summarise the state of knowledge, identify key gaps and propose a research agenda to
improve knowledge related to the drivers of low-flow events.
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Report context
This report is part of a larger series of reports produced for the National Water Commission’s Low
Flows Project (Figure S1).
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
Low flow hydrological classification of Australia
Early warning, compliance and diagnostic monitoring of ecological responses to low flows
Review of literature quantifying ecological responses to low flows
Synthesis of case studies quantifying ecological responses to low flows
Eleven case study reports quantifying ecological responses to low flows
Figure S1: Context of reports produced in the National Water Commission's Low Flows Project (group
one, teal = modelling-related reports; group two, green = Waterlines report; group three, orange =
ecology-related reports).
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Introduction
Project scope and approach
Low flows are critical for sustaining ecosystems during dry periods by maintaining water availability
and quality. Knowledge of low-flow behaviour is increasingly important as water extraction grows and
as the frequency and/or duration of drought conditions increase.
The National Water Commission has initiated a low flows project to provide water planners and
managers with better information and tools to achieve environmental and related objectives affected
by low flows. This project’s first stage is a scoping study intended to provide clear direction to the
Commission on priorities for further work in two key areas:
a. monitoring and modelling of low flows; and
b. ecological knowledge needs related to low flows.
This report focuses on the first key area. It summarises the limitations, issues and gaps with respect
to the monitoring and modelling of low flows to inform the setting and assessment of environmental
flow and related objectives across Australia. It then proposes potential ways to address these.
The initial draft was based on a literature review and the combined experience of the authors. The
project then sought the input of specialists with knowledge and experience of low-flow hydrology,
water resource supply modelling, hydraulic modelling, hydrography and ecology in order to a) confirm
and/or further identify the key issues and gaps in current monitoring and modelling of low flows with a
focus on achieving environmental flow objectives, and b) recommend solutions to address issues and
fill gaps.
The proposals (and gaps) in this report will be considered and prioritised by an advisory group of
water planners and managers to assess, for example, how readily achievable they are, and whether
state agencies or other institutions already have actions in place to achieve them. Priority solutions
will be progressed in Stage 2 of the Low Flows project.
Report structure
The information presented in this report is divided into two parts.
Part I: Identifying gaps and limitations
A comprehensive review of the monitoring and modelling of low flows is provided in Part I. ARI
reviewed and developed a list of low-flow indicators that are ecologically relevant (Rolls et al. 2010).
The ability to measure or estimate these low-flow indicators is discussed in Chapter Error! Reference
source not found.. Wherever possible and appropriate to the scenario of interest, low-flow indicators
are calculated using measured historical streamflows. The effectiveness of current streamflow
monitoring is reviewed in Chapter 2. Where streamflow measurements are not available other
modelling techniques are required to estimate streamflows and these are addressed in Chapter 3. In
Chapter 4 the estimation of low flows in regulated systems is addressed. In many catchments
anthropogenic influences such as diversions, farm dams, groundwater extractions and land use
changes may affect low flows and these are discussed in Chapter 5. In Chapter 6 the methods to
monitor and model the mechanisms that generate low flows are discussed. Ecological processes are
influenced by the water levels in a river and the use of hydraulic models to represent low-flow
hydraulics is reviewed briefly in Chapter 7. The review leads to the identification of approximately 50
gaps in existing knowledge and these are listed in Chapter 8.
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Part II: Identifying solutions
Part II identifies possible solutions to the 50+ gaps identified in Part I. Solutions to address each gap
are proposed in Section 9.2. The 11 key gaps and associated solutions arising from the workshop are
described in more detail in Section 9.3.
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PART I: Identifying gaps and limitations
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1. Low-flow indicators
1.1. Introduction
Low-flow periods are a natural feature of Australian river systems but can be a period of high stress
for aquatic ecosystems. Decreasing the magnitude of low flows reduces the availability of in-stream
habitat, which can lead to a long-term reduction in the viability of populations of flora and fauna.
Extended durations of zero or cease-to-flow periods can also harm aquatic ecosystems since they
can result in partial or complete drying of the channel. This may lead to loss of connectivity between
pools and even complete loss of aquatic habitat. In regulated river systems the magnitude of low
flows may be increased as rivers are used to convey water from a reservoir to users who require
supply - such alteration to a more persistent flow regime can also have an ecological effect.
Low-flow indicators provide one means to objectively assess the relative environmental risk due to
changes in the low-flow regime. Typically these assessments look at changes in a low-flow indicator
over time or as a result of increased anthropogenic influences in a catchment. Low-flow indicators can
also be used to assess the benefits of alternative investment strategies. Accordingly, any change in
low-flow indicators can be used in conjunction with an assessment of corresponding environmental
values to help weigh up the benefits and disadvantages of any strategy that involves changes to the
flow regime.
A plethora of different hydrological indices has been developed and used to characterise the flow
regime, both in Australia and overseas. As part of the Low Flows project 28 low-flow indicators have
been identified from a review of literature related to low-flow ecology and indicators by the Australian
Rivers Institute (Appendix A). This chapter first discusses how to select and prioritise useful low-flow
indictors (Section 1.2). As the calculation of indicators typically requires a time-series of flow, the
derivation of these time-series is introduced in Section 1.3.
1.2. Prioritisation of low-flow indicators
Many low-flow indicators are available to characterise a flow regime and prioritisation of indicators is
usually required based on criteria such as:

clarity of the relationship between the indictor and an ecological response

ease of measurement of the indicator

sensitivity of the indicator to changes in flow behaviour

ability to meaningfully compare the indicator between catchments

ability to meaningfully compare the indicator over time.
Each of these criteria is discussed below.
1.2.1. Clarity of the relationship between the indicator and an
ecological response
An overview of the links between low-flow indicators and ecological response is presented in
Appendix A to justify each indicator. The importance of each low-flow indicator may vary between
regions and this is discussed in the table. The geographical and regional variation in low-flow metric
redundancy across Australia should be established.
The statistical redundancy in the Appendix A indicators should also be determined since many of the
low-flow indicators presented will be strongly correlated. One review of several studies investigating
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the issue of interdependence (Smakhtin 2001) recommends that only one low-flow indicator is
required, however the indicators considered in that review differ from those listed here and initial
studies in the Low Flow ecology project (Figure S1) indicate that four to six indicators can generally
characterise a low-flow regime.
The indicators included in Appendix A relate to river flow however from an ecological perspective it is
important to consider hydraulic characteristics in conjunction with flow. It would be useful to identify
further potential low-flow indicators that relate to hydraulic characteristics (see Chapter 7).
1.2.2. Ease of measurement of the indicator
Calculation of the low-flow indicators in Appendix A is relatively straightforward if a time-series of daily
streamflows is available. However, derivation of the required streamflow datasets presents a
challenging practical problem. It is the main focus of this review and is introduced in Section 1.3.
Once a daily time-series of streamflows is developed, software packages are freely available that are
capable of calculating most of the low-flow indicators from Appendix A. These packages include the
River Analysis Package (RAP), which is available as part of the eWater toolkit (Marsh 2003), and
AquaPak, which was developed by Dr Rory Nathan and is available on the SKM website (Gordon et
al. 2004). Most of the indicators can be calculated using these packages directly, with the exception of
the indicators related to antecedent and post low-flow event conditions. These indicators could be
included in a software package if required.
There are several methods available to calculate the Baseflow Index (BFI). The Lynn and Holick filter
is commonly used. The results can be sensitive to the digital filter parameters selected by the
practitioner. Work is underway to investigate appropriate values to adopt for those parameters.
Due to the nature of the data available, monthly flows are generally more accurate than daily flows.
However, ecological responses often occur due to flow events lasting only one or two days, and
hence the flow indices presented in Appendix A are generally based on streamflows at a daily timestep. There are two possible approaches to address this mismatch. The first and preferred approach
is to further improve the accuracy of daily streamflows. However, in some regions it may not be
practical to obtain daily streamflows. In these regions a second approach may be required in which
ecological indicators are developed to conform to the available monthly data. However, there is little in
the way of monthly indicators that are ecologically meaningful. SKM (2005) addressed this issue by
comparing daily and monthly flow indices and found the variability in 10 daily indices could be largely
explained by five monthly indices. In data-poor regions the use of monthly indices that reflect
ecologically meaningful daily indices may be required.
1.2.3. Sensitivity of the indicator to changes in flow behaviour
The traditional approach to assessing flow stress involves identifying the differences between
streamflow behaviour under current and natural 1 flow conditions. The low-flow indices can be
calculated using data representing both these flow conditions. A large change in a low-flow indicator
between natural and current conditions will represent a higher likelihood of ecological stress than a
small change. A more meaningful assessment of ecological stress can be provided if the change
observed in the indicator is put into its hydrologic context; that is, if the current low-flow indicator is
compared with the range experienced under the natural flow regime. In other words, the ecological
This is sometimes referred to as the ‘unimpacted’ or ‘pre-development’ condition as it represents the streamflow that would
occur if all anthropogenic extractions and diversions ceased, under current (or possibly historic) conditions of land use cover.
1
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stress is likely to be greater if the current flow regime sits outside the variability observed in the
natural flow regime. Figure 1 illustrates the difference in the impact of a fixed reduction in average
flows in two systems of differing variability. The same concept can be applied to other flow indices,
including indices that reflect the magnitude and frequency of low flows. SKM (2005) developed a nonparametric approach to compare current and natural flow indices in which the degree of flow stress is
standardised by reference to the cumulative exceedence distribution of the natural flow regime. The
approach developed by SKM (2005) is referred to as the ‘range-standardised’ approach. It is
acknowledged, however, that some non-hydrologic stresses in the same ecosystem, such as poor
water quality, may result in ecosystems being more sensitive to changes in low flow than would
otherwise have been the case under natural flow conditions.
Figure 1: Illustration of difference in impact of a fixed reduction in average flows on two systems of
differing variability (the average flows under natural and current conditions is the same for both cases,
but the significance of the impacts is greater for biota adapted to a system of low variability). Source:
SKM (2005)
1.2.4. Ability to meaningfully compare the indicator between
catchments
A comparison of flow stress at the regional scale is often required. Low-flow hydrology varies
significantly across Australia and is largely characterised by the combination of hydrogeology and
climate. Even in those areas that experience a similar climate, it is common to find streams that
exhibit vastly different cease-to-flow properties. The variability of flows is considerably different across
Australia. The 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 variability observed in the flow regime (see Figure
1). The application of the ‘range-standardised’ approach allows comparison across regions with
different flow regimes – all other stress-related factors being equal.
1.2.5. Ability to meaningfully compare the indicator over time
Low-flow indices are sensitive to the length of streamflow record used in the calculations. SKM (2005)
analysed this sensitivity by looking at the variation in the indicator values calculated using five, 10, 15,
20 and 25 years of data. The results generally show a marked reduction in standard error in all
indices once the length of record reaches about 15 years. A similar analysis was undertaken by
Kennard et al. (2009), which also found that 15 years of streamflow data was required to estimate
flow indicators. However, the length of record required to calculate low-flow indicators associated with
less frequent events has not been investigated.
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1.3. Deriving time-series streamflow data
The derivation of low-flow indicators is based on a time-series of streamflows. Typically the indicators
are calculated to represent historical, natural or current flow conditions. The method used to derive
these streamflows varies between sites that are:

gauged versus ungauged

regulated versus unregulated2.
The general process to derive streamflows for each combination of these conditions is described in
this section.
The process to derive streamflows at a gauged and unregulated site is shown in Figure 2. The
gauged streamflows represent the historical conditions (see Chapter 2). To derive a natural timeseries the historical impacts of anthropogenic activities (such as extractions) are added back to the
gauged streamflows. To estimate a time-series of flows representing current conditions, the
anthropogenic impacts at the current level of development (lod) are subtracted from the natural timeseries. Estimation of the reduction in streamflows caused by anthropogenic activities is discussed in
Chapter 5.
Cease-to-flow events (where there is no flow recorded at the gauging station) may be partially due to
anthropogenic activities. In these cases the natural time-series should equal the anthropogenic
effects. At other times there may be no water available and under natural conditions a cease-to-flow
event would have occurred. It is difficult to distinguish between these two situations and assumptions
must be made by practitioners. It should also be acknowledged that subsurface connectivity 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)
Historical
Flows
Add Historical
Anthropogenic Effects
(Chapter 6)
Subtract Anthropogenic
Effects at Current lod
(Chapter 6)
Natural
Flows
Current
Flows
Figure 2: Derivation of a flow time-series at a gauged and unregulated site
The process to derive streamflows at an ungauged and unregulated site is shown in Figure 3. A
method is required to estimate the natural flows in the catchment, such as the use of streamflow
transposition or the application of a catchment model (see Chapter 3). The historical and current flows
are then estimated by taking into account the anthropogenic effects.
2
In Queensland, regulated and unregulated water systems are referred to as supplemented and unsupplemented systems
respectively.
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Estimate of Natural Flow
(Chapter 4)
Subtract Anthropogenic
Effects at Current lod
(Chapter 6)
Subtract Historical
Anthropogenic Effects
(Chapter 6)
Historical
Flows
Natural
Flows
Current
Flows
Figure 3: Derivation of a flow time-series at an ungauged and unregulated site
The process at a regulated site is a little more complex. Gauged streamflows will represent historical
flows at sites with a gauge. However, at other ungauged sites a water resource system model is
required to model the historical impacts. These models capture the effect of water supply
infrastructure and operating rules (Chapter 4), and may also be used to predict flows under current
and pre-development conditions. An equivalent natural flow model is required to derive natural flows
in these systems.
Estimate of Natural Flow
(Chapter 4)
Gauged Streamflow
(Chapter 3)
Water Resource System Model
(Chapter 5)
Run model with
historical operating
rules and demands
(Chapter 5)
Natural
Flows
Historical
Flows
Run model with
current operating
rules and demands
(Chapter 5)
Current
Flows
Figure 4: Derivation of a flow time-series at a regulated site
The various components of estimating the time-series of flow are covered in more detail in chapters 2
to 5.
A common theme throughout this report surrounds the difficulties involved in estimating a daily timeseries of flow. At an ungauged location the time-series is subject to a range of model uncertainties
that include model calibration and extrapolation to an ungauged location (chapters 3 and 4). Even at a
gauged location there is uncertainty in the streamflow measurements (Chapter 2). All sites are subject
to the uncertainty in estimating anthropogenic influences (Chapter 5). All of the different sources of
uncertainty will influence the accuracy of the low-flow indicators. Yet even though the accuracy of
indicators depends on many site-specific factors (e.g. historical gauging or the nature of
anthropogenic influences), some general guidance on their likely accuracy could benefit water
managers. Several case studies could be undertaken to demonstrate the possible magnitude of these
uncertainties. It should also be noted that in tropical systems a daily time-series may not be required
to identify the persistence of refugia because predictable low flows occur for extended periods.
The archiving of reference natural and current streamflows is currently poor. These datasets are
typically prepared on a river-by-river basis at different times and by different people. While they are
generally available, the effort required to obtain and understand the assumptions behind them is
sometimes more difficult than it should be. This situation would be less challenging if sufficient
detailed documentation about the model architecture, calibration process and scenario establishment
were readily available. Where revisions to datasets have occurred, there is not always adequate
version control, which creates duplication and the potential for use of superseded datasets. These
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datasets are highly valuable and have various uses for multiple stakeholders. A repository of these
datasets for key environmental flow sites, either centrally stored or distributed but maintained in a
consistent manner by local agencies, could offer greater ease of access and certainty for users of
these datasets. Resourcing of this data provision and storage will be essential if the same issues are
not to arise in the future.
When archiving these datasets, consistent notes should accompany them to indicate which
anthropogenic influences have specifically been considered in the derivation of ‘natural’ flows, as well
as a reference to readily available technical reports documenting the flow derivation.
In addition to deriving low-flow indicators under natural (or reference) and current conditions, the likely
changes to low-flow indicators under future scenarios (such as climate change) may be useful.
However, the influence of longer-term climate regime variability (or change) on the low-flow indicators
is not well understood.
1.4. Summary
A list of hydrological indicators related to low flows has been compiled (Appendix A). Existing software
packages (e.g. RAP) are available to calculate most of these indicators. However, the main challenge
in deriving these indicators is the generation of a daily time-series of flow that may represent natural,
current or historical conditions. The methods available to generate these time-series vary between
sites that are gauged/ungauged and regulated/unregulated.
The key gaps and limitations related to low-flow indicators are:

the indices do not enable comparison between regions

the uncertainty associated with low-flow indicators is not well understood.
Other gaps and limitations identified in the review are as follows:

most low-flow indicators can be calculated using existing software, with the exception of
indicators related to antecedent and post low-flow event conditions

there are difficulties in deriving daily time-series of flow to calculate the flow indicators in datapoor areas

it is difficult to prioritise adoption of the 28 low-flow indicators

estimation of a natural time-series of flow requires assumptions about the role of
anthropogenic effects in cease-to-flow events

the length of data required to calculate low-flow indicators associated with less frequent
events is not known

the influence of longer-term climate regime variability (or change) on the low-flow indicators is
not well understood

