guidelines for modelling water sharing rules in ewater source
DESCRIPTION
Water sharing rules are frequently encapsulated in some form of water management plan, or policy, which often has statutory status. Water sharing rules are developed for individual river systems and this can occur for a variety of reasons. For example, the aims could be to maintain or improve ecological functions, sustain the regional economy and protect the social values and benefits of the river system. Fundamental to developing water sharing rules in this situation is an understanding of environmental water needs, water entitlements including their priority of access, basic landholder rights, allocation of water and operation of water accounts. In regulated systems these rules are implemented in practice as operating rules for dams, rules for water allocation, rules governing access to water and water accounts, while in unregulated systems, implementation is via rules governing access to water and water accounts. Rules governing access to water may be attached to licences. Modelling of water sharing rules entails representing the water resource system, its water users, infrastructure details, environmental assets and processes for implementation of these rules.TRANSCRIPT
Towards best practice model application
Black, D.C. and Podger, G.M.
Guidelines for modelling water sharing rules in eWater Source
Guidelines for modelling water sharing rules in eWater Source
ii
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Citing this document
Black, D.C. and Podger, G.M. (2012) Guidelines for modelling water sharing rules in eWater Source:
Towards best practice model application. eWater Cooperative Research Centre.
Publication date: July 2012
ISBN 978-1-921543-74-6
Acknowledgments
eWater CRC acknowledges and thanks all partners to the CRC and individuals who have contributed to
the research and development of this publication. In particular, the contributions of the following individuals
to the drafting of this document have been invaluable and are gratefully acknowledged: Andrew Close,
Paul Harding, Barry James and Chris Ribbons.
eWater CRC gratefully acknowledges the Australian Government’s financial contribution to this project
through its agencies, the Department of Industry, Innovation, Science, Research and Tertiary Education,
the Department of Sustainability, Environment, Water, Population and Communities, and the National
Water Commission
For more information:
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www.ewater.com.au
Guidelines for modelling water sharing rules in eWater Source
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Contents
1 Introduction ................................................................. 1
1.1 Background ........................................................................................................................... 1
1.2 Scope .................................................................................................................................... 2
2 Procedure for quality assured modelling of water sharing
rules ............................................................................ 3
2.1 Project administration ........................................................................................................... 3
Peer review ........................................................................................................................... 3
Stakeholder consultation....................................................................................................... 4
2.2 Problem definition ................................................................................................................. 5
Problem statement ................................................................................................................ 5
Objectives ............................................................................................................................. 6
Understanding problem domain ............................................................................................ 6
System definition................................................................................................................... 7
Conceptual models ............................................................................................................... 7
Metrics and criteria................................................................................................................ 8
Decision variables ................................................................................................................. 8
Uncertainty and risk .............................................................................................................. 9
Preliminary assessment ...................................................................................................... 10
2.3 Option modelling ................................................................................................................. 10
Methodology development .................................................................................................. 10
Gather and clean up data ................................................................................................... 10
Setting up and building a model ......................................................................................... 14
Calibrate model ................................................................................................................... 15
Validate model .................................................................................................................... 17
Sensitivity/uncertainty analysis ........................................................................................... 17
Develop, test and explore options....................................................................................... 19
Reporting and communication of scenario results .............................................................. 19
Model acceptance ............................................................................................................... 21
2.4 Compare options and select the “best” ............................................................................... 23
Option selection criteria ...................................................................................................... 23
3 References ................................................................ 24
Guidelines for modelling water sharing rules in eWater Source
1
1 Introduction
1.1 Background
Water sharing rules are frequently encapsulated in some form of water management plan, or
policy, which often has statutory status. Water sharing rules are developed for individual river
systems and this can occur for a variety of reasons. For example, the aims could be to
maintain or improve ecological functions, sustain the regional economy and protect the
social values and benefits of the river system. Fundamental to developing water sharing
rules in this situation is an understanding of environmental water needs, water entitlements
including their priority of access, basic landholder rights, allocation of water and operation of
water accounts. In regulated systems these rules are implemented in practice as operating
rules for dams, rules for water allocation, rules governing access to water and water
accounts, while in unregulated systems, implementation is via rules governing access to
water and water accounts. Rules governing access to water may be attached to licences.
Modelling of water sharing rules entails representing the water resource system, its water
users, infrastructure details, environmental assets and processes for implementation of
these rules.
Water sharing rules need to be developed considering the natural variability of climate and
stream flow and how these might constrain water availability. Access by water users is also
governed by water use accounting procedures that might limit annual use or the volumes of
water held in water accounts or carried over from year to year. Therefore, modelling the
assessment of water availability (ie resource assessment), trigger thresholds for restrictions,
and water use accounting procedures is integral to the modelling of water sharing rules.
At the same time, water use patterns may be influenced by expectations of future water
availability. For example in low water availability years water users might expect water
availability to improve in the near term (eg irrigators planting more irrigated crop than current
water availability can support on the expectation that availability will improve sufficiently
during the irrigation season to support the full crop). Also during high water availability years
water users might expect to get access to large volumes of off allocation flow, be able to
store that water and plant greater areas. This risk taking behaviour may be affected by
changes in, or introduction of, water sharing rules.
Modelling water sharing rules is often the main focus of water management modelling
studies, and the process of arriving at an agreed set of rules that can impact water users,
including the environment, is usually socially and politically sensitive. This sensitivity is a
major factor underlying Australian water management agencies’ needs for best practice
modelling guidelines.
To meet its responsibilities to its partners and to meet this need for guidelines, eWater is
developing a family of guidelines, comprising Guidelines for water management modelling
(Black et al, 2011) and a series of guidelines covering application of various aspects of
eWater Source. These guidelines are one member of this series. They provide guidance
Guidelines for modelling water sharing rules in eWater Source
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directly relevant to modelling water sharing rules and support best practice application of
eWater Source for this purpose.
These guidelines complement eWater’s generic guidelines and should be used in
conjunction with them, as they are not intended to be a stand-alone document. They also
need to be used together with other guidelines in the series as needed. In common with the
other guidelines in this series, and the generic guidelines, these guidelines are mainly
intended for use by practising modellers with appropriate background; ie they are not a text
book.
It is emphasised that the procedure in the generic guidelines is intended to allow flexibility in
the way it is used, and this flexibility also extends to these guidelines.
1.2 Scope
These guidelines provide guidance relevant to modelling the practical implementation of
water sharing rules via river and dam operating rules and rules governing access to water.
They also provide guidance relevant to modelling the assessment of water availability (ie
resource assessment) and water use accounting procedures. However, the closely related
topic of modelling restriction trigger thresholds in storages (eg target curves) is covered in
the companion guidelines on storage modelling, and is outside the scope of these
guidelines.
eWater’s Guidelines for water management modelling (Black et al, 2011) describe a
procedure for quality assured model application which can be summarised as comprising
four phases:
1 Project management,
2 Problem definition,
3 Option modelling,
4 Compare options and select the most appropriate.
These guidelines deal mainly with Phases 2 and 3. From the point of view of modelling water
sharing rules, the generic guidelines provide sufficient information relevant to Phases 1 and
4, particularly as this activity is usually just one of several comprising a project as a whole,
and Phases 1 and 4 would be considered in more detail in the planning and undertaking of
the overall project. However, guidance on aspects of Phases 1 and 4 specifically relating to
modelling water sharing rules is provided, where the need has been identified, at appropriate
points in these guidelines.
