Using Water-Sensitive Urban Design to

improve drainage capacity

Examination of the impact of distributed and catchment scale Water -Sensitive Urban
Design systems on flow frequency

Bachelor Thesis
Executed May – August 2014

Course name: Bachelor Eindopdracht

Course ID: 192284108
Student name: Robin Noordhoek
Student ID: s1071874
Date: 01-09-2014

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Abstract
Commissioned by the Centre for Water Management and Reuse, located in Adelaide, South Australia,
this research was carried out to examine the impact of distributed and catchment scale Water-
Sensitive Urban Design systems on runoff flow frequency.

Currently, Greater Adelaide’s water supply for drinking and non-drinking purposes falls short of the
demand. This shortfall will only increase in the future due to rising demand and diminishing resources
if the South Australian Government does not undertake action. Also, the ratio of infill to fringe
development for new housing will shift to a more infill-orientated ratio in Adelaide. This increased
dwelling intensity poses challenges to infrastructure in the existing urban environment of the Greater
Adelaide region. Amongst other things, this means that metropolitan catchment areas where infill
development takes place will be likely to experience changes in stormwater runoff flow regimes.

One of those areas is the Frederick Street catchment, a 44.7-Ha urban catchment which is the study
area of this report. Building a new drainage system for the entire catchment is an expensive and time-
consuming solution which will also cause a lot of nuisance. This is why alternative approaches are being
taken into consideration. Water Sensitive Urban Design seems a promising solution to the problem.
Therefore, it has to be investigated if Water-Sensitive Urban Design can be applied in the catchment
area in order to reduce the effects caused by infill development on flow frequency. The research can
contribute to the understanding of the impact of infill development on a medium sized urban
catchment. It is important to understand the impact of infill development and how to overcome these
impacts with WSUD tools. This might lead to sustainable solutions which do not involve drastic and
costly adjustments to urban drainage systems.

The objective of the project is to determine suitable WSUD measures for the catchment by producing
an updated version of the catchment model using flow data being collected since August 2013. The
existing model was updated and then calibrated. When the model was calibrated, the use of several
suitable WSUD measures were simulated on the catchment to view their effect on flow frequency.

The results of the simulation show that the total volume of runoff increases by 12% (and an average
increase of 11% in peak flows) if no action is undertaken. The use of rainwater tanks and/or
bioretention systems within the catchment can be effective to maintain the current flow levels, or even
decrease the runoff flows and volumes.

It was found that Water-Sensitive Urban Design can be used to preserve the existing flow regimes of
the Frederick Street catchment. For street scale WSUD measures, rainwater tanks and bioretention
systems are showing promising simulation results for reducing runoff volumes and peak flows. The
most effective way of reducing runoff volumes seems to be the installation of rainwater tanks. Peak
flow reduction on the other hand can be achieved by both rainwater tanks and bioretention basins.
Although bioretention basins achieve a higher overall reduction of peak flows, it should be noted that
for very extreme storm events they are not capable of significant peak flow reduction.

Therefore a mix of both small rainwater tanks for all houses and bioretention basins seems to be the
best option for preserving the flow regimes in the Frederick Street catchment. Another option, which
does not need the construction of bioretention basins is to connect every house in the catchment to
a bigger (e.g. 5 kL) rainwater tank.

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Foreword
This report is the outcome of my internship at the Centre for Water Management & Reuse at the
University of South Australia. The project was conducted as the final part of my Bachelor in Civil
Engineering. It allowed me to apply my previous experience in the field of Civil Engineering on water-
related issues at the Centre for Water Management & Reuse. Moreover, staying in Australia for three
months proved to be an excellent opportunity to improve my communication skills in English.

I would like to thank Dr. Baden Myers, my supervisor at the Centre for Water Management & Reuse,
and Mr. David Pezzaniti, my co-supervisor at the Centre for Water Management & Reuse, for all their
advice, help and guidance during my assignment. I would also like to thank Dr. Marcela Brugnach, my
supervisor at the University of Twente, for her supervision and advice and Ms. Ellen van Oosterzee for
helping me with the visa application.

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Table of Contents
Abstract ................................................................................................................................................... 2
Foreword ................................................................................................................................................. 3
List of figures ........................................................................................................................................... 5
List of tables ............................................................................................................................................ 5
1 Introduction ..................................................................................................................................... 6
1.1 Problem definition................................................................................................................... 6
1.1.1 Introduction ..................................................................................................................... 6
1.1.2 Water Management in South Australia........................................................................... 6
1.2 Research design ....................................................................................................................... 6
1.2.1 Centre for Water Management and Reuse (CWMR) ...................................................... 6
1.2.2 The study area ................................................................................................................. 7
1.2.3 Research objective .......................................................................................................... 8
1.3 Research questions.................................................................................................................. 8
1.4 Research methods ................................................................................................................... 9
1.5 Importance of the research ..................................................................................................... 9
2 Theoretical context ....................................................................................................................... 10
2.1 Water-Sensitive Urban Design (WSUD) ................................................................................. 10
2.1.1 What is Water-Sensitive Urban Design? ....................................................................... 10
2.1.2 Water-Sensitive Urban Design in practice..................................................................... 11
2.2 Software ................................................................................................................................ 12
2.2.1 Quantum Geographic Information System (QGIS) ........................................................ 12
2.2.2 Storm Water Management Model (SWMM) ................................................................ 12
2.2.3 Parameter estimation software (PEST 13.0) ................................................................. 12
3 Flow frequency analysis ................................................................................................................ 13
3.1 Available data ........................................................................................................................ 13
3.2 Calibration of the model ....................................................................................................... 13
3.3 Data validation ...................................................................................................................... 18
4 Analysis of WSUD effectiveness .................................................................................................... 19
4.1 Design of the analysis ............................................................................................................ 19
4.2 Analysis of WSUD effectiveness on flow frequency .............................................................. 20
4.2.1 Rainwater tanks ............................................................................................................. 20
4.2.2 Bioretention basins........................................................................................................ 23
4.2.3 Peak flow reduction....................................................................................................... 24
4.3 Assessment of viability .......................................................................................................... 25
5 Discussion ...................................................................................................................................... 26
6 Conclusion ..................................................................................................................................... 28
7 Recommendations......................................................................................................................... 29
8 References ..................................................................................................................................... 30
Appendices ............................................................................................................................................ 31
Appendix A: overview of common WSUD measures ........................................................................ 32
Appendix B: preliminary investigation study area ............................................................................ 34
Appendix C: Decision process flowchart ........................................................................................... 37
Appendix D: Simulated vs. Actual runoff........................................................................................... 38
Appendix E: Antecedent rainfall vs. Volumetric runoff coefficient................................................... 44
Appendix F: Legislative requirements and approvals for rainwater tanks and bioretention basins 47
Appendix G: Peak flow simulation results using various WSUD measures ....................................... 48
Appendix H: Maps and statistics ....................................................................................................... 52

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List of figures
Figure 1-1: The Frederick St. catchment ................................................................................................. 7
Figure 1-2: An example of housing development on Cliff street ............................................................ 8
Figure 2-1: The natural, urban and WSUD water balance .................................................................... 10
Figure 2-2: A rainwater tank.................................................................................................................. 11
Figure 2-3: A bioretention basin ............................................................................................................ 11
Figure 2-4: A visualisation of the subcatchments of the Frederick Street catchment in EPA SWMM .. 12
Figure 3-1: The location of the two gauges within the catchment ....................................................... 13
Figure 3-2: Representation of the catchment in QGIS .......................................................................... 14
Figure 3-3: Visualisation of new roof area (shown in orange) per subcatchment ................................ 14
Figure 3-4: Coefficient of determination for the antecedent wetness ................................................. 17
Figure 3-5: Antecedent rainfall vs. runoff coefficient for 12 (numbered) storm events ...................... 18
Figure 4-1: Volumetric runoff for several scenarios.............................................................................. 20
Figure 4-2: 1 kL rainwater tank effectiveness ....................................................................................... 21
Figure 4-3: 2 kL rainwater tank effectiveness ....................................................................................... 21
Figure 4-4: 5 kL rainwater tank effectiveness ....................................................................................... 22
Figure 4-5: Proposed locations of the bioretention basins ................................................................... 23
Figure 4-6: Bioretention effectiveness .................................................................................................. 23
Figure 4-7: Predicted change in peak flows .......................................................................................... 24
Figure 4-8: Hydrograph showing the effect of the '5 kL rainwater tanks for all houses' scenario ....... 25
Figure C-1: The WSUD selection process............................................................................................... 37