the likelihood of low-flow events under future scenarios is not well understood

reference natural (and current) flows are poorly archived and are usually not readily available
from state agencies for ongoing use.
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2. Measuring and monitoring low flows
2.1. Introduction
Where they are available, gauged streamflows provide a time-series of historical streamflows. In
unregulated catchments gauged streamflows are also the basis for estimating a time-series of
streamflow representative of natural and current conditions. The time-series of streamflows are used
to generate the required low-flow indicators. In regulated catchments they form the basis for the
calibration of river system models that are used to assess the impacts of management decisions on
flow and usage regimes.
The most common method of streamflow gauging across Australia is based on the measurement of
stream level and conversion to streamflow using a rating curve (or stage discharge relationship). This
method and key knowledge gaps are described in Section 2.2. There are few alternative techniques
available – these are discussed in Sections 2.3 and 2.4. Finally, the current limitations and gaps in
existing monitoring networks are discussed in Section 2.5.
2.2. Streamflow measurement using a rating curve
At each streamflow gauging site the water level is measured frequently. The water level is then
converted to a flow rate using the rating curve. Water levels below a defined threshold will indicate a
cease-to-flow event. The rating curve is constructed based on a sample of streamflows measured
using the velocity-area method and their corresponding water level (a concurrent streamflow and
water level data sample is termed a ‘gauging’). The rating curve can be fit to the gaugings either using
statistical techniques or can include some subjective judgement that may take into account the
influence of the shape of the river cross-section and downstream obstructions. Details of these
methods can be found in standard hydrology textbooks (such as Dingman 1994; Herschy 1985).
The uncertainty associated with streamflow measurements depends on the measurement error
associated with the water level and uncertainty in the rating curve, which in turn depends on the
number of gaugings used to develop the rating curve and the variation between the individual
gaugings. There is an Australian Standard that specifies a method to quantify the uncertainty
associated with streamflow measurements (Standards Australia 1990). Several studies have applied
this standard at sites across Australia. At the 71 sites analysed by Ozbey et al. (2008) in Gippsland
(Victoria), the overall uncertainty in the 2005–06 annual flow was found to range between ±2 and ±24
per cent, with the majority between ±5 and ±15 per cent. The method was also used to assess 14
streamflow gauges within the Werribee River catchment (Victoria) and the uncertainty in the annual
streamflows during 2005–06 ranged from ±4 to ±41 per cent of the reported flow (Lowe 2009).
The uncertainty in streamflow measurements at low flows will vary between sites. The uncertainty in
the water level measurement will vary between instrumentation. The number of historical gaugings
made at low flows will influence the uncertainty in the rating curve at low flows. The nature of the
cross-section of the stream is also influential. For a wide river without an incised channel, a small
change in the water level will result in a large proportional change in the discharge at low flows. As
such, uncertainty in water level measurements can result in a large uncertainty in discharge at low
flows in percentage terms. Techniques are available to calculate the uncertainty in streamflow
measurements at low flows and the necessary data can generally be obtained. However, these
assessments are rarely undertaken and the general user is often unaware of the potential uncertainty
associated with the streamflow measurements.
For very low water levels it may be necessary to estimate the streamflow by extrapolating the rating
curve beyond the range of gauged flows. At extremely low flows it can be difficult to obtain gaugings if
the water depth is too low to allow a current meter or the velocity is too slow to spin the propeller of
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the current meter (Scanlon 2007). Quality codes are assigned to each streamflow measurement and
will identify measurements that are based on an extrapolation from the rating curve.
A streamflow gauge may not be capable of measuring all of the flow at the site. For example, if the
streamflow measurements are taken at a weir, the measurements may not include any water that
bypasses the weir through a fish passage or is released as a passing flow. Additionally, streamflow
gauges do not measure subsurface flows.
It is important that periods where a stream ceases to flow are identified through monitoring. At many
locations there is a control structure such as a v-notch weir or a natural rock bar that makes it easy to
identify when there is a cease-to-flow event. However, there may be difficulties where there is a
natural cross-section and its shape changes over time through geomorphological processes.
The ability to monitor low flows varies according to the climate, access and geomorphology of river
systems. In rivers with multiple flow paths, unstable cross-sections and poor access, it is difficult to
monitor streamflows accurately. This is evident in the remote carbonate aquifers of tropical northern
Australia, where features such as naturally forming tufa dams in carbonate aquifer catchments can
lead to low flows appearing to increase throughout the dry season when this is actually not the case.
The extent to which this issue has been resolved and the ability to address it with further investment
in research or alternative monitoring technologies could be discussed with hydrographers from the
Northern Territory Department of Natural Resources, Environment, the Arts and Sport (NRETAS) who
have previously reported this issue. The quality of monitoring is also time- and event-dependent, as
was evident in the post-bushfire periods in southern Australia, when the movement of ash and
sediment significantly altered channel cross-sections.
2.3. Satellite remote sensing
Monitoring low flows in remote or ungauged catchments presents a serious challenge to water
resource management due to the limited amount of observed information on flow behaviour and
patterns. Installing gauging stations in remote locations can be costly as well as problematic in terms
of maintenance and servicing. Furthermore, stream gauge data represents behaviour at a single
point, and therefore may not represent the total flow in certain circumstances, such as river braiding.
Satellite remote sensing could potentially provide much of the information needed to make decisions
on water resources. Stewardson et al. (2009) note several well-developed practical methods for using
satellite remote sensing information to observe and characterise inundated areas as well as timedependent behaviour. A wide range of options are available that vary in cost, accuracy and
applicability to the particular requirements of a project.
Essentially, each method consists of the analysis and interpretation of multispectral satellite image
data to establish the condition of a study area at a particular point in time. Often this requires some
knowledge of the particular conditions on the ground, such as vegetation and soil type, which can
affect how the satellite-based information is interpreted (Stewardson et al. 2009).
Mapping areas of inundation during a particular flow or flood event can be analysed in conjunction
with knowledge of the study area’s landscape and hydrology to estimate flows. The analysis of
satellite remote sensing images over time can provide both short- and long-term information about
inundation extents. This process will require calibration over a period of time to produce useful results.
However, Stewardson et al. (2009) identified several challenges in estimating total inundated area,
and therefore challenges in using satellite-based information in estimating flows:
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
There is generally a trade-off between temporal and spatial resolution. Stewardson et al.
(2009) identified two satellites, Landsat TM5 and MODIS, which can capture medium-scale
imagery useful for estimating inundated areas over Australia’s broad and remote semi-arid
region3. MODIS is able to capture daily imagery, but it has a spatial resolution of 250 m. This
resolution is likely to be poor at observing low-flow areas since the inundated areas may not
be distinguishable at a pixel scale of 250 m. The imagery captured by Landsat TM5 has a
pixel size of 30 m, which is a more appropriate scale for observing low flows and those at a
river channel scale (Stewardson et al. 2009). However, the frequency of the Landsat TM5
passing is intervals of 16 days, which may be too coarse to observe some infrequent and brief
events that may still be important in terms of estimating water resources. In addition, both
satellite sensors using the visible range of the spectral data will be inhibited by cloud cover
that may be associated with the rainfall and flow events.

There is also a trade-off between spatial resolution and cost. MODIS imagery is available
freely to download (although costs associated with the effort required to select and download
relevant imagery should be factored in). There is a cost associated with acquiring Landsat
TM5 imagery and therefore the number of images required needs to be balanced against the
study area extent and budget available. The number of images required also influences the
cost of analysis.

Landsat TM5 imagery is available from the mid 1980s through to the present, with some gaps
due to downtime of the satellite operation. In addition the satellite is well past its intended
lifespan and its future operation is uncertain.
Landsat TM imagery can also be used to identify waterbodies across the landscape. SKM (2006)
used Landsat TM imagery to identify permanent wetlands in the Wimmera (Victoria). Several images,
spanning 1992–2005, were compared to evaluate their permanency by monitoring wetland area
changes over time. This data was fed into a geographic information system (GIS) where it was used
to classify wetlands based on the presence of water following different meteorological conditions and
at different times of year.
In semi-arid and arid regions of Australia the presence and persistence of waterbodies can be inferred
from the presence of vegetation. Satellite remote sensing can be used to detect the location of
vegetation over time and may prove to be a more efficient way of monitoring the persistence of
waterbodies.
In using satellite remote sensing information to observe inundation levels, the specific requirements of
observing low flows must be carefully considered. It will be necessary to determine which satellite
data is at an appropriate temporal and spatial resolution to observe the river channels and inundated
areas, as well as important changes in flow level over time. Coarser resolution data such as that of
the MODIS satellite is available at daily intervals. Although larger pixel-size data is unlikely to be able
to accurately represent inundated areas, by maintaining a continuous sequence of data and
comparing this with ground observations, a relationship can be established between spectral
behaviour and flow levels (Stewardson et al. 2009).
The data-interpretation method must be considered to enable a meaningful result. It is imperative that
sources of error are well understood before making this selection, such as the effects of cloud cover,
turbidity and soil type (Stewardson et al. 2009).
3
There are a large number of satellites that capture imagery at a range of scales such as Spot, Quickbird and Worldview 2
which capture imagery 10 to 20 m, 1 to 5 m and < 1 m respectively.
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Finally, any remote sensing application must be verified and ground-truthed. Significant effort in
ground-truthing is required for understanding the uncertainty of the data compared with ground-based
monitoring. This would allow the appropriate context to be placed on information when the resource
manager or stakeholders are making decisions that depend on the different data.
2.4. Other techniques for streamflow measurement
Streamflow measurement using a rating curve is the most common method, but other techniques are
emerging that may provide better and more accurate representation of low flows. Alternative
techniques may be particularly useful at sites that are influenced by backwater effects, weeds and
sedimentation, unstable bed conditions or at which the discharge can vary considerably with only a
small change in the water levels.
Acoustic (or ultrasonic) meters are based on the measurement of sound signals. There are two main
types of acoustic meters. The ultrasonic doppler meter measures the time taken for an acoustic signal
sent into the water to bounce back. The ultrasonic transit time meter measures the time taken for an
acoustic signal to travel between two transducers. These meters measure the velocity in the river at a
particular depth. To measure the flow in a river, the meter either needs to be placed at a depth that
represents the average velocity, or meters need to be placed at several depths (WMO 2008).
Electromagnetic meters are another alternative. They pass an electrical current through the meter and
the voltage measured is proportional to the velocity of the water (Australian National Committee on
Irrigation and Drainage 2002). Currently these technologies do not provide better measurements at
low flows than conventional methods.
In some cases the water level measurement that corresponds to zero or low flows will provide useful
information to assess ecological water requirements and estimation of the streamflow is not required.
For example, monitoring of the water levels within off-stream waterbodies provides information on
their persistence, but these measurements are not widely made.
2.5. Monitoring networks
Each state and territory in Australia collects streamflow measurements from a network of sites
(Ladson 2008). It is important that these networks are able to be used to measure low flows to
achieve water plan objectives and to set and assess compliance against low-flow diversion rules.
Streamflow gauging along a river combined with metering of any major off-takes should be
established at a spatial and temporal scale commensurate with this ability. In the Murray Darling
Basin this need has become especially important with the shepherding of water from upstream
tributaries such as the Darling River to deliver ecological outcomes in the lower Murray River in South
Australia. Streamflow gauging becomes even more important if diversions are not monitored during
the event, so that river operators can assess the volume of any losses along the reach. Operators can
then decide whether they fall outside of the range of anticipated losses and thus may be attributable
to unauthorised take. Improving the spatial coverage and monitoring frequency of streamflow gauging
and diversions will also help to define low-flow management rules for the environment to a similar
level of certainty as those used for supplying consumptive users. This applies both to existing and
new diversions. Seasonal monitoring of low flows and diversions would lend much support to
recommendations on environmental flows.
From an ecological measurement perspective, streamflow gauges (flow or level) would ideally be
located at ecologically relevant locations, or at least at locations where the flow characteristics were
representative of the relevant location. In practice, factors such as resourcing, access, cross sectional
stability and the need for information to manage a water supply system have driven the decisions on
the location of streamflow gauges. An inventory of important ecological locations that are not currently
gauged could be assembled and the practicality and cost/benefit of monitoring at or near these sites
NATIONAL WATER COMMISSION — Low flows report series
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assessed. This information could inform future changes to gauging networks and encourage
consideration of aquatic ecosystem management needs.
Real-time information about low flows may be required for management purposes. For example, an
environmental water manager may decide to release water from storage or place a ban on diverters
once the flow in a river falls below a particular trigger. Real-time information is available at some
locations and is used by water authorities across Australia. However, access to this information is
limited and may not be available to all relevant stakeholders.
Data from existing gauging networks is available via a few different sources, but most states have
made data available on the internet (Ladson 2008). Not all of these sites currently provide access to
quality codes or gauging history, which would be useful information for low-flow studies. The
Australian Bureau of Meteorology also plays an important role in data provision and is working
towards providing an integrated source of information (Australian Bureau of Meteorology 2010).
2.6. Summary
A network of streamflow gauges across Australia provides useful information about low flows. The key
gaps and limitations related to measuring and monitoring low flows are:

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 available

there are several well-developed practical methods for using satellite remote sensing
information to observe and characterise inundated areas as well as time-dependent
behaviour, but adequate on-ground observations are required to ground-truth interpretations

the current spatial coverage and monitoring frequency of streamflow gauging and diversion
metering may not adequately protect water flows to meet ecological needs and objectives, or
inform the setting and compliance of low-flow management rules

the water levels in off-stream waterbodies are important, but not commonly measured.
Other gaps and limitations identified are:

limited number of gaugings available during low-flow periods

difficulty measuring very low flows using a current meter

measurement of low flows at unstable cross-sections is difficult

the channel is not always well defined and it can be difficult to determine the low-flow paths

the benefits of other emerging streamflow measurement technologies in measuring low flows
are not widely understood

the measurement uncertainty associated with water levels will vary between different
instrumentation

there is flow through fish passages that is not recorded during gauging

current monitoring techniques do not pick up subsurface flow

monitoring needs to be able to identify cease-to-flow events.
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3. Estimating low flows at ungauged sites
3.1. Introduction
Low-flow indicators may be required at ungauged sites. For the purposes of this discussion ungauged
sites may include those with no streamflow data, or those with some streamflow data that requires
infilling or extrapolation before it can be used for its intended purpose. There are two main
approaches to developing a time-series of flow at ungauged sites: streamflow transposition and
catchment modelling (WMO 2008). A description of streamflow transposition is given in Section 3.2,
followed by a review of rainfall-runoff models in Section 3.3. Given the uncertainties in estimating a
time-series of daily flows, an appropriate alternative is to estimate the low-flow indicators directly from
catchment characteristics (Section 3.4).
All of these methods provide results that are notionally representative of natural conditions. To
estimate flows representative of historical or current conditions, the influence of anthropogenic
influences must be taken into account (Figure 3). The quantification of anthropogenic influences is
discussed in Chapter 5.
3.2. Streamflow transposition
The transposition method uses the streamflows recorded at a gauged catchment to estimate the
streamflow at an ungauged site. The recorded streamflows are factored up or down using a
transposition relationship. In applying this approach two steps are taken. Firstly, the most appropriate
gauged catchment must be selected and secondly, a transposition relationship needs to be
determined.
The best results are obtained when the site selected for transposition is either directly upstream or
downstream of the site of interest (WMO 2008). If such a site is not available, site selection should be
based on the gauged catchment’s proximity and its hydrological similarity (WMO 2008). Lowe and
Nathan (2006) developed a method for selecting appropriate sites across Victoria. As it is not possible
to measure the hydrological similarity of ungauged catchments, the similarity of catchments with
regard to characteristics influencing the hydrological regime (such as rainfall, soil permeability, stream
frequency, forest cover) was used as a surrogate for hydrological similarity. The selection of these
characteristics was based on an analysis of 165 gauged catchments in Victoria (Lowe & Nathan,
2006).
The transposition relationship is used to factor the gauged streamflow to represent the ungauged
catchment. If a short period of gauged data is available at the ungauged site, this should be used to
calculate the transposition relationship. The transposition factor can be based on the relative
catchment area, or may also take into account differences in rainfall (WMO 2008). Gan, McMahon
and O’Neil (1991) based it on the catchment area, mean annual rainfall and the coefficient of variation
of the annual rainfall. Other studies have based 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 (Lowe & Nathan 2006; WMO 2008). Spot flow measurements at the otherwise ungauged
site may be used to verify transposition relationships using other parameters if the spot flow data is
insufficient to develop such a relationship.
As described above, the streamflows at the ungauged location are estimated by multiplying the
streamflows in the gauged catchment by a transposition factor. Using this method, any cease-to-flow
event (i.e. zero flow) observed at the gauged location will be assumed at the ungauged location.
Therefore it is important that the gauged and ungauged sites have similar cease-to-flow
characteristics.
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The streamflow transposition methods described above can be tailored to low flows. For example,
Voorwinde et al. (2003) allocated gauging stations to more than 1600 Victorian catchments for the
purpose of monitoring low flows, while SKM (1999) investigated low-flow homogeneity in the
Hawkesbury-Nepean Basin in New South Wales. However, the geologic units that control low-flow
behaviour are much more difficult to characterise than the topographic and climatic drivers that control
average and high flows. Factors that influence low flows – which are not as important for average or
high flows – include the ‘distribution and infiltration characteristics of soils, the hydraulic
characteristics and extent to the aquifers, the rate, frequency and amount of recharge’ (Smakhtin
2001). The quantification of these factors is an intrinsic difficulty when using streamflow transposition
to estimate low flows. Even if the characteristics that determine low flows were understood, the
adoption of these techniques may be hampered by limited access to information on catchment
characteristics. A national coverage of catchment characteristics may become available from the
Australian Bureau of Meteorology, which would resolve this issue. Another impediment is the time and
effort required to develop procedures to select catchments that have similar low-flow behaviour and
transposition factors appropriate for low flows.
3.3. Catchment modelling
In a rainfall-runoff model a time-series of rainfall and evaporation is used to estimate streamflows. To
apply a rainfall-runoff model in an ungauged catchment, the following steps are undertaken:
1. A rainfall-runoff model is selected
2. Model parameters are determined for a selection of gauged catchments via calibration
3. Model parameters are applied to the ungauged catchment with or without adjustment
The conceptual rainfall-runoff model is used to predict streamflows with the transposed model
parameters and climate data. Hydrologists have focused their attention on refining and improving this
approach for several decades. A brief summary of these steps and the remaining gaps in knowledge
are provided below.
3.3.1. Model selection
Many different rainfall-runoff models have been developed over the years. Some of the more
commonly used models have been compiled into the online Rainfall Runoff Library (RRL),
http://www.toolkit.net.au/Tools/RRL, which is maintained by the eWater CRC, although the number of
models used by industry and academia extends beyond this list and other models are used outside of
Australia.
Rainfall-runoff models vary in their structure and the number of parameters included in the model. The
low-flow behaviour of these models is commonly controlled by simplistic conceptual ‘buckets’ that are
poorly suited to modelling low-flow behaviour at the daily time-step. Low flows, particularly over
extended dry periods, arise from multiple subsurface units that become depleted at different stages.
More complex models are better able to model low flows, however the difficulty in calibration is
increased, as is transposition of the model parameters to ungauged catchments (as discussed in the
next section). Some of these rainfall-runoff models provide a better representation of low flows. For
example, there are two versions of the AWBM rainfall-runoff model. One version is better suited to
estimating low flows and the other high flows and floods (Boughton 2004).
The processes governing runoff also vary and are different in dry, arid regions (Wei et al. 1998).
Estimation of streamflows in these regions is difficult (Ladson 2008). The IHACRES model is
considered to be one appropriate for use in ephemeral catchments (Ladson 2008). Costelloe et al.
(2005) found that a lumped conceptual rainfall-runoff model did not adequately represent large arid
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catchments due to the heterogeneity in characteristics across the catchment. Improved results were
obtained using a semi-distributed grid-based conceptual model.
Specialised models are required to adequately model low flows in some specific environments. In
alpine areas, for example, snowmelt affects low-flow behaviour and hence rainfall-runoff models
should ideally have a snowmelt module when being applied there. Snowmelt algorithms for use in
rainfall-runoff models are widely available in both Europe and North America. Similarly in catchments
with mixed geology, the ability to accurately model low flows with many rainfall-runoff models can be
poor. The availability of only a single groundwater discharge parameter in SIMHYD was noted as a
potential limitation in modelling carbonate aquifer catchments in northern Australia, for example,
where groundwater discharge can operate at two speeds – depending on the storage content of
carbonate and non-carbonate aquifers during the dry season (SKM 2007).
Combined hydrologic and hydrogeologic models have been developed and applied in isolated cases
in recent years. These models present the opportunity to better model surface water/groundwater
interaction processes at low flows, but are currently highly parameterised and are not supported by
adequate input data. Input data requirements can be significantly greater for these models than
traditional rainfall-runoff models. Computing speed and storage has traditionally also been a problem
with these models, but this has improved markedly in recent times.
A few studies have investigated the relative performance of models in estimating low flows and in
ephemeral catchments (Ye et al. 1997). While there appears to be an understanding of the relative
strengths and weakness of the common rainfall-runoff models among experienced hydrologists, the
provision of clear guidance in the RRL would go a long way to fostering a wider appreciation.
3.3.2. Model calibration
During model calibration the parameter values are selected to find the best fit between the estimated
and observed streamflows. Objective functions measure model performance and can be used to
select model parameters. The following objective functions are commonly used for a calibration that
focuses on fitting to low flows (Ladson 2008):