Guidelines for modelling water sharing rules in eWater Source
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2 Procedure for quality assured
modelling of water sharing rules
2.1 Project administration
The guidance on steps in the Project Administration phase given in eWater’s Guidelines for
water management modelling (Black et al, 2011) adequately covers the requirements in
relation to modelling water sharing rules. Where this modelling is seen to be sensitive, the
guidance provided should be read from this perspective. This applies particularly to peer
review and stakeholder consultation, where needs in relation to modelling water sharing
rules could determine the needs for the project as a whole. These two aspects are discussed
further below.
Peer review
From the point of view of modelling water sharing rules, peer review should occur at a
number of steps, including (but not limited to):
• When setting up and building the model; involvement of peer reviewers is strongly
recommended as, amongst other things, it will facilitate peer review following model
calibration, validation and sensitivity/uncertainty analysis.
• Following model calibration, validation and sensitivity/uncertainty analysis; it is most
important that peer review is undertaken at this stage for establishing model credibility
and fitness for purpose.
• During the process of exploring options; involvement of peer reviewers is
recommended to give added confidence in the credibility of model results, especially
where results could be contentious.
• During the process of selecting the preferred option, peer review may be required,
particularly if this involves use of analytical techniques not subject to peer review at
other steps (such as multi-criteria analysis; MCA).
There are a number of specific points peer review should address, as appropriate. These
include considerations such as the degree of aggregation of water users, approaches
adopted for disaggregating water usage and other data, and the approach adopted for
representing existing water sharing rules in the model, and are relevant for scenario
analyses as well as for model calibration and validation. These would be additional to
considerations such as overall model set up, choice of calibration metrics, the scope and
quality of calibration and validation, and choice of metrics and criteria for use in selecting the
preferred option.
All these considerations are also relevant to establishing the fitness for purpose of the
model, and peer review can therefore make a valuable contribution to this. A necessary
Guidelines for modelling water sharing rules in eWater Source
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adjunct to establishing fitness for purpose is gaining stakeholder acceptance of the credibility
of the model and results it produces, and the importance of peer review in this context is
emphasised (ie the greatest value from the peer review process can be obtained if it is co-
ordinated within the framework of the stakeholder consultation process).
Stakeholder consultation
Stakeholder consultation is especially important when a project is socially or politically
sensitive, which is likely when modelling water sharing rules. Initiating consultation early in
the process will help allay possible fears of stakeholders and facilitate gaining their trust and
support for the modelling. It is important that stakeholder consultation occurs as follows:
• During the problem definition phase, particularly when developing the problem
statement, defining objectives and developing the conceptual model, and also when
deciding metrics and criteria, and decision variables.
• During the option modelling phase, particularly following model calibration, validation
and sensitivity/uncertainty analysis (and peer review) and during the development,
testing and exploring of options, but also when setting up and building the model.
• During the phase to select the preferred option, as stakeholder preferences could
have a major influence on the result of this phase.
Aims of stakeholder consultation should include developing confidence in the credibility of
the model and its impartiality (eg no hidden agendas in the model), the modelling approach
and the results with the objective of keeping technical aspects of the modelling separate
from politics. To achieve this there is a need for transparency: to be honest about the
limitations of model as well as its strengths, particularly about uncertainty, but without
unnecessarily undermining confidence in the modelling. This provides a path towards
gaining acceptance of the rules that are underpinned by the modelling. Hence, the necessity
for clear communication tailored to the audience, and for peer review.
However, while stakeholder engagement can have great benefits, the process of
engagement has to be carefully managed as it can be diverted by various interests. The
engagement process needs a strong educational component at the beginning and this has to
be continuing as stakeholder representatives may change during the process. Also, at
various stages there is a need for public engagement as sometimes information may not be
disseminated by the stakeholder representatives.
Workshops and other meetings with community representatives are potentially valuable
mechanisms for engaging with stakeholders. Walking stakeholders through the various
stages of the model setup, calibration and scenario running gives them greater
understanding of the model as well as an understanding of its accuracy and limitations.
These meetings may also be a useful source of data, as discussed in the section on Gather
and clean-up data below.
Discussions with stakeholders should emphasise that models are information tools
supporting water planners and only part of the process for arriving at a satisfactory solution.
Models provide the best information available at the time, but a process needs to be put in
place to allow model enhancements/improvements to better inform the process in the future.
Implementing water sharing rules should be an adaptive process.
Before any model is presented to stakeholders in the consultation process the model needs
to be stable and robust. Demonstrating and explaining baseline and scenario model results
Guidelines for modelling water sharing rules in eWater Source
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to stakeholders may be difficult enough without having to explain that numbers are changing
due to model upgrades or bug fixes. The same stable model should preferably be used
throughout the whole consultation process to maintain stakeholder confidence in the model
and the predicted outcome. However, while the software should be as stable as possible, the
stakeholder consultation process could lead to the discovery of new information that either
warrants or necessitates improving or correcting the model. In this situation, the effects of
changes in the model on the results should be explained to stakeholders so they can clearly
see what they are.
While the model should be stable and robust, there will still be uncertainties in model results
and these should be acknowledged and explained in communications with stakeholders,
even if this might prove to be difficult to do. This applies particularly where socio-economic
impacts could be severe: convincing stakeholders of the need for changes in this type of
situation can be difficult when there is significant uncertainty in the model results. Even if
stakeholders are keen to know the uncertainty in the modelling results they may not know
how to deal with it. These difficulties can be minimised, if not overcome, by combining
uncertainty analysis with a risk assessment which shows what the consequences of the
uncertainty are expected to be. This is discussed further in the sections on Uncertainty and
Risk and on Sensitivity/Uncertainty Analysis, below.
During scenario modelling, regular meetings enable stakeholders to critique results and
propose new scenarios to be modelled. In the interests of achieving constructive outcomes,
the aim should be to keep discussions focussed on what the results are showing rather than
arguments about the credibility of the model and the results in themselves. It also needs to
be ensured stakeholders understand the time and effort required to produce results,
especially in circumstances where code changes or other major changes are involved, and
expectations of what can be delivered in a given time frame need to be managed.
If public meetings are held, needs for transparency, establishing the credibility of the
modelling, clear communication tailored to the audience and keeping the modelling apart
from the politics, become even more important. While presentation of information is very
important, finding ways to put the model results in a form that is easy to understand by the
non-specialist can be a big challenge and, if necessary, expert advice should be sought on
suitable approaches. Skilled communication is also needed, especially when communicating
with the public, and the task should be assigned to someone with the appropriate skills, not
necessarily the modeller.