List of tables
Table 3-1: Summary of catchment properties for the Frederick Street catchment ............................. 14
Table 3-2: The selected 12 storm events .............................................................................................. 15
Table 3-3: Predicted and recorded runoff coefficients for 12 selected events in 2013 and 2014 ........ 16
Table 3-4: Key properties of the Frederick Street model ...................................................................... 18
Table 4-1: Overview of characteristics for 1993, 2013 and 2040.......................................................... 19
Table 4-2: Predicted change in catchment properties .......................................................................... 19
Table 4-3: No WSUD prediction ............................................................................................................ 20
Table 4-4: 1 kL rainwater tank simulation results ................................................................................. 20
Table 4-5: 2 kL rainwater tank simulation results ................................................................................. 21
Table 4-6: 5 kL rainwater tank simulation results ................................................................................. 22
Table 4-7: Storage and underdrain properties ...................................................................................... 23
Table 4-8: Bioretention simulation results ............................................................................................ 23
Table A-1: Overview of WSUD measures .............................................................................................. 32

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1 Introduction

1.1 Problem definition

1.1.1 Introduction
South Australia is the driest state of the driest inhabited continent on earth. Adelaide, the capital city
of South Australia, is the state capital with the least amount of annual rainfall (550 mm) per year.

The CSIRO, Australia’s national science agency, believes South Australia may experience an overall
decline in rainfall between 15 to 30% by 2050. The state is also experiencing population growth: the
number of people living in South Australia (currently 1.65 million) will exceed 2 million by 2027. It is
expected that the water demand will sharply rise, while the available water resources will decline.

Currently, Greater Adelaide’s water supply for drinking and non-drinking purposes falls short of the
demand. This shortfall will only increase in the future due to the rising demand and diminishing
resources if the South Australian Government does not undertake action. (Government of South
Australia, 2009). For companies and inhabitants of the area, this means that cooperation is needed in
order to secure the water supply.

1.1.2 Water Management in South Australia

The rising demand and diminishing resources led to water management being marked as a key priority
for South Australia. Due to a changing climate and rising demand for water, many water related targets
have been set up for wastewater, irrigation, ground water and storm water management. The South
Australian government recently issued many important strategic plans in which water management
plays a vital role, for example the strategic water management document Water for good – A plan to
ensure our water future to 2050 (Government of South Australia, 2009). In this document, the need to
increase stormwater and wastewater reuse is being stressed.

Also, South Australia’s Strategic Plan (Government of South Australia, 2014) and The 30-year plan for
greater Adelaide (SA DPLG, 2010) were issued. Both plans provide long-term visions regarding a variety
of subjects, including water management. And, more importantly for this research, they both indicate
that the ratio of infill to fringe development for new housing will shift to a more infill-orientated ratio
in Adelaide. This increased dwelling intensity poses challenges to infrastructure in the existing urban
environment of the Greater Adelaide region. Amongst other things, this means that metropolitan
catchment areas where infill development takes place will be likely to experience changes in
stormwater runoff flow regimes. One of those areas is the Frederick Street catchment, a 44.7-Ha urban
catchment which is the study area of this report.

1.2 Research design

1.2.1 Centre for Water Management and Reuse (CWMR)
The Centre for Water Management and Reuse at the University of South Australia is one of the parties
who works on providing solutions to the problems posed in the strategic plans. The Centre has
connections with industry, government and environmental agencies and does research in the field of
water quality and water quantity. For many water related problems in the metropolitan area of
Adelaide, Water Sensitive Urban Design (WSUD) seems like a promising way to deal with the
challenges. Water-Sensitive Urban Design is a design approach which aims to integrate the urban water
cycle into urban design. There is a lot of WSUD related knowledge within the CWMR. The research will
focus on examining the impact of WSUD on flow frequencies in urban areas. More information on
Water-Sensitive Urban Design can be found in chapter 2.

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1.2.2 The study area
This research report will focus on the Frederick Street catchment in Glengowrie, a suburb of Adelaide.
Glengowrie is an urban area with a population density of 2480 inhabitants/km2. The area of the
Frederick Street catchment is 44,7 ha. A map of the catchment, provided by the CWMR, is shown
below. Over the years, infill development has taken place in the area, and this process is likely to
continue. The housing development leads to an increase in impervious area, which influences the flow
regime of the catchment, leading to bigger peak flows during runoff causing rainfall events. Building a
new drainage system for the entire catchment is an expensive and time-consuming solution which will
also cause a lot of nuisance. This is why alternative approaches are being taken into consideration.
Water-Sensitive Urban Design seems a promising solution to the problem. Therefore, it has to be
investigated if Water-Sensitive Urban Design can be applied in the catchment area in order to reduce
the effects caused by infill development on flow frequency.

Figure 1-1: The Frederick St. catchment

A reliable hydrological model was developed for the catchment in 1993. However, housing
development is known to have occurred in the Frederick Street catchment since that time, mainly by
the redevelopment of individual allotments from a single dwelling to multiple units or an increase in
dwelling size. The exact changes between the situation in 1993 and 2013 will be investigated by using
aerial photography. Because of the good availability of data and the relatively small (typically urban)
size of the catchment area, the Frederick Street catchment represents an ideal opportunity to explore
the effects of urban infill development on runoff flow rate and volume. The effects can be analysed by
comparing peak flow and runoff volumes before and after the development. The same simulation
techniques can also be applied to explore the potential of on-site and distributed WSUD systems to
manage the change in runoff flow rate and volumes.

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1.2.3 Research objective
In 1993, extensive research produced data to support a reliable hydrological model for the catchment
area. However, since that time the catchment area has experienced infill development, where housing
numbers and impervious areas have increased on existing allotments. An example is shown in figure
1-2. This might have resulted in changing flow frequencies for the catchment area. The objective of
the project will be to determine suitable WSUD measures for the catchment by producing an updated
version of the catchment model using flow data being collected since August 2013. The existing model
will be updated and then calibrated. When the model is calibrated, the use of several suitable WSUD
measures can be simulated on the catchment to view their effect on flow frequency. It is intended that
any changes which might have occurred in the area, will not have an effect on the flow regime of the
catchment. Therefore, using Water-Sensitive Urban Design to maintain the old flow frequencies by
improving drainage capacity is desired.

Figure 1-2: An example of housing development on Cliff street

1.3 Research questions

Main question:

How can the existing flow regimes of the Frederick Street catchment be preserved after the
redevelopment of the catchment area?

Subquestions:

 What is the current flow regime of the study area?

 How has/will the redevelopment of the catchment area affect the flow regime?
 Which WSUD-related solutions are available and how well will they be able to preserve the
flow regimes?
 How can Water-Sensitive Urban Design be used effectively to maintain the current flow
frequency?

The first two subquestions will be answered in though the flow frequency analysis (chapter 3), the
last two subquestions will be answered by an analysis of WSUD effectiveness (chapter 4).

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1.4 Research methods
In order to answer the research questions, the assignment is structured in an orderly way. The first
two subquestions require a good understanding of the flow regime and a realistic runoff model. After
that, the WSUD principles will be simulated in order to develop recommendations. The entire process
is described briefly below.

