Hydrological indicators of water stress
Dr Nick Marsh
Yorb Pty Ltd
July 2010
This report was prepared for the Australian Bureau of
Meteorology to:
Report on the review of level three indicators for the
National Water Commission’s ‘National Inventory of
Water Stressed Catchments and Aquifers project’
This report was compiled with input from several sources; particular acknowledgment is given to Dr
Mark Kennard, Dr Rory Nathan, Dr Nick Bond and Dr Lisa Lowe for their considered input.
Citation: Marsh, N, 2010, Hydrological indicators of water stress, report prepared for the Bureau of
Meteorology for the National Water Commission, Canberra
Your Orb
Your Choice
www.yorb.com.au
National Water Commission Cover Note
This report is one of several reports prepared for the ‘Assessing Water Stress in Australian
Catchments and Aquifers’ project (formerly titled the National Inventory of Water Stressed
Catchments and Aquifers) which provides an assessment of the extent to which surface and
groundwater systems have been hydrologically altered because of water extraction,
regulation or flow alteration. Reports include:
Overarching report
NWC, 2012, Assessing water stress in Australian catchments and aquifers, National Water
Commission, Canberra.
Supporting reports
Marsh, N 2010, Hydrological indicators of water stress, report prepared for the Bureau of
Meteorology for the National Water Commission.
O’Keefe, V and Hamstead, M 2010, Understanding jurisdictional and Murray Darling Basin
Authority approaches to identifying water stress, report prepared for the National
Water Commission.
Robinson, W 2010, Investigating ecological indicators of stress from water scarcity,
discussion paper prepared for the National Water Commission.
Sinclair Knight Merz, 2012, Assessing water stress in Australian catchments and aquifers,
technical report prepared for the National Water Commission.
Note - supporting reports do not necessarily reflect the views or opinions of the Commission.
1 Executive Summary
One of the requirements of the National Inventory of Water Stressed Catchments and Aquifers
project is to analyse flow regimes to highlight areas of potential ecological water stress. This report
describes the approach, sample analysis and recommendations for flow regime analysis.
The approach recommended is to use a multi-metric approach based on the (SKM, 2005) Flow
Stressed Ranking (FSR) approach for flow analysis. The FSR approach was specifically designed for
comparative flow analysis as is required in this project and has already been applied in some form in
most of Australia’s water management jurisdictions. Therefore there is already a broad
understanding of the benefits and limitations of the approach.
Having selected a multi-metric approach, this report is focused on testing the underlying flow
metrics for their suitability for application across the whole of Australia and to test additional
metrics.
The approach for this project task was to;
1) consult with individuals who had expertise in applying hydrological metrics for analysing
flow regimes, with the specific purpose to
a. check on the suitability of applying the metrics across a broad spatial scale
(Tasmania to Northern Australia).
b. identify other more suitable metrics.
c. learn from their experience on the limitations of the approach.
2) Calculate flow metrics for representative sites for subsequent consideration.
3) Use the results from the metrics calculated at representative sites as a basis for discussion
and recommendation on the selection reporting of metrics for this project.
1.1 Metrics considered
The Flow Stressed Ranking (SKM 2005) and Sustainable Rivers Audit (Davies et. Al. 2008) metrics
considered here were:
1. High Flow
2. High Flow Ranking (slight variation on High flow to account for computation nuances of
Spreadsheet packages)
3. Low flow
4. Zero Flow
5. Monthly Variation
4
6. Seasonal Period
7. Mean Annual Discharge
8. Median Annual Discharge
Four additional metrics were developed in the course of this project, they are described in the body
of the report, the additional metrics were applied to sample data sets and the recommendations
following the expert discussions were to modify and retain the Seasonal Dry Period (SDP) metric and
use it to replace the existing SRA Seasonal Period index.
Table 1: additional metrics considered.
Metric
Description
High Flood Flow
Changes in the frequency of 1 in 4 flood
(HFF)
High Flood Period
Changes in the longest inter-flood dry
Between (HFPB)
period
Low Flow Duration
(LFD)
Seasonal Dry Period
(SDP)
Changes in the duration of low flow
conditions
Changes in the proportion of the total
flow which occurs in the
predevelopment driest six
Recommendation
Rejected – highly correlated with
existing high flow index
Partially accepted–apply the
metric to all sites, and make an
assessment on its relative value
before publishing.
Rejected – highly correlated with
existing low flow index
Modify to range standardise the
results and use to replace the
existing Seasonal period metric.
(the metric presented is the
refined range standardised
version)
1.2 Recommended metrics
The recommended metrics are all range standardised at the given site, which implies that the scores
can be used for comparison between sites.
1) High Flow
2) High Flow Period Between (new) may be excluded after consideration of a larger data set
3) Low flow
4) Zero flow
5) Monthly variation
6) Seasonal Dry Period (new)
The inclusion of ratio scores of mean annual discharge and median annual discharge as reported in
the Sustainable Rivers Audit (2008) are not recommended as multi-metric indices because these
metrics are highly correlated with the high flow metric, and the ratio and non-range standardised
nature of the metrics does not allow a similar comparison between sites. However, the mean annual
and median annual discharge ratio metrics could be presented as an additional information layer as
these metrics have ecological significance.
5
1.3 Integration, aggregation and reporting
1.3.1 At a site integration
Several alternative at-a-site integration techniques were considered. A common issue across all
integration methods was difficulty in interpreting the resulting score. The recommendation is to not
integration the flow metrics into a single site based score, but to limit the number of flow metrics (to
about five) and present all flow metric scores for a site. Where a single summary is required, for the
purpose of this project where the intention is to firstly identify any areas of potential water stress, it
is recommended that the single lowest score be presented.
1.3.2 For a region aggregation
In order to produce the final NWC reporting product it is recommended that a group with expertise
in the area of multi-metric aggregation techniques be presented with a range of alternative
reporting representations and they help to finalise the reporting approach. The primary concern
here is that a spatial aggregation technique may both over or under-represent the degree of
hydrological alteration. Recommended alternative spatial considerations are to:
1) Represent a region by the single lowest score of any individual metric across the whole
region.
2) Weight the combined minimum scores for sites across a region by the stream length that
each represents.
3) Create a spatial layer for each of the five metric scores and apply both the lowest score for
the whole region and create a weighted score by stream length.
1.4 Extending the reporting to areas without comparative
data sets
The Flow Stressed Ranking approach is designed for comparing two concurrent flow scenarios. In
Locations where these are not available the Flow Stressed Ranking approach cannot be used. More
generally, the concept of reporting potential ecological water stress due to flow regulation cannot
be conducted in the absence of a ‘pre-development’ case with which to compare.
For the purpose of filling in the gaps for this reporting cycle, one alternative could be to correlate
spatial metrics (e.g. percentage of available surface water allocated for use) with the five
recommended flow metrics, where they are spatially concurrent. Then use the spatial metrics to
predict what the flow metrics may be in these unmodelled regions. This of course assumes a similar
method of water resource management (e.g. flood harvesting versus storage and release), and the
comparative assessments should be applied with this in mind.