2.2 Problem definition
Problem statement
In river systems where there are water sharing rules already in place, problems requiring
modelling input may arise due to reasons such as:
• development of a new water policy;
• adjusting an existing policy; or
• modifying the way an existing policy is implemented, perhaps because it is not
meeting agreed objectives.
Guidelines for modelling water sharing rules in eWater Source
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The issues to be addressed usually revolve around questions of how to best manage these
systems within changing physical, social and economic constraints and the changing
demands of water users, including the environment.
Where new developments are being investigated, the problem could be a need to explore
options for water sharing rules to inform development of policies and procedures for
managing these new developments.
However, in either case, the specifics of the problem to be addressed from a modelling
perspective will almost certainly need to be discussed and confirmed with relevant
stakeholders, particularly the person or group commissioning the work.
Objectives
In existing regulated systems, and in unregulated systems where there are water sharing
rules already in place, the primary objective of a modelling study will very often be to define a
new set of water sharing rules or modifications to an existing set of water sharing rules.
Commonly, this will be driven by a new, or changed, water policy supporting an overall water
management objective, which might also be refined. However, this overall water
management objective will rarely be sufficient in itself as a modelling objective and, as a
general rule, it will be necessary to confirm the specific modelling objectives with relevant
stakeholders. The primary stakeholder will be the person or group commissioning the study.
However there may also be other interested or affected parties who will need to be consulted
during the process of defining the model objectives (eg river operators, water users,
environmental managers, etc).
When modelling new developments, modelling water sharing rules may not be the initial
objective and only a secondary consideration. Nevertheless, an appropriate objective or
range of objectives should be agreed with relevant stakeholders.
In either case, it might also be appropriate to consider possible secondary objectives. These
could include using the model to support a comparison of the performance of actual
operation of the rules with the expected performance, taking into account the effects of
climate variability during the assessment period. Other possibilities include using the model
to investigate potential climate change impacts and impacts due to other non-stationary
issues like changes in land use (farm dams etc), bushfires and groundwater.
In order to best define the modelling objective, an initial view of the form of the rules should
be developed. If there are existing rules, it may be appropriate to start from these and then
consider changes relative to the existing rules. The form of the rules should be linked to the
overall water management objective and cater for the needs of all water users, including the
needs of environmental assets, as appropriate. It also needs to be borne in mind that when
considering the form of the rules, this could also extend to water use accounting rules,
resource assessment procedures and trigger thresholds for restrictions, and possible
changes in these. This initial view will be the basis for developing modelling scenarios.
Understanding problem domain
This step involves identifying and agreeing with stakeholders, the range of disciplines that
needs to be considered to address the problem at hand. Potentially, the range of disciplines
relevant to modelling water sharing rules is quite wide.
Guidelines for modelling water sharing rules in eWater Source
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For example, when there is a mix of consumptive and non-consumptive water users, and the
scope of work includes consideration of environmental flow rules as well as water supply for
human needs (which could include urban, hydro-power, industrial, agricultural and
aquaculture), it may be appropriate to consult specialists in various aspects of aquatic
ecology in addition to obtaining advice from specialists on supplying water for human needs.
Input from economists and specialists on social acceptance and adaptation may also be
needed if effective outcomes are to be obtained and understood.
A similar situation applies when modelling of water quality is involved, which may require
consideration of dilution flow rules, interception schemes or flushing flows. Expertise on
water quality criteria and receiving water dynamics may need to be consulted if effective
outcomes are to be obtained and understood.
When modelling an existing regulated system, input from dam operators is essential to
understanding the practicalities of implementing water sharing rules and representing the
rules realistically in the model. Input from operators responsible for collecting or maintaining
information on water usage and accounts may also be required. These aspects are
discussed further in the section on data gathering and clean-up.
System definition
From the point of view of modelling water sharing rules, there are a number of particular
aspects to consider in the system definition step in addition to the points in the generic
guidelines. These include:
• In addition to its biophysical features, the system could encompass water
management policies, which could be in strategies, plans or legislation; water usage
recording and accounting systems; operating rules and real time operating decisions
in existing regulated systems; sociological and behavioural aspects (eg water user
practices); and economics.
• How individual water users are to be represented; what degree of aggregation is
appropriate, having regard to data reliability and privacy issues, amongst others.
• How environmental water holders are to be represented: whether each holder of
environmental entitlements will be represented individually or be combined as a
group having regard to availability of long term environmental watering plans.
• Constraints on availability of data on water usage, water user behaviour and
practices, water use accounts, and operating rules and practices, in existing systems.
• Ambiguities and uncertainties in water management strategies, policies, plans and
legislation, which need to be clarified eg “by a process determined by the Minister”.
On occasion it may be necessary to seek legal advice to resolve these.
• Differences between water management rules and how these rules are
operationalised within the system.
Conceptual models
As water sharing rules typically comprise a number of components, it is important that these
components and how they interact are understood and agreed between stakeholders, in
conceptual terms at least. As discussed previously in relation to defining objectives, not only
do these include elements of water sharing rules themselves but they also include the
Guidelines for modelling water sharing rules in eWater Source
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various elements of water use accounting rules, resource assessment procedures and
trigger thresholds for restrictions. Furthermore, as water sharing rules are rarely modelled in
isolation from other aspects of river system behaviour, it is important their conceptual model
is considered in the wider river system modelling context as well.
Metrics and criteria
The metrics and criteria adopted should be linked to the modelling objective, and should be
based on the initial view of the form of the rules developed when defining this objective. They
should also be linked to the overall water management objective and cater for the needs of
all water users, including the needs of environmental assets, as appropriate. Active
participation of stakeholders in deciding metrics and criteria should assist in gaining their
acceptance and support. Results from scenario modelling should be able to be compared
directly with the adopted metrics and criteria.
Many of the metrics used to demonstrate outcomes of the water sharing rules are presented
in terms of relative change (eg change relative to some base case). Given some of the
uncertainties (discussed in the section on Uncertainty and Risk, below) more confidence can
be placed in the relative difference in outcomes than the absolute numbers.
Relevant examples of metrics and criteria include reliability of water access, or supply, for
urban and irrigation water supplies. They also include performance requirements for
environmental flows such as the frequency and duration of inundation of wetland areas, and
durations of intervals between events.
When investigating changes in water sharing rules, relevant criteria might include allowable
changes in access to water by various categories of users, and deciding on these might
involve making trade-offs which some users are sensitive to. However, in some cases it may
not be possible to decide criteria such as these prior to modelling, and they may have to be
allowed to emerge during the process of exploring scenarios, which should enable the trade-
offs involved to be better understood.
When deciding on metrics and criteria, consideration should be given to the reliability of the
basis for these and sensitivity if they are not met to varying degrees. For example, if the
requirement is for a wetland to be inundated for 30 days every 5 years on average, but the
model results predict inundation occurring for only 29 days every 5 years on average, then
what are the consequences of this, and do they matter? However, if the duration is only 20
days, or 15 days, then how does the situation change? Similar considerations apply to urban
and irrigation water supplies.
Decision variables
Decision variables include any factors that stakeholders can adjust to influence the
performance of the system and, as such, are inputs to developing and modelling scenarios.