In order to work with a reliable and up-to-date model, changes in the area of the catchment need to
be taken into account (for example housing development or changes in soil conditions). The most
important change in the Frederick Street catchment will be housing development, which leads to an
increased impervious area. First, the percentage of growth of the impervious area needs to be
investigated. In order to assume the growth percentage of impervious area within the catchment,
available data about the catchment area will be updated by using the spatial information system QGIS
and satellite images from 1993 and 2013. Changes in the amount of pervious and impervious area will
be analysed and then used to update the model in EPA SWMM. After this, the model will be calibrated.
Model parameters include for example storage losses, Manning’s n values for pervious and impervious
areas and infiltration rates for soil. All relevant model parameters will be analysed to ensure a good
calibration. Most of this information can be found in the flow frequency analysis in chapter 3.

Following the calibration, the model will be used to simulate Water-Sensitive Urban Design principles,
in order to develop recommendations for implementing WSUD at the allotment level (with infill
development) or in the streetscape in the catchment to preserve the existing flow regime at 1993
levels. This report focusses on distributed systems throughout the catchment. Examples of WSUD
measures which can be simulated using the model are rainwater tanks or rain gardens. The model will
also be used to simulate the flow regime of the catchment in 2040. For that year, a number of scenarios
(with and without WSUD measures) will be analysed in order to determine whether Water-Sensitive
Urban Design can be an effective way to reduce peak flows in the Frederick Street catchment in the
future. The result will be a newly calibrated model with updated spatial information, and an overview
of the flow regimes in 1993, 2013 and the predicted flows for 2040 with and without several Water-
Sensitive Urban Design measures. The analysis of WSUD effectiveness in chapter 4 explains all of this
in more detail.

1.5 Importance of the research

The research can contribute to the understanding of the impact of infill development on a medium
sized urban catchment. In some ways, the Frederick Street catchment can be seen as a test case for
various urban catchments in the Greater Adelaide region, due to the typical urban characteristics (infill
development, flat terrain) and the availability of flow data. It is important to understand the impact of
infill development and how to overcome these impacts with WSUD tools. This might lead to sustainable
solutions which do not involve drastic and costly adjustments to urban drainage systems.

9
2 Theoretical context
In this chapter, an overview of the field of Water-Sensitive Urban Design and the software which was
used during the project is given. All of these subjects will be explained briefly below.

2.1 Water-Sensitive Urban Design (WSUD)

This section will give an overview of the main principles of Water-Sensitive Urban Design and several
suitable WSUD measures for the Frederick Street catchment.

2.1.1 What is Water-Sensitive Urban Design?

Water-Sensitive Urban Design (WSUD) is an approach to urban planning and design that integrates the
management of the total water cycle into the urban development process. It includes:

 Integrated management of groundwater, surface runoff (including stormwater), drinking

water and wastewater to protect water related environmental, recreational and cultural
values;
 Storage, treatment and beneficial use of runoff and wastewater;
 Using vegetation for water quality purposes;
 Utilising water saving measures to minimise requirements for drinking and non-drinking water
purposes.

Therefore, Water-Sensitive Urban Design incorporates all water resources, including surface water,
groundwater, urban and roof runoff and wastewater (Local Government Association of South
Australia, 2009).

Water-Sensitive Urban Design can play an important role in improving drainage capacity. Because most
WSUD measures focus on retention of rainfall, peaks in drainage flows during heavy rainfall can be
reduced, and the drainage will be spread out across a longer period of time.

Figure 2-1: The natural, urban and WSUD water balance

(Retrieved from http://waterbydesign.com.au/whatiswsud/ on 01-07-2014)

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2.1.2 Water-Sensitive Urban Design in practice
There is a wide range of WSUD measures which can be applied to new developments in the greater
Adelaide region. The South Australian government documented 16 different kinds of WSUD measures
which are suitable in the state. These measures vary from small to extensive measures, and take into
account water quality and/or water quantity. A brief summary of all WSUD measures can be seen in
appendix A. From all possible options, the measures which suited the purpose of this project (reduction
of peak flows and runoff volumes) and the urban environment of the Frederick Street catchment (infill
development, relatively flat terrain) best, were selected. The selected measures can be installed with
new development progress, unlike larger systems such as wetlands which require a lot of space. The
selected measures will be explained briefly below.

2.1.2.1 Rainwater tanks

A rainwater tank is designed and to capture and store
rainwater from gutters or downpipes on a building. A
rainwater tank only collects rainwater or mains water.
Captured water is then available for commercial, industrial
or domestic uses (Local Government Association of South
Australia, 2009). Rainwater from a tank can be used to
irrigate gardens or meet interior demands. The rainwater
storage can be refilled more often if the tank is used to
meet interior demands, because this uses water at a more
constant rate. Using rainwater for a combination of uses Figure 2-2: A rainwater tank
can lead to optimum mains water saving and possibly large
reductions in runoff charges for the catchment. It should be noted that rainwater tanks provide limited
water quality control, primarily through sedimentation processes. This can be enhanced by elevating
the outlet to a height greater than 100 millimetres above the tank floor.

It is currently mandatory for class 1 buildings, as defined in the Australian Building Code, to have an
alternative mains water supply, which is often met through installation of a rainwater tank plumbed
into the dwelling. There are a number of standards which apply to the construction and installation of
rainwater tanks. More information on this can be seen in appendix E. The most important requirement
regarding the reduction of peak flows is that every new dwelling is required to have an additional water
supply for mains water. The most popular way to meet this requirement is by connecting a rainwater
tank of at least 1kL, plumbed for internal use, to the house.

2.1.2.2 Bioretention basins

Bioretention systems are Water-Sensitive Urban Design measures
that involve some treatment by vegetation prior to the filtration of
runoff through a prescribed media. Following treatment, water may
infiltrate to the subsoil. The most common implementations of
bioretention systems for streetscapes are bioretention swales and
bioretention basins. For an urban area with very little available space,
such as the Frederick Street catchment, bioretention basins seem to
be the most appropriate measure.

Bioretention basins provide water quality treatment as well as flow

control. A bioretention basin is characterised by the ability to detain
runoff in a depression storage above the bioretention system. Figure 2-3: A bioretention basin

11
However, the low void ratios of soils used in these systems (typical value is 0.2) and their limited
infiltration rates (typically 150 to 300 mm/h) limits their potential to provide flood control. An
approximation of the available flood storage volume is a combination of 20% of the soil volume plus
the above lying ponding volume, although in practice the available soil storage is unlikely to be fully
utilised during a high intensity storm event (Local Government Association of South Australia, 2009).

2.2 Software
This section will provide an overview of the software used during the project. Working with the Storm
Water Management Model (SWMM) was one of the main tasks of this project.

2.2.1 Quantum Geographic Information System (QGIS)

QGIS (version 2.2) was used as the main spatial information software for this assignment. It is an
application that provides data viewing, editing, and analysis capabilities. QGIS was used to map the
changes per subcatchment in pervious/impervious area within the catchment. This was done using
satellite images from 1993 and 2013.

2.2.2 Storm Water Management Model (SWMM)

The modelling software used for this project is the Storm Water Management Model (version 5.1) by
the United States Environmental Protection Agency, referred to as EPA SWMM. The software is
available via the website of the United States Environmental Protection Agency.

“EPA SWMM is a dynamic rainfall-runoff simulation model

used for single event or long-term (continuous) simulation of
runoff quality and quantity from primarily urban areas. The
runoff component of SWMM operates on a collection of
subcatchment areas that receive precipitation and generate
runoff and pollutant loads. The routing portion of SWMM
transports this runoff through a system of pipes, channels,
storage/treatment devices, pumps, and regulators. SWMM
tracks the quantity and quality of runoff generated within
each subcatchment, and the flow rate, flow depth, and quality
of water in each pipe and channel during a simulation period Figure 2-4: A visualisation of the
compromised of multiple time steps.” (Rossman, 2007) subcatchments of the Frederick Street
catchment in EPA SWMM

2.2.3 Parameter estimation software (PEST 13.0)

PEST is a software package for model-independent parameter estimation and uncertainty analysis.
During this project, version 13.0 of PEST was used to aid the calibration of the model. PEST 13.0 runs
on DOS and can be used for parameter definition and recognition, observation definition and
recognition and predictive analysis (Doherty, 2010). For this project, PEST was used to calibrate the
values of a number of soil characteristics. More information about the calibration of the model can be
found in section 3.2.