6
Contents
1
2
3
4
5
6
7
Executive Summary .............................................................................................................. 4
1.1
Metrics considered ................................................................................................................. 4
1.2
Recommended metrics ........................................................................................................... 5
1.3
Integration, aggregation and reporting .................................................................................. 6
1.4
Extending the reporting to areas without comparative data sets .......................................... 6
Background .......................................................................................................................... 9
2.1
National Water Commission Inventory................................................................................... 9
2.2
Hydrological indicators mapping project ................................................................................ 9
Considerations for hydrological alteration metrics ............................................................... 10
Hydrologic Metrics.............................................................................................................. 12
4.1
High-Flow Metric (HF) ........................................................................................................... 13
4.2
Proportion of Zero Flow Metric (PZ) ..................................................................................... 14
4.3
Low-Flow Metric (LF) ............................................................................................................ 14
4.4
Monthly Variation Metric (CV) .............................................................................................. 15
4.5
Seasonal Period Metric (SP) .................................................................................................. 16
4.6
Mean Annual Discharge Metric (MNAQ) .............................................................................. 16
4.7
Median Annual Discharge Metric (MDAQ) ........................................................................... 17
Additional Metrics .............................................................................................................. 18
5.1
The high flow metric is not high enough .............................................................................. 18
5.2
Time between wetland or floodplain inundation is critical .................................................. 19
5.3
The duration of low flow events is critical for instream biota .............................................. 19
5.4
Seasonality of flow is a strong predictor of fish in the Tropics ............................................. 20
Integration and Aggregation techniques .............................................................................. 21
6.1
SRA Approach........................................................................................................................ 21
6.2
FSR at a site Integration ........................................................................................................ 23
6.3
Recommended at a site integration ..................................................................................... 24
Example applications .......................................................................................................... 25
7.1
Condamine downstream from St George(Murray Darling) .................................................. 26
7.2
Lower Murrumbidgee NSW (Maude Weir - Lowbidgee area) (Murray Darling) ................. 27
7.3
Lower Goulburn River (VIC) (Murray Darling) ....................................................................... 28
7.4
Gwydir River @ yarraman (NSW) (Murray Darling) .............................................................. 29
7.5
Murray River @ SA border – Chowilla area (NSW) (Murray Darling) ................................... 30
7.6
Warrego River @ charleville (Qld) (Murray Darling)............................................................. 31
7.7
Daly river at Beeboom (Northern Australia) ......................................................................... 32
7.8
Daly at Dorisvale (Northern Australia) .................................................................................. 33
7.9
Katherine River @Galloping Jacks (Northern Australia) ....................................................... 34
7.10 Katherine River @ Knotts Crossing (Northern Australia) ...................................................... 35
7.11 Tasmania _ sub catchment (TBD) 533.................................................................................. 36
7.12 Tasmania _ sub catchment (TBD) 547.................................................................................. 37
7.13 Tasmania _ sub catchment (TBD) 530.................................................................................. 38
7.14 Tasmania _ sub catchment (TBD) 73.................................................................................... 39
7.15 Tasmania _ sub catchment (TBD) 80.................................................................................... 40
7.16 Tasmania _ sub catchment (TBD) 82.................................................................................... 41
7.17 Tasmania _ sub catchment (TBD) 83.................................................................................... 42
7
7.18 Tasmania _ sub catchment (TBD) 84..................................................................................... 43
8 Results and discussion ........................................................................................................ 44
8.1
High flow ............................................................................................................................... 44
8.2
Low Flow ............................................................................................................................... 44
8.3
Coefficient of Variation ......................................................................................................... 45
8.4
Seasonality ............................................................................................................................ 45
8.5
Mean and Median ................................................................................................................. 45
9 Summary plots for comparison ........................................................................................... 47
10 References ......................................................................................................................... 57
8
2 Background
2.1 National Water Commission Inventory
One of the key aims of improved water planning and management under the National Water
Initiative (NWI) is to avoid over allocation and overuse of surface and groundwater systems, and to
return already over allocated and/or overused systems to sustainable levels of extraction.
The National Water Commission’s (NWC) 2009 and 2007 Biennial Assessments on progress of water
reform have, however, identified shortcomings in how water plans implement the concept of
environmental sustainability and in the recovery of water from over allocated and overused systems.
Consequently, the NWC has identified addressing over allocation and overuse in water systems as a
high priority.
A major difficulty in addressing over allocation and overuse issues is the absence of a nationally
agreed method for determining the sustainable levels of extraction within a water system. As a
consequence the extent of over allocation is unknown at a national level. However in the absence of
an agreed procedure, the Commission believes it is possible to provide defensible evidence of the
extent to which water scarcity is causing significant water stress to water systems. This scarcity can
arise from climatic changes and other causes as well as from water extraction and use.
The National Inventory of Water Stressed Catchments and Aquifers project proposes to develop an
Australia wide picture of water stress using a systematic and transparent approach that distinguishes
where possible between different causes of water stress, and is informed as much as possible by
existing processes and indicators.
The Inventory is being developed through the following stages:
o
Understanding existing approaches to identifying water stressed catchments and aquifers,
e.g. those used by jurisdictions and the MDBA
o
Producing a series of maps, and an associated report, of the hydrological pressures present in
each catchment/aquifer (undertaken by the Bureau of Meteorology)
o
Clarifying the feasibility of using ecological indicators that are sensitive to water-scarcity to
help determine levels of water stress via a discussion paper and workshop. If feasible, an
ecological indicators project will be implemented
o
Commissioning discussion papers related to other dimensions of water stress and, if feasible
and supported by the Steering Committee, developing indicators
o
Integrating and packaging the above to produce a national inventory of water stressed
2.2 Hydrological indicators mapping project
The second stage in the above the NWC Inventory list is the work being undertaken by the Bureau of
Meteorology and is the focus of this project. The Bureau is contributing to this Inventory Project of
the NWC by mapping readily available indicators of hydrological pressure and alteration in
catchments and aquifers across Australia. This is to serve as evidence of the extent to which
anthropogenic-induced water scarcity is potentially compromising ecological health.
9
3 Considerations for hydrological alteration metrics
Within the National Inventory of Water Stressed Catchments and Aquifers project whole of Australia
spatial layers are being used to compare a range of measures of potential water stress such as
surface water availability, extractive licences by region, and groundwater availability versus use.
These comparisons are very informative for showing spatial patterns in gross changes to volume, but
they do not well describe the components of the flow regime which are affected by water
management which may in turn have ecological consequences. For example it is difficult to interpret
the ecological consequences of a 10% reduction in the mean annual discharge without first
quantifying the relative changes to the ecologically important components of the flow regime.
This report summarises the results of reviewing the methods of analysing flow regimes to quantify
flow alteration. There are several approaches to quantifying the ecological components of the flow
regime potentially suitable for this project (summarised in Table 1), and for this project we wish to
either use one of these methods directly or with refinement. The purpose of this report is to inform
the selection of the appropriate method. The specific constraints of this project which will impact on
the appropriate methods are:
1) Be amenable to Sustainable Yields data sets
The sustainable yields projects (Murray Darling, Tasmania, south west Western Australia,
Northern Australia) have long duration scenarios which compare current allocation of water
resources across alternative climate regimes. An additional ‘without’ water resource
development scenario is available for the Murray Darling and Tasmania studies. These two
scenarios allow the relative comparison of the long term (regime) implications of the current
water management practices to be assessed. Similar modelled data sets are held by the state
jurisdictions in eastern Australia and could also be included if the modelled scenarios are made
available.
2) Be nationally applicable.
The approach should be suitable for coverage of the entire country, but at least the CSIRO
Sustainable Yield regions. The key issue in considering national applicability of the approach is to
ensure that flow metrics are appropriate for application across different climatic regions and
regions with different water management approaches.
3) Work with monthly time series data
While some regions have daily data available, the northern Australia sustainable yields data is
only available on a monthly timestep (check), hence the method must be applicable to monthly
data
4) Be sensitive to ecological water stress
The purpose of the hydrological analysis is to indicate systems which may have water stressed
ecosystems, hence the metrics should have an ecological basis for use and be sensitive to common
extractive practices. For example a 20year ARI flood has considerable geomorphic and related
10
ecological function, however it is unlikely to be greatly affected by regulation, so inclusion of this
type of metric would dilute the result if metrics are integrated.