They are likely to be closely related to the metrics and criteria discussed in the preceding
section, which are evaluated after the model run. Agreeing on the values of decision
variables can be expected to involve making trade-offs, and the outcome could be expected
to affect the predicted performance of the system. Decision variables also impact on the
factors underlying the trade-off process, such as likely economic and amenity impacts due to
changes in reliability of urban and irrigation water supplies, and likely impacts on the health
of environmental assets due to changes in watering regime.
Guidelines for modelling water sharing rules in eWater Source
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Initially, decision variables may not be able to be quantified except in a preliminary way.
Results from scenario modelling may provide the understanding needed to support making
the trade-offs necessary and enable realistic quantification (some may never be able to be
quantified and it may be inappropriate to try, but it may be possible to define them
qualitatively). If this process leads to an outcome that is not satisfactory then it may be
necessary to review the decision variables and try again.
Uncertainty and risk
Uncertainty
In the context of modelling water sharing rules there are a number of sources of uncertainty
that are particularly relevant. These include:
• Limitations in quality of water use data. This applies especially to data on irrigator
behaviour and their infrastructure, but may extend to data for other categories of
water user as well; noting that behaviour and infrastructure may change over time. It
also applies to data on water use and water accounts, as this normally has to be
disaggregated where it is available. These limitations have implications for the quality
of calibration achievable.
• Ability to represent rules, whether existing or proposed, in the model. In addition,
where there are existing rules, there may be differences between the rules as
specified and actual implementation practices, and differences in the ways rules are
implemented from time to time. In practice, operators may make decisions on
occasions which are difficult to describe in terms that are suitable for modelling and
also operational practices may be affected by maintenance of infrastructure at
various times, possibly for quite lengthy periods.
In addition to model and data related sources of uncertainty, there is uncertainty relating to
the rules themselves; for example, that environmental flow rules will deliver the
environmental outcomes sought; that changing the access to water, and perhaps reliability of
supply, for all water users will have economic and amenity impacts as predicted.
More detailed guidance on uncertainty analysis is provided in separate guidelines on this
subject (Lerat et al, in prep).
Risk
Note: the standard definition of risk in AS/NZS ISO31000:2009 is “the effect of uncertainty
on objectives”.
With respect to risk, it is important to consider both the likelihood and potential
consequences of successful implementation of new or changed rules and also of
unsuccessful implementation. This should include consideration of social impacts as well as
economic and environmental impacts. When evaluating scenarios and identifying the
preferred option, trade-offs may be necessary to achieve a reasonable balance between
social, economic and environmental impacts. The process in Phase 4 of the procedure in the
generic guidelines is designed to support making better informed trade-offs.
Guidelines for modelling water sharing rules in eWater Source
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Preliminary assessment
The rationale for developing an initial view of the form of the required water sharing rules is
discussed earlier in the context of defining objectives. In addition, a preliminary assessment
of how these rules are expected to perform should be made, and this should be linked to the
agreed performance metrics and criteria.
2.3 Option modelling
Methodology development
Modelling water sharing rules is usually one activity within a wider project but, given this may
be the main reason the project is being undertaken, it may have a major influence on
decisions about methodology to be adopted for the project as a whole. However, this activity
cannot be considered in isolation and other factors, such as data constraints, may override
preferences for modelling water sharing rules. Where this occurs, compromises may have to
be made which will necessitate a less than desirable approach to modelling water sharing
rules. In this situation, it will be useful to document the implications of this for the expected
accuracy and reliability of results, if only in qualitative terms, so that stakeholders can clearly
see what these are. Assessment of uncertainty and sensitivity analysis (discussed in the
section on Sensitivity/uncertainty analysis) will be of help in this regard.
Gather and clean up data
The following discussion applies mainly to modelling water sharing rules in systems with
existing developments and rules. However, when modelling systems where there is currently
no development or water sharing rules, this discussion provides a potentially useful checklist
of points to consider for modelling water sharing rules.
Note that separate guidelines on data gathering and review in the context of Source are
proposed and these will give more comprehensive coverage of this topic.
Data types
Potential sources of data on water sharing rules include inter-jurisdictional agreements or
treaties, and water management strategies, plans, policies and legislation. These rules could
include the following, not necessarily independent, aspects (based on DERM, 2011):
• Water access rules and allocation policies;
• Flood control rules;
• Release rules: irrigation, industrial, urban, hydropower, environmental, recreational;
• Diversion rules;
• Water transfer rules;
• Security of water supply requirements for various categories of water users
(potentially, including the environment);
• Rules defining storage carryover volumes and reserves to be held;
Guidelines for modelling water sharing rules in eWater Source
11
• Allowances for transmission losses, such as evaporation and seepage losses, and
gains such as downstream tributary inflows;
• Restriction rules and supply capacity constraints;
• Rules for operation of fish passage devices; and
• Inter-jurisdictional agreements or treaties, and other strategies, plans, policies and
legislation.
Information on procedures used to implement water sharing rules in real time should also be
collected. In particular, information should be sought from dam operators as implementation
of rules in practice may differ at various times from the formal rules. Dam or system
operators are also valuable sources of information on how practical proposed changes in
rules, or new rules, are going to be operationalised.
Information on water user accounting systems, such as annual accounting, continuous
accounting, capacity sharing and continuous sharing is needed as accounting systems
affect, and are affected by, the rules. Information on release calculation methods is needed
as well.
For purposes of model calibration and validation particularly, data is needed on water use
volumes and patterns, how these are affected by water user decision making, and the
factors influencing these decisions. Relevant factors could include:
• Allocation announcements (where used);
• Allocation carryover rules and actual carryover volumes;
• Status of individual accounts and the rules for operating these accounts;
• Water ordering procedures;
• Whether off-allocation water is available or not;
• Temporary and permanent water trades;
• Water user licence conditions;
• Crop areas and crop types planted;
• Water user infrastructure;
• Antecedent conditions;
• Relationships between storage volume, seasonal forecasts, minimum inflows (where
used) and the announced allocation;
• Expectations (forecasts) of future water availability (amongst other things, these can
influence risk taking behaviour of water users), and
• Other potential drivers of risk taking behaviour of water users, including hydrological
characteristics such as seasonality and reliability of flow, level of security of supply
required, whether perennial or annual crop (in the case of irrigators).
Insight into how these might change when modelling scenarios is needed as well.
Other policies, plans, strategies and legislation not directly related to water management
may also have a bearing on water sharing rules, and these need to be sought out and their
implications understood. These could include national and social development plans, primary
industry policies, and biodiversity protection strategies.
Guidelines for modelling water sharing rules in eWater Source
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Data sources
The main sources of data are usually the responsible water management and operating
agencies. Potential sources within these agencies include licensing databases, hydrographic
data databases, water use billing systems, records from water use accounting and water
ordering systems, plans and drawings of infrastructure, policy and other related documents
and files, policy staff, operating staff, and field staff such as metering inspectors and
advisers.