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3 Flow frequency analysis
This chapter gives insight in the flow regimes of the catchment, and shows how redevelopment of the
area will affect the flows and runoff volumes of the area.

3.1 Available data

The available data consists of measurements from two
rainfall gauges (at Frederick Street and the Morphett
Arms hotel, see Figure 3-1) and one flow gauge, located
at the bottom of the catchment at Frederick Street. Data
from between 09-08-2013 and 24-05-2014 was made
available by Water Data Services Pty Ltd, the company
which is responsible for the management of the gauges.
The data from this period was verified and was
continuous. All data was available in 5-minute time steps.
The recorded rainfall per gauge was provided in steps of
0.2 mm for both gauges, and the flow gauge at Frederick
Street also provided information other information (flow, Figure 3-1: The location of the two gauges within
the catchment
depth, velocity, pH, water temperature, etc.).

3.2 Calibration of the model

Previous modelling of the Frederick Street catchment was undertaken by Kemp (2002) who used runoff
flow data from the catchment in 1993 and 1994 to verify that the ILSAX (stormwater drainage) model
was suitable for simulating runoff in urban catchments. The input data to the model used by Kemp was
based on data collected in the Frederick Street catchment in and around 1992-1993 as part of the
original monitoring of the catchment by the ‘Q/Q Group’. (Argue, Good, & Mulcahy, 1994) The
catchment’s contributing areas (pervious, directly connected impervious and supplementary paved
areas) for the ILSAX model were determined by analysis of aerial photography and on-site inspection.
Based on the on-site inspection, the catchment was dived into 54 subcatchments.

This model, referred to as the ‘1993 model’, has been used as the basis for the 2013 model. The 1993
model is calibrated to rainfall from between 1993 and 1994. However, after running the model with
data from 2013, it became clear that while the model was calibrated well to suit the specific 1993-1994
rainfall events, it did not provide a reliable model for other periods of time. This is a common mistake
made in modelling. (American Society of Civil Engineers, 1993). This meant the model, at that stage,
was not good enough (yet) to be able to successfully simulate the impact of infill development and the
effectiveness of WSUD principles to reduce this impact. Further adjustments had to be made in order
to get a good and reliable model.

13
First, the spatial information of the area was updated to
2013. In twenty years, a few dozen new houses were built
within the catchment. Also, a lot of ‘old’ houses have been
expanded by adding extensions to them. Changes in
driveways, sidewalks and gardens was also taken into
account. All the new information was then used to
calculate the new values for impervious/pervious areas.
The programme used to do this was QGIS.

In QGIS, the surface areas where categorised using four

different layers: roads, roofs, directly connected
impervious area and indirectly connected impervious
area. Roads and roofs are directly connected to the
drainage system. Directly connected impervious area are Figure 3-2: Representation of the catchment in QGIS
the pieces of land where runoff is directly connected to
the drainage system by travelling over other impervious
area, whereas indirectly connected impervious areas do
not connect directly to the drainage system and first have
to travel over pervious area. This categorisation is
important because each layer has its own values for
runoff time and volumetric runoff coefficient. Also, there
is a difference in water quality between these layers, but
this is not directly relevant for this specific project. The
calculated values for the different layers were then used
to update the SWMM model.

Overall, a 4% increase in impervious area was noted.

Figure 3-3: Visualisation of new roof area (shown
Changes were found in 31 out of 54 subcatchments, which in orange) per subcatchment
led to an 18950 m2 increase of impervious area in total. 48
buildings were removed, while 118 new buildings were erected. The mean area of the removed
buildings was 196 m2, while the mean area of new allotments was 242 m2. A quick overview of the new
mean values for the catchment can be seen in table 3-1.

Table 3-1: Summary of catchment properties for the Frederick Street catchment
Catchment property 1993 2013
Total area (ha) 44,7 44,7
Directly connected impervious area* (%) 30% 34%
Indirectly connected impervious area (%) 17% 17%
Pervious area (%) 53% 49%
* The directly connected impervious area includes roads and roofs.

The most remarkable changes compared to the old model are the adjustments to the soil
characteristics. In SWMM, there are three choices for modelling infiltration: Horton’s equation, the
Green-Ampt method and the Curve Number method. These are all common methods for infiltration
modelling. For this project, Horton’s equation was used.

Horton’s equation is a method based on empirical observations. The theory is based on the fact that
infiltration is faster in dry ground, so as rain continues and the ground becomes wetter, the infiltration

14
rate decreases. The reason that infiltration is faster when the ground is dry is that there are more spaces
for the water to fit so capillary forces that pull the water down into the ground are stronger. Horton’s
equation assumes that infiltration decreases exponentially from an initial maximum rate to some
minimum rate over the course of a long rainfall event. Input parameters required by the method
include the maximum and minimum infiltration rates, a decay coefficient that describes how fast the
rate decreases over time, and a drying time for fully saturated soil. Horton’s equation is a commonly
used infiltration modelling method, but like every model it has its limitations. The method assumes
that the rainfall rate, R is greater than the infiltration rate throughout the rain. If at any time the rainfall
rate is slower than the infiltration rate, the ground will lose some water to lower levels, and Horton's
theory must be modified in order to provide a realistic prediction. (Aron, 1992)

The data was analysed by looking at the 12 biggest rainfall events during the study period. Their
characteristics are shown below. The intensity of the events was categorised into three different
categories: low (< 0.2 m3/s), medium (0.2 to 0.5 m3/s) and high (> 0.5 m3/s).
Table 3-2: The selected 12 storm events

Rainfall Flow Vol. Runoff Recorded peak flow

3 3
Event # Intensity Date volume (m ) volume (m ) coefficient (m/s)
1 High 29-04-14 12232 4355 0,356 0,582
2 High 2-05-14 9437 3545 0,376 0,505
3 Medium 12-09-13 10749 2509 0,233 0,334
4 Medium 13-02-14 19177 5227 0,273 0,414
5 Medium 14-02-14 17838 6488 0,364 0,362
6 Medium 5-05-14 3299 1124 0,341 0,347
7 Medium 9-05-14 10593 3999 0,378 0,280
8 Low 21-08-13 2745 837 0,305 0,145
9 Low 2-10-13 1697 533 0,314 0,119
10 Low 8-04-14 1133 270 0,238 0,090
11 Low 2-05-14 776 324 0,417 0,087
12 Low 9-05-14 5241 2187 0,417 0,155

An initial overview of the data indicated that there may be problems with the assumed Horton
infiltration parameters in the existing 1993 model. Overestimation of the peaks, and underestimation
of the tails of the hydrographs occurred using the 1993 model to simulate 2013 rainfall events. Also,
the runoff coefficient of the catchment, determined based on measured flow data, was found to
increase when two or more consecutive storm events with short intervals occurred (as can be seen in
table XX). The most logical explanation for this was the saturation of the soil, which led to a decreased
capability of absorbing rainfall. It is likely that the 1993 model underestimated the influence of soil
characteristics on runoff. This suspicion became stronger when it was found that the model seemed
to have a stable volumetric runoff coefficient (roughly between 0.25 to 0.30 for the 12 selected rainfall
events in 2013 and 2014) while in reality the runoff coefficient proved to me more variable (roughly
between 0.25 to 0.40). A quick comparison between the model and measured values at the Frederick
Street gauge can be seen below.