The list in table 1 is not of five independent flow analysis approaches, but rather variations of multimetric flow alteration quantifications. The general order of development was that the approach
commenced with the development of hydrologic sub-score in the Victorian Index of Stream
Condition, followed by subsequent review and refinement for different applications. This pedigree
of adoption and improvement of the same general approach of considering several key elements of
the hydrograph provides a strong position for the NWC to also apply a similar approach.
11
Table 1: Alternative approaches for quantifying the ecological components of the flow regime
Hydrologic index system
and component
indicators
Site application
to-date
Multijurisdictional
application
Data used for
hydrologic analysis
Key Reference
SRA Hydrology Index
(SRA-HI) and its 5
component indicators
(Norris et al, 2008)
Evaluated for 469
sites across MD
Basin
Involvement
by Vic, NSW,
ACT, QLD and
MDBC
Monthly data
Davies et al 2008
Tasmanian River
Condition Index:
Hydrology component of
consisting of 12
indicators
Trials conducted
at trial sites on
various
Tasmanian rivers
Tasmania only
Daily data
Flow Stressed Ranking,
Vic
Evaluated at 551
Vic sites
Victoria only
ISC Hydrology Sub-index,
Vic
Approx 1000 Vic
sites
Victoria only
Derived from 5 indicators
Reports published
for 1999 and 2004
Hydrological Disturbance
Index, Australian
Assessment of River
Condition
Not clear as to
number of sites
where
Hydrological
Disturbance Index
calculated
Intended to be
repeated at 3
year intervals
Modelled reference
condition sequence
NRM South (2009)
Modelled reference
condition sequence
Monthly data
SKM 2005
Modelled/transposed
reference condition
sequence
derived from 6 indicators
Monthly data
Modelled/transposed
reference condition
sequence
National
Monthly data
Ladson and White
(1999) and DSE (2006)
Norris et. al. (2001)
Modelled reference
condition sequence
4 Hydrologic Metrics.
As the Sustainable River Audit (Davies et al 2008) index is the most recent incarnation of the flow
stressed ranking style multi-metric approach and because it was considered to be the most
appropriate for application in the Murray Darling Basin which in turn is likely to contain many of the
most water stressed catchments in Australia, the metrics used in the SRA forms the starting position
12
for which metrics should be included in the multi metric index. The following sections describe firstly
the flow metrics included in the SRA (Davies et al. 2008). followed by additional metrics which have
been considered for inclusion in this analysis.
4.1 High-Flow Metric (HF)
The High Flow Metric (HF) considers the two highest two flow months of each year and compares
these between the two scenarios.
4.1.1 Ecological significance
The high flow metric indicates changes in the magnitude of high flows. Flood flows determine
maximum depths, velocities and shear stresses. They drive fluvial geomorphic processes,
transporting and depositing sediment and changing channel shape, and may act as a ‘disturbance’,
removing vegetation and other organic matter and re-setting the processes of succession. Reduced
flood flows can mean fewer over-bank flows, limiting connectivity between the channel and
floodplain. Populations of many native species of flora and fauna recruit on a large scale during highflow periods.
4.1.2 High Flow calculation method
HF is the mean of the highest and second highest monthly flows (top 12th and second top 12th flows,
or 8.3rd and 16.7th percentiles), thus:
HF= (HF8.3 + HF16.7) /2
where
HF8.3 is the range-standardized high-flow index based on the 8.3% exceedance flow,
similarly HF16.7 is the range-standardized high-flow index based on the 16.7% exceedance flow
HF8.3 = 1 – 2 × | Pile(Q8.3r) – Pile(Q8.3c) |
HF16.7 = 1 – 2 × | Pile(Q16.7r) – Pile(Q16.7c) |
Where:
Q8.3c = Current 8.3% exceedance flow (ML)
Q8.3r = Reference 8.3% exceedance flow (ML)
Pile(Q8.3c) = Proportion of years that the 8.3rd percentile current flow is exceeded by the
annual 8.3rd percentile Reference flow
Pile(Q8.3r) = Proportion of years that the 8.3rd percentile Reference flow is exceeded by the
annual 8.3rd percentile Reference flow
Q16.7c = Current 16.7% exceedance flow (ML)
Q16.7r = Reference 16.7% exceedance flow (ML)
13
Pile(Q16.7c) = Proportion of years that the 16.7rd percentile current flow is exceeded by the
annual 16.7rd percentile Reference flow
Pile(Q16.7r) = Proportion of years that the 16.7rd percentile Reference flow is exceeded by
the annual 16.7rd percentile Reference flow
A word of warning when using Microsoft Excel in calculating this metric. The basis of this metric is
the selection of the highest and second highest monthly flows for the year, however the percentiles
function in Excel will not allow you to select precisely this value (due to an n-1 value in the
percentiles formula). The resulting metric calculated using excel is very closely correlated to the one
intended as demonstrated in the example analysis where both are calculated to allow comparison.
4.2 Proportion of Zero Flow Metric (PZ)
The proportion of Zero flows metric compares the proportion of months with zero flow under the
two scenarios.
4.2.1 Ecological Significance
The zero flow months are extreme low-flow periods when habitats are restricted and water quality is
prone to deteriorate. They are a natural feature of ephemeral and episodic streams, but may harm
perennial communities needing continuous access to water. Extended zero-flow periods can result in
drying of the channel, leading to loss of connectivity between pools and even complete loss of
aquatic habitat. Under natural conditions, some kinds of aquatic biota are able to recolonise dried
channels, once flow resumes.
4.2.2 Calculation method
PZ is calculated as:
PZ = 1 – 2 × [ max(PZr, PZc) – min( PZr, PZc) ]
where
PZc =Proportion of zero monthly flows over the period of record under current conditions
PZr = Proportion of zero monthly flows over the period of record under Reference Condition
4.3 Low-Flow Metric (LF)
The Low Flow Metric reflects changes in the magnitude of low flows under the two scenarios.
4.3.1 Ecological Significance
Lowflow periods are a natural feature of many Australian rivers, but they reduce the availability of
instream habitat and are stressful for some species of aquatic biota.
4.3.2 Calculation method
The low flow metric is calculated in the same way is the high flow metric but using the lowest two
months of the year. It is calculated as the mean of the lowest and second lowest monthly flows
(bottom 12th and second bottom 12th flows, or 91.7th and 83.3rd percentiles), thus:
LF = (LF91.7 + LF83.3) /2
14
where
LF91.7 is the range-standardized low-flow index based on the 91.7% exceedance flow, from
LF91.7 = 1–2 × | Pile(Q91.7r) – Pile(Q91.7c) |
LF83.3 is the range-standardized low-flow index based on the 83.3% exceedance flow, from
LF83.3 = 1–2 × | Pile(Q83.3r) – Pile(Q83.3c) |
where
Q91.7c = Current 91.7% exceedance flow (ML)
Q91.7r = Reference 91.7% exceedance flow (ML)
Pile(Q91.7c) = Proportion of years that the annual 91.7th percentile current flow is exceeded
by the annual 91.7th percentile Reference flow
Pile(Q91.7r) = Proportion of years that the 91.7th percentile Reference flow is exceeded by
the annual 91.7th percentile Reference flow
Q83.3c = Current 83.3% exceedance flow (ML)
Q83.3r = Reference 83.3% exceedance flow (ML)
Pile(Q83.3c) = Proportion of years that the annual 83.3th percentile current flow is exceeded
by the annual 83.3th percentile Reference flow
Pile(Q83.3r) = Proportion of years that the 83.3th percentile Reference flow is exceeded by
the annual 83.3th
As with the high flow metric, using Microsoft Excel to calculate this metric will not give you precisely
the value intended but a close and highly correlated value.