Other agencies and organisations may also be sources of data. These could include an
environmental management agency, which might have a compliance role and also have a
role in rule setting, such as for environmental flows or water quality management; this
agency may also be a source of data on aquatic environmental assets. Agriculture agencies
are another potential source of data, with respect to irrigation enterprises, as are local
government and water utilities, and agencies collecting national data (such as the Australian
Bureau of Statistics and the Australian Bureau of Meteorology).
Water users are valuable sources of information on their infrastructure and how they use it,
although some users may have privacy issues. Obtaining information on a confidential basis
may overcome these concerns, but this will depend on a level of trust being established with
the users. It may be easier for some water users to provide data if they can be assured they
will be grouped for modelling, and it will not be possible to identify individuals in the results.
Stakeholder consultation is one way of achieving the level of trust required (but not
necessarily the only way); individual meetings and questionnaires are among potentially
suitable techniques to use for obtaining the data.
Data quality issues
Some issues with data quality are:
• Practices associated with day-to-day operation of storages are often poorly
documented and can only be ascertained through direct communication with the
operators.
• River system models often require water usage and accounting data at smaller time
steps than has been collected. Therefore, the data has to be disaggregated, as
discussed below.
• Where water usage is metered, the data may be subject to large errors related to
meter type and age, and also due to variations in the head (water level) in the river.
For example, where diversion is by pumping, pumps become less efficient at low
heads (water levels) and, if metering is based on counting pump revolutions or
energy use, this can lead to usage being overestimated. Where sufficient data on
metering accuracy exists, water usage data should be adjusted accordingly in order
to ensure correct representation in the water balance. Where water usage is not
metered, surrogate data should be sought. For example, for irrigation water usage a
suitable surrogate may be crop area data together with a pro-rata allowance of water
per unit area of crop; while for urban water usage a per capita allowance may be
suitable, with adjustment for commercial and industrial purposes.
• There might be reliability issues with data obtained from water users, especially if it is
obtained by questionnaire, and it should be ground-truthed where possible. Remote
sensing can provide a useful means of independent verification of some data
Guidelines for modelling water sharing rules in eWater Source
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supplied by water users, such as irrigated crop areas and on-farm storage
characteristics, although remote sensing techniques may fail to distinguish irrigated
crops from dryland crops and limitations in remote sensing imagery frequency and
resolution may constrain accuracy. Other data types, such as pump capacities, may
be able to be cross-checked with data held by the water agencies.
Data disaggregation approaches
Data sets relevant to modelling of water sharing rules which may require disaggregation
potentially include water usage data, water account data and water order data; used in
model calibration and validation. While these types of data might be collected on a
continuous basis (eg for major canal diversions), very often the data is collected at longer
intervals which may range from monthly, to 3 monthly and up to annual.
There are many techniques available for disaggregation. However, irrespective of the
technique chosen, it should be borne in mind that, as disaggregation typically involves
imposing an assumed pattern on the raw data to provide data at the required time interval,
model results may be sensitive to the disaggregated pattern adopted and this may affect the
quality of model calibration and validation achievable. If this is a concern then the sensitivity
could be checked by disaggregating using a different pattern and comparing results obtained
with the different patterns. Sensitivity to the disaggregation pattern can be a particular
problem when usage is driven by flow events (eg off allocation extraction into on farm
storages).
Care also needs to be taken to ensure the disaggregated pattern is not distorted by errors in
the data used to derive the pattern. For example, if residual flows between two gauging
stations are being used as the basis for deriving a daily pattern for water usage data
(recorded, say, monthly) then there are several potential sources of error that should be
considered. These include instrumentation errors, groundwater/surface water interactions (ie
transmission losses or gains) and residual catchment inflows.
One potentially useful approach to minimising the problem of errors is to calibrate the model
for pre-development conditions and use the results to evaluate unaccounted differences.
Allowances can then be made for these differences in the disaggregation methodology.
However, it needs to be recognised that the unaccounted differences may be subject to
change due to data non-stationarity issues, discussed below.
Data non-stationarity issues
Factors directly relevant to modelling water sharing rules (ie calibration and validation) which
can cause non-stationarity include:
• Pattern of diversions: eg growth in urban water demands, growth in areas developed
for irrigation, changes in farm infrastructure, such as growth in on farm storage
capacity which could especially impact on unregulated diversions, change in irrigation
efficiency, change in type of crop and season planted.
• Changes in farmer behaviour. Experience shows there are differences in farmers’ risk
behaviour after a drought compared to their behaviour after a series of wet years.
Planting behaviour is also liable to change when new varieties of a given crop are
introduced, in addition to changes due to a change in crop type.
Guidelines for modelling water sharing rules in eWater Source
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• Changes in water accounting arrangements, and changes in water sharing rules
affecting dam release patterns.
• Consequent changes in transmission loss regime.
• Development / upgrading of major infrastructure such as dams.
• Geomorphological changes, such as changes in braided channel systems due to
floods, changes to constraints through structural works or land purchase, and
groundwater level changes affecting transmission losses and gains.
• Land management and use changes, including effects of forest growth, bushfires and
recovery from these, development of farm dams and other interception schemes in
catchments.
• Climate change, and medium term climate variability cycles (say, 30 years or longer
in duration).
• Instrumentation changes.
Growth in use, infrastructure and operational changes may be readily accommodated in
model calibration and validation, but adjusting for changes such as transmission losses may
require use of change detection techniques (Kundzewicz and Robson, 2004; Radziejewski
and Kundzewicz, 2004; WMO, 2009; Yue and Pilon, 2004).
Setting up and building a model
The important point to consider in this step is that the model should be able to simulate any
existing and past water sharing rules, needed for model calibration and validation, and also
be able to simulate anticipated scenarios for new rules, as far as these can be reasonably
foreseen. It should be possible to anticipate likely scenarios to at least some degree when
defining objectives and during the preliminary analysis step. However, it is acknowledged
that often unforeseen scenarios will emerge which, if they are to be analysed, will
unavoidably entail changes to the model set up and may possibly entail changes to the
model code, or new or changed plug-ins, as well.
The model structure needs to take into account requirements for modelling water users and
water use accounting systems as well as water sharing rules. Requirements for modelling
water users, such as how they are grouped, should come from the system definition and
methodology development steps but they may need to be revisited when setting up the
model. Other elements of water sharing rules, such as off-allocation systems, may have a
bearing on the approach adopted to grouping water users (here the term “off-allocation”
refers to access by water users to flood and other flows in excess of ordered water, and
deemed to be in excess of replenishment and environmental needs, which is additional to
their allocated water entitlement). In some cases, external factors, such as socio-political
considerations, may override technical considerations and a particular level of aggregation
which cannot be justified solely on technical grounds may have to be adopted.
In existing regulated systems, the model needs to adequately (realistically) represent current
operating practices, and operational characteristics (eg behaviour of re-regulating storages,
allowances for transmission losses, etc) and constraints (eg channel capacity); and also how
these might change in response to changes in water sharing rules. For modelling new
developments, potential operating constraints and how to represent these should be
considered. If the model is well set up then it should enable potential new rules to be
represented in a way that lends itself to practical implementation (and if proposed new rules
Guidelines for modelling water sharing rules in eWater Source
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cannot be realistically represented in the model then this may raise questions as to whether
they can be implemented in practice).