15
Table 3-3: Predicted and recorded runoff coefficients for 12 selected events in 2013 and 2014
Event # Total amount Predicted flow Recorded flow Predicted Vol. Recorded Vol.
of rainfall (m3) volume (m3) volume (m3) runoff coefficient runoff coefficient
1 12232 3582 4355 0,293 0,356
2 9437 2631 3545 0,279 0,376
3 10749 3051 2509 0,284 0,233
4 19177 5613 5227 0,293 0,273
5 17838 5133 6488 0,288 0,364
6 3299 846 1124 0,256 0,341
7 10593 3030 3999 0,286 0,378
8 2745 702 837 0,256 0,305
9 1697 381 533 0,225 0,314
10 1133 192 270 0,170 0,238
11 776 165 324 0,213 0,417
12 5241 1524 2187 0,291 0,417

Average: 0,264 0,334

In order to get a better understanding of the effects of the soil saturation on the volumetric runoff
coefficient, the available data was analysed. The results can be seen in figure 3-4 and appendix D. In
can clearly be seen that the rainfall in previous days (known as the Antecedent Precipitation Index, or
API) does have a significant effect on the volumetric runoff coefficient. This is something the old model
seemed to underestimate, given the relatively low and non-variable values for the runoff coefficient it
produced. For the 5-day API, a common time period for this kind of research (Kjelsen, 2007), an
increase from roughly 0.30 to 0.40 was noted for the storm events with respect to dry and very wet
antecedent days in 2013 and 2014. This pointed in the direction of a relation between antecedent
wetness and volumetric runoff coefficient for these short storm events. The results of the analysis
were not conclusive, but reasonable R-squared (coefficient of determination) values (around 0.4 to
0.5) indicated there might be a relation. This was then taken into account for the new calibration of
the model.

A number of infiltration characteristics were recalibrated, for example maximum and minimum
infiltration rates, the decay constant (values usually range between 2 and 7) and the drying time (2 to
14 days) (Rossman, 2007). The recalibration was done using the calibration software PEST.

16
A remarkable finding was that a longer time span than commonly used seemed to predict the runoff
coefficient best. Although the 5-day antecedent wetness (API5) is a commonly used characteristic,
results indicate that a longer time span might be more suitable to predict the runoff coefficient in this
catchment. As figure 3-4 shows, the coefficient of determination for API14 is the highest and therefore
best. However, further research is needed to prove this hypothesis. It should be noted that soil
saturation measurement through collection of soil samples would have resulted in a more accurate
analysis. Field work might be a good recommendation for further research. However, for this project
the confirmation that soil characteristics seem to influence the flow rates is sufficient. This means the
soil characteristics will get a more prominent place in the calibration than previously assumed.

Statistical analysis
0,6
Coefficient of determination (R2)

0,510
0,5 0,443
0,409
0,384
0,4 0,364

0,3

0,2

0,1 0,061

0
0 5 10 15 20 25
Days before storm event taken into account (API)

Figure 3-4: Coefficient of determination for the antecedent wetness

17
The 2-, 5-, 7-, 14- and 21-day API graphs are shown in appendix E. The graph for the 5-day API, with
the 12 selected events labelled, is also shown below. An increase in volumetric runoff coefficient for
periods with high amounts of rainfall can be seen.

Antecedent rainfall vs. Volumetric runoff coefficient (5 days)

0,450
12 11
0,400
Volumetric runoff coefficient

7 2 5
0,350 1
6
9
0,300 8
4
0,250 10
3
0,200
0,150
0,100
0,050
0,000
0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0 45,0
API5 (mm)

Figure 3-5: Antecedent rainfall vs. runoff coefficient for 12 (numbered) storm events

After all these findings the model was re-calibrated using the new area values, 2013-2014 rainfall data
from both gauges and the new insights on soil characteristics. The parameter estimation software used
to do this was PEST. This led to the key parameters as shown in table 3-4.
Table 3-4: Key properties of the Frederick Street model

Model parameter Unit Initial value Final value

Impervious area roughness, Nimp - 0.01 0.01
Pervious area roughness, Nperv - 0.03 0.032
Maximum soil infiltration rate (mm/hr) 100 100
Minimum soil infiltration rate (mm/hr) 8 3.440
Decay h-1 2 2.261
Drying time days 5 2.723
Impervious area depression storage (loss), Simp mm 0.5 0.579
Pervious area depression storage (loss), Sperv mm 5 2.990

3.3 Data validation

Furthermore, the recorded rainfall at the two gauges was validated. There were no strange gaps or
peaks in the data provided. However, one rain gauge recorded a 17% larger volume of rain than the
other, which might seem odd, given that the gauges are located about a kilometre from each other.
After these findings, the data was sent to Water Data Services, the company who provided the rain
gauge data, in order for it to be checked and to see if both gauges functioned normally. Water Data
Services did not find any strange circumstances which might explain the difference. After this, a site
visit was conducted, but this also did not bring to light any circumstances which might explain the
difference (for example an object blocking the gauges). Therefore, it was assumed the measures
amounts of rainfall at both gauge locations were accurate enough to use for the simulations.

18
4 Analysis of WSUD effectiveness
Now that an understanding of the flow regimes and the effects of infill development have been
established, the effectiveness of the WSUD measures can be analysed.

EPA SWMM was used to determine the effectiveness of several Water-Sensitive Urban Design
measures for the catchment. As well as the effectiveness, the viability of the measures will also be
briefly assessed.

4.1 Design of the analysis

After the calibration of the model and validation of the data, the model could be used to analyse the
effectiveness of several Water-Sensitive Urban Design principles on flow frequency. For the analysis,
three benchmark years have been set: 1993 (old situation), 2013 (current situation) and 2040 (several
potential development scenarios). Below, a short summary will be given of their characteristics.

Rainfall data Spatial data WSUD?

1993 2013-2014 1993 land use No
2013 2013-2014 2013 land use 1-kL rainwater tank for
houses after July 2006
2040, no measures 2013-2014 2013 land use + prediction No new measures
2040, rainwater tanks 2013-2014 2013 land use + prediction 1-,2-, and 5-kL
Rainwater tanks
2040, Bioretention 2013-2014 2013 land use + prediction Bioretention basins
systems
Table 4-1: Overview of characteristics for 1993, 2013 and 2040

For 2013, it was assumed that all houses built after July 2006 were fitted with a 1 kL rainwater tank,
connected to a roof area of 50 m2. This because according to the Development Act 1993, all new houses
and house extensions greater than 50 square metres are required to have an additional water supply
to supplement mains water after 1 July 2006. Furthermore, the minimum required connected roof
area is 50 m2. It was assumed that only the houses built after July 2006 were fitted with a rainwater
tank. By using a proportion of the 1993 to 2013 development, this led to the assumption that until
2013 the number of connected rainwater tanks was 41 (the number of houses assumed to be built
after July 2006), with a 1-kL rainwater tank which is connected to a roof area of 50 m2. The average
water demand from the rainwater tanks currently lies around 100 L/day.

For the 2040 scenarios, it was assumed that the infill development of the past 20 years would continue
at the same speed. This meant that, compared to 2013, 65 house will be demolished and 159 new ones
will be built. This leads to an overall increase of 94 houses. Because of the new housing developments,
it was assumed that the 159 new buildings all had 50 m2 of roof area connected to a rainwater tanks,
thus leading to an additional 7950 m2 of roof area connected to rainwater tanks. Overall, the
percentage of impervious area will increase to 40% of the total area.

An assessment of available space for bioretention systems was done by a site visit and the use of
satellite images.
Table 4-2: Predicted change in catchment properties

Catchment property 1993 2013 2040 (prediction)

Total area (ha) 44,7 44,7 44,7
Directly connected impervious area* (%) 30% 34% 40%
Indirectly connected impervious area (%) 17% 17% 17%
Pervious area (%) 53% 49% 43%

19
4.2 Analysis of WSUD effectiveness on flow frequency
In this chapter the results of the simulations will be shown and discussed. The chapter is divided into
three sections: rainwater tanks, bioretention basins and the detention basin. For comparison, the
volumes for 2013, and the 2040 scenario without any new WSUD measures will be shown in the results
as well.
Table 4-3: No WSUD prediction

Scenario Total volume of runoff (m3)

1993 35130
2013 38247
2040, no new WSUD 42987

4.2.1 Rainwater tanks

The effectiveness of rainwater tanks on the reduction of runoff volume is shown below. The application
of rainwater tanks of 1kL, 2kL and 5kL were simulated. 1kL rainwater tanks have been compulsory for
all new houses since July 2006. The effect of WSUD measures for all expected new housing, as well as
for all houses within the catchment has been analysed.