4.4 Monthly Variation Metric (CV)
The coefficient of variation compares flow variability between scenarios over all months of the year.
4.4.1 Ecological Significance
Variations in flows and water levels affect the composition, structure and zonation of aquatic and
riparian plant communities, and provide life-history cues for many plant and animal species.
Reduced flow variation may indicate hydraulic changes, including reductions in longitudinal and
lateral connectivity, hence habitat complexity. This index does not measure seasonal timing—a
reversed seasonal regime could have the same score as a reference regime.
4.4.2 Calculation method
The coefficient of variation compares the coefficients of variation (standard deviation divided by
mean) of monthly flows under current and Reference Condition:
CV = CVr / CVc
Where:
15
CVc = Current monthly coefficient of variation
CVr = Reference monthly coefficient of variation
4.5 Seasonal Period Metric (SP)
The seasonal period measures the shift between the months of maximum flow and minimum flow
between scenarios.
4.5.1 Ecological significance
The seasonal timing of periods of low and high flow affects the responses of plant and animal
communities. In the southern Murray-Darling Basin, the flora and fauna are adapted to high flows in
winter/spring and low flows in summer/autumn, whereas the converse is true for northern regions
of the Basin. Changes to seasonal patterns, such as those associated with irrigation, have caused
significant changes in some riverine and floodplain communities.
4.5.2 Calculation method
The seasonal period metric is derived from frequency distributions showing the percentage of years
that maximum and minimum annual flows fall in a given month under current and Reference
conditions.
minimum proportions (from current or Reference data) in each month are summed, as follows:
where
SP_fd= Comparison of frequency distribution seasonal period index
PHCi = Percentage of years when the ith month has highest flow under current conditions
PHRi = Percentage of years when the ith month has highest flow under Reference Condition
PLCi = Percentage of years when the ith month has lowest flow under current conditions
PLRi = Percentage of years when the ith month has lowest flow under Reference Condition
4.6 Mean Annual Discharge Metric (MNAQ)
The mean annual discharge metric used in the SRA (Davies 2008) is the ratio of the long-term mean
annual discharge under current conditions to that under Reference Condition. This differs from the
FSR Mean Annual Flow Index (SKM 2005), which estimates changes in the proportions of time that
mean annual flows are exceeded. The mean annual flow index used in the SRA study was not range
standardised, the FSR approach considered a range standardised interpretation of the mean annual
discharge score (although did not recommend a mean annual discharge metric in the final scoreing
system).
16
4.6.1 Ecological significance
It is difficult to link the mean annual discharge metric to any specific ecosystem impact but, in
general, virtually all aquatic, riparian and floodplain communities would be affected by significant
changes in mean annual flow.
4.6.2 Calculation Method
The method of calculation used in the SRA is simply the ratio of the mean annual flow values
between scenarios. The method tested by SKm in the development of the FSR is based on a range
standardised approach of the proportion of time the ‘natural’ mean annual flow is exceeded.
where:
Am = Range-standardised mean annual flow index
Qc = Average current annual flow (ML/year)
Qu = Average unimpacted annual flow (ML/year)
Prop (Qc) = Proportion of time that the average current annual flow is exceeded under
unimpacted conditions
Prop(Qu) = Proportion of time that the average unimpacted annual flow is exceeded under
unimpacted conditions
In order to make the index more ecologically significant, the above equation was applied to five flow
values, ranging from 80% to 120% of the mean. The mean annual flow index is calculated as the
average of the range-standardised indices for the five flow intervals:
Where
A = Range-standardised mean annual flow index
An = Range-standardised mean annual flow index for a given flow interval
N = Number of flow intervals
For the example analysis only the SRA (ratio approach) was calculated for the mean index.
4.7 Median Annual Discharge Metric (MDAQ)
The median annual discharge metric used in the SRA (Davies et al 2008) is the ratio of the long-term
median annual discharge of current conditions to Reference Condition. A median indicates the
discharge that prevails 50% of the time. Medians indicate the distribution of annual flows in terms of
rank values rather than actual values, as does the mean.
17
5 Additional Metrics
The following issues summarise concerns and possible alternative or additional metrics with the
application of the existing range of indices across the whole country. These alternative metrics were
developed by speaking to experts who had experience in applying similar multi metric indices in
jurisdictions across Australia. Each of the suggested scores are included in the subsequent example
applications for the consideration and recommendation.
5.1 The high flow metric is not high enough
5.1.1 Ecological significance
The high flow metric is a comparison of the average of the highest two months of flow each year and
how often they exceed the predevelopment monthly flows of the same percentile. In this way the
measures are a number of times of exceedance (represented as a proportional change between
scenarios) but with no measure of by how much the exceedance occurs. Hence this is really a
measure of change in frequency of sub-annual events. However for many large wetlands of the
Murray Darling Basin it is a 3-5 year event (natural regime) which is required as an effective wetting
event (See CSIRO Murray Darling sustainable yields reports 2008). If flow regulation severely reduces
the 3-5 return interval flood (as demonstrated for many catchments in the Murray Darling
sustainable Yields reports) but still maintains relatively high inchannel flow (such as through
regulated flow), then the high flow metric may be insufficient to describe the flow alteration. The
high flow metric is principally measuring sub-annual within channel flow. But there is a need to also
consider a ‘flood plain’ or ‘wetland connection’ metric to ensure that the existing high flow metric is
adequately covering this component of the flow regime.
5.1.2 Calculation method
We propose a similar percentile exceedance type measure (called high flood flow (HFF)) as with the
existing high flow metric which relates to around the one in four year monthly flow. This is
determined by using the 25th percentile of the annual values of maximum total monthly flow for the
predevelopment case. This value is the total monthly flow that is exceeded in 25 out of 100 years.
For both the current and predevelopment scenarios, the proportion of years where this flow is equal
or exceed is then compared to give a range standardised score similar to the SRA and FSR high flow
score.
HFF = 1 – 2 × |Prop(Q25n) – Prop(Q25c) |
Where:
Prop(Q25c) = Proportion of years that the 25th percentile monthly flow for the reference
regime is exceeded in the current regime
Prop(Q25n) = Proportion of years that the 25th percentile monthly flow for the reference
regime is exceeded in the reference regime (this will be 0.25)
18
5.2 Time between wetland or floodplain inundation is
critical
5.2.1 Ecological significance
The above described SRA metrics treat each year as an independent data set, akin to a sample of
temporaly unrelated data. However from an ecological perspective, the sequencing of years is very
important. For wetland vegetation, the average period between watering may be less important
than the single longest period between watering events. Similarly for in-channel organisms such as
fish, the duration of low flow may be very important, especially if this persists for a period longer
than the reproductive life span, whereby a multiyear drought may produce a local extinction. We
propose a sub-indice to quantify the time between flood plain / wetland connection and another to
quantify the duration of drought in the next section.
5.2.2 Calculation method
For quantifying the period between floodplain/wetland connection, we suggest a High Flow Period
Between (HFPB) metric which is a measure of the relative change in the longest period high flow
events. This is based on the same definition of a high flow as used in the suggested High Flow
Frequency (HFF) metric above whereby a high flow threshold is determined as the 25th percentile of
the annual values of maximum total monthly flow for the predevelopment case. The HFPB is then
the ratio of the change in the single longest period between the current and predevelopment
scenarios. A sub-index score of 0.7 would mean that the longest period of no connection between
the floodplain/wetland and the stream had increased by 30%.
The draw back with this approach is that it is not range standardised and both scenarios must be
concurrent as is the case for the sustainable yields projects.
HFPB = Pern/Perc
Where:
Pern = single longest continuous period where the natural monthly flow totals are below the 25th
percentile of annual maximum monthly flow totals for the natural regime.