Calibrate model
The extent of calibration needed or possible when modelling water sharing rules will depend
on whether there are rules already in existence or not; and if there are existing rules, to what
extent they are relevant to modelling proposed changes or new rules. Key points are:
• If the modelling software does not allow for aspects such as water sharing rules and
water supply infrastructure to vary within a model run, then calibration and validation
in the traditional sense (ie comparing modelled data against observed data for a
different period than used to calibrate the model) are possible only when rules have
been in place for some time; and this is typically rare.
• There may be differences between the way rules are operationalised and the way
they are specified in a policy or plan; in this situation, calibration and validation should
be based on operational practice. The rules as specified in a policy or plan could then
be modelled as a scenario and results compared, if desired.
• Data available for calibration and validation may not be representative of the range of
hydrologic and water availability conditions that could occur, which will limit the
quality of calibration and validation achievable, and the confidence that can be placed
in model results.
• Most of what is practicable relates to sensitivity analysis, rather than calibration and
validation, which is discussed in the section on Sensitivity/uncertainty analysis.
• Sensitivity analysis includes making checks to ensure rules in the model are
operating as intended; this applies whether calibration and validation are possible or
not, and applies to the modelling of new rules (scenarios) as well. The analysis
involves ensuring all aspects of the rules are activated which will necessitate pushing
the model to simulate both wet and dry extremes.
• When calibration is possible, it is likely to entail iterating between the Calibrate model,
Validate model and Sensitivity/uncertainty analysis steps.
Considerations relevant when calibration is possible are discussed below, mainly in the
context of calibration of the model as a whole.
Where there are no existing rules, or rules that are relevant to modelling proposed changes,
calibration for rules is not possible but the issues discussed below should be taken into
account when translating representations of rules in models to rules able to be applied in
practice.
When modelling a system with existing water sharing rules, and calibrating the modelling of
these is part of a larger calibration exercise for a river system model as a whole, it is likely to
take place late in the calibration process, after the calibration of physical characteristics such
as routing and the storage water balance (using observed historical inflow and release data).
Cumulative errors in the calibration results from these earlier steps may have an adverse
effect on the quality of calibration achievable for modelling water sharing rules. Adverse
effects can be minimised by adopting a staged calibration strategy, starting with calibrating
demands and water user behaviour using historical storage releases, operating
rules/practices and flow data, allocation/off-allocation data and water account data.
Guidelines for modelling water sharing rules in eWater Source
16
The next step would be storage behaviour calibration, with releases no longer forced, which
is the step where water sharing rule calibration typically occurs. Values of parameters used
to represent water sharing rules may need adjusting from initial estimates to enable storage
behaviour to be adequately reproduced.
To get the best results, advice should be sought from river operators and field operatives on
results obtained compared to actual storage behaviour and the reasons for, and significance
of, differences between them. If operating practices are significantly different from specified
rules then it may be necessary to calibrate using operating practices, and treat modelling of
the specified rules as a scenario, supported by sensitivity analysis as discussed in the
section on Sensitivity/uncertainty analysis below.
Other parameters requiring adjustment could include over order factors (used to represent
operator and water user behaviour: operators sometimes release more water than is strictly
necessary and water users sometimes inflate their orders as well, both aiming to ensure
there is no shortfall in deliveries), parameters used in representing re-regulating storage
behaviour and parameters used in representing water ordering, water allocations and off-
allocation periods (when water used is not debited from accounts). During storage behaviour
calibration, it may be convenient to initially force some of these to historical values
(particularly water allocations and off-allocation periods) and then progressively allow them
to be simulated, as a means of unpacking the influences of the various parameters on the
calibration. However, this approach will not avoid the necessity to revisit and fine tune the
calibration of other parameters initially calibrated while these ones were forced to historical
values.
Model responses should be evaluated for periods when there are no water orders as well as
for periods when there are water orders (DERM, 2011), where the presence or absence of
water orders could be a function of time of year (eg whether in the irrigation season or not) or
seasonal conditions (ie whether wet or dry), or a combination of these.
There may also be interaction with values of parameters representing aspects of water user
behaviour, such as risk taking. The approach adopted of aggregating water users may have
a bearing on the extent and nature of adjustments needed as well. Hence, further adjustment
of the demand calibration may prove to be necessary during storage calibration. However, it
is unlikely there will be a need to adjust values of parameters representing water use
accounting rules.
In unregulated systems, water sharing rule calibration will have to be undertaken at the same
time as demand calibration. Staged calibration is not possible as there are no regulating
storages involved.
When interpreting results it is especially important that modellers should:
• have a sound understanding of how the model is working;
• be able to identify any results that appear to be counter intuitive and understand
whether they are valid or not; and
• where counter intuitive results are valid, be able to explain and document the
reasons.
As with calibration and validation of all models, representative periods of record should be
chosen for water sharing rule modelling calibration and validation whenever possible.
However, when calibrating for water sharing rules, the choice is often constrained by data
availability limitations. In addition to data availability, points to consider include:
Guidelines for modelling water sharing rules in eWater Source
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• Relevance as a baseline for modelling, which relates to the non-stationarity issue
discussed in the section on Gather and clean up data.
• Diversity in resource availability and total water usage
• Related to climatic variability, the model should be tested over periods with
varied water availability and water usage levels whenever possible.
• For example, during a wet period there may be plenty of water available but
water usage will be low if rainfall exceeds irrigation demand. High water usage
may occur early in a dry period, when there is still adequate water available, but
when resources become limited water usage will be low.
The goodness of fit between modelled and recorded data should be evaluated using a
number of comparative statistics (and definitely more than one), which could be the same as
usually used when calibrating other aspects of the model. Where the water sharing rule
calibration and validation is based on disaggregated data, the period used in the statistics
should be no shorter than the interval at which the data is collected. In other words, if water
usage data is collected at three monthly intervals, for example, then three monthly statistics
or statistics for a longer period (eg annual) should be used.
Validate model
As stated in the generic guidelines, it is important to recognise that validation is a test of
usefulness, not truth (CREM, 2008; Oreskes et al, 1994; Silberstein, 2006); ie “verification”,
which is a test of truth, is not logically possible.
Validating the modelling of water sharing rules using independent data is not often possible
or worthwhile, and validation will have to rely on sensitivity analysis. If the independent data
is for rules that are identical to the rules that applied during the calibration period, but the
hydrological conditions are different, then using this data for validation is likely to be
valuable. If the only independent data available is for a period when the rules are different
then this is unlikely to be helpful for validating the modelling of water sharing rules (although
it may well be useful for validating other aspects of the modelling) and validation may have to
rely on peer review and interaction with stakeholders to gain acceptance and assurance that
the calibrated model is working correctly. Peer review and interaction with stakeholders
should occur in any event.