Volumetric runoff for several 2040 scenarios

44000 42987
43000
VOLUMETRIC RUNOFF (M3)

42081
42000 41559
41106
41000
40000
39000 38418
38000
37000 36558
36000 34923
35000
34000
NO WSUD 1 KL NEW 2 KL NEW 5 KL NEW 1 KL ALL 2 KL ALL 5 KL ALL

Figure 4-1: Volumetric runoff for several scenarios

4.2.1.1 1 kL rainwater tanks

The effectiveness of 1 kL rainwater tanks on reducing runoff volumes has been simulated using
SWMM. The results are shown below.
Table 4-4: 1 kL rainwater tank simulation results

Scenario Total volume of runoff (m3)

1993 35130
2013 38247
2040, no new WSUD (prediction) 42987
2040, 1 kL rainwater tanks for new houses 42081
2040, 1 kL rainwater tanks for all houses 38418

20
According to current legislation, every new
house needs to be fitted with a 1-kL rainwater
tank. If the local government decides to maintain
this rule, this will lead to an expected 2%
decrease of flow volumes compared to a
situation without new WSUD. This is not enough
to maintain the current flow regime.

Fitting all houses with a 1-kL rainwater tank leads

to an 11% decrease of flow volumes, restoring
them to the current level.
Figure 4-2: 1 kL rainwater tank effectiveness

4.2.1.2 2 kL rainwater tanks

The effectiveness of 2 kL rainwater tanks on reducing runoff volumes has been simulated using
SWMM. The results are shown below.
Table 4-5: 2 kL rainwater tank simulation results

Scenario Total volume of runoff (m3)

1993 35130
2013 38247
2040, no new WSUD (prediction) 42987
2040, 2 kL rainwater tanks for new houses 41559
2040, 2 kL rainwater tanks for all houses 36558

Not very surprisingly, the appliance of 2-kL

rainwater tanks forces reduction of the flow
volumes even more. Installing 2-kL rainwater
tanks for new houses lead to a 3% decrease of
the volume.

Applying 2-kL rainwater tanks to every house

within the catchment leads to a 15% decrease.
This restores the flow volumes to a pre-2013
level, however not as low as the 1993 level.

Figure 4-3: 2 kL rainwater tank effectiveness

21
4.2.1.3 5 kL rainwater tanks
The effectiveness of 5 kL rainwater tanks has been simulated using SWMM. The results are shown
below.
Table 4-6: 5 kL rainwater tank simulation results

Scenario Total volume of runoff (m3)

1993 35130
2013 38247
2040, no new WSUD (prediction) 42987
2040, 5 kL rainwater tanks for new houses 41106
2040, 5 kL rainwater tanks for all houses 34923

The biggest rainwater tanks that were

considered for the allotments in the catchment
were 5-kL rainwater tanks. Bigger tanks were not
seen as realistic, and even the appliance of 5-kL
rainwater tanks does not seem feasible, due to
the large amount of space they require.

However, the 5-kL rainwater tanks are effective

in restoring the 1993 flow levels (a 19%
decrease) if applied to all houses. If applied only
to new housing developments, the tanks achieve
a 4% reduction.
Figure 4-4: 5 kL rainwater tank effectiveness

22
4.2.2 Bioretention basins
For the simulation of the effectiveness of street scale bioretention basins, a number of assumptions
were made. The properties in table 4-7 were used for the simulation. These values are values
commonly used within the CWMR, and most of them were derived from Rossman’s SWMM user
manual. (Rossman, 2007). Furthermore, it was assumed that a set of basins could be integrated in the
streetscape roughly every 100 metres on suitable locations. A site visit gave an insight in good ways to
integrate the basins into the streets. For the simulation this resulted in 82 basins, spread out across 44
subcatchments. The locations of these basins are shown in figure 4-5.
Table 4-7: Storage and underdrain properties

Soil storage properties

Thickness (mm) 850
Porosity (volume fraction)* 0.437
Field capacity (volume fraction)* 0.062
Wilting Point (volume fraction)* 0.024
Conductivity (mm/hr) 150
Conductivity slope 5
Suction head (mm)* 1.93
Underground storage properties
Thickness (mm) 250
Void ratio (voids/solids) 0.1
Seepage rate (mm/hr) 0.36
Clogging factor 0
Underdrain properties
Drain coefficient (mm/hr) 18.5 Figure 4-5: Proposed locations of the bioretention basins
Drain exponent 0.51
Drain offset (mm) 50
*Derived from the SWMM User Manual

Table 4-8: Bioretention simulation results

Scenario Total volume of runoff (m3)

1993 35130
2013 38247
2040, no new WSUD (prediction) 42987
2040, bioretention 41562

Compared to rainwater tanks, bioretention systems

seem to be less effective in reducing flow volumes,
as expected. The construction of 82 bioretention
basins (without impermeable liner) within the
catchment leads to an expected 3% decrease of the
flow volume. This is not enough to restore the pre-
development levels in the catchment. However, it
should be noted that bioretention systems have
other advantages than just water quantity
reduction. As mentioned before, the basins can
have positive effects on for example water quality.
Figure 4-6: Bioretention effectiveness

23
4.2.3 Peak flow reduction
Besides the reduction of volumetric runoff for several WSUD scenarios, an analysis has also been done
on the predicted peak flows for the scenarios in the year 2040. This was done by looking at the twelve
selected storm events. The results show that in the scenario without any new Water-Sensitive Urban
Design, peak flows for the storm events would rise by 11% on average. All of the results can be found
in appendix G.

The construction of rainwater tanks on new houses leads to a decrease of the peak flows compared to
the scenario without Water-Sensitive Urban Design, but not enough to maintain the current peak
flows. Additional measures will be needed in order to maintain the peak flows.

A more extreme measure such as connecting every house to a rainwater tank seems to be able to
maintain the current flows, or even reduce them. The most effective measure to counter rising peak
flows is the bioretention scenario, leading to a 31% decrease in peak flows compared to the current
levels. However, it should be noted that most of the reduction accomplished by bioretention systems
is from the smaller, less extreme storm events. More about this can be seen in appendix G.

Predicted change in peak flows 2013-2040

Bioretention

5 kL all

2 kL all
WSUD scenario

1 kL all

5 kL new

2 kL new

1 kL new

No WSUD

-40 -30 -20 -10 0 10 20

Average change in peak flows (%)

Figure 4-7: Predicted change in peak flows

24
A hydrograph showing an impression of the impact of applying rainwater tanks to the catchment is
shown in figure 4-8. In this graph, the 5 kL rainwater tank for all houses scenario is shown. Results
for other (less drastic) rainwater tank scenarios show a smaller, but similar reduction of peak flows.

Reducing peak flows - rainwater tanks

0,800

0,700

0,600

0,500
Flow (m3/s)

Predicted 2013 flow

0,400
Predicted 2040 flow
0,300 (No WSUD)
Predicted 2040 flow
0,200 (5 kL all houses)

0,100

0,000
0 150 300 450
Time (minutes)

Figure 4-8: Hydrograph showing the effect of the '5 kL rainwater tanks for all houses' scenario

4.3 Assessment of viability

A short assessment has been made of the viability of the simulated measures mentioned earlier in this
chapter.

The size of the rainwater tanks is an important variable in the simulation of the effectiveness of the
tanks. Current legislation requires every new allotment to be fitted with a 1 kL rainwater tank,
connected to at least 50 m2 of roof area. Therefore, the scenario in which new houses will be equipped
with 1 kL rainwater tanks is the most likely one. However, bigger tanks are also an option. Important
cons about bigger tanks are the extra space they require and the fact that they are more expensive for
the developers and/or residents to purchase. On the other hand, they are more effective in forcing
back the peak flows and flow volumes.

Fitting every house with a rainwater tank is also an option. The results of the simulation indicate that
this is an effective measure which is able to maintain the current flow regime. However, obliging all
residents to install a rainwater tank requires new legislation and significant investments by local or
state authorities.