Perc = single longest continuous period where the current monthly flow totals are below the 25th
percentile of annual maximum monthly flow totals for the natural regime.
5.3 The duration of low flow events is critical for instream
biota
For instream biota the same issues apply as for a wetland, with the persistent of low flow conditions
presenting a threat to reproduction. The same approach is suggested for the HFPB, but called a Low
Flow Duration (LFD) metric whereby the 75th percentile of the annual values of maximum total
monthly flow for the predevelopment scenario is used to set a low flow threshold. The number of
consecutive years where the maximum of the total monthly flows for the year do not exceed this
threshold is a measure of instream stress through low flow persistence. Conversely if flow
19
regulation seeks to artificially reduce the low flow period, this will adversely effect those species
naturally adapted to the location and may result in invasion and habitat competition by nonendemic species.
5.3.1 Calculation method
The LFD would then be the ratio of the change in the single longest period (years) of below 25th
percentile predevelopment flow between the current and predevelopment scenarios. A sub-index
score of 0.7 would mean that the longest low flow period in the current scenario record was 30%
longer (or possible shorter) than the predevelopment scenario.
The draw back with this approach is that it is not range standardised and both scenarios must be
concurrent as is the case for the sustainable yields projects.
LFD= Pern/Perc
Where:
Pern = single longest continuous period where the natural monthly flow totals are below the 75th
percentile of annual maximum monthly flow totals for the natural regime.
Perc = single longest continuous period where the current monthly flow totals are below the 75th
percentile of annual maximum monthly flow totals for the natural regime.
5.4 Seasonality of flow is a strong predictor of fish in the
Tropics
5.4.1 Ecological significance
Analysis by Pusey and Kennard (2004) has shown that the strength of seasonality of flow, or actually
the size of the wet relative to the dry season flow is a strong predictor of fish species richness. For
those streams with a strong seasonality of flow, the species richness was lower than those with a
more constant or are more perennial in flow. The rationale for finding is that greater habitat
specialisation may be fostered in rivers with predictable flow regimes, whereby generalist species
are more likely to be successful in rivers with highly seasonal regimes. The metric used by Pusey and
Kennard is the ratio of the total flow during the driest six consecutive months to the total annual
flow. We propose the same metric, but with a range standardised version to allow comparison
between streams.
5.4.2 Calculation method
This metric is determined by firstly identifying the six consecutive months which have the lowest
total discharge for the natural scenario. This is done by creating a moving 6 month total for the
entire record, and then creating a total for each of twelve possible six month moving totals. The
lowest of these twelve is used to identify the six month period with the lowest total flow. For each
year of record, a ratio of the total flow for these driest six months and the total annual flow is
calculated and the average of this low/total ratio for the natural regime is then determined. The
natural and current regimes are then compared on a year by year basis to determine the number of
years that natural Mean(low/total) ratio is exceeded, which allows a count of the proportion of years
that the average low flow is exceeded. The proportion of times the natural low flow is exceeded is
20
then compared between the scenarios to give a range standardised comparison to reflect the
change in the dry flow period between the scenarios.
SDP= 1 – 2 × |P(dryn) – P(dryc) |
Where:
P(dryn) = Proportion of years that the mean natural dry period ratio (MNDPR) is exceed under the
natural regime.
Pile(Q25n) = Proportion of years that the mean natural dry period ratio is exceed under the natural
regime.
Where:
MNDPR = average of the annual ratio of the driest six months to the total annual flow.
Where:
The driest six months is the six month period with the lowest total discharge over the entire record.
For this metric sensitivity analysis has been conducted on the dry period – 3-9 months was
considered.
6 Integration and Aggregation techniques
6.1 SRA Approach
6.1.1 At a site integration
For the SRA, sub-indices or flow metrics are first aggregated to the five indicator scores. Where there
is more than one sub-index (low flow, gross flow volume) the relative value of the sub-indices is
considered in terms of the alternative combinations and a resulting expert derived weighting index is
provided for the higher level indicator (Table 2). For example if the change in the mean flow is high
and change in the median is low this results in an overall higher gross volume indicator score than if
the median is high and the mean is low. The five indicator scores (High flow, low flow, variability,
seasonality, gross volume) are then again aggregated using an expert derived weighting to give a
total 0-100 score. The expert derived weighting (Table 2) allows the consideration of the relative
importance of each of the indicators. Whilst not explicitly stated, it appears form table 2 that the
experts used to derive the overall scoring system placed the highest emphasis on the high flow
indicators. It is not clear from the SRA 2008 report how a distinction was made between high and
low condition.
The expert derived ranking system in Table 2 provides an excellent way to combine hard to interpret
information, although it is difficult to interpret the resulting score without going back to either this
table to see why a score was achieved or to go back to the original indicator scores.
21
Table 2: Generating hydrological condition scores from five indicators (HFE – High Flow Indicator)
High Flow
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
Low flow
H
H
H
H
H
H
H
H
L
L
L
L
L
L
L
L
H
H
H
H
H
H
H
H
L
L
L
L
L
L
L
L
Variability
H
H
H
H
L
L
L
L
H
H
H
H
L
L
L
L
H
H
H
H
L
L
L
L
H
H
H
H
L
L
L
L
Seasonality
H
H
L
L
H
H
L
L
H
H
L
L
H
H
L
L
H
H
L
L
H
H
L
L
H
H
L
L
H
H
L
L
Gross volume
H
L
H
L
H
L
H
L
H
L
H
L
H
L
H
L
H
L
H
L
H
L
H
L
H
L
H
L
H
L
H
L
Score
100
93
87
80
80
73
67
60
73
67
60
53
53
47
40
33
67
60
53
47
47
40
33
27
40
33
27
20
20
13
7
0
6.1.2 SRA Regional Aggregation
Many reaches were assessed in each reporting catchment for the SRA, as you may expect the upper
catchment scores where often high and the lower catchment scores where poor due to the
intervening hydrological alteration. The SRA did not aggregate the hydrological scores into a single
valley wide value but rather reported the spatial distribution of bands of scores (Figure 1). The
reporting for this project will be at a national scale and will require some high level catchment score
as well as within catchment reporting similar to the SRA.
22
Figure 1: Example hydrological reporting from the SRA.
6.2 FSR at a site Integration
The 2005 FSR report considers a range of methods to aggregate the indicator score to give an overall
site based hydrology score. The simple arithmetic mean is presented as a simple and easy to
interpret summary, and this approach logically suggests that any site with multiple indicators of the
23
hydrology under stress will have an overall lower score. However if one single element of the flow
regime is dramatically altered such as a seasonal flow reversal then the averaging approach will not
reflect this and the overall score could be high for that site even though the regime is dramatically
altered in one critical element (Figure 2).
Figure 2: averaging the indicator scores gives the Goulburn downstream of Eildon a higher score
than the Wimmera (from SKM 2005 FSR report p 53).