Sensitivity/uncertainty analysis
As indicated in the section on Calibrate model, sensitivity analysis is essential for ensuring
water sharing rules, as represented in the model, are operating as intended. The important
aspect to check is how the rules as modelled perform under extreme conditions, especially
extreme dry conditions, but also under very wet conditions; whether modelled behaviour is in
accordance with expectations. Amongst other reasons, this can provide valuable insight into
how water management can be expected to work under these conditions; it also provides
insight into uncertainties in model results. Failing to check this behaviour can lead to
problems, particularly when modelling scenarios where the extremes may become more
common, such as when modelling climate change scenarios. Specific points include:
1 Rules as prescribed in relevant planning documents (such as water policies) and as
implemented in practice, and differences between them need to be captured; whether
Guidelines for modelling water sharing rules in eWater Source
18
both need to be modelled may be contingent on the extent of the differences and on
overall project objectives.
2 It should also be borne in mind there may be uncertainties in implementation in
practice due to factors such as scheduled and unscheduled maintenance of
infrastructure, and ad hoc operational decisions.
3 Performance should be evaluated in going from wet conditions to extended drought;
that is, performance as the system is modelled to run out of water needs to be
evaluated, even if an artificial input data time series has to be created to achieve this
(eg an extended period of zero inflows).
4 The priority order (hierarchy) with which supplies to different classes of water users
are restricted and then cease as the system dries off may need to be considered. For
example, the relative priority between general security and high security users is clear.
However, there may also need to be priorities set, and modelled, between different
classes of high security users (eg supply for critical human water needs is likely to
have higher priority than high security irrigation supplies).
5 Results may be sensitive to the distribution of resources between storages. For
example, where a system wide allocation is made considering resources in a number
of storages but supplies to part of the system are restricted by low levels in a particular
storage.
6 Results may be sensitive to changes in assumptions about initial conditions, especially
in storages, and performance for a range of starting conditions should be checked.
7 Alternative sequencing of extremes, especially dry extremes in the context of water
sharing, should be considered for a number of reasons, including:
a) Performance behaviour if there is a drier sequence than the worst on record
should be evaluated, if only to support planning for this eventuality. This might
include consideration of rights to water in dead storage even though storages
may not have reached such low levels historically.
b) Rules should not be fine tuned to a single sequence, as the future will almost
certainly be different.
c) Wet sequences should be evaluated to investigate whether there is a point
where the rules become inconsequential, and the potential consequences of
this.
d) Likely effects of seasonality changes can be investigated; particularly if the
system is at risk of changing from being perennial to ephemeral. Effects may
include changes in transmission losses, which might cause the loss allowance
to become inadequate, and changes in water delivery patterns for water users,
including the environment.
e) Security of supply criteria may be sensitive to factors such as the severity of
exceedance of a threshold (eg for water quality), durations of events (whether
high or low flow or water quality events) and intervals between events as well as
probabilities of occurrence of events, even if they are not couched in these
terms. For example, for a general security supply a requirement might be to
supply the full allocation in 60% of years, but the consequences for water users
if the supply fails in five consecutive years might be very different to the
consequences if the supply fails in five individual years, each separated by a
number of good years. In the case of a water quality threshold, exceeding the
Guidelines for modelling water sharing rules in eWater Source
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threshold by 10% for a short period may be of little consequence, but if it is a
long term persisting exceedance the consequences might be severe; also the
intervals between short term exceedances might have a bearing on the nature
of the consequences.
f) Estimates of the probabilities of events will be more reliable if multiple
sequences are generated than if a single sequence is used, and the
uncertainties surrounding these estimates can also be evaluated. The
uncertainty results will provide information on the confidence, and confidence
intervals, associated with the probability estimates.
8 The above points provide the basis of a risk management approach to water
management.
9 When evaluating the results of these sensitivity analyses, the detail and intent of the
underlying planning document (or draft, as appropriate) should be checked for
consistency with those results; noting that planning documents often do not go into
details, especially in relation to management expectations under extreme conditions.
More detailed guidance on uncertainty analysis is provided in separate guidelines on this
subject (Lerat et al, in prep).
Develop, test and explore options
As indicated in the generic guidelines, this step should be undertaken in consultation with
stakeholders, as discussed in the section in these guidelines on Stakeholder interaction,
supported by appropriate levels of peer review as discussed in the section in these
guidelines on Peer review.
Scenario modelling should include evaluation of predicted performance under extreme
conditions as a matter of course, as discussed in the section on Sensitivity/uncertainty
analysis above.
Options investigated should be realistic, ie if adopted they can be implemented in practice.
Representation in the model needs to be realistic and options should not be too finely tuned
to the particular characteristics of the input data sets used, especially the time series data, in
terms of their modelled performance (sensitivity analysis should help avoid this). If realistic
representation of a scenario entails a change in the model then the calibration and validation
of the model as a whole should be checked; this is especially important if the model code is
changed.
Absolute values from scenario modelling results may have a high level of uncertainty but
results from one scenario relative to another, or to a baseline case, may be more reliable
and therefore meaningfully compared. Interpretation of results should be cognisant of this
and, where possible, quantitative analysis should be used to determine whether the model
has enough resolution to compare impacts of management scenarios. For example the
signal to noise ratio (Bormann, 2005) or comparison of confidence intervals could be used.
Reporting and communication of scenario results
A number of points relevant to reporting or otherwise communicating the results of scenario
analyses for water sharing rules are discussed in the section on Stakeholder Consultation,
above. More general points are discussed in the section on Report/communicate scenario
analyses in the generic guidelines.
Guidelines for modelling water sharing rules in eWater Source
20
The required outputs from scenario modelling will be application specific. Generic statistics
such as averages over the simulation period may be somewhat informative but, following on
from the points discussed in the section on Sensitivity/uncertainty analysis above, in many
cases a sufficient understanding of impacts or outcomes requires more detailed reporting of
model results.
For example, a useful way of presenting results for reliability of supply is by using a reliability
plot which shows water allocated as a percentage of entitlement versus percentage of water
years modelled this allocation is equalled or exceeded (eg see Figure 1). However, as this
plot uses ranked data, similar to a flow-duration curve, all information about sequencing is
lost and additional plots and tables are needed if information on sequencing is to be
provided. These might include time series plots and tables or charts of statistics of
exceedance events and intervals between events, amongst other things.
Figure 1: Sample plots for showing reliability of supply results
Much the same situation applies when exceedances of thresholds are of interest. Results
could be presented in the form of exceedance severity-frequency and duration plots (similar
to rainfall IFD plots), as illustrated in
Figure 2, with confidence limits added if required; box and whisker plots are another useful
means of presentation. However, as these also lose information about sequencing, they
would have to be supported by additional plots and tables or charts to provide this
information.
Guidelines for modelling water sharing rules in eWater Source
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Sample curves for given threshold values Sample curves for given event durations
Figure 2: Sample plots for presenting threshold exceedance probability results
Further points to consider include:
• The hydrologic data sequence, or sequences, used as input to the modelling may
contain a number of predominantly wet spells and a number of predominantly dry
spells of various durations. If relative impacts vary markedly between wet and dry
spells the results for these spells should be reported separately in addition to the
overall results.