sum of square roots

sum of squares of differences of square roots

sum of squares of differences of values raised to the power of 0.2

sum of absolute differences of logs.
These objective functions are included in available rainfall-runoff packages (such as those in the RRL)
and are easily adopted. While these objective functions are commonly used, there has been no formal
testing of their adequacy.
Calibration also relies on the skill of the modeller to specifically match the proportion of time with
cease-to-flow, the flow duration curve and baseflow recession curve. Automated procedures for
calibration that use objective functions have significantly reduced processing times for calibration, but
at present are generally unable to achieve the same level of accuracy as manual calibrations.
As with any model, the reliability of the results will depend on the length of data available for
calibration and how well the calibration data represents the conditions that the model is being used to
predict. A model calibrated over a period of low flows will provide a better estimate of low flows than a
model calibrated over a period of high flows. The transparency of the model calibration approach and
how the results are reported can vary.
The shift in climate in south-eastern and south-western Australia during the past 10 to 30 years has
created some uncertainties in the accuracy of previously calibrated rainfall-runoff models. Models that
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were calibrated to data collected before the climate shift often over-estimate low flows in more recent
periods. This is possibly due to a shift in the relationship between rainfall and runoff as a result of
changes in soil moisture and plant uptake and use of water. The inter-annual rainfall conditions that
affect soil moisture and groundwater stores are outside of the historical conditions of the calibration
period. A review of the calibration period of rainfall-runoff models across southern Australia and a
recalibration of those models to more recent data should be undertaken where this has not already
occurred. Understanding the relationship between evapotranspiration and temperature, which is still
being debated in Australia, will have important implications for both the parameterisation and
calibration of rainfall-runoff models under climate change conditions.
3.3.3. Transposition of model parameters
If a period of gauged streamflow record is available at the site, the model parameters are derived
thorough calibration of the model to the available data. In locations where no streamflow record
exists, the model parameters need to be transposed from a gauged catchment. Several approaches
have been trialled and used to transpose model parameters from a gauged to an ungauged
catchment. These include adopting model parameters from nearby gauged catchments (e.g. Merz &
Bloschl 2004; Post et al. 2007) or developing prediction equations that link individual model
parameters to physical catchment characteristics (McIntyre et al. 2005; Seibert 1999; Wagener &
Wheater 2006). Rather than estimate model parameters individually, more recently attempts have
been made to transfer entire sets of model parameters based on the similarity of the gauged and
ungauged catchments (e.g. Bardossy 2007; McIntyre et al. 2005; Reichl et al. 2006, 2007).
Several attempts have been made to reduce the influence of parameter uncertainty on the prediction
of runoff. Simple rainfall-runoff models have been developed with few parameters to eliminate any
inter-dependencies (e.g. Jayasuriya et al. 1991, 1994). Attempts at parameter regression using these
models have reported improvements (e.g. Boughton 1984; Jayasuriya et al. 1994; Nathan et al. 1996;
Parajka et al. 2007). The approach developed by Nathan et al. (1996) was used to estimate flows
across Victoria as an input to determining bulk water entitlements and provides a practical example of
model parameter transposition.
Despite the considerable effort devoted to this area, there are still substantial uncertainties associated
with ungauged runoff estimated using rainfall-runoff models (Sivapalan 2003). The difficulties in
predicting runoff in ungauged basins has been attributed to the uncertainty in the calibrated model
predictions (Bardossy 2007; Reichl et al. 2007), the heterogeneity of runoff processes and catchment
characteristics (Sivapalan 2003), the use of non-representative physical catchment characteristics
(Parajka et al. 2007), uncertainty in the catchment characteristics, and uncertainty in the input data
and model structure (Reichl et al. 2007).
3.4. Direct estimation of low-flow indicators
Given the uncertainties associated with estimating a time-series of natural daily flows at an ungauged
location, it may be more appropriate to directly estimate the low-flow indicators in these catchments
based on catchment characteristics such as climate, hydrogeology, soils, topography and land use.
This approach could be applied across Australia and applied to a range of low-flow indicators. The
Low flow manual (WMO 2008) provides a comprehensive description of the methodology and
examples of its application. Direct estimation of low-flow indicators was most recently undertaken for
the Northern Australia Sustainable Yields (NASY) project and has also been undertaken for southeastern and south-western Australia.
Direct estimation of low-flow indicators is helped by knowledge of cease-to-flow conditions in any
given river. This can be informed by spot measurements during extreme droughts or in some cases
by anecdotal evidence from water utility operators and river managers. Having access to this
information would also be useful to indicate likely refuges for ecosystems during low-flow periods and
NATIONAL WATER COMMISSION — Low flows report series
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could be coupled with remote sensing information to indicate the presence or absence of permanent
pools during extreme droughts. The 2006–07 drought in south-eastern Australia event could be
analysed.
3.5. Comparison of techniques
A comparison by CSIRO and SKM of direct estimation of low-flow indicators through regional
regression versus estimation by transposition of rainfall-runoff models by nearest neighbour, indicated
that while both methods were similarly accurate for medium to high flows, direct estimation performed
better for low flow indicators. The disadvantage of this approach is that it does not provide a timeseries of data, but can be useful to condition rainfall-runoff modelling results, as demonstrated in the
NASY project.
Direct transposition of streamflow data and rainfall-runoff models both suffer from problems
associated with the spatial representation of rainfall. Any research into better spatial representation of
time-series rainfall data, such as the use of radar or other technologies, will serve to improve rainfallrunoff modelling, including in low-flow periods (e.g. low-flow fresh events).
Direct transposition also suffers from potential differences in baseflow recession behaviour. For short
periods of missing data, alternative techniques for infilling data may be warranted, but at present there
are no readily available tools to help with this. For example, in a period of no rainfall, using an
exponential baseflow recession curve from the last gauged reading to the next available one will
perform significantly better than either transposition or rainfall-runoff modelling.
The techniques presented are not useful for modelling in-stream storage behaviour after flows have
ceased. For example, a rainfall-runoff model does not identify low-flow refuges and is not suitable for
modelling the persistence of a waterhole. In these instances other types of models are required.
3.6. Summary
Two methods to estimate a time-series of natural flow at an ungauged location are presented above.
Both approaches rely on a series of assumptions, including the selection of a representative gauged
catchment. Given the uncertainties associated with these methods, it may be more appropriate to
estimate the low-flow indicators directly from catchment characteristics.
The key gaps and limitations related to estimating flows at ungauged locations are:

the relative ability of commonly available rainfall-runoff models to represent low flows is not
widely understood

no study has been conducted to determine which objective functions should be used to
calibrate to low flows.
Other gaps and limitations identified in the review are as follows:

the catchment characteristics that control low-flow behaviour are difficult to identify and
characterise

a method to rapidly determine the hydrological similarity of catchments with respect to low
flows is not available

transposition methods tend to be based on transposition factors related to the average flow

the shift in climate in south-eastern and south-western Australia during the past 10 to 30
years has created some uncertainties in the accuracy of previously calibrated rainfall-runoff
models
NATIONAL WATER COMMISSION — Low flows report series
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
the selection of catchment model parameters for ungauged catchments introduces
uncertainty

a substantial amount of effort is required to adequately estimate a time-series of daily
streamflows at an ungauged site

the location of perennial stream reaches and low-flow refuges for in-stream biota are not
always known

rainfall-runoff models are not useful for modelling processes at a small scale (e.g. waterhole).
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4. Estimating low flows in regulated
systems
4.1. Introduction
The method adopted to estimate low flows in a regulated water supply system can vary between flows
required to represent historical, current and natural scenarios (Figure 4). Due to the need to capture
the complex management arrangements that exist in regulated systems, a hydrologic river system
model is often required to represent flows under pre- and current development.
A comprehensive review of the limitations of water resource system models (or river modelling) was
undertaken for the Murray-Darling Basin by Van Dijk et al. (2008). The limitations and gaps in
estimating low flows using water resource system models within this chapter draws heavily on this
previous review.
4.2. Water resource system models
Water resource system models are used to simulate the storage and movement of water within a
regulated water supply system. These models represent rivers, reservoirs, major diversions and
access rules. Typically the models are used to facilitate water resource planning, both short and long
term. The most commonly used models are listed in Table 1.
Table 1: Water resource system models
Model
Predominant area of use
IQQM
New South Wales and Queensland
REALM
Victoria and Western Australia
WATHNET
Sydney and South East Queensland Water Grid
MSM-BIGMOD
Murray River
WaterCress
South Australia
SGNT13
Queensland (St George system within the Condamine-Balonne region)
SnowyHydro
New South Wales (Snowy Hydro)
Hydstra
Tasmania
River Manager
Trial applications being undertaken throughout Australia
The degree of regulation and effect on low flows can vary considerably across a region. The spatial
and temporal resolution of the river system model and its ability to replicate day-to-day river
operational practices will affect its ability to model low flows at a site of interest. The level of spatial
representation included in the models varies and some interpolation may be required if the site of
interest is not represented within the model. River system models are typically only representative of
the locations that they are calibrated against. The temporal resolution is also important. IQQM
operates on a daily time-step, while the time-step used within REALM can be daily, weekly or
monthly. The low-flow indicators are based on a daily time-step. If a weekly or monthly REALM model
is used, data manipulation and interpolation is required to generate low-flow indicators for the
scenarios modelled. During the past decade more REALM models have been developed with (or
converted to) a daily time-step, but there are some notable exceptions. For example, the Goulburn
Simulation Model used to represent Northern Victoria is at a monthly time-step. A major difference
between IQQM and REALM is the ability to route flows through the model, although modellers are
using methods to incorporate routing into a REALM model (Department of Sustainability and
Environment 2009).
NATIONAL WATER COMMISSION — Low flows report series
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Van Dijk et al. (2008) undertook a comprehensive review of the uncertainty in river modelling across
the Murray-Darling Basin and found that models provided a very poor representation of low flows. The
poor performance is likely to be attributable to the difficulties in representing losses within the system
and the lack of data on diversions. Adequate representation of system operation, surface
water/groundwater interactions and uncertainty in model inputs also play a role. The ability to
adequately model low flows will also be influenced by other factors such as the model calibration and
representation of water trading.
River losses can be large, particularly in the large low-lying rivers. During low flows these losses may
be attributable to direct evaporation, seepage, groundwater recharge, bed losses and losses to the
banks of the stream (Smakhtin 2001). The relative contribution of each of these is poorly understood
(Smakhtin 2001) and overall losses are determined by undertaking a reach balance, with loss volume
equal to the inflows less the outflows if all other inflows and outflows are ‘known’. The accuracy of the
estimate will depend on the uncertainties associated with all of the inflows and outflows used in the
calculations (see Section 2.2). Lowe et al. (2009) investigated the magnitude of the river losses along
the Campaspe River, Victoria. The uncertainty was found to range between ±13 to ±1263 per cent of
the best estimate of the river losses for each month analysed and was mostly due to the uncertainty in
the streamflow measurements. The influence of the uncertainties in the inflows and outflows will
decrease as the length of the reach considered increases (Dingman 1994). However, as the length of
the reach increases, so does the influence of attenuation and this can cause difficulties in estimating
losses, particularly during periods of low flows.
The historical magnitude of river losses may be estimated using an inflow-outflow analysis, as
described in the preceding paragraph. Typically these losses are represented in the model as either a
constant value or as a function of the flow in the river. As well as not capturing the likely temporal
variation of losses, the relationship between river flow and the magnitude of losses may be weak (as
found by Lowe et al. (2009)) or may vary depending on antecedent conditions. The representation of
losses within the model may also be altered during the model calibration process. During calibration
the focus is usually on achieving the best prediction of overall system yields and may be poorly suited
to simulating low-flow conditions. In these situations the losses are not likely to represent true losses
but rather a combination of factors including errors in other model inputs (Van Dijk et al. 2008).
The flow in a regulated river will in most cases depend on the magnitude and timing of diversions.
Assumptions are required to model diversions when there is a lack of data. Van Dijk et al. (2008)
conclude that this can lead to a poor representation of low flows. A more detailed discussion
regarding diversions is provided in Section 5.2. Groundwater extractions can also have a substantial
impact on low flows, particularly along reaches where there is high connectivity. The influence of
these extractions is not always represented within models, but the integration of these models was
undertaken as part of the Murray-Darling Basin Sustainable Yields project.
The water resource supply models represent the operation of water supply systems. The rules
included in the model may not adequately represent actual operation during periods of low flows if the
rules included in the model are a simplification of the actual operation, if the operating rules have
changed over time or if there have been times when the system has not operated according to the set
rules. As an example, river operators decide to release water from regulated storages to meet
demands by considering a number of factors. These include the expected transmission losses, useful
downstream tributary contributions, and alterations to orders as a result of short-term weather
fluctuations. All of these factors require the operator to make forecasts in relation to future conditions.
The quality of the forecast dictates whether too much, just enough or too little water is released from
the storage to meet demands. Representation of these forecast practices in river system models is
either non-existent (in the case of losses and demand reduction) or crude (in the case of tributary
utilisation). As a consequence the ability of the river system model to reproduce the daily pattern of
dam releases and downstream low flows is severely compromised.
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Low-flow regimes are often heavily influenced by the operation of in-stream weirs. The operation of
these and the effects on flows are generally poorly represented in hydrology river system models. As
an example, a large number of in-stream weirs were removed from the New South Wales river system
models due to model instabilities. Hydraulic models offer a better representation of the influence of
these in-stream weirs.
Model calibration will also affect the quality of low-flow estimates. The emphasis placed on matching
low flows during calibration will vary depending on the model’s main purpose. For example, the
calibration of models used for environmental flow studies will focus on low flows, while a model used
for long-term water resource planning may not place a high weighting on matching daily low-flow
events but be more interested in capturing overall flow variability through flow duration curve
matching. This was identified as an issue in the Warrego by CSIRO (2007). The importance of flows
to refuge pools was identified as important by CSIRO (2007), however it was not possible to model
low ‘refreshing’ flows to the pools because the models were not adequately calibrated for this part of
the flow regime. The model’s ability to represent low flows will also depend on the period used for
calibration; that is, a model calibration over a period of low flows may provide a better representation
than a model calibration during a relatively wet period. A model can be calibrated at a number of
locations. The calibration of a model for long-term water resource planning will focus on matching
reservoir storage volumes and the flow at large offtake points in the system and this may come at the
expense of matching downstream flows. For consistency, there is generally only one recognised
water resource model for use by government agencies within a particular river basin, so decisions
about improving calibration accuracy at one part of the flow regime (or location in the system) at the
expense of another will usually involve some trade-offs in relation to the model applications. A review
of the ability of these models to represent low flows at ecologically important locations would help
managers and planners determine if the model results are suitable for their needs.
In addition to the difficulty in reproducing observed low flows, water resource system models may not
represent cease-to-flow events well. In recognition of this, flows below a nominated threshold are
often considered to be equivalent to a cease-to-flow. For example, in Queensland all flows modelled
by IQQM to be less than 2 ML/day are assumed to be a cease-to-flow event. With monthly models,
such as the northern Victorian REALM models, the ability to identify within-month cease-to-flow
events is poor.
Despite the representation of perfect trade at lumped nodes in river system models, a very large
proportion of water trading activity is not dynamically incorporated. This is especially the case when
undertaking alternative climate scenarios such as under climate change. Although the magnitude of
diversions under climate change is usually adjusted for the change in climate, the location of the
diversions is not adjusted. Some research into coupled hydrologic-economic models has been
undertaken for use in water trading scenarios – using REALM for example (Weinmann et al. 2005) –
however this has not resulted in water trading algorithms being adopted into water resource modelling
more generally. Improved understanding of likely water market behaviour during low-flow periods and
incorporation of this knowledge into water resource modelling would be beneficial for alternative
climate and water management scenarios.
Access to the water resource system models is not always available and some stakeholders rely on
model outputs that are made public. The limitations of the models in estimating low flows are most
commonly reported in technical documents that are not made public and require a technical
background to understand.
4.3. Summary
Water resource system models are used to estimate flows within a regulated system. Van Dijk et al.
(2008) found these models provided a poor representation of the timing of low flows and this was
most likely due to the poor representation of river losses, daily diversions, and operational practices
NATIONAL WATER COMMISSION — Low flows report series
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within these models. These models should be used with caution when developing water plans that
focus on low-flow ecological responses.
The key issues and gaps related to modelling flows within a regulated system are:

there are large uncertainties associated with estimates of river losses

river losses may be represented poorly within a model.
Other gaps and limitations identified in the review are as follows:

the degree of regulation and effect on low flows can vary considerably across a region

not all models are represented on a daily time-step

models may not represent the daily operation of a water supply system

models may not represent cease-to-flow events well

models do not include dynamic representation of water trading

models may not be calibrated to represent low flows and the limitations may not be
communicated to all relevant stakeholders.
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5. Quantifying anthropogenic influences
5.1. Introduction
The difference between historical, current and natural flow series is the effect of anthropogenic
influences on the flow regime. In essence, any change in a flow indicator between these scenarios is
simply a measure of the impact of anthropogenic influences on the low-flow regime. As such, the
quantification of anthropogenic influences is critical.
Anthropogenic influences include the direct extraction of water from waterways (Section 5.2), the
water harvested by farm dams (Section 5.3) the reductions in low flows that result from groundwater
extractions (Section 5.4) and changes in land use (Section 5.5). Low flows can also be increased by
discharges into a waterway (Section 5.6). This chapter presents a brief review of each of these
influences. Other influences not addressed in this section include the artificial drainage of valleys, the
influence of floodplain structures and small weirs, the influence of irrigation return flows and interbasin transfer schemes.
5.2. Direct extractions
Water extracted directly from waterways or waterholes is used for a variety of purposes across
Australia and the nature of the licences used to manage these extractions varies between the
different uses and across jurisdictions. These extractions will impact on low flows, particularly as the
demand for water tends to be greater during dry periods.
Some direct extractions are metered. Metered diversions are subject to metering error, but this
uncertainty is often minimal compared with the uncertainty introduced by disaggregating metered
volumes to a daily time-step. Meters tend to be read on an opportunistic, quarterly or seasonal basis.
Therefore the estimation of extractions on a daily or monthly time-step requires disaggregation and
reliance on a number of assumptions. The daily pattern of extractions for irrigation may be based on
estimates of irrigation demands – derived based on irrigation orders in a regulated system or using
programs such as PRIDE developed by Erlanger, Poulton and Weinmann (1992) or the United
Nations FAO56-based models that use the methods documented in Allen et.al. (1998) – or based on
the pattern of net evaporation. However, some irrigators will extract water when it is available and
store it in an off-stream dam. Extractions for domestic and stock purposes are more likely to occur
uniformly across the year, but there is little evidence on which to base this assumption. Even where
diversions are metered, the data is generally collected by a water utility and is not readily available to
external parties. In the future this information may be collected and made available by the Bureau of
Meteorology.
Other diversions are not metered and the magnitude and timing of the extractions must be estimated.
The estimated diversions may be based on a licensed volume or modelled using information on the
intended use and climate information (e.g. PRIDE). In these cases there are substantial uncertainties
associated with the magnitude and timing of diversions. Estimates of irrigation water use on a daily
time-step are poor. Many of the decisions are based on poor interpretation and representation of the
behaviour of irrigators in the river system models.
Trials of the use of smart meters on private diversions have occurred in a number of places around
Australia, including the Yarra Valley in Victoria. The preliminary outcomes of these trials highlight that
a wealth of information can be obtained, particularly in relation to the management of private
diversions at low flows and the relative adherence to restriction policies by private diverters. The use
of these meters in other regions could play a critical role in real-time management of water, especially
in managing for low-flow ecological responses in unregulated systems. While the benefits of using
smart meters are clear from these trials, a business case for the use of smart meters on private
NATIONAL WATER COMMISSION — Low flows report series
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diversions has not been prepared and further investment is required to identify when and where smart
meters are economically advantageous to install and use.
Further uncertainty is introduced when estimates are required of the historical extent of extractions,
particularly when information is not available on the historical number of licences.
5.3. Farm dams
In some regions of Australia farm dams extract a substantial proportion of the available resources.
Farm dams may have a substantial impact on low flows. Until it is full, a farm dam will capture all the
catchment runoff intercepted by it. Farm dams intercept the first catchment flows after summer,
thereby extending the period of time over which the waterway could be experiencing dry conditions.
The impact of farm dams on streamflows are not measured but generally estimated using the
simulations model, Tool for Estimating Dam Impacts (TEDI). TEDI undertakes a water balance for
each farm dam in the catchment and calculates their cumulative impact on streamflows (Nathan et al.
2000). Inputs to the model include the number and volume of farm dams, data to estimate the net
inflows to each dam and a demand factor. The demand factor is the average volume of water
extracted from the dam, presented as a proportion of the total dam capacity. The TEDI model has
been used to estimate farm dam impacts across many regions of Australia.
The TEDI model operates on a monthly time-step. The next version of TEDI (called STEDI) will
enable farm dam impacts to be modelled on a daily time-step. However, the daily estimates will only
be as reliable as the model inputs. There are substantial uncertainties associated with some of the
TEDI model inputs and a framework to assess these uncertainties was developed by Lowe and
Nathan (2008). The uncertainties associated with farm dam impacts were assessed for the Werribee
Basin, Victoria, on a monthly time-step. Results showed that the volume of farm dams varied by ±11
per cent and the impact on streamflows varied by ±29 per cent. The Murray-Darling Basin Authority is
funding a study to improve some of the inputs to TEDI, however the uncertainties associated with
daily impacts are likely to remain substantial.
One of the challenges in estimating the impact of farm dams is simply identifying the number of farm
dams across a catchment. Typically farm dams are identified from aerial photography. To obtain an
estimate of historical farm dam impacts the historical number of farm dams present in the catchment
can be determined by looking at old aerial photography. However, this can be an expensive exercise
and is rarely undertaken.
5.4. Groundwater extractions
Groundwater extractions can reduce the amount of groundwater discharge into waterways. In
particular, groundwater extractions affect low flows because they reduce the baseflow contribution.
There are a range of issues associated with monitoring and modelling of groundwater extractions,
including identifying the location of groundwater extractions, obtaining information on the use of the
water and modelling user behaviour. The impact of groundwater extractions can be estimated using
groundwater models (see Section 6.3).
5.5. Land use change
The land use in a catchment influences the streamflows and a change in land use can alter the lowflow regime. Pusey et al. (2009) reviewed the changes in land use since European colonisation due to
changes in vegetation type, grazing and fire regime. There are many examples presented in the
literature that show that changes to the vegetation type, afforestation, deforestation and catchment
NATIONAL WATER COMMISSION — Low flows report series
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urbanisation alter low-flow characteristics (Smakhtin 2001). These changes will influence the low-flow
regimes of most Australian waterways.
Pusey et al. (2009) conclude that due to the influence of land use changes, gauged streamflows do
not represent a natural flow regime. In previous studies (e.g. SKM 2005), the influence of land use
changes has not been taken into account in deriving a time-series of ‘natural’ flows. For this reason,
the natural flow regime is sometimes referred to as the ‘unimpacted’ or ‘pre-development’ condition as
it represents the streamflow that would occur if all anthropogenic extractions and diversions ceased,
under current (or possibly historic) conditions of land use cover.
However, recent years have seen investment in better understanding the changes in streamflows due
to changes in land use. Peel (2009) notes that the number of journal articles in this area has
increased dramatically since 2000 and provides an overview of recent developments in this field. The
basis of much modelling in this area is based on the work of Zhang et al. (2001) who looked at the
response of mean annual evapotranspiration to vegetation changes at a catchment scale. The eWater
CRC toolkit provides several tools to help hydrologists and water managers quantify these changes.
For example, one of the features of WaterCAST (a whole of catchment model) is the ability to model
different land use types (Cook et al. 2009). The different characteristics of each land use type are
included in the model by specifying different rainfall-runoff model parameters for each land use type
(Chiew 2003). Another eWater model, the Forest Cover Flow Change tool (FCFC), can be used to
quantify the impact of large changes in forest cover on daily streamflows. The reliability of these
models on a daily time-step requires warrants further investigation.
5.6. Wastewater treatment plant discharges
Wastewater treatment plants and other similar discharges can influence low flows. In dry periods,
these discharges can sometimes be the only source of water in a stream and can turn an ephemeral
stream into a perennial one. The location of these treatment plant discharges is not currently mapped
in any readily available format across Australia, with the information currently being held within
individual water utilities. Having access to a nationwide map of these discharge locations, together
with the agency responsible for managing those discharges, would support low-flow investigations.
Other similar discharges include return flows from irrigation, coal seam gas discharges, mine water
and other industrial discharges.
5.7. Summary
The estimation of anthropogenic influence on streamflow involves the careful treatment of many
sparse datasets related to system operation, extractions for urban and rural demands, farm dams,
groundwater extractions and land use changes. The time-step for which these datasets are available
varies and can be limited to a monthly or seasonal time-step. Hence, our ability to quantify the various
factors that modify flow behaviour decreases as the time-step of interest decreases. Thus, while we
might be able to derive streamflows representative of natural and current conditions at an annual level
with some degree of confidence, the potential for errors when attempting to characterise differences
in low flows is considerable. Indeed the nature of the available data is such that it could be argued
that the derivation of a daily time-series simply reflects the nature of the methods and assumptions
used in its derivation. The shortest time-step that is commensurate with the level of information and
estimation techniques available in Australia is at best monthly.
Given the difficulties in estimating anthropogenic influences at a daily time-step, two possible
approaches could be adopted to assess the impact on low flows:

derive low-flow indicators at a monthly time-step in data-poor regions, or
NATIONAL WATER COMMISSION — Low flows report series
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
develop simple models to estimate the change in a low-flow indicator due to various levels of
anthropogenic influences.
The key issues and gaps related to modelling anthropogenic influences are:

smart meters are not widely used

estimates of irrigation water use on a daily time-step are poor – many of the decisions are
based on poor interpretation and representation of the behaviour of irrigators in the river
system models.
Other gaps and limitations identified in the review are as follows:

difficulty in estimating all anthropogenic influences at a daily time-step

the volume of pumping from waterholes is not well known

the monitoring and modelling of groundwater extractions can be improved

the seasonal impact of land use change on streamflows is not very well understood

readily available information on low-flow discharge locations from sources such as
wastewater, return flows from irrigation and coal seam gas

floodplain structures and small weirs located on a waterway can affect low flows.
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6. Mechanisms generating low flows
6.1. Introduction
It is important to understand the mechanisms that generate low flows. The prediction of low flows
under different scenarios (e.g. climate change) will be improved if the processes that produce low
flows are better understood. Also water managers will be able to more efficiently address issues of
stress during low-flow periods if the drivers of low-flow events are known. For example, the benefit of
installing a low-flow bypass on farm dams can be assessed if the contribution of surface runoff during
low-flow periods is understood.
While this report does not specifically address water quality issues, an improved understanding of the
mechanisms that generate low flows will help managers better understand issues such as the impact
of reduced low flows on the salinity dynamics in permanent pools. For example, the relative
contribution of surface runoff and groundwater inflows to a waterway will influence the water quality,
and surface runoff may play an important role in maintaining lower salinity levels.
6.2. Identifying and monitoring sources of low flow
There are essentially four sources of low flows (Smakhtin 2001):
1. Groundwater – discharge from groundwater storage
2. Unsaturated zone flow – also known as throughflow
3. Bank storage – during high-flow events water seeps into the river banks and discharges back into
the river once the flow event has receded. This source of low flows is important in broad alluvial
flood plains
4. Delayed surface water – seepage from large waterbodies (e.g. lakes and reservoirs)
In addition, direct rainfall and localised runoff may play an important role in the persistence of
waterholes. It is possible that more than one driver will influence a particular low-flow event.
Worldwide there has been little investigation into the mechanisms that generate low flows.
The contribution of groundwater discharge to low flows can be monitored by analysing the
hydrochemistry of the groundwater and low flows, for example chloride and radon concentrations are
higher in groundwater and will decay rapidly once discharged into a waterway. Another monitoring
approach is to take streamflow gauging at intervals along a river reach. Increases in the streamflow
along reaches that do not receive tributary inflows are typically attributed to groundwater discharge.
Both of these approaches are resource intensive and only a few streams across Australia have been
assessed. Most studies in Australia have focused on reaches with groundwater discharges and little
work has been done to monitor surface water/groundwater interactions in losing streams.
6.3. Modelling
Groundwater modelling can be undertaken at different levels of complexity. Analytical modelling
adopts standard equations and relies on simplifying assumptions to model groundwater systems.
Numerical models (such as MODFLOW) are more complex, but require more data for calibration and
validation. A more detailed description of groundwater models can be found in standard groundwater
text books or in Rassam and Werner (2008).
NATIONAL WATER COMMISSION — Low flows report series
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The focus of recent research has been on linking groundwater and surface water models (Rassam &
Werner, 2008) and this should improve the ability of models to estimate low flows. eWater is currently
preparing protocols for linking river and groundwater models.
Streams and rivers across the Murray-Darling Basin have been categorised as either gaining or losing
streams. This categorisation was based on a comparison of groundwater levels and stream levels.
This provides useful information for a variety of purposes and may be used to improve the calibration
of river models. This study could be extended beyond the Murray-Darling Basin, but the extent will
depend on the number and location of groundwater bores and streamflow gauges.
Difficulties arise when generalising the mechanisms that generate low flows because these relate
strongly to local and regional conditions and are highly dependent on the scale used to manage the
resource. For example, the models used to understand the mechanisms providing flow into a small
pool are likely to differ to a study covering a larger system or the entire Murray-Darling Basin.
6.4. Summary
Issues and gaps related to understanding the mechanisms generating low flows are:

worldwide there has been little investigation into the mechanisms that generate low flows or
the synergistic interactions among them

few studies have monitored surface water/groundwater interactions in losing streams

the location of gaining and losing river reaches is not widely mapped outside of the MurrayDarling Basin.
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7. Hydraulic characteristics
7.1. Introduction
Previous chapters have focused on hydrologic or flow related limitations and gaps. However, from an
ecological perspective it is important to consider the hydraulic characteristics of the stream in
conjunction with its hydrologic characteristics. The hydraulic characteristics of a waterway at low flows
determine the amount of habitat and degree of connectivity, and during extended low flows the
hydraulic characteristics determine the location and longevity of refuges.
7.2. Hydraulic modelling
At a streamflow gauging site the relationship between the flow in the river and the depth of water is
relatively well understood (see Section 2.2). The challenge lies in understanding the relationship
between the flow recorded at a streamflow gauging site and other locations along a river.
A hydraulic model (such as HEC-RAS) can be used to model the relationship between flow and depth
at ungauged locations. Like all models, the accuracy of hydraulic models depends on the amount of
data available for calibration and the results will become less reliable if the model is used to
extrapolate beyond the range of calibration measurements. These models require information on the
shape of the cross-sections of the river and are calibrated to the water levels measured at known flow
rates. This process involves several areas of uncertainty:

Survey – due to cost limitations, between six and 15 cross-sections are typically captured per
site. More cross-sections would enable a better understanding of the hydraulic conditions in
the stream. More cross-sections would also allow better calibration of a model, especially in
lowland areas where stream gradients are low.

Measured water levels – due to cost limitations, water levels are usually measured on a single
day, thereby representing water level for one particular flow. This means that the calibrated
hydraulic model is accurate for that flow, but will be less accurate for significantly higher or
lower flows.