6.2.1 Statistical integration
There are a range of statistical approaches for metric integration and aggregation such as where
measures of group dissimilarity can be used as an index of hydrologic alteration. Such approaches
are useful for providing a single metric but as with all integration, the underlying metrics need to
made available for sensible interpretation
6.3 Recommended at a site integration
The purpose of this project is highlight areas under potential hydrological stress, not to give an
overall score of performance. With this in mind it is important that hydrological alteration like that in
the Goulburn River below Eildon (Figure 2) should be identified by the integration system used in
this project. A significant problem with any integration is that the indicators are assumed to be of
equal value and are linearly related to ecological risk. This problem has been solved via the SRA
expert lookup table which effectively provides a variable ranking depending on combinations of
scores. The question is how relevant such a score would be if applied outside the Murray Darling
basin. Some alternatives are considered below. As a general principal, the range standardised
approach adopted in the development of the FSR is a sound basis allow relative comparison of
results, because the reported metrics are effectively scaled to the expected range, which will allow
24
comparison of the metric scores between sites. Where the metric is not range standardised, a metric
score
6.3.1 Option 1: report Lowest indicator score:
One simple approach to report all potential areas of high ecological risk through hydrological
alteration by reporting the single lowest metric score for a site. This alleviates the problem of
dampening the effect of a single highly altered part of the flow regime due to averaging across the
metrics. However a problem then arises when all or many metrics are moderately impacted but
none is dramatically impacted, in this case simply reporting the worst single metric doesn’t account
for a cumulative impact of many areas of the flow regime being altered. For example a site where all
metrics are 70% is likely to be at higher risk than one where a single metric is at 65%.
6.3.2 Option2: Rank cumulative score
In order to not diminish the value of cumulative impacts of multiple elements of the hydrological
regime being altered some form of weighted cumulative score could be considered. Preferably this
would both identify sites of large change in a single metric as well as taking account of the
cumulative impact reflected in multiple metric changes. As a first approach, the five underlying
indice scores are determined by taking the minimum of the sub- metric scores. For the five indices,
the maximum deviation is multiplied by 5, the next by 4 and so on to give a total deviation score
which in turn is divided by the sum of the multipliers. This is effectively a weighted averaging
whereby the weighting is based on deviation from the reference, where small deviation is given a
lower weighting.
6.3.3 Biological Rank score
A further option is to develop a weighting scheme based on the relative contribution of each metric
in predicting some biological pattern. For example, these metrics could be used to construct broad
scale models to predict fish species richness. The relative weighting of the metrics (effectively their
relative coefficient values) could be used as a basis for weighting. The difficulty here is that different
ecosystem components (fish, vegetation, birds) would respond differently, and hence the relative
weighting may tend to be a reflection of the available species data than a truly broad indication of
the most important aspects of the flow regime. This approach is not recommended other than for
specific local application.
7 Example applications
The following example applications have been run to inform the discussion of how appropriate it
may be to apply the SRA in regions where is has not been considered (i.e. Northern Australia) and to
test the additional metrics presented above. Each of the pages provides a brief summary of the
hydrologic change between a modelled predevelopment or natural scenario and a modelled current
development scenario over an extended period (mostly greater than 50 years). For each example
consider the sub-scores and the sub-score aggregation technique.
25
7.1 Condamine downstream from St George(Murray Darling)
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
11
20
82%
Max duration of below 75th
percentile
LFD
4
7
75%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
1308673
917639
-30%
3596437
2962250
-18%
1620336
1135702
-30%
938199
529742
-44%
476134
190127
-60%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.58
0.80
0.86
0.55
0.95
0.98
0.57
integrated
0.55
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.81
0.68
0.98
0.70
0.56
0.81
0.68
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.57
new
new
0.56
0.55
0.64
0.59
26
7.2 Lower Murrumbidgee NSW (Maude Weir - Lowbidgee
area) (Murray Darling)
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
11
19
73%
Max duration of below 75th
percentile
LFD
4
10
150%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
2961100
1414415
-52%
5272908
3773600
-28%
3932901
1850189
-53%
2854850
970947
-66%
1791943
452207
-75%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.19
0.39
0.71
0.58
0.70
1.00
0.40
integrated
0.19
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.55
0.63
1.00
0.48
0.34
0.55
0.63
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.40
new
new
0.34
0.19
0.42
0.35
27
7.3 Lower Goulburn River (VIC) (Murray Darling)
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
13
38
192%
Max duration of below 75th
percentile
LFD
3
11
267%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
3231029
1583918
-51%
6188903
4107174
-34%
4394935
2095432
-52%
2875598
1159219
-60%
1941005
556502
-71%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.30
0.38
0.64
0.34
0.28
1.00
0.27
integrated
0.30
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.67
0.60
0.80
0.49
0.40
0.67
0.60
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.27
new
new
0.40
0.27
0.45
0.38
28
7.4 Gwydir River @ yarraman (NSW) (Murray Darling)
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
15
29
93%
Max duration of below 75th
percentile
LFD
4
6
50%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
388782
312142
-20%
1076379
772598
-28%
503723
340750
-32%
254130
220317
-13%
162929
159637
-2%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.77
0.84
0.73
0.52
0.22
1.00
0.67
integrated
0.52
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
1.03
0.77
0.82
0.80
0.87
1.03
0.77
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.22
new
new
0.80
0.22
0.67
0.54
29
7.5 Murray River @ SA border – Chowilla area (NSW)
(Murray Darling)
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
11
24
118%
Max duration of below 75th
percentile
LFD
4
11
175%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
12669422
6846916
-46%
22308661 15611380
-30%
15075948
8975951
-40%
11326717
5141216
-55%
8495494
3197133
-62%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.28
0.20
0.66
0.46
0.71
1.00
0.36
integrated
0.20
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.69
0.63
0.86
0.54
0.45
0.69
0.63
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.36
new
new
0.45
0.20
0.47
0.38
30
7.6 Warrego River @ charleville (Qld) (Murray Darling)
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
11
11
0%
Max duration of below 75th
percentile
LFD
4
4
0%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev Current
Change
173978
169871
-2%
587892
579448
-1%
183216
180198
-2%
88415
85262
-4%
39305
36700
-7%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.94
0.98
0.98
1.00
1.00
0.96
1.00
integrated
0.94
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.98
0.99
1.00
0.98
0.96
0.98
0.99
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.96
new
new
0.96
0.94
0.96
0.96
31
7.7 Daly river at Beeboom (Northern Australia)
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
15
18
20%
Max duration of below 75th
percentile (years of drought)
LFD
3
3
0%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
5193027
5151884
-1%
12145709 12032828
-1%
6369451
6320080
-1%
4519958
4451786
-2%
1920249
1877816
-2%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.96
1.00
0.98
0.83
0.67
1.00
1.00
integrated
0.83
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.99
0.98
0.93
0.99
0.98
0.99
0.93
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.67
new
new
0.98
0.67
0.88
0.83
32
7.8 Daly at Dorisvale (Northern Australia)
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
15
15
0%
Max duration of below 75th
percentile (years of drought)
LFD
4
4
0%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
3438496
3406087
-1%
8566456
8495616
-1%
4520012
4483739
-1%
2837760
2800021
-1%
1146883
1115572
-3%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.97
1.00
1.00
1.00
0.46
1.00
1.00
integrated
0.97
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.99
0.95
0.83
0.99
0.99
0.99
0.83
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.46
new
new
0.99
0.46
0.85
0.77
33
7.9 Katherine River @Galloping Jacks (Northern Australia)
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
14
17
21%
Max duration of below 75th
percentile (years of drought)
LFD
3
3