The construction of bioretention basins throughout the catchment does not need new legislation. In
fact, some parts of the catchment (and similar) catchments have already been fitted with similar
basins, although on a smaller scale than simulated in this report. It is advised to construct the basins
when roadwork is being done to minimise costs and nuisance during the construction of the
bioretention basins. It is important to consider that the effectiveness of bioretention basins over a
longer period of time has not been evaluated yet.

For future research it is advised to conduct a full cost-benefit analysis (installation, maintenance and
running costs) of each WSUD measure in order to aid the decision making process.

25
5 Discussion
In the end, the model gave a good understanding of the flow regimes, and proved to be a helpful aid
to answer the research questions. The outcomes of the research were as expected and the report as a
whole shows promising prospects for the use of Water-Sensitive Urban Design in medium sized urban
catchments.

But like with every other project, several problems were encountered. First of all, when the two rain
gauges in the area were compared it was found that, for the period of August 2013 – May 2014, the
Frederick Street rain gauge (A5040561) received a substantially larger amount of rainfall (332 mm)
than the Morphett Arms rain gauge (A5040556), which recorded only 283 mm of rainfall. This
difference of 17% seems odd for two pluviometers which are located in the same urban area less than
a kilometre from each other. An explanation could not be found. One possible explanation is the fact
that the Frederick Street gauge (A5040561) has been replaced between 1993 and 2013, which might
have led to different rain recordings. However, the gauge performed well when it was calibrated after
the installation. For further research, it might be good to wait for both of the rain gauges to be
recalibrated. Although no abnormalities were found by experts, the 17% difference in measured
rainfall between the gauges suggests that the gauges might need a new calibration. This will be done
on the next site visit by Water Data Services Ltd.

One rain gauge (A5040556) was moved approximately 60 metres to the south since the 1993 rainfall
recordings. This might have led to slightly different recordings than on the old location.

February 2014 was one of the wettest summer months in the recorded history of rainfall in Adelaide.
On average, Adelaide receives about 20 mm rain in February. In 2014, this was more than 80 mm (4
times the average). Such extreme weather conditions might lead to distorted model results, since the
model seems to predict the extreme events not as well as common events.

Also, the influence of antecedent precipitation should be further investigated. The findings of this
research suggest that taking a longer period into account than the commonly used 5-day antecedent
wetness might lead to a more accurate model in the case of the Frederick Street model. However,
more research needs to be done to confirm this presumption.

In order to get a more accurate understanding of the soil behaviour, it is advised to work with daily
records of rainfall and evaporation. Daily evaporation records were not available for this research, only
monthly averages. Furthermore, working with data from a longer time period than just 9 months might
improve the quality of the research as well.

It may be debated whether Horton’s method is the best way to model the soil infiltration, since it has
its shortcomings. If at any time the rainfall rate is slower than the infiltration rate, the ground will lose
some water to lower levels, which might not be realistic. Other methods have their own shortcomings,
and because this was the most common method used in South Australia, Horton’s equation was selected.
The other options were not put to the test due to time restrictions.

The rate of infill development will probably slow down over time instead of the assumed linear increase
because there are fewer allotments available for redevelopment as development progresses. This has
not been considered in the projections in this report.

It was assumed that there is no increase in indirect impervious area. Further research should investigate
whether this assumption is reasonable.

26
It should also be noted that the effectiveness of the WSUD measures was the main topic of this research.
However, not only WSUD effectiveness and cost-effectiveness should be taken into account. Local
councils and their legislation have a big impact on the decision making process when choosing which
WSUD measures to apply as well.

Overall, the model and the simulations seem to be of good use in order to get an understanding of the
effects of infill development on flow regimes in urban areas and how WSUD can be used to counter those
effects. As mentioned in this section, further research needs to be done, but the results from this report
look promising.

27
6 Conclusion
The current flow regime of the Frederick Street catchment has been assessed and a model has been
set up to analyse the impact of infill development on the flow regime. Redevelopment within the
catchment area is expected to lead to an overall increase of 12% in runoff volume, and an 11% increase
in peak flows by 2040 if no WSUD measures would be implemented.

Water-Sensitive Urban Design can be used to preserve the existing flow regimes of the Frederick Street
catchment. For street scale WSUD measures, rainwater tanks and bioretention systems are showing
promising simulation results for reducing runoff volumes and peak flows. The most effective way of
reducing runoff volumes is the installation of rainwater tanks. Peak flow reduction on the other hand
can be achieved by both rainwater tanks and bioretention basins. Although bioretention basins achieve
a higher overall reduction of peak flows, it should be noted that for very extreme storm events they
are not capable of significant peak flow reduction.

Therefore a mix of both small (1 kL) rainwater tanks for all houses in combination and bioretention
systems seems to be the best option for preserving the flow regimes in the Frederick Street catchment.
Another option is to connect every house in the catchment to a bigger (e.g. 5 kL) rainwater tank.

Although the peak flows and runoff volumes would not increase as much as without Water-Sensitive
Urban Design, continuation of the current policies would lead to an increase in flow volumes and peak
flows. Therefore, additional action needs to be undertaken to preserve the existing flow regime. This
report provides delicate, sustainable and relatively cheap solutions for the expected increase in peak
flows and runoff volumes, possibly saving local governments and residents a lot of money and
nuisance.

The existing flow regimes of the Frederick Street catchment can be preserved by either constructing
new drainage systems (a costly solution) or by using Water-Sensitive Urban Design. Peak flows can be
preserved or even reduced by fitting every house with a rainwater tank of at least 1 kL, or by installing
streetscape bioretention basins. Runoff volumes can be preserved or reduced by fitting every house
with a rainwater tank of at least 1 kL.

28
7 Recommendations
There are several recommendations for further research on this topic. They include recommendations
for future data analysis as well as advice for the appliance of WSUD measures in the Frederick Street
catchment and similar urban catchments.

It should always be taken into account that the decision on what WSUD measures to implement
depends on the focus of the drainage targets. If the targets are related to runoff volume reduction,
rainwater tanks are the best option. In case of peak flow related targets, a combination of rainwater
tanks and bioretention basins is recommended.

There are several recommendations regarding the data analysis. First, when the rainfall gauges have
been re-calibrated, new data should be compared with the old data in order to see whether the
irregularities regarding rainfall measurements were caused by a bad calibration of the gauges. It is
further recommended that other soil infiltration models are taken into account, this was not done for
this research due to time restrictions.

Future research should include a full cost-benefit analysis of each WSUD option, as well as an
investigation on the development of the amount in indirectly connected impervious area.

Before any decisions on WSUD measures are taken, it is advised to discuss the findings of the research
with the involved local councils to see whether changes need to be made to current legislation.

It should be noted that the results of the research are subject to sensitivity before being adopted.
Assumptions have been made for parts of the project such as the water demand and soil infiltration
parameters. Further research should clarify whether the assumptions made were accurate enough to
justify the conclusions of this report.

Overall, the outcome of this research shows promising prospects, and therefore it is recommended to
further investigate the implications Water-Sensitive Urban Design can have on preserving flow regimes
in developing urban catchments. If continued, this research can contribute to cost-effective and
sustainable solutions for several urban water challenges.

For now, results indicate that (local) governments should focus on investigating possibilities to connect
1 kL rainwater tanks to all houses, if necessary in combination with distributed streetscape bioretention
basins.

29
8 References
American Society of Civil Engineers. (1993). Criteria for evaluation of watershed models. Journal of
Irrigation and Drainage Engineering, 429-442.

Argue, J. E., Good, K., & Mulcahy, D. E. (1994). Planning, Instrumentation and Data for an Urban
Drainage Network in Adelaide, South Australia. Water Down Under, November edition, p.
287 - 294.

Aron, G. (1992). Adaptation of Horton and SCS Infiltration Equations to Complex Storms. J. Irrig. Drain
Eng., 118(2), 275–284.