Estimation of flows at the site – commonly, study sites are located away from established
stream gauging sites. In upland areas, it is possible to estimate flows because they are
typically proportional to the upstream catchment area. Lowland areas are more complex, as a
combination of surface water contributions and groundwater interaction can sometimes make
flows along a reach highly variable and unpredictable. A better understanding of groundwater
interaction in lowland streams would be helpful (i.e. identifying which reaches are gaining or
losing during low-flow periods).
The cost associated with the field measurements needed to define the cross-sections along the river
and obtain measurements for calibration can limit the application of hydraulic models. However,
LiDAR data is becoming more widely available (particularly along waterways) and can be used to
obtain much of the information needed for hydraulic models for larger lowland streams, provided the
LiDAR is captured during periods of very low flow or is able to provide ground-surface information
below the water surface. Unfortunately, for narrow streams or upland streams, LiDAR currently does
not have sufficient resolution to identify some of the key habitat features. In addition, the presence of
significant tree cover makes LiDAR less effective, obscuring details of habitat and geomorphology
along stream banks.
Even with the availability of LiDAR data it may be a costly exercise to develop hydraulic models for all
sites in which water managers wish to understand the nature of low flows. There may be some water
depths that are critical for ecological processes (e.g. to maintain connectivity between pools). A
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review of the flows where these depths are provided – at sites that have a hydraulic model available –
may allow generalisations that can be applied to other sites. For example, SKM (2005) compared the
minimum low flows recommended by 10 environmental flow studies from Victoria and found that the
recommendation most commonly corresponded to flow with an exceedence value of 90 per cent or
more. However, a large variation in results was observed – both between different studies and
between different reaches within each study.
An important aspect of management during low-flow periods is the protection of refuges or locations
where water will remain in-stream even during cease-to-flow events. These locations can be identified
if the geomorphology of the stream is well understood. LiDAR information or a detailed survey of a
waterway can be used to identify pools along the river. The length of time these pools will contain
water will depend on the rate of evaporation and also the nature of the connectivity with the
groundwater. While there is good coverage of measurements to enable estimates of evaporation to
be made, the nature of groundwater interactions at such a specific location may be more difficult.
7.3. Summary
From an ecological perspective it is important to consider the magnitude of low flows in conjunction
with the hydraulic characteristics of the stream. ARI recommends that further consideration be given
to low-flow indicators that represent hydraulic characteristics (Rolls et al. 2010). Hydraulic models can
be used to understand the relationship between flow and water levels along a river, but it can be
costly to obtain all of the required model inputs.
The issues and gaps related to understanding the hydraulic characteristics of low flows are:

considerable time and expense is required to understand the hydraulic characteristics of a
stream

at present little information is available to help water managers understand the longevity of
pools during a cease-to-flow event

the location of weirs and flow-control structures are not always known.
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8. Summary of issues and gaps
The gaps and limitations in monitoring and modelling low flows identified are compiled in the table
below, with the key gaps and limitations denoted in bold text.
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Table 2: Summary of identified gaps for monitoring and modelling low flows
Topic
Low-flow indicators
Measuring and
monitoring
Estimating flows in
unregulated
catchments
Issues and gaps
1
The indices do not enable comparison between regions.
2
The uncertainty associated with low-flow indicators is not well
understood.
3
Most low-flow indicators can be calculated using existing software, with the
exception of indicators related to antecedent and post low-flow event
conditions.
4
There are difficulties in deriving daily time-series of flow to calculate the flow
indicators in data-poor areas.
5
It is difficult to prioritise the adoption of the 28 low-flow indicators.
6
The estimation of a natural time-series of flow requires assumptions about the
role of anthropogenic effects in cease-to-flow events.
7
The influence of longer-term climate regime variability (or change) on the lowflow indicators is not well understood.
8
Reference natural (and current) flows are poorly archived and are usually not
readily available from state agencies for ongoing use. (Note this does not refer
to gauged streamflows.)
9
The length of data required to calculate low-flow indicators associated with
less frequent events is not known.
10
The likelihood of low-flow events under future scenarios is not well
understood.
11
Inconsistent language is used to refer to low-flow metrics, indicators and
descriptors.
12
Users are unaware of the uncertainty in low-flow streamflow measurements.
13
Streamflows at many important ecological locations are not gauged.
14
Real-time flow information is not widely available.
15
Current locations and monitoring frequencies of streamflow and diversion
gauging may not adequately measure and safeguard water being provided to
meet ecological needs.
16
The water levels in off-stream waterbodies are important, but not commonly
measured.
17
Limited number of gaugings available during low-flow periods.
18
The measurement uncertainty associated with water levels will vary between
different instrumentation.
19
Difficulty measuring very low flows using a current meter.
20
Measurement of low flows at unstable cross-sections.
21
The benefits of emerging streamflow measurement technologies in measuring
low flows are not widely understood.
22
Ecologists need to be able to identify cease-to-flow events.
23
Current monitoring techniques do not pick up subsurface flow.
24
There is flow through in fish passages that is not recorded during gauging.
25
The relative ability of commonly available rainfall-runoff models to represent
low flows is not widely understood.
26
No study has been conducted to determine which objective functions should
be used to calibrate to low flows.
27
The catchment characteristics that control low-flow behaviour are difficult to
identify and characterise.
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Topic
Estimating flows in
unregulated catchments
cont’d
Estimating flows in
regulated catchments
Estimating anthropogenic
influences
Mechanisms generating
low flows
Hydraulic characteristics
Issues and gaps
28
A method to rapidly determine the hydrological similarity of catchments with
respect to low flows is not available.
29
Transposition methods tend to be based on transposition factors related to
the average flow.
30
The shift in climate in south-eastern and south-western Australia during the
past 10 to 30 years has created uncertainties in the accuracy of previously
calibrated rainfall-runoff models.
31
The selection of catchment model parameters for ungauged catchments
introduces uncertainty.
32
A substantial amount of effort is required to adequately estimate a timeseries of daily streamflows at an ungauged site.
33
The location of perennial stream reaches and low-flow refuges for in-stream
biota is not always known.
34
Rainfall-runoff models are not useful for modelling processes at a small
scale (e.g. waterhole).
35
It can be difficult to determine the low-flow paths in poorly defined channels.
36
There are large uncertainties associated with estimates of river losses.
37
River losses may be represented poorly within a model.
38
Not all models are represented on a daily time-step.
39
Model may not represent the daily operation of a water supply system.
40
Models do not include dynamic representation of water trading.
41
Models may not represent cease-to-flow events well.
42
Models may not be calibrated to represent low flows and the limitations may
not be communicated to all relevant stakeholders.
43
The degree of regulation and effect on low flows can vary considerably
across a region.
44
Smart meters are not widely used - a strong business case for their use is
needed
45
Estimates of irrigation water use on a daily time-step are poor. Many of the
decisions are based on poor interpretation and representation of the
behaviour of irrigators in the river system models.
46
Difficulty in estimating anthropogenic influences at a daily time-step.
47
Readily available information on low-flow discharge locations from sources
such as wastewater treatment plants, return flows from irrigation and coal
seam gas.
48
The seasonal impact of land use change on streamflows is not very well
understood.
49
Floodplain structures and small weirs located on a waterway can alter lowflow characteristics.
50
The volume of pumping from waterholes is not well known.
51
There are a range of issues around monitoring and modelling of
groundwater extractions.
52
Worldwide there has been little investigation into the mechanisms that
generate low flows.
53
Few studies have monitored surface water/groundwater interactions in
losing streams.
54
The location of gaining and losing river reaches is not mapped outside of
the Murray-Darling Basin.
55
Considerable time and expense is required to understand the hydraulic
characteristics of a stream.
56
At present little information is available to help water managers understand
the longevity of pools during a cease-to-flow event.
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57
The location of weirs and flow-control systems is not always known.
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PART II: Identifying solutions
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9. Proposed solutions
9.1. Introduction
Part I of this report identified more than 50 gaps and limitations in the current monitoring and
modelling of low flows. At this stage of the project a workshop was held with specialists with
knowledge and experience of low-flow hydrology, water resource supply modelling, hydraulic
modelling, hydrography and ecology (Appendix B) to review the gaps and limitations already
identified, extend or contract these as necessary, prioritise them and identify possible solutions
(Appendices C and D). The workshop’s main outcome was 11 proposed solutions to address key
gaps (see Section 0).
The proposed solutions will be refined and prioritised through consultation with a broader group of
stakeholders via the project advisory group. The highest priority will be pursued in Stage 2 of the Low
Flows project.
9.2. Proposed solutions
Solutions to address each of the issues and gaps are proposed in the table below. Details of eleven
solutions are provided in Section 0.
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Table 3: Summary of solutions to gaps in monitoring and modelling low flows
Topic
Low-flow
indicators
Issues and gaps
Proposed solutions
1
The indices do not enable comparison
between regions.
Proposal 1 in Section 0
2
The uncertainty associated with low-flow
indicators is not well understood.
Proposal 2 in Section 0
3
Most low-flow indicators can be calculated
using existing software, with the exception
of indicators related to antecedent and post
low-flow event conditions.
Proposal 2 in Section 0
4
There are difficulties in deriving daily timeseries of flow to calculate the flow indicators
in data-poor areas.
Investigate the use of low-flow indicators
that can be derived from monthly data in
data-poor areas.
5
It is difficult to prioritise the adoption of the
28 low-flow indicators.
Investigate the redundancy in the 28 lowflow indicators.
6
The estimation of a natural time-series of
flow requires assumptions about the role of
anthropogenic effects in cease-to-flow
events.
Develop guidelines to help practitioners
estimate cease-to-flow events in a natural
time-series of flow.
7
The influence of longer-term climate regime
variability (or change) on the low-flow
indicators is not well understood.
Invest in a long-term research program.
8
Reference natural (and current) flows are
poorly archived and are usually not readily
available from state agencies for ongoing
use. (Note this does not refer to gauged
streamflows.)
A database of time-series of reference
natural (and current) streamflows could be
established and maintained for use in ecohydrologic studies. Information should be
available about the quality of the modelled
streamflows, including what anthropogenic
influences have been considered in the
derivation of natural flows and what level of
development was adopted for the current
flows.
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Topic
Monitoring
Estimating
flows in
Issues and gaps
Proposed solutions
9
The length of data required to calculate lowflow indicators associated with less frequent
events is not known.
Proposal 2 in Section 9.3
10
The likelihood of low-flow events under
future scenarios is not well understood.
Use stochastic data to predict the likelihood
of future low-flow events.
11
Inconsistent language is used to refer to
low-flow metrics, indicators and descriptors.
Adopt the nomenclature used in the
Sustainable Rivers Audit.
12
Users are unaware of the uncertainty in lowflow streamflow measurements.
Proposal 3 in Section 9.3
13
The streamflows at many important
ecological locations are not gauged.
Proposal 4 in Section 9.3
Streamflow measurements are commonly
used to represent a larger river reach.
Metadata that defines the river reach that is
represented by each gauge may help
planners and managers select the most
appropriate streamflow gauge for any
assessment.
14
Real-time flow information is not widely
available.
Proposal 3 in Section 9.3
15
Current locations and monitoring
frequencies of streamflow and diversion
gauging may not adequately measure and
safeguard water provided to meet ecological
needs.
Proposal 4 in Section 9.3
16
The water levels in off-stream waterbodies
are important, but not commonly measured.
Proposal 4 in Section 9.3
17
Limited number of gaugings available during
low-flow periods.
Provide a funding scheme to collect more
gaugings during low-flow events at
important sites.
18
The measurement uncertainty associated
with water levels will vary between different
instrumentation.
Proposal 3 in Section 9.3
19
Difficulty measuring very low flows using a
current meter.
Discuss with NRETAS hydrographers the
potential for research or alternative
technologies to better monitor low flows in
carbonate aquifer catchments.
20
Measurement of low flows at unstable crosssections.
The use of calibrated flow structures can be
used to improve the measurement of low
flows at unstable cross-sections.
21
The benefits of emerging streamflow
measurement technologies in measuring
low flows are not widely understood.
Identify when and where new techniques
are economically advantageous over the
more traditional approaches in monitoring
low flows. However, at present these
technologies do not provide better
measurements of low flows than
conventional methods.
Investigate using remote sensing
information to provide information about
pool depth or area.
22
Ecologists need to be able to identify ceaseto-flow events.
Proposal 3 in Section 9.3
23
Current monitoring techniques do not pick
up subsurface flow.
Proposal 3 in Section 9.3
24
There is flow through fish passages that is
not recorded during gauging.
Proposal 3 in Section 9.3
25
The relative ability of commonly available
rainfall-runoff models to represent low flows
Proposal 5 in Section 9.3
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Topic
Issues and gaps
unregulated
catchments
is not widely understood.
Estimating
flows in
regulated
catchments
Proposed solutions
26
There has been no study to determine
which objective functions should be used to
calibrate to low flows.
Proposal 5 in Section 9.3
27
The catchment characteristics that control
low-flow behaviour are difficult to identify
and characterise.
Proposal 11 in Section 9.3
28
A method to rapidly determine the
hydrological similarity of catchments with
respect to low flows is not available.
Undertake a study to develop a tool to
rapidly determine the similarity of
catchments with regard to low flows.
29
Transposition methods tend to be based on
transposition factors related to the average
flow.
Proposal 5 in Section 9.3
30
The shift in climate in south-eastern and
south-western Australia during the past 10
to 30 years has created some uncertainties
in the accuracy of previously calibrated
rainfall-runoff models.
Proposal 5 in Section 9.3
A review of the calibration period of rainfallrunoff models across southern Australia and
a recalibration of those models to more
recent data should be undertaken where
this has not already occurred.
31
The selection of catchment model
parameters for ungauged catchments
introduces uncertainty.
Provide funding to ongoing research in this
area.
32
A substantial amount of effort is required to
adequately estimate a time-series of daily
streamflows at an ungauged site.
Develop models to estimate low-flow
indicators from catchment characteristics.
33
The location of perennial stream reaches
and low-flow refuges for in-stream biota is
not always known.
Develop an atlas of refuges. Proposal 6 in
Section 0
34
Rainfall-runoff models are not useful for
modelling processes at a small scale (e.g.
waterhole).
Proposal 6 in Section 0
35
The channel is not always well defined and
it can be difficult to determine the low-flow
paths.
Use remote sensing to identify flow paths.
36
There are large uncertainties associated
with estimates of river losses.
Proposal 7 in Section 0
37
River losses may be represented poorly
within a model.
Proposal 7 in Section 0
Establish and publish plausible ranges of
river losses for different river systems that
can be used to verify model results.
38
Not all models are represented on a daily
time-step.
Provide funding to help agencies convert
models to a daily time-step.
39
Model may not represent the daily operation
of a water supply system.
Provide funding to help agencies improve or
update the representation of operational
practices within the models.
40
Models do not include dynamic
representation of water trading.
Improve the understanding of likely water
market behaviour during low-flow periods
and include this knowledge in water
resource models.
41
Models may not represent cease-to-flow
events well.
Provide funding to help agencies improve
representation of cease-to-flow events in
models.
42
Models may not be calibrated to represent
low flows and the limitations may not be
communicated to all relevant stakeholders.
Proposal 7 in Section 0
43
The degree of regulation and effect on low
flows can vary considerably across a region.
Develop a regional summary of the location
of regulation and the effect of regulation on
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Topic
Issues and gaps
Proposed solutions
low flows.
Estimating
anthropogen
ic influences
Mechanisms
generating
low flows
Hydraulic
characteristi
cs
44
A business case for the use of smart meters
has not been prepared.
Proposal 8 in Section 9.3
45
Estimates of irrigation water use on a daily
time-step are poor. Many of the decisions
are based on poor interpretation and
representation of the behaviour of irrigators
in the river system models.
Proposal 9 in Section 9.3
46
Difficulty in estimating anthropogenic
influences at a daily time-step.
Undertake detailed studies for a range of
case study sites to examine the impact of
anthropogenic influences on daily low-flow
indicators. Develop model to estimate these
changes in other catchments.
47
Readily available information on low-flow
discharge locations from sources such as
wastewater treatment plants, return flows
from irrigation and coal seam gas.
Map low-flow discharge locations across
Australia.
48
The seasonal impact of land use change on
streamflows is not very well understood.
Proposal 10 in Section 9.3
49
Floodplain structures and small weirs
located on a waterway can alter low-flow
characteristics.
Promote the availability and use of LiDAR
information.
50
The volume of pumping from waterholes is
not well known.
Invest in additional metering.
51
There are a range of issues around
monitoring and modelling of groundwater
extractions.
Invest in additional metering.
52
Worldwide there has been little investigation
into the mechanisms that generate low
flows.
Proposal 11 in Section 9.3
53
Few studies have monitored surface
water/groundwater interactions in losing
streams.
Undertake a monitoring program in some
losing streams.
54
The location of gaining and losing river
reaches is not mapped outside of the
Murray-Darling Basin.
Extend the study to regions outside the
Murray-Darling Basin that have sufficient
data.
55
Considerable time and expense is required
to understand the hydraulic characteristics
of a stream.
Promote the availability and use of LiDAR
information.
Investigate the relationship between
critically important water depths and lowflow indicators.
56
At present little information is available to
help water managers understand the
longevity of pools during a cease-to-flow
event.
Proposal 4 in Section 9.3
Proposal 6 in Section 9.3
Mapping of major pools along rivers.
Investigation of the connection of these
pools to the groundwater system.
Collection of anecdotal evidence about the
persistence of pools during recent cease-toflow events.
Where a gauging station is located in a weir
pool it will continue to measure water levels
after a cease-to-flow event. This information
could be used to better understand the
persistence of waterholes in a region.
57
The location of weirs and flow-control
systems is not always known.
Promote the availability and use of LiDAR
information.
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9.3. Key proposed solutions
Proposal 1: Develop low-flow indicators for regional comparison
Objective: To enable comparison of low-flow indicators at sites across a region.
Description: Low-flow indicators provide one means to objectively assess the relative environmental
risk due to changes in the low-flow regime. ARI reviewed the literature related to low-flow ecology and
indicators and created a list of 28 low-flow indicators (Rolls et al., 2010). A comparison of flow stress
at the regional scale is often required. A meaningful comparison is possible if the low-flow indicators
are described in relation to the variability of the natural flow regime. Using this approach: a high score
represents a score that is well within the conditions experienced under natural conditions and a low
score represents deviation from the natural conditions. A range-standardised approach has been
adopted in other studies of flow indicators (i.e. Sustainable Rivers Audit and the Victorian Flow Stress
Ranking) and the concepts developed in these studies should be applied to low-flow indicators.
Outcomes: Low-flow indicators that can be used to meaningfully compare low-flow indicators across
a region.
Expected timeline for completion: six to 12 months
Proposal 2: Improve awareness of the uncertainty associated with
low-flow indicators
Objective: To improve awareness of the uncertainty associated with low-flow indicators.
Description: The uncertainty associated with low-flow indicators originates from a number of sources.
The derivation of a daily time-series of streamflows may be based on measured streamflows that are
affected by measurement error. Where measured streamflows are not available, or a time-series
representing natural conditions is required, modelled streamflows are generated. These also rely on a
series of assumptions which also contain uncertainty. The length of the period of streamflows used to
calculate the low-flow indicators will also contribute to the overall uncertainty.
The possible magnitude of uncertainties associated with low-flow magnitudes will be demonstrated
using a number of case studies. Key sources of uncertainty (e.g. measurement uncertainty) will be
identified, quantified and combined to estimate the overall uncertainty. The uncertainty analysis may
also be used to investigate issues such as the:

relative accuracy of indicators calculated using daily and monthly time-series

relationship between accuracy and length of record used to calculate flow indicators

sensitivity of each low-flow indicator to each source of uncertainty

the ability to detect relative changes in an indicator between scenarios where the absolute
value of the indicator is uncertain.
Based on the outcomes of the case study, guidelines will be developed to allow similar analyses to be
undertaken in other regions. These guidelines would also present a standard approach for
communicating information about uncertainty and guidance on how to use the information to improve
decision making.
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Most low-flow indicators can be calculated using existing software, with the exception of indicators
related to antecedent and post low-flow event conditions. These software packages could be updated
to incorporate the additional indicators and expanded to enable the uncertainty in the flow indicators
to be calculated.
Outcomes: Clear guidance on the likely magnitude of uncertainty in low-flow indicators; methods and
tools to quantify the uncertainty; an understanding of the main factors contributing to the uncertainty;
and guidelines for using this information to improve decision making.
Expected timeline for completion: one to two years
Proposal 3: Improve the availability of streamflow information and
metadata
Objective: To improve the availability of streamflow information and provide metadata to allow
planners and managers to assess whether streamflows measured or modelled at a site are suitable
for a particular purpose.
Description: Most states have made data available on the internet, however the management of low
flows requires real-time information about low flows and may be improved if data were available
online.
The suitability of a streamflow time-series for a particular purpose will depend on the quality of
measurements made during low-flow periods. The quality of streamflow data will vary between
gauges and some may provide poor measurements of low flows. Little information is available to help
users assess the accuracy of the streamflow measurements and consequently determine their
suitability for a particular purpose. Metadata that would provide useful information includes a
description of:

the stability of the cross-section and presence of anabranches

the ability to detect a cease-to-flow event

any structures that bypass the gauge (such as a fish ladder)

any qualitative information available regarding subsurface flow

list of any known flow-regulating structures upstream

the gauging history

quality codes associated with each flow measurement

the accuracy of the water level measurements

the uncertainty associated with streamflow measurements of varying magnitudes.
An additional task could be added to this proposal; that is, establishing and maintaining a database of
time-series of reference natural (and current) streamflows for use in eco-hydrologic studies.
Information should be available on the quality of the modelled streamflows, including what
anthropogenic influences were considered in the derivation of natural flows and what level of
development was adopted for the current flows.
This proposal has been developed to improve the information available for helping practitioners select
appropriate gauges for low-flow analysis. However, the availability of this information has wider
benefits and will allow the suitability of sites to be assessed for a range of purposes.
Outcomes: A database of all Australian streamflow gauges and locations of modelled streamflows
that provides information to allow users to assess the suitability of data for a particular purpose.
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Expected timeline for completion: one to two years
Proposal 4: Increase metering and monitoring of ecologically
relevant sites
Objective: To increase the metering of low-flow events at ecologically relevant sites.
Description: Monitoring of water levels and streamflows provides important information for the
management of low flows. Not all ecologically relevant sites are currently metered. In particular, the
water levels in pools and off-stream waterbodies are important, but not commonly measured. Key
ecologically relevant sites that are not currently monitored need to be identified. At some sites water
level measurements may be sufficient. The work required to monitor these sites needs to be
quantified and used to rank the sites according to the benefit of monitoring relative to the required
investment. The assessment should also consider the homogeneity of the flows along the reach to
identify the region represented by any additional gauges. The benefits associated with this proposal
may extend beyond a better understanding of low flows.
Outcomes: Extended network of water level and streamflow monitoring.
Expected timeline for completion: Ongoing
Proposal 5: Develop guidelines for estimating low flows
Objective: To improve the accuracy of modelled low flows.
Description: Methods to estimate flows at ungauged locations have traditionally been aimed at
improving estimates of system yield, not low flows. Estimation of low flows may require a different
approach. Guidance is required to help modellers choose between using streamflow transposition or
a rainfall-runoff model to estimate low flows at a given site. Guidance is also required to help
modellers apply these techniques to low flows.

A transposition method suited to low flows needs to be developed and guidance provided for
its application that includes the selection of an appropriate gauge and calculation of a
transposition factor.

Guidance is required to help modellers select an appropriate rainfall-runoff model, calibration
period and objective function for use during calibration. In particular, the guidelines should
highlight the importance of recalibrating models using recent periods of low flows.
Outcomes: Guidelines that recommend an appropriate model selection and calibration strategy for
low flows.
Expected timeline for completion: six to 12 months.
Proposal 6: Improve understanding of the location and longevity of
pools and waterholes
Objective: To improve the understanding of the location and longevity of pools and waterholes.
Description: At present little information is available to help water managers understand the longevity
of pools during a cease-to-flow event. Firstly, the location of perennial streams, permanent pools and
waterholes should be mapped based on recent past extreme droughts and making use of remote
sensing information. Off-river storages such as farm dams may also be important for identifying
regional-scale refuges. Models to predict the persistence of pools should be developed and used to
extrapolate data from measured systems to other systems.
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Outcomes: Map of the location of pools and waterholes and models to predict the persistence of
these waterbodies.
Expected timeline for completion: one to two years.
Proposal 7: Improve representation of losses in water resource
supply models
Objective: To transparently and consistently represent losses within water resource system models.
Description: The representation of losses in models varies between agencies and even individual
modellers. In many models the ‘loss’ will represent the errors in the model in addition to the physical
process. Furthermore, losses in the models are often temporally static and only reflect average
conditions. Guidelines that outline best practice are required to improve the representation of losses
in these models. These guidelines will cover the methods recommended for quantifying losses,
appropriate methods for representation in a model, calibration strategies and reporting requirements.
The guidelines will also outline how the operational decisions made by system operators affect
system losses and how to represent these decisions within the model.
Outcomes: Adoption of a consistent and improved modelling approach will give planners and
managers greater confidence in the estimates of low flows generated by water resource supply
models.
Expected timeline for completion: six to 12 months.
Proposal 8: Develop a business case for smart metering
Objective: To identify when and where smart meters are economically advantageous to install and
use.
Description: Trials of the use of smart meters on private diversions have occurred in a number of
places around Australia. The preliminary outcomes of these trials highlight that a wealth of information
can be obtained, particularly in relation to the management of private diversions at low flows. The use
of these meters in other regions could play a critical role in real-time management of water, especially
in managing for low-flow ecological responses in unregulated systems. A business case for the use of
smart meters on private diversions and other extractions (e.g. groundwater bores, farm dams) could
be used to identify when and where smart meters are economically advantageous to install and use.
The benefits of this proposal would extend beyond a better understanding of low flows.
Outcomes: Planners and managers who can make informed decisions on smart metering.
Expected timeline for completion: four to six months
Proposal 9: Improve modelling of irrigation water use
Objective: To improve estimates of relevant time-step irrigation water use.
Description: Estimates of irrigation water use on a daily time-step are poor. Models of crop water
requirements are available and widely accepted. However, these models do not account for irrigator
behaviour that may be responding to other drivers such as allocation announcements and commodity
prices. As such, many of the models are based on poor interpretation and representation of the
behaviour of irrigators. More sophisticated models are required to reflect the uncertainty in irrigator
behaviour. The benefits of this proposal would extend beyond a better understanding of low flows.
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Outcomes: More realistic estimates of daily (or relevant time-step) irrigation water use and as a
consequence, improved estimates of low flows.
Expected timeline for completion: one to two years
Proposal 10: Improve understanding of the seasonal impacts of
land use change on low flows
Objective: To understand the seasonal impacts of land use change on low flows.
Description: The seasonal impact of land use change on streamflows is not very well understood, but
it is expected the effect will be greater during lows flows than other parts of the flow regime. Existing
datasets may be used to compare land use change impacts between seasons.
Outcomes: Seasonal impacts of land use change.
Expected timeline for completion: four to six months
Proposal 11: Review mechanisms that generate low flows
Objective: To improve the understanding of the mechanisms that generate low flows.
Description: An understanding of the mechanisms that generate low flows is required to predict the
impact of climate change scenarios on low flows and to most effectively address issues of stress
during low-flow periods. Worldwide there has been little investigation into the mechanisms that
generate low flows. A comprehensive review of the existing literature is required to summarise the
state of knowledge, identify key gaps and propose a research agenda to improve knowledge related
to the drivers of low-flow events. The outcomes of the review may also be used to assess how well
these processes are represented within rainfall-runoff models.
Outcomes: A review of the mechanisms that generate low flows and a clear research agenda that
may lead to the development of better models and more accurate identification of losses.
Expected timeline for completion: four to six months.
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Appendices
Appendix A: Low-flow indicators
Descriptors of low-flow hydrology (hydrological metrics) within priority components of the flow regime, their known ecological relevance and eco-regional
differences. Source: Australian Rivers Institute (Rob Rolls, Nick Marsh, Fran Sheldon) via the ecological component of the low flows project.
HYDROLOGIC METRIC U T
DEFINITION
SOURCE
EXPECTED ECOLOGICAL RELEVANCE & CAVEATS
ECO-REGIONAL (& OTHER) DIFFERENCES
Stage 1b,
modified
from
Puckridge
et al.
(1998)
• Historical factors affect evolutionary adaptations of aquatic biota and can
inform as to whether a system is typically ‘dry’ or ‘wet’, thereby informing the
expected ecological responses
• Cumulative effects of reduced discharge impact community more strongly than
short-term effects (Finn et al. 2009)
• Long-term data may be required to assess ecological recovery from low flow and
drought events (Dewson et al. 2007, a-d)
• Recovery will also depend on event duration, magnitude, timing and frequency
(Lake 2003)
• Recovery may be confounded by lag effects due to different levels of tolerance
and adaptations to low-flow conditions (including antecedent and post-flow
characteristics). Positive response of algal and invertebrates with short-generations
may be fast; those of aquatic macrophytes, large invertebrates and fish may be
prolonged (Lake 2008)
Temporary/intermittent systems
• Long-term antecedent conditions may be the driving force
behind invertebrate responses (Fritz & Dodds 2002).
• Adaptations of biota to variable connectivity may reduce
detection of ecological responses.
• Recovery may be quick for highly adapted and tolerant taxa,
particularly for invertebrates (e.g. Caruso 2002)
• Antecedent flow permanence may be critical in determining
invertebrate community responses (Stubbington et al. 2009)
Groundwater-dependent systems
• Recovery of invertebrates may correlate with recovery of
groundwater inputs
• Rapid recession may lower recruitment of floodplain spawners compared with
channel spawners (Puckridge et al. 1998); increased burrowing and stranding of
certain fish species (e.g. galaxids) may occur along with short-term increases in
invertebrate drift (Dewson et al. 2007b; James & Suren 2009)
Stream size
• Drift is unlikely to be viable escape strategy in small shallow
streams (James & Suren 2009)
Principle 1: Antecedent and post low-flow event conditions
Median of sums of
4 A
every 3, 5 and 7 years’
annual number of zeroflow days
Median of the sums of every 3, 5
and 7 years’ annual number of days
having zero flow (moving count)
CV sums of every 3, 5
and 7 years’ annual
number of zero-flow
days
CV in the sums of every 3, 5 and 7
years’ annual number of days having
zero flow (moving count)
7 A
Median of sums of
4 A
every 3, 5 and 7 years’
annual number of
<baseflow days
Median of the sums of every 3, 5
and 7 years’ annual number of days
having below baseflow but above
zero flow (moving count)
CV sums of every 3, 5
and 7 years’ annual
number of <baseflow
days
7 A
CV in the sums of every 3, 5 and 7
years’ annual number of days having
below baseflow but above zero flow
(moving count)
Median of the 30d,
90d, 1y, 2y and 5y
discharge before and
after the annual
minimum
1 M, Median of the total discharge over
S, monthly, seasonal and annual
A timeframes before and after the
occurrence of the annual minimum
Fall rate before below
baseflow conditions
6 D
CV fall rate
7 D
Mean rate of negative changes in flow Modified
from one day to the next before flows from Olden
with <baseflow magnitude
and Poff
(2003)
CV in rate of negative changes in flow
from one day to the next before flows
with <baseflow magnitude
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HYDROLOGIC METRIC U T
DEFINITION
SOURCE
EXPECTED ECOLOGICAL RELEVANCE & CAVEATS
ECO-REGIONAL (& OTHER) DIFFERENCES
Kennard et
al. (2010)
• Extended low flows may increase competitive interactions between predators and
prey (Bond 2008) and may restrict species dispersal, especially for fish (Arthington &
Pusey 2003)
• Extended low-flow duration may lead to reduction in water quality, increased
salinity (from surface water concentration and or groundwater intrusion), hypoxia or
anoxia, algal blooms and increased retention of organic matter (Lind et al. 2006;
Lake 2008)
• High variability in low-flow duration may correlate with brief and/ or flexible
lifecycles of aquatic biota (Puckridge et al. 1998)
• Prolonged low flows may temporarily increase the density of aquatic biota, but
abundances and richness may decline as the low-flow period extends
• Extended low- or zero-flow days may lead to dominance by physically tolerant taxa,
more large carnivores, and mortality from predation, parasitism and/or starvation
(Puckridge et al. 1998; Lake 2008; Burford et al. 2008)
• Time between flow pulses may control algal growth (Caruso 2001)
Temporary/ intermittent systems
• ‘Increased dry-spell duration in dryland or intermittent rivers
will lead to reduced diversity and biomass of invertebrates
and fish due to reduction in permanent, suitable aquatic habitat’
(Poff et al. 2010: 157)
• ‘Increased duration of extreme low flows will result in riparian
canopy die-back in arid to semi-arid landscapes’ (Poff et al.
2010: 157)
Semi-arid and temperate regions of the Murray-Darling river
system
• Some fish species spawn and recruit during extended lowflow periods and warmer months (‘low-flow recruitment
hypothesis’; Humphries et al. 1999)
Dryland systems (e.g. Cooper Creek)
• Increased disconnection among habitats may increase spatial
variability in macroinvertebrate and fish assemblages (Sheldon
et al. 2002; Arthington et al. 2005)
• Low variability in magnitude may be correlated with greater proportions or
abundances of flow-adapted taxa and encourage the growth of aquatic macrophytes
(Bunn & Arthington 2002)
• “Depletion of low flows will lead to progressive reduction in total secondary
production as habitat area becomes marginal in quality or is lost” (Poff et al. 2010:
157)
Perennial systems
•
‘Depletion of extreme low flows in perennial
streams and subsequent drying will lead to rapid loss of
diversity and biomass in invertebrates and fish due to declines
in wetted riffle habitat, lowered residual pool area⁄depth when
riffles stop flowing, loss of connectivity between viable habitat
patches and poor water quality’ (Poff et al. 2010: 157)
Principle 2: Duration
Annual minima of 1, 3,
7, 30
and 90 day means
1 D, Magnitude of minimum annual flows
M, of various duration, ranging from
S daily to seasonal (i.e. 1, 3, 7, 30
and 90 days respectively)
CV annual minima of 1, 7 D, CV in magnitude of minimum annual
3, 7,
M, flows of various duration, ranging
30 and 90 day means
S from daily to seasonal (i.e. 1, 3, 7,
30 and 90 days respectively)
Low-spell duration
(<75th,
<90th and <99th
percentile)
4 A
Mean duration of flows which remain
below a lower threshold defined by
the 75th, 90th and 99th percentiles,
respectively (from the flow duration
curve)
CV low- spell duration 7 A
(<75th,<90th and <99th
percentile
CV in duration of annual
occurrences during which the
magnitude of flow remains below a
lower threshold (75th, 90th and 99th
percentiles, respectively)
Number of zero-flow
days
5 A
Mean annual number of days having
zero flow
CV number of zero-flow 7 A
days
CV in annual number of days having
zero flow
Number of <baseflow
days
5 A
Mean annual number of days having
below baseflow but above zero flow
CV number of
<baseflow days
7 A
CV in annual number of days having
below baseflow but above zero flow
Median of annual
minimum
flows
7 A
Median of the lowest annual daily
flow divided by the mean annual
daily flow averaged across all years
Baseflow index
7 A
Ratio of baseflow to total flow,
averaged across all years, where
baseflow is calculated using three
way digital filter
Barma
Water &
SKM
Principle 3: Magnitude
Kennard et
al. (2010)
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HYDROLOGIC METRIC U T
DEFINITION
SOURCE
EXPECTED ECOLOGICAL RELEVANCE & CAVEATS
ECO-REGIONAL (& OTHER) DIFFERENCES
• ‘Augmentation of low flows: may lead to an initial increase in total primary and
secondary production but this would decline with drowning of productive riffles
and/or increased turbidity and decreased light penetration; will cause a decline in
richness and abundance of species with preferences for slow-flowing, shallow- water
habitats, whereas fluvial specialists or obligate rheophilic species would shift in
distribution or decline in richness and abundance if low flows were depleted; will
result in increased establishment and persistence of aquatic and riparian vegetation
with concomitant shifts in species distributions towards increased dominance by
fewer species’ (Poff et al. 2010: 157)
• Decreased magnitude (and extended duration) will reduce riffle habitat availability
and convert deeper, pool zones into refugia
• Decreased magnitudes may reduce fish body size and/or growth rates (Harvey et
al. 2006; Walters & Post 2008)
Spatial location of refugia
• In systems where riffle habitats and refugia (e.g. pools or
waterholes) are spatially close, broadscale or highly significant
changes in biotic assemblages may not be detected
• Frequency and timing of low-flow events affect long-term species diversity, lifehistory strategies, and the timing and extent of recovery
• Increased variability of frequency of low flows may increase variation in water
quality (Magoulik & Kobza 2003)
• High variability of timing may correlate with flexible life-history characteristics
(Puckridge et al. 1998)
• Low predictability may be correlated with flexible breeding systems
(Puckridge et al. 1998)
• In general, Australian macroinvertebrates are well-adapted to high levels of flow
variability (low predictability) and their responses may be too subtle to detect.
However, this may not apply in regulated systems where natural levels of flow
variability have been lost
• Decreased variability (increased predictability) may lead to the loss of refugial
habitat resulting in decreased species abundance and diversity, and inhibit the
dispersal and migration of biota (Leigh & Sheldon 2008)
• Water abstraction and groundwater extraction will have the greatest ecological
impacts during times of naturally occurring low-flow periods, particularly in small
streams (Deitch et al. 2009)
• Predictability and seasonality may be driven by regulated, unregulated, tropical or
other types of riverine systems
Perennial systems
• Stable baseflows in subtropical and tropical regions are
important for fish spawning and recruitment during low-flow
periods (Bunn & Arthington 2002)
Perennial systems with regular flow regimes
• Increased variability may reduce ecosystem function and
lead to loss of spawning and other life-history stage triggers
resulting in decreased species abundance and diversity (Leigh
& Sheldon 2008)
Floodplain rivers
• Decreased frequency of drying may reduce microinvertebrate
(e.g. zooplankton) richness and result in adverse effects on
waterbird and fish breeding in floodplains (Jenkins & Boulton
2003)
Temporary and highly intermittent systems
• Increased variability may lead to shifts in community
composition (Leigh & Sheldon 2008)
• Decreased variability may reduce ecosystem function and
species beta (among habitat)-diversity (Leigh & Sheldon 2008)
Wet-dry tropics
(Grayson et al. 1996)
CV Baseflow Index
7 A
CV in Baseflow Index
Low-flow discharge
(75th, 90th, and 99th
percentile)
1 A
75th, 90th and 99th percentile,
respectively from the flow duration
curve
Specific mean annual
minimum runoff
2 A
Mean annual minimum flow divided by
catchment area
Principle 4: Frequency and timing (predictability)
Low-flow spell count
(<75th,<90th and <99th
percentile)
5 A
Mean number of annual
occurrences during which the
magnitude of flow remains below a
lower threshold defined by the 75th,
90th and 99th percentiles,
respectively (from the flow duration
curve)
CV of low-flow spell
count (<75th, <90th
and <99th percentile)
7 A
CV in number of annual
occurrences during which the
magnitude of flow remains below a
lower threshold (75th, 90th and 99th
percentiles, respectively)
Julian date of annual
minimum
7 D
Mean Julian date of the 1-day annual
minimum flow
across all years
CV Julian date of
annual
minimum
7 D
CV in Julian date of the 1-day annual
minimum flow
across all years
Kennard et
al. (2010)
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HYDROLOGIC METRIC U T
DEFINITION
SOURCE
Predictability (P) of
minimum daily flow
7 D
Colwell’s (1974) predictability (P) of
minimum daily flow
Seasonality (M/P) of
minimum daily flow
7 D
Colwell’s (1974) seasonality (M/P) of
minimum daily flow
Variability of annual
number
of trough to trough
pulses
7 A
Variability (range/median) of number Puckridge
of annual trough to trough
et al.
occurrences
(1998)
Inverse of variability
between
months of number of
monthly troughs
7 M
Inverse of variability (median/range)
between months of the number of
troughs in each month
EXPECTED ECOLOGICAL RELEVANCE & CAVEATS
ECO-REGIONAL (& OTHER) DIFFERENCES
• Changes in seasonality and increased variability of low-flow
periods may reduce ecosystem function and lead to the loss of
spawning and other life-history stage triggers resulting in
decreased species abundance and diversity (Leigh & Sheldon
2008)
U, units of measurement: 1, ML d-1; 2, ML d-1 km-1; 4, d; 5, d y-1; 6, ML d-1 d-1; 7, dimensionless. T, temporal aspect of the metric: D, daily; M, monthly; S, seasonal; A, annual. Independence
criteria for low-spell frequency and duration = 7 d between spells. Colwell's (1974) predictability (P) of flow is composed of two independent, additive components: constancy (C – a measure of
temporal invariance) and contingency (M – a measure of periodicity), calculated using mean, minimum and maximum daily flows, respectively, in each month, and 11 flow classes (log2 class size)
with a central class of 20x mean daily flow.
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Appendix B: Scoping workshop participants
Name
Organisation
Key expertise
Tom McMahon
University of Melbourne
Hydrology
Nurella Ozbey
Thiess Services Victoria
Hydrography
Steve Clarke
Water Technologies
Hydraulic modelling
Ray Evans
Sinclair Knight Merz
Hydrogeologist
Bill Young
Murray-Darling Basin Authority
Modelling, hydrology etc
Malcolm Watson
Australian Bureau of Meteorology
Flow indicators
Jon Marshall
Queensland Department of Environment and
Resource Management
Ecology
Sonia Colville
DEWHA Lake Eyre Basin
Water policy/process
Rory Nathan
Sinclair Knight Merz
Hydrology
Paul Wettin
Consultant
Water management etc
(Daren Barma
Barma Water Resources
Modelling, hydrology)
(Lisa Lowe
Sinclair Knight Merz
Hydrology)
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Appendix C: Scoping workshop notes
Note – these points accompany the table of issues, gaps and solutions.
1.
2.
3.
Low-flow indicators