0%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
854140
830606
-3%
2416335
2380210
-1%
1153162
1128370
-2%
721356
692016
-4%
245471
224026
-9%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.99
0.99
0.96
0.82
0.47
1.00
1.00
integrated
0.82
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.98
0.91
0.67
0.97
0.96
0.98
0.67
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.47
new
new
0.96
0.47
0.78
0.69
34
7.10 Katherine River @ Knotts Crossing (Northern Australia)
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
17
19
12%
Max duration of below 75th
percentile (years of drought)
LFD
3
3
0%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
684598
677629
-1%
1955232
1939263
-1%
910035
901028
-1%
585444
584620
0%
199289
190738
-4%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.99
1.00
0.98
0.89
0.59
1.00
1.00
integrated
0.89
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
1.00
0.96
0.89
0.99
1.00
1.00
0.89
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.59
new
new
0.99
0.59
0.87
0.81
35
7.11 Tasmania _ sub catchment (TBD) 533
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
15
15
0%
Max duration of below 75th
percentile (years of drought)
LFD
5
5
0%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev Current
Change
62482
61460
-2%
148463
147038
-1%
82241
80984
-2%
50377
49427
-2%
28521
27534
-3%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.99
1.00
1.00
1.00
0.77
0.97
1.00
integrated
0.99
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.99
0.90
1.00
0.98
0.98
0.99
0.90
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.77
new
new
0.98
0.77
0.93
0.89
36
7.12 Tasmania _ sub catchment (TBD) 547
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
15
15
0%
Max duration of below 75th
percentile (years of drought)
LFD
4
4
0%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
1875994
1874777
0%
3964433
3963126
0%
2393347
2392089
0%
1665081
1663909
0%
1133326
1132042
0%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
1.00
1.00
1.00
1.00
0.99
1.00
1.00
integrated
1.00
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
1.00
0.99
1.00
1.00
1.00
1.00
0.99
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.99
new
new
1.00
0.99
1.00
0.99
37
7.13 Tasmania _ sub catchment (TBD) 530
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
11
11
0%
Max duration of below 75th
percentile (years of drought)
LFD
3
3
0%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev Current
Change
284170
232928
-18%
599089
518690
-13%
361808
302374
-16%
261428
214336
-18%
183531
122449
-33%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.71
0.88
0.90
1.00
0.46
0.68
1.00
integrated
0.71
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.87
0.62
0.93
0.82
0.82
0.87
0.62
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.46
new
new
0.82
0.46
0.70
0.63
38
7.14 Tasmania _ sub catchment (TBD) 73
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
21
21
0%
Max duration of below 75th
percentile (years of drought)
LFD
7
7
0%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
1640148
1449884
-12%
3652717
3426226
-6%
2049534
1867168
-9%
1377776
1202374
-13%
878338
698653
-20%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.81
0.93
1.00
1.00
0.48
0.93
1.00
integrated
0.81
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.91
0.73
0.95
0.88
0.87
0.91
0.73
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.48
new
new
0.87
0.48
0.76
0.69
39
7.15 Tasmania _ sub catchment (TBD) 80
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
21
21
0%
Max duration of below 75th
percentile (years of drought)
LFD
3
3
0%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev Current
Change
331582
294981
-11%
801123
752085
-6%
421082
383280
-9%
296269
256745
-13%
167294
134795
-19%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.87
0.95
1.00
1.00
0.49
0.94
1.00
integrated
0.87
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.91
0.79
0.88
0.89
0.87
0.91
0.79
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.49
new
new
0.87
0.49
0.78
0.72
40
7.16 Tasmania _ sub catchment (TBD) 82
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
24
24
0%
Max duration of below 75th
percentile (years of drought)
LFD
4
4
0%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
538480
538359
0%
1193995
1193874
0%
675040
674919
0%
449750
449629
0%
286691
286571
0%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
1.00
1.00
1.00
1.00
1.00
1.00
1.00
integrated
1.00
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
1.00
0.99
1.00
1.00
1.00
1.00
0.99
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
1.00
new
new
1.00
0.99
1.00
1.00
41
7.17 Tasmania _ sub catchment (TBD) 83
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
24
27
13%
Max duration of below 75th
percentile (years of drought)
LFD
4
10
150%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
2450052
1656392
-32%
5532595
4091139
-26%
3084948
2070741
-33%
2028292
1175836
-42%
1299230
717413
-45%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.37
0.55
0.79
0.89
0.30
1.00
0.40
integrated
0.37
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.90
0.76
0.86
0.68
0.58
0.90
0.76
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.30
new
new
0.58
0.30
0.46
0.28
42
7.18 Tasmania _ sub catchment (TBD) 84
Summary
Mean Annual Flow (ML/y)
5th percentile annual flow (ML/y)
25th percentile annual flow (ML/y)
Median annual flow (ML/y)
75th Percentile annual flow (ML/y)
MAF
5AF
25AF
MedAF
75AF
Max period between floods 25th
percentile annual flow (Years)
FPB
24
27
13%
Max duration of below 75th
percentile (years of drought)
LFD
4
7
75%
Index
High flow
High Flow Ranking*
High flow flood*
High flow flood period between*
Low flow
Zero flow
Low flow duration*
Predev
Current
Change
3626318
2832538
-22%
8051584
6633657
-18%
4504590
3530708
-22%
3011664
2105259
-30%
1905358
1366887
-28%
HF
HFR
HFF
HFPB
LF
PZ
LFD
index
0.60
0.75
0.83
0.89
0.23
1.00
0.57
integrated
0.60
Monthly variation
Seasonal Period
Seasonal Dry Period*
Mean Annual Discharge
Median Annual Discharge
CV
SP
SDP
MNAQ
MDAQ
0.95
0.89
0.93
0.78
0.70
0.95
0.89
Summary score for reporting
Minimum
Mean
Weighted
revised
new
new
0.23
new
new
0.70
0.23
0.58
0.41
43
8 Results and discussion
The summary plots (Figures 3-10) provide a summary of the individual site analysis presented above.
The figures are arranged by region with sample sites from the Murray Darling, Daly River (northern
Australia) and example data from Tasmania. Figure 3 summarises the volumetric alteration for each
site and the Murray darling examples show the most dramatic alteration in flow metrics which is a
reflection of the up to around 50% reduction in mean annual flow.
The comparison of integration techniques (Figure 4) shows that the ‘mean’ of subscores does have a
dampening effect compared to the ‘minimum’. Only one of the sites (site 84 in Tasmania) has a
lower ‘ranked’ score than the ‘minimum’ score, but otherwise the ranked score closely mirrors the
averaging approach and because it is more complicated to implement and interpret there is no
advantage in using the ranked weighting approach for integrating the site based metric scores. There
are some sites where based on the ‘mean’ the rank condition of a site would be higher than if based
on the minimum, presumably this is because of the dampening effect of averaging. Hence based on
the data analysed, the ‘minimum’ approach appears to be a useful integration technique where a
single summary metric is required
Figure 5 shows that while for several sites there are simular alterations across several metrics, there
are some sites where only one or two flow metrics have been significantly altered, for example, the
Daly River at Dorisvale has a low ‘Low Flow’ metric but all other metrics are relatively high. This is
further support for using the single lowest value as a simple and informative integration metric.
8.1 High flow
Where the high flow component of the flow regime has not been dramatically altered, there is little
difference between the high flow metrics considered (Figure 6). However for the Murray Darling
sites there is a dramatic and inconsistent difference between these metrics. The first metric (HFR)is
the SRA/FSR based metric, the second is a based on a higher flow threshold which generally has a
higher score, implying that the flow alteration in these sites has a more dramatic affect on the within
year high flows than the larger 4 year return interval flood. The period between these larger floods
(HFPB) is correlated with the other high flow metrics (Table 3) but different enough to warrant
consideration as an impendent metric, particularly in combination with the SRA HF metric.
8.2 Low Flow
The proportion of zero flows targets an ecologically important component of the flow regime,
however for the data sets tested, this does not alter greater between the scenarios and hence the
metric does not indicate much change between scenarios (Figure 7). The newly suggested low flow
duration metric (LFD) is only weekly correlated with the SRA Low flow metric (LF) but is highly
correlated with the high flow metrics(Table 3), implying that the LFD metric is not required if high
flow metrics are to be used.
44
8.3 Coefficient of Variation
The coefficient of variation is most closely correlated with the high flow metrics but is dissimilar
enough to warrant inclusion of the CV as a separate metric.