• Results of sensitivity analyses should be presented as well as results of scenario
analyses.
• Any apparently anomalous results should be presented and the reasons for them
explained. Apparent anomalies can occur for a variety of reasons when analysing
and comparing scenarios. For example the rules in one scenario might cause the
storage to be modelled as falling below a critical threshold or, conversely, to spill, at
one point in time whereas in another scenario this does not happen; but if the rules or
the storage behaviour are sensitive to this difference then the impacts may be
disproportionate.
Model acceptance
The generic guidelines state that model acceptance means gaining acceptance the model is
fit for purpose. Therefore, gaining model acceptance and understanding what the term “fit for
purpose” means in practice is essential for modelling water sharing rules and for minimising
the potential for controversy that may surround this activity.
Importantly, it may be the case that it is necessary to accept a model which is less than ideal
because limitations in data availability, or other constraints, prevent doing any better.
However, provided the model can be demonstrated to be useful within the constraints that
apply, and subject to caveats about accuracy, then it may still be seen to be fit for purpose.
This may be especially true if the model is demonstrably the best achievable under the
circumstances.
Guidelines for modelling water sharing rules in eWater Source
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There are a number of criteria relevant to modelling water sharing rules that could be
assessed to determine whether a model is suitable for its intended purpose. Preferably the
metrics used should be quantitative, such as the comparative statistics for evaluating the
model calibration, but where this is not possible, qualitative measures should be used.
Directly assessing fitness for purpose for modelling water sharing rules will only be possible
when there are existing rules to test against. By using model results to evaluate how well
existing rules are operating as intended (discussed in the section on Sensitivity/uncertainty
analysis above) the fitness for purpose of the model can be established. As this involves
comparisons with policy or other water management documents, depending on the level of
detail in these documents, this assessment is likely to require use of qualitative measures
rather than quantitative metrics. When there are no existing rules to test against only indirect
assessment is possible. Sensitivity analysis results may assist in this situation, although
sensitivity itself is not an indication of model fitness.
Regardless of whether qualitative or quantitative metrics are used, they should not be used
in isolation to evaluate fitness for purpose (in isolation, failure to meet these may not
necessarily be an indication that the model is not fit for purpose, nor would success in
meeting them necessarily be an indication that the model is fit for purpose). The evaluation
should also consider criteria for assessing the fitness for purpose of the overall model. These
criteria include:
1 Does the model replicate historical data sufficiently well for important flow, storage or
water usage characteristics? The definition of sufficient needs to be considered with
respect to the model use and alternative sources of information. For example, if the
water sharing rules are highly sensitive to an absolute prediction then the highest
accuracy is required. A comparison of relative impacts between scenarios needs to
consider whether it is valid to compare expected values or if the prediction probability
density function needs to be compared. For the latter, it will be necessary to have
relatively low uncertainty (noise) compared to the signal due to management impact
being examined (Bormann, 2005).
2 What confidence can be placed on the model calibration, validation and
sensitivity/uncertainty analysis? Where these are based on a satisfactory length and
range of data (including extremes such as floods and extended droughts), and where
the data is of good quality, then the diagnostic results should be reliable.
3 Is prediction uncertainty evaluated, and are the methodology and results acceptable?
4 Where required for evaluation of management scenarios, does the model include
sufficient flexibility to be easily adjusted to simulate the required scenarios? Is the
required data and expertise appropriate?
5 Are the parameter values and internal fluxes physically realistic? Are they applicable
to scenarios anticipated to be modelled?
A possible approach to assessing fitness for purpose would be to express the performance
criteria as targets and use them to determine a performance class (where Class 1 is the
best). Each performance class would have reliability and accuracy caveats associated with
it, and the model would be assessed as being “fit for purpose subject to the caveats that
apply”, regardless of performance class (if the model did not meet the criteria for the lowest
performance class then this would be indication that the model is too unreliable to be useful
and therefore not fit for purpose). An example of such an approach has been adopted for
assessing the fitness for purpose of models under the Basin Salinity Management Strategy
for the Murray-Darling Basin (Murray-Darling Basin Commission, 2005; Appendix 2.5).
Guidelines for modelling water sharing rules in eWater Source
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If a model fails on any one of the criteria then it would be downgraded to the next lower
performance class. However, specification of simple thresholds may be too strict, and it may
be appropriate to include a tolerance allowance. If one target is not met the model does not
get downgraded as long as the failure is not too severe but if more than one is not met then
the model is downgraded irrespective of the severity of the shortfall. What is meant by “not
too severe” would have to be defined. For example, the target value of the coefficient of
efficiency could be 0.8 or better, and the tolerance allowance could be 0.05. Where this
target is the only one not met, the model would not be downgraded unless the coefficient of
efficiency was less than, say, 0.75. The target could also be expressed in terms of a range of
values if required (eg for Class 1, the calibration period should not be less than 10 to 20
years).
This approach would have the advantage of accommodating the situation where data
availability limitations constrain the overall quality of the model achievable, while also making
it clear where the model is constrained and why. It also avoids the need to set criterion
weights and the consequent potential to disguise poor aspects of model performance.
2.4 Compare options and select the “best”
Information on this subject is provided in eWater’s Guidelines for water management
modelling (Black et al, 2011). Some additional points, relating to criteria on which the
selection of the preferred options could be based, are in the next section.
Option selection criteria
Many of the metrics and criteria relevant to modelling water sharing rules also have potential
application in a decision making process to select the preferred option. Quantitative
measures such as reliability of water access, or supply, criteria for urban and irrigation water
supplies, and criteria for environmental flows are potentially useful for defining objective
functions for optimisation. These measures may also be useful with MCA, either used
directly or converted into more qualitative measures (eg measures of environmental health –
good, fair or poor).
Ultimately, selecting the best or preferred water sharing rule option will come down to a trade
off process. There are very few water sharing rules that do not have some adverse impacts
on something or someone. The skill is to find a solution that all impacted parties are
prepared to accept and have implemented. Any implementation process needs to be
followed up with a monitoring and auditing process that can assess the benefits from the
water sharing rules and if needed fine tune the water sharing rules in the future.
Guidelines for modelling water sharing rules in eWater Source
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3 References AS/NZS ISO31000:2009. Risk Management – Principles and Guidelines. Standards
Australia and Standards New Zealand. ISBN 0 7337 9289 8.
Black, D.C., Wallbrink, P.J., Jordan, P.W., Waters, D., Carroll, C., and Blackmore, J.M.
(2011). Guidelines for water management modelling: Towards best-practice
model application. eWater Cooperative Research Centre, Canberra, ACT.
September. ISBN 978-1-921543-46-3.
Bormann, H. (2005) Evaluation of hydrological models for scenario analyses: Signal-to-
noise-ratio between scenario effects and model uncertainty. Advances in
Geosciences, 5: 43–48. Available at: www.adv-geosci.net/5/43/2005/adgeo-5-
43-2005.pdf.
CREM (2008) Guidance on the Development, Evaluation and Application of Environmental
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