The indicators have little value unless the environmental objectives are clear.

The ecology is also affected by non-hydrological factors during low flows (e.g.
water quality).

The language used in the report around indicators, descriptors and metrics needs
to be tighter. The SRA will provide guidance on the appropriate terminology to
use.

The scoping paper suggests that only 15 years of data is required to calculate the
indicators. The emphasis in the scoping paper should be changed to make it
clear that this is a minimum requirement only as the length of record increases,
so does the robustness of the indicators.
Monitoring low flows

The scoping report makes the assumption that streamflow gauging is the primary
data source. There may be other ecologically relevant data, such as remotely
sensed data.

Stage data may be useful, even without the ability to convert to a flow using a
rating curve.
Estimating low flows in unregulated and ungauged catchments

4.
Estimating low flows in the regulated system

5.
6.
The definition of an unregulated catchment varies across Australia. The scoping
report needs to better define the difference between a regulated and unregulated
system.
A water supply model is not always appropriate for estimating natural flows.
These models tend to be calibrated to the current system operation and
geomorphology that won’t apply under natural conditions.
Quantifying anthropogenic influences

It is not clear to what extent anthropogenic influences need to be considered. For
example, do changes to the system that occurred 200 years ago need to be
considered?

The reference condition may not need to be the pre-European flow data as the
available ecological habitat does not necessarily represent pre-European
conditions.
Mechanisms generating low flows

An improved understanding of the mechanisms that generate low flows will be
useful if water managers are able to control/manage these mechanisms.
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7.
8.
9.
Hydraulic characteristics

The length of time that water remains in a pool is an important aspect of the lowflow regime.

Only in-channel low flows were considered by the workshop. It is recommended
that any consideration of flooding be removed from the project scope.
Other

Low flows can be an ecological benefit or ecological stress.

The issue of scale wasn’t discussed in the scoping paper. The scale at which the
ecology is being considered will drive the monitoring and modelling required. For
example, the monitoring and modelling required will vary between assessments
of the ecology at a particular water hole versus across the entire Murray-Darling
Basin.
Priority solutions

The priority solutions identified during the workshop and presented to the broader
workshop were:

The low-flow indicators need to be comparative across a region and over time.

A common language to define indicators/descriptors/metrics is required.

The uncertainty associated with indicators will vary with the method of
calculation, the type of indicator and the length of record used. It is recommended
that several case studies are undertaken to demonstrate the possible magnitude
of uncertainties associated with low-flow indicators.

Metadata should be provided with streamflow gauging data (e.g. stability of
control, presence of a fish passage etc.) to help users determine if the data is
suitable for their needs.

Users are unaware of the uncertainty in low-flow streamflow measurements. It is
recommended that tools be developed to allow users to better understand this
uncertainty.

Install simple depth probes in-stream and in waterholes to improve monitoring of
low flows.

Develop guidelines for rainfall-runoff modelling that cover the selection of a
model, choice of calibration period, objective function etc.

Improve understanding of the nature of river losses by undertaking a review of
previous studies and undertake additional field investigations.

Different approaches are used by modellers to characterise losses, even within
the same organisation. It is recommended that guidelines be developed to
improve the representation of losses in models.

The operational decisions made regarding expected losses in a river will
influence low flows. These decisions are not adequately included in water supply
system models.

Further investment should be used to identify when and where smart meters are
economically advantageous to install and use in both surface water and
groundwater systems.
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
The impact of land use change at a sub-annual time-step is not well understood
and further research is required to estimate low flows under a natural flow
scenario.

The behavioural decisions made by irrigators needs to be better understood and
represented in models of irrigation water use to produce more meaningful daily
demand patterns.