8.4 Seasonality
The two seasonality metrics are not correlated with each other and the proposed seasonal dry
period (SDP) metric is not well correlated with any other metric (Figure 7, Table 3). The SDP appears
to be most sensitive to low flow modification in the wet tropics and on this basis it is recommended
for inclusion.
Sensitivity analysis was conducted on the seasonal record length to test how important the
definition of the dry period length is to the metric result. The seasonal dry period was applied for a
period of 3-10 months and the resulting metric was surprisingly sensitive to the dry period length,
Table 4 shows the consistently low correlation between the alternative dry period lengths. This is
thought to reflect the less strong seasonal pattern of the Murray Darling sites. When only the
northern Australia sites are considered (Table 5), there is a very strong correlation between the
alternative scores for season lengths up to 7 months, and then this correlation declines. Figure 10
also shows a stepped change in the score values from a period of greater than 7 months. It is
recommended to use a seasonal period of 6 months.
We recommend to include the seasonal dry period metric as it is more sensitive than the current
seasonal period metric for tropical streams but to also retain the existing seasonal period metric as it
is more sensitive for southern streams.
8.5 Mean and Median
The mean and median metrics are closely correlated with each other (Figure 11, Table 3) and the
high flow metrics. These metrics provide little additional information to the above metrics and need
not be included in the analysis.
Table 3: Correlation matrix between all considered metric
HF
HFR
HFF
HFPB
LF
PZ
LFD
CV
SP
SDP
MNAQ
HF
1.000
HFR
0.957
1.000
HFF
0.904
0.920
1.000
HFPB
0.717
0.758
0.878
1.000
LF
0.301
0.247
0.393
0.214
1.000
PZ
-0.046
-0.151
-0.150
-0.307
0.081
1.000
LFD
0.943
0.928
0.944
0.811
0.324
-0.288
1.000
CV
0.877
0.860
0.728
0.668
0.037
0.030
0.745
1.000
SP
0.821
0.750
0.744
0.646
0.348
0.345
0.683
0.808
1.000
SDP
0.071
0.153
0.262
0.317
0.649
-0.147
0.161
-0.032
0.138
1.000
MNAQ
0.986
0.952
0.928
0.796
0.297
-0.048
0.939
0.903
0.863
0.111
1.000
MDAQ
0.985
0.937
0.881
0.757
0.230
-0.084
0.936
0.915
0.825
0.060
0.988
MDAQ
1.000
45
Table 4: correlation of low flow duration score for different dry period lengths across all sites
(correlation of the score with Seasonal Period score is also shown)
3
4
5
6
7
8
9
10
SP
3
1.000
0.841
0.653
0.607
0.469
0.394
0.317
0.186
0.354
4
5
1.000
0.814
0.849
0.788
0.564
0.521
0.335
0.380
6
1.000
0.784
0.739
0.655
0.487
0.515
0.419
7
1.000
0.843
0.514
0.622
0.415
0.137
8
1.000
0.741
0.712
0.570
0.171
9
1.000
0.829
0.883
0.563
1.000
0.858
0.422
10
SP
1.000
0.517
1.000
Table 5: correlation of low flow duration score for different dry period lengths for northern Australia
sites only (correlation of the score with Seasonal Period score is also shown)
3
4
5
6
7
8
9
10
SP
3
1.000
0.990
0.980
0.952
0.975
0.634
0.891
0.842
0.968
4
5
6
7
8
9
10
SP
1.000
0.983
0.958
0.993
0.661
0.929
0.905
0.977
1.000
0.994
0.992
0.773
0.957
0.907
0.998
1.000
0.979
0.839
0.973
0.915
0.997
1.000
0.742
0.966
0.941
0.992
1.000
0.873
0.808
0.802
1.000
0.980
0.972
1.000
0.926
1.000
46
9 Summary plots for comparison
300%
Flow summary metrics: change from natural
250%
200%
150%
MAF
5AF
25AF
MedAF
100%
75AF
FPB
LFD
50%
0%
Figure 3: percentage hydrologic change (relative to the natural scenario) for sites used in example metric comparison (MAF – Mean annual flow, 5AF – 5th
percentile of annual flow total, 25 AF – 25th percentile of annual flow totals, Med AF – median of annual flow totals, 75AF – 75th percentile of annual flow
totals, FPB – maximum period between floods (defined as 75th percentile years), LFD – maximum duration of low flow (defined as 25th percentile years).
47
1.2
Alternative integrated scores
1
0.8
0.6
min
mean
0.4
weighted
0.2
0
48
Figure 4: Hydrological alteration summary scores using three different methods
1.2
All metrics
1
0.8
HF
HFR
HFF
0.6
HFPB
LF
PZ
LFD
0.4
CV
SP
SDP
MNAQ
0.2
MDAQ
0
49
Figure 5: All sub metrics for all sites
1.2
High Flow
1
0.8
0.6
HFR
HFF
0.4
HFPB
0.2
0
50
Figure 6: High flow metrics for consideration
1.2
Low Flow
1
0.8
0.6
LF
PZ
0.4
LFD
0.2
0
51
Figure 7: Low flow metrics considered
CV
1.2
1
0.8
0.6
CV
0.4
0.2
0
52
Figure 8: Coefficient of variation scores.
1.2
Seasonal Period
1
0.8
0.6
SP
SDP
0.4
0.2
0
53
Figure 9: Measures of seasonality (SP- seasonal period as defined in SRA/FSR and SDP – seasonal dry period as defined in this report)
1.1
Seasonal Dry Period score northern australia
1.05
Seasonal Dry Period Score
1
0.95
0.9
Daly @Beeboom
0.85
Daly@Dorisvale
0.8
Katherine@GallopingJacks
0.75
Katherine@Knotts Crossing
0.7
0.65
0.6
2
3
4
5
6
7
8
9
10
11
Months considered in score
Figure 10: seasonal dry period score for northern Australia for alternative ‘dry period’ durations.
54
1.2
Mean & Median
1
0.8
0.6
MNAQ
MDAQ
0.4
0.2
0
Figure 11: mean and median scores for selected sites.
55
56
10References
CSIRO (2008) Water Availability in the Murray-Darling Basin. A report to the Australian Government
from the CSIRO Murray-Darling Basin Sustainable Yields Project. CSIRO, Australia.
Davies, P. Harris, J., Hillman, T. Walker, K. (2008) Sustainable Rivers Audit: a report on the ecological
health of rivers in the Murray-Darling Basin, 2004-2007. Prepared by the Independent Sustainable
Rivers Audit Group for the Murray–Darling Basin Ministerial Council. Murray Darling Basin
Commission
DSE (2006) Index of Stream Condition Users Manual, (2nd Edition). Victorian Government,
Melbourne, Australia.
Ladson. A. and White, L. (1999) Index of Stream Condition: the Second Benchmark of Victorian River
condition. Department of Natural resources and Environment, Melbourne, Australia.
Norris, R., Prosser, I., Young, B., Liston, P., Bauer, N., Davies, N., Dyer, F., Linke, S. and Thoms, M
(2001) Assessment of River Condition: An Audit of the Ecological Condition of Australian Rivers. Final
Report submitted to the National Land and Water Resources Audit Office. September 2001.
NRM South (2009) Tasmanian River Condition Index Reference Manual. NRM South, Hobart.
Pusey, B., Arthington, A. And Kennard, M 92004) Hydrologic regime and its influence on broad scale
patterns of fish biodiversity in north-eastern Australian rivers. Pp75-81 in Proceedings of the fifth
international symposium on ecohydraulics. aquatic habitats, analysis and restoration, Madrid Sept
2004.
SKM (2005) Development and Application of a flow stressed ranking procedure. SKM, Armidale, Vic.
57