Doherty, J. (2010). PEST: Model-Independent Parameter Estimation, user manual 5th edition.
Brisbane, Australia: Watermark Numerical Computing.

eWater Ltd. (2011). Guidelines for water management modelling. Canberra: CRC Australia.

Government of South Australia. (2009). Water for good - A plan to ensure our water future to 2050.
Adelaide, SA, Australia: Government of South Australia.

Government of South Australia. (2013). Designing a WSUD strategy for your development. Adelaide,
SA, Australia: Government of South Australia.

Government of South Australia. (2013). Water sensitive urban design; Creating more liveable and
water sensitive cities in South Australia. Retrieved from Department of Environment, Water
and Natural Resources: http://www.environment.sa.gov.au/files/516f3ac2-16ff-43fd-b078-
a26900b99a81/water-sensitive-urban-design-policy-gen.pdf

Government of South Australia. (2014). South Australia's Strategic Plan. Adelaide, SA, Australia:
Government of South Australia.

Kemp, D. J. (2002). The development of a rainfall-runoff-routing model (RRR). Adelaide: University of

South Australia.

Kjelsen, T. R. (2007). The revised FSR/FEH rainfall runoff method. Oxfordshire, UK: Centre for Ecology
& Hydrology.

Local Government Association of South Australia. (2009). Institutionalising Water-Sensitive Urban

Design - Technical manual. Adelaide: Local Government Association of South Australia.

Rossman, L. A. (2007). Storm water management model, user's manual. Cincinnati, Ohio: EPA.

SA DPLG. (2010). The 30-year plan for Greater Adelaide. Adelaide, SA, Australia: South Australian
Department of Planning and Local Government.

Urban Drainage and Flood Control Dictrict. (2007). Drainage criteria manual. Denver, Colorado:
UDFCD.

30
Appendices

Appendix A: overview of common WSUD measures ............................................................................ 32

Appendix B: preliminary investigation study area ................................................................................ 34
Appendix C: Decision process flowchart ............................................................................................... 37
Appendix D: Simulated vs. Actual runoff............................................................................................... 38
Appendix E: Antecedent rainfall vs. Volumetric runoff coefficient....................................................... 44
Appendix F: Legislative requirements and approvals for rainwater tanks and bioretention basins……47
Appendix G: Peak flow simulation results using various WSUD measures…………………………………………48
Appendix H: Maps and statistics ........................................................................................................... 52

31
Appendix A: overview of common WSUD measures

Table A-0-1: Overview of WSUD measures (Government of South Australia, 2013)

# Measure More information Focus of WSUD Potential benefits Suitable

measure conditions
Water Water
quality quantity
1 Demand Water Medium High Reductions in Residential,
reduction conservation mains water supply commercial
(water-efficient & industrial
fixtures and sites
appliances, etc.)
2 Rainwater Capture and Low High Reduction in water Proximity to
tanks storage of supply and peak roof
rainwater runoff rates
3 Rain gardens Gardens with Medium High Peak runoff Allotment
runoff directed into reduction, water scale
them quality and
biodiversity
benefits
4 Green roofs Vegetated roof Medium Medium Water retention, Flat roofs
covers biodiversity
benefits
5 Infiltration Shallow excavated High Medium Reduce surface Sandy soils
systems trenches runoff, water with deep
quality benefits groundwater
6 Pervious Porous/permeable High Medium Retention and Allotments
pavements pavements detention of areas with
runoff, minimise low amounts
sediment export of traffic
7 Urban water Collection of water Medium High Storage, reduction Areas with a
harvesting and resources (ponds, in mains water lot of space
reuse wetlands, supply, recreation and high
rainwater storage, demand
etc.)
8 Gross Remove large High Low Reduction of litter, Site and
pollutant traps solids from debris and precinct
drainage system sediment scales
9 Bioretention Filtration/ High Low Water quality, Flat terrain
basins bioretention street amenity,
trenches flood retardation
11 Swales Linear depressions Low Low Reducing runoff, Flat terrain
capable of positive effects on or mild
capturing runoff biodiversity and slopes
amenity
12 Buffer strips Broad depressions High Low Reducing runoff, Flat terrain
capable of positive effects on or mild
capturing runoff biodiversity and slopes
amenity

32
13 Sedimentation Coarse sediment High Medium Good pre- Big areas of
basins capture in basins treatment for flat land
wetlands or
bioretention basins
14 Constructed Created versions of High High Water quality, Big areas of
wetlands natural wetlands reduces runoff, flat land
ecological and
recreational value
15 Wastewater Reuse of Medium High Nutrient reduction Residential,
management waterwater on site to receiving commercial
environments, & industrial
mains water sites
reduction
16 Syphonic Roofwater Low High Reduction in water Suitable
roofwater harvesting for tall supply and peak roofs
systems or large buildings runoff rates

33
Appendix B: preliminary investigation study area

In 1993, extensive research has produced a reliable hydrological model for the Frederick St. catchment
area. The model was calibrated using rainfall data from that period. However, it had to be investigated
whether the model would also work properly when new rainfall data and new area information was
added.

In order to investigate this, continuous 5-minute rainfall data from August 2013 – May 2014 was used
to see whether the 1993 model still provided a good estimation of the flows in the catchment. Rainfall
events which led to a substantial amount of rainfall (and flows bigger than 0.2 m3/s) were selected to
see whether the model could still be used for stormwater modelling. 12 rainfall events were selected
and simulated using EPA SWMM. The results can be seen on page 36.

The results show that the model in EPA SWMM both over- and underpredicts the flows within the
catchment with the 2013-2014 rainfall data. One might have expected the simulated values to be lower
than the actual flow values. This because of the infill development which has occurred, which will most
likely lead to more extreme peaks due to the increase of impervious area. However, in the model this
did not happen in most cases. Therefore, further investigation of the catchment area was needed in
order to see whether this problem could be solved by updating the percentages of pervious and
impervious area per subcatchment.

The spatial information system QGIS was used to do this update. This was done using satellite images
from 2013. For most subcatchments, the new satellite images showed an increase in impervious area
(leading to increased peak flows). This was then incorporated into the model. Twelve ‘rainfall events’
where selected between August 2013 and May 2014 to test the accuracy of the model. Their intensity
was categorised as either ‘high’ (flows of > 0.5 m/s), ‘medium’ (flows between 0.2 m/s and 0.5 m/s) or
‘low (flows of < 0.2 m/s) ’ based on the peak flow. After applying the new spatial information the model
still didn’t perform well. An example of this is given in figure 1.

Event 1
0,700
0,600
0,500
Flow (m3/s)

0,400
Predicted (EPA SWMM)
0,300
Actual flow
0,200
Predicted (after QGIS)
0,100
0,000
0 150 300 450
Time (minutes)

Figure B-1: Actual flows vs. predicted flows for a storm event on 12-09-2013. The blue line represents the prediction with
2013-2014 rainfall data using the old (1993) model. The grey line represents the non-calibrated run with updated spatial
information.

34
Other things that should be taken into account include the following:

 When the two rain gauges in the area were

Recorded rainfall (mm)
compared it was found that, for the period
of August 2013 – May 2014, the Frederick 50

Street rain gauge (A5040561) received a 45

substantially larger amount of rainfall (332 40

Rainfall A5040556 (mm)

mm) than the Morphett Arms rain gauge 35
(A5040556), which recorded only 283 mm 30
of rainfall. This difference of 17% seems odd 25
for two pluviometers which are located in 20
the same urban area less than a kilometre 15
from each other. 10
5
 A new rain gauge has been installed at the
0
Frederick Street gauge (A5040561), which 0 10 20 30 40 50
might have led to different rain recordings Rainfall A5040561 (mm)
than previous.
 One rain gauge (A5040556) was moved Figure B-2: Recorded rainfall at Morphett Arms (A5040556) and
approximately 60 metres to the south. Frederick St. (A5040561) for 12 selected storms

 The value for the volumetric runoff coefficient is varying per event. The most important factor
that causes this seems to be the saturation of the soil. For events which are preceded by