Worldwide there has been little investigation into the mechanisms that generate
low flows. A literature review of this topic is recommended.
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Appendix D: Table of issues, gaps and solutions
The table presented in this appendix was used to facilitate discussion during the workshop. The table lists all of the identified issues and gaps and was used
to identify possible solutions as well as any further gaps. The table was also used to document discussion related to the rationale behind the proposed
solution, the practicalities of the proposed solution, any dependencies and the regional applicability of the solution. The content of the table that was
generated before the workshop is in black text, and the content added during the workshop is in orange text.
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Topic
Low-flow
indicators
Issues and gaps
Possible solutions
Existing gaps in the
current monitoring
and modelling of low
flows to achieve
environmental
objectives
Possible solutions to
address issues and
fill gaps
Most low-flow
indicators can be
calculated using
existing software,
with the exception of
indicators related to
antecedent and post
low-flow event
conditions.
Incorporate these
additional indicators
into existing
software packages
used in the industry.
The indices do not
enable comparison
between regions.
Apply a rangestandardised
approach.
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
How relevant or
important is the
proposed issue or
gap in terms of
improved water
planning and
management?
(e.g.1: urgently
needs filling for
ungauged
catchments across
Australia; e.g.2:
important in SA, NT
and WA in the long
term)
a. How relevant is
the proposed
solution in terms of
improved water
planning
&management?
(e.g.1. relevant now
across Vic and
NSW; e.g.2: v
important in SE Aust
in long term, not
relevant to SW Aust)
b. Is a better
solution(s)
potentially
available?*
a. How well
does the
solution fit with
existing
jurisdictional
processes,
systems,
technologies
etc.?
b. What is the
spatial extent
and temporal
scale of
relevance to the
solution?
There is little need
for this solution as
most indicators can
already be
calculated in existing
software packages.
This is an issue that
is not well thought
about in the table of
low-flow indicators.
Relevant where we
want to make
comparisons across
a region.
The rangestandardised
approach allows
sites to be
compared against
the likelihood of risk
to the ecological
system.
There are difficulties
Investigate the use
Practicality
and
dependencies
a. How
technically or
conceptually
difficult is the
proposed
solution?
b. Are external
inputs required
to achieve a
successful
outcome?
c. To what
extent does
solution add
value to existing
investment?
Expected cost
and timeline
a. What is the
anticipated
cost?
b. What is the
anticipated time
to implement
(given costing
above)?
c. What is the
potential for coinvestment?
Overall priority
High/med/low
priority from the
perspective of
this group?
Easily applied
when required.
The individual
indicators will
have varying
importance in
different
regions.
Key
In some regions and
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Topic
Issues and gaps
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
in deriving daily
time-series of flow to
calculate the flow
indicators in datapoor areas.
of low-flow
indicators that can
be derived from
monthly data in
data-poor areas.
It is difficult to
prioritise the
adoption of the 28
low-flow indicators.
Investigate the
redundancy in the
28 low-flow
indicators.
The uncertainty in
the indicators is also
important and could
be used to select the
smaller subset of
indicators.
The estimation of a
natural time-series
of flow requires
assumptions about
the role of
anthropogenic
effects in cease-toflow events.
Develop guidelines
to help practitioners
estimate cease-toflow events in a
natural time-series
of flow.
It is important that
ecologists and water
planners and
managers can
identify cease-toflow events.
The uncertainty
associated with lowflow indicators is not
well understood.
Undertake several
case studies to
demonstrate the
possible magnitude
of uncertainties
associated with lowflow indicators. The
sensitivity of each
indicator to the
various sources of
uncertainty could
also be explored.
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
time scales the use
of monthly data is
appropriate.
This solution is more
appropriate when
the ecological
outcomes are better
defined and data is
available.
The relevance of
this solution will
depend on the ability
of ecologists and
decision makers to
use the information.
– An uncertainty
analysis can be
used to demonstrate
how the uncertainty
can most efficiently
be reduced.
– An uncertainty
analysis could be
used to compare the
accuracy of using
daily versus monthly
streamflows.
This solution
could lead onto
a study to
develop
guidelines (or a
tool) to
undertake
similar analysis
in other
systems. This
would have
greater regional
applicability.
Key
– The
uncertainty
associated with
the low-flow
indicators
originates from
several sources,
including the
NATIONAL WATER COMMISSION — Low flows report series
60
Topic
Issues and gaps
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
uncertainty in
deriving the
daily timeseries, the
length of record
used in
derivation. The
solution would
need to
consider a
range of
sources of
uncertainty.
Develop a standard
approach for
communicating
information about
uncertainty.
The communication
of uncertainty varies
and may cause
confusion in the
public. A consistent
approach needs to
be developed and
widely adopted.
The influence of
longer-term climate
regime variability (or
change) on the lowflow indicators is not
well understood.
NATIONAL WATER COMMISSION — Low flows report series
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Topic
Issues and gaps
Possible solutions
Reference natural
(and current) flows
are poorly archived
and are usually not
readily available
from state agencies
for ongoing use.
(Note this does not
refer to gauged
streamflows.)
Either the Bureau of
Meteorology, state
agencies or local
catchment
management
agencies establish
and maintain timeseries of reference
natural (and current)
streamflows at key
environmental flow
sites for use in eco-hydrologic studies.
This should include
indications of what
anthropogenic
influences have
been considered in
the derivation of
natural flows.
The language in the
scoping study used
to refer to indicators/
descriptors/ metrics
is loose.
The scoping study
should be revised to
provide consistency
in the language
used.
The length of data
required to calculate
low-flow indicators
associated with less
frequent events is
not known.
Investigate the
length of data
required to calculate
individual low-flow
indicators.
The likelihood of
low-flow events
Use stochastic data
to predict the
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
The data may be
available within a
given organisation,
but not publically
available.
The metadata
associated with the
time-series of flows
should also be made
available so users
are aware of the
limitations or
assumptions
required to generate
the time-series.
–The assumptions
made to generate a
time-series of the
reference condition
will vary between
sites (e.g. does the
reference condition
take into account
changes in land
use?). The
assumptions made
in generating these
time-series are not
always clear.
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
The bureau isn’t
currently
planning to
collect this
information.
Key
This is a major
research
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62
Topic
Monitoring
Issues and gaps
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
activity.
under future
scenarios is not well
understood.
likelihood of future
low-flow events.
Limited number of
gaugings available
during low-flow
periods.
Provide a funding
scheme to collect
more gaugings
during low-flow
events at important
sites.
Changes in the river
cross-section will
have a larger impact
at the low-flow
range. Regular
gauging is required
to pick up the small
changes in the
cross-section that
will influence the
measurement of
flows over this
range.
Regular review and
reporting of
uncertainty
associated with low
flows at a variety of
sites.
Information on the
uncertainty of
gauges is not widely
available.
The measurement
uncertainty
associated with
water levels will vary
between different
instrumentation.
Users are unaware
of the uncertainty in
low-flow streamflow
measurements.
Key
Development of a
tool to allow users to
rapidly assess the
uncertainty with the
low flows.
Provision of access
to gauging history
and quality codes for
all online hydrologic
data.
Difficulty measuring
Discuss with
NATIONAL WATER COMMISSION — Low flows report series
63
Topic
Issues and gaps
very low flows using
a current meter.
Measurement of low
flows at unstable
cross-sections.
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
NRETAS
hydrographers the
potential for
research or
alternative
technologies to
better monitor low
flows in carbonate
aquifer catchments.
None, apart from
ensuring that sites
are adequately
selected for low
flows.
The selection of a
suitable crosssection is very
important for
measuring low
flows.
The use of
calibrated flow
structures can be
used to improve the
measurement of low
flows at unstable
cross-sections.
The benefits of
emerging
streamflow
measurement
technologies in
measuring low flows
are not widely
understood.
The streamflows at
many important
ecological locations
are not gauged.
Identify when and
where new
techniques are
economically
advantageous over
the more traditional
approaches in
monitoring low
flows.
Assemble an
inventory of
important ecological
locations that are
not currently gauged
and assess the
Improved
measurement
technologies could
be used to improve
rating curves at low
flows.
The acoustic
doppler provides
better
measurements at
high flows. Currently
these technologies
do not provide better
measurements at
low flows than
conventional
methods.
Little to follow
up here.
The location of
current gauging
stations may not be
at sites that
represent the larger
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Topic
Issues and gaps
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
practicality of
monitoring at these
sites.
system. The
selection of sites is
based on where it is
possible to
undertake gaugings.
Identify river
reaches that are
represented by each
gauge.
The spatial
relevance of a
gauge may vary
between ecological
values.
Real-time flow
information is not
widely available.
Provide real-time
flow information on a
widely accessible
website.
Ecologists need to
be able to identify
cease-to-flow
events.
Set up a web-cam at
gauging sites (or
other important
sites) to monitor if
there is flow.
This type of
investigation
has already
been
undertaken for
the MDB, but is
not available
nationally.
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
Key (partly
linked to the
above point)
Key
At many locations
there is a control
structure that makes
it easy to identify
when there is a
cease-to-flow event.
This is only difficult
in natural crosssections.
Identify gauges
which can
‘accurately’
determine if there is
a cease-to-flow
event.
Recession curves
can be used to
identify cease-toflow events.
Current monitoring
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Topic
Issues and gaps
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
techniques do not
pick up subsurface
flow.
There is flow
through fish
passages that is not
recorded during
gauging.
Estimating
flows in
unregulat
ed
catchment
s
The water levels in
off-stream
waterbodies are
important, but not
commonly
measured.
Invest money in
establishing water
level measurement
in off-stream
waterbodies.
The catchment
characteristics that
control low-flow
behaviour are
difficult to identify
and characterise.
Review existing
literature that
describes the
catchment
characteristics that
influence low flows
and identify and
collate spatial
datasets available
that relate to these
catchment
characteristics.
A method to rapidly
determine the
hydrological
similarity of
catchments with
respect to low flows
is not available.
Undertake a study to
develop a tool to
rapidly determine
the similarity of
catchments with
regard to low flows.
Transposition
methods tend to be
based on
transposition factors
related to the
average flow.
Develop a
transposition
method suited to low
flows.
Key
The way flow data is
interpolated
between gauging
stations is generally
based on yield
considerations and
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Topic
Issues and gaps
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
does not take into
account losses
along the river
reach. The losses
may not always be
evenly distributed
along a river reach.
The relative ability of
commonly available
rainfall-runoff
models to represent
low flows is not
widely understood.
Review the ability of
commonly available
rainfall-runoff
models to represent
low flows and
develop an
information sheet.
– It may be difficult
to model low flows
using a rainfallrunoff model
because low flows
occur when there
has been little
rainfall. Low flows
are determined by
the ‘buckets’ used to
model groundwater
stores.
– Better guidance is
needed to help
modellers select an
appropriate model
for different
purposes.
– Linked surface
water/groundwater
models have been
developed. A more
suitable approach
may be possible.
– Review the
algorithms used to
look at groundwater
discharges.
This review
could draw on
the work
undertaken by
Boughton and
the
development of
the IHACRES
model.
Key – also
consider the
calibration time
period required,
appropriate
calibration
procedure and
objective
functions. This
solution could
also link to the
uncertainty
issue/solution.
– Models need to
represent the
persistence of flow
in a river.
The shift in climate
in south-eastern and
south-western
Australia over the
past 10 to 30 years
has created some
uncertainties in the
accuracy of
previously calibrated
rainfall-runoff
A review of the
calibration period of
rainfall-runoff
models across
southern Australia
and a recalibration
of those models to
more recent data
should be
undertaken where
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Topic
Issues and gaps
Possible solutions
models.
this has not already
occurred.
There has been no
study to determine
which objective
functions should be
used to calibrate to
low flows.
Undertake a study.
The selection of
catchment model
parameters for
ungauged
catchments
introduces
uncertainty.
Provide funding for
ongoing research in
this area.
A substantial
amount of effort is
required to
adequately estimate
a time-series of daily
streamflows at an
ungauged site.
Develop models to
estimate low-flow
indicators from
catchment
characteristics.
Atlas of perennial
streams and lowflow refuges for instream biota.
Map perennial
streams and
permanent pools
during recent past
extreme droughts.
Rainfall-runoff
models are not
useful for modelling
processes at a small
scale (e.g.
waterhole).
Develop
deterministic models
to represent smallerscale systems.
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
Practicality
and
dependencies
There are some
objective functions
that are commonly
used to calibrate to
low flows, but these
have not been
formally tested.
Expected cost
and timeline
Overall priority
Key
A similar atlas has
been prepared in the
United States over a
long period of time.
The maps show a
decrease in the
number of perennial
streams.
Qld has done
some work
modelling the
persistence of
waterholes.
These models
are used when
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Topic
Issues and gaps
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
IQQM shows no
flow.
The channel is not
always well defined
and it can be difficult
to determine the
low-flow paths.
Use remote sensing
to identify flow
paths.
The key issue is the
location of
waterholes and their
longevity.
Melbourne
University has
done some
work in this
area.
(Note: this is also an
issue for monitoring
low flows.)
Estimating
flows in
regulated
catchment
s
Not all models are
represented on a
daily time-step.
Provide funding to
help agencies
convert models to a
daily time-step.
There are large
uncertainties
associated with
estimates of river
losses.
Improve
understanding of the
nature of river
losses by
undertaking a review
of previous studies.
Several of these
reviews have
already been done.
A short review (a
couple of days) is
recommended that
focuses on
developing
experiments to
obtain more data.
Key – link to the
next action.
Undertake additional
field investigations
and analysis to ‘fill in
the gaps’ found
during the review.
A better way to
address this issue is
to undertake a water
balance for reaches
that takes into
account other
inflows and outflows.
Increase the number
of sites where
gaugings are taken
to improve the
quantification of river
losses.
River losses may be
Review and assess
In existing models
Develop guidelines
Key
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Topic
Issues and gaps
represented poorly
within a model.
Possible solutions
the adequacy of
methods to
represent river
losses within
models.
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
the ‘loss’ will
incorporate the
errors in the model.
The loss functions in
models do not
always represent
real processes.
for modelling losses
in these models.
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
– The representation
of losses in models
varies between
organisations and
individual modellers.
System operators
make an
assessment of
forecasted system
losses when they
release water. The
operational
decisions made
should be
represented in the
models. Also, any
improved estimates
of river losses
should be fed back
to system operators.
Key – but
include as a
subset of
above.
Establish and
publish plausible
ranges of river
losses for different
river systems that
can be used to verify
model results.
Model may not
represent the daily
operation of a water
supply system.
Provide funding to
help agencies
improve or update
the representation of
operational practices
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Topic
Issues and gaps
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
within the models.
Models do not
include dynamic
representation of
water trading.
Improve the
understanding of
likely water market
behaviour during
low-flow periods and
incorporate this
knowledge into
water resource
models.
Models do not
represent cease-toflow events well. For
example in Qld
IQQM models when
the modelled flow is
less than 2 ML/day,
it is assumed to be a
cease-to-flow event.
Models may not be
calibrated to
represent low flows
and the limitations
may not be
communicated to all
relevant
stakeholders.
Review of the ability
of existing models to
represent low flows
at ecologically
important locations.
The degree of
regulation and effect
on low flows can
vary considerably
across a region.
Estimating
anthropog
enic
influences
Difficulty in
estimating
anthropogenic
influences at a daily
time-step.
Undertake detailed
studies for a range
of case study sites
to examine the
impact of
anthropogenic
influences on daily
It would be useful to
understand the
stochastic properties
of anthropogenic
activities.
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Topic
Issues and gaps
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
low-flow indicators.
Develop model to
estimate these
changes in other
catchments.
A business case for
the use of smart
meters on private
diversions has not
been prepared.
Further investment
could be used to
identify when and
where smart meters
are economically
advantageous to
install and use.
Readily available
information on lowflow discharge
locations from
sources such as
wastewater
treatment plants,
return flows from
irrigation and coal
seam gas.
Map low-flow
discharge locations
across Australia.
The seasonal impact
of land use change
on streamflows is
not very well
understood.
Key – but
expand to be
more holistic.
An understanding of
the magnitude of
historical return
flows is important as
they are required to
estimate historical
anthropogenic
influences.
It may be
appropriate to adopt
a reference
condition that
includes the current
land use.
– Land use is
changing in irrigation
systems as a
response to low
water availability
(e.g. Shepparton
region).
Alice Best’s
PhD in this area
may have data
that could be
useful for
looking at the
seasonal
influences of
land use
change.
Lower than
other solutions.
– Low flows may be
more sensitive to
changes in land use
than other parts of
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Topic
Issues and gaps
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
the flow regime.
Need to understand
where it is important
to understand
anthropogenic
changes.
Estimates of
irrigation water use
on a daily time-step
are poor. Many of
the decisions are
based on poor
interpretation and
representation of the
behaviour of
irrigators in the river
system models.
This issue
influences both
groundwater
and surface
water
extractions.
Key
The accuracy of
diversions in
systems will improve
after modernisation
activities.
There are a range of
anthropogenic
influences that will
affect low flows.
These include
floodplain structures
and small weirs
located on a
waterway. Even a
mining road can
alter low-flow
characteristics.
The volume of
pumping from
waterholes is not
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Topic
Issues and gaps
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
well known.
There are a range of
issues around
monitoring and
modelling of
groundwater
extractions.
Mechanis
ms
generatin
g low
flows
Hydraulic
characteri
stics
There are issues in
understanding the
number and volume
of domestic and
stock extractions.
Few studies have
monitored
groundwater and
surface water
interactions in losing
streams.
Undertake a
monitoring program
in some losing
streams.
The location of
gaining and loosing
river reaches is not
mapped outside of
the Murray-Darling
Basin.
Extend the study to
regions outside the
MDB that have
sufficient data.
Worldwide there has
been little
investigation into the
mechanisms that
generate low flows.
Undertake a
literature review of
what is known and
what the gaps are
and identify the next
steps of a study.
An improved
understanding of the
mechanisms may
guide improvement
of modelling of low
flows.
Considerable time
and expense is
required to
understand the
hydraulic
Promote the
availability and use
of LiDAR
information.
LiDAR information
can be used for
characterisation of
wetlands and
channels.
This issue is
driven by the
spatial scale.
The results are
more useful at a
smaller spatial
scale, e.g. more
relevant for
Lindsay
Walpole Island,
but less relevant
at the MDB
scale.
The results are
sensitive to the
time at which
the
measurements
are taken.
Key
– Sophisticated
models are not
needed to better
use LiDAR data.
– The timing of
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Topic
Issues and gaps
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
characteristics of a
stream.
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
data capture is
important. The
information is
best when it is
captured during
periods of low
(or no) flows. It
may be difficult
to obtain good
data at weir
pools or areas
that are always
inundated.
Investigate the
relationship between
critically important
water depths and
low-flow indicators.
At present little
information is
available to help
water managers
understand the
longevity of pools
during a cease-toflow event.
Mapping of major
pools along rivers.
LiDAR data can be
used to identify
where there is still
water in the system
(remnant
waterholes) after a
period of low flows.
Remote sensing
data may be better
to do this.
Investigation of the
connection of these
pools to the
groundwater
system.
Collection of
anecdotal evidence
about the
persistence of pools
during recent ceaseto-flow events.
NATIONAL WATER COMMISSION — Low flows report series
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Topic
Issues and gaps
Possible solutions
Relevance of
Relevance of
Regional
issue/gap
solution
applicability
Practicality
and
dependencies
Expected cost
and timeline
Overall priority
Put in some low cost
water level meters.
Remote sensing
data.
Where a gauging
station is located in
a weir pool it will
continue to measure
water levels after a
cease-to-flow event.
This information
could be used to
better understand
the persistence of
waterholes in a
region.
Develop models to
predict the
persistence of pools.
Use these models to
extrapolate data
from measured
systems to other
systems.
Location of weirs
and flow-control
systems.
Use of LiDAR data
to identify these
structures.
Can identify
these structures
from LiDAR
data if you are
looking
specifically for
these, but can
be hard to
identify.
* If a better solution(s) is proposed please add/insert a new line to the table and assess solution with criteria
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References
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crop water requirements, no. 56, Food and Agriculture Organization of the United Nations.
Australian Bureau of Meteorology 2010, Improving water information.
Australian National Committee on Irrigation and Drainage 2002, Know the flow: flow metering training
manual,
Bardossy, A 2007, ‘Calibration of hydrological model parameters for ungauged catchments’,
Hydrology and Earth System Sciences, 11(2): 703–710.
Boughton W 2004, ‘The Australian water balance model’, Environmental Modelling & Software,
19(10): 943–956.
—1984, ‘A simple model for estimating the water yield of ungauged catchments’, Engineering
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HS 2003, ‘Generalisation for rainfall-runoff model parameters for modelling applications’, 28th
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Wollongong, NSW, pp. 2.203–2.209.
Cook, FJ, Jordan, P, Waters, DK & Rahman, JM, 2009. WaterCAST – Whole of Catchment Hydrology
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Costelloe, JF, Grayson, RB and McMahon, TA, 2005, ‘Modelling stream flow for use in ecological
studies in a large, arid zone river, central Australia’, Hydrological Processes, 19(6).
CSIRO 2007, Warrego regional report, Murray-Darling Basin Sustainable Yields Project.
Department of Sustainability and Environment 2009, Download REALM manuals.
Dingman, SL 1994, Physical hydrology, Prentice Hall, Upper Saddle River, N.J., xiv, 575 pp.
Erlanger, PD, Poulton, D & Weinmann, PE 1992, ‘Development and application of an irrigation
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Gan, KC, McMahon, TA & O'Neill, IC 1991, ‘Transposition of monthly streamflow data to ungauged
catchments’, Nordic Hydrology, 22: 109–122.
Gordon, N, McMahon, T, Finlayson, B, Gippel, C & Nathan, R 2004, Stream hydrology: an
introduction for ecologists, John Wiley and Sons.
Herschy, RW 1985, Streamflow measurement, E & FN Spoon, Cambridge, Great Britain.
Jayasuriya, N, McMahon, TA & O'Neill, IC 1991, ‘Development of a simplified two-parameter rainfallrunoff model with potential for ungauged catchment application’, International Hydrology and
Water Resources Symposium, Perth, Australia, pp. 498–503.
Jayasuriya, N, McMahon, TA, O'Neill, IC & Nathan, RJ 1994, ‘A methodology for estimating
streamflow yield from small rural ungauged catchments’, Water Down Under '94, Adelaide,
Australia, pp. 33–38.
Kennard, M, Mackay, SJ, Pusey, B, Olden, JD & Marsh, N 2009, ‘Quantifying uncertainty in estimation
of hydrologic metrics – implications of discharge record length and record period’,
Ecohydrological regionalisation of Australia: a tool for management and science, Land and
Water Australia.
Ladson, A 2008, Hydrology: an Australian introduction, Oxford University Press, Melbourne.
Lowe, L 2009, Addressing uncertainties associated with water accounting, University of Melbourne,
Melbourne, 502 pp.
NATIONAL WATER COMMISSION — Low flows report series
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Reports in the low flows series
Balcombe SR & Sternberg D 2012, Fish response to low flows in dryland rivers of western
Queensland, National Water Commission, Canberra.
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Barma Water Resources & Sinclair Knight Merz 2012, Low-flow hydrological monitoring and modelling
gaps, report by for the National Water Commission, Canberra.
Barmah D & Varley I 2012a, Hydrologic modelling practices for estimating low flows – stocktake,
review and case studies, National Water Commission, Canberra
Barmah D & Varley I 2012b, Hydrologic modelling practices for estimating low flows – guidelines,
National Water Commission, Canberra
Bond N 2012, Fish responses to low flows in lowland streams: a summary of findings from the Granite
Creeks system, Victoria, National Water Commission, Canberra.
Bond N, Thomson J & Reich P 2012, Macroinvertebrate responses to antecedent flow, long-term flow
regime characteristics and landscape context in Victorian rivers, National Water Commission,
Canberra.
Chessman B, Haeusler T & Brooks A 2012, Macroinvertebrate responses to low-flow conditions in
New South Wales rivers, National Water Commission, Canberra.
Deane D 2012, Macroinvertebrate and fish responses to low flows in South Australian rivers, National
Water Commission, Canberra.
Dostine PL & Humphrey CL 2012, Macroinvertebrate responses to reduced baseflow in a stream in
the monsoonal tropics of northern Australia, National Water Commission, Canberra.
Hardie, SA, Bobbi, CJ & Barmuta, LA 2012, Macroinvertebrate and water quality responses to low
flows in Tasmanian rivers, National Water Commission, Canberra.
Kitsios A, Galvin L, Leigh C & Storer T 2012, Fish and invertebrate responses to dry season and
antecedent flow in south-west Western Australian streams, National Water Commission,
Canberra.
Leigh, C 2012, Macroinvertebrate responses to dry season and antecedent flow in highly seasonal
streams and rivers of the wet-dry tropics, Northern Territory, National Water Commission,
Canberra.
Mackay S, Marsh N, Sheldon F & Kennard M 2012, Low-flow hydrological classification of Australia,
National Water Commission, Canberra.
Marsh N, Sheldon F & Rolls R 2012, Synthesis of case studies quantifying ecological responses to
low flows, National Water Commission, Canberra
Rolls R, Marsh N & Sheldon F 2012, Review of literature quantifying ecological responses to low
flows, National Water Commission, Canberra.
Rolls R, Sheldon F & Marsh N 2012, Macroinvertebrate responses to prolonged low flow in subtropical Australia, National Water Commission, Canberra.
Sheldon F, Marsh N & Rolls R 2012, Early warning, compliance and diagnostic monitoring of
ecological responses to low flows, National Water Commission, Canberra.
Smythe-McGuiness Y. Lobegeiger J, Marshall J, Prasad R, Steward A, Negus P, McGregor G & Choy
S 2012, Macroinvertebrate responses to altered low-flow hydrology in Queensland rivers,
National Water Commission, Canberra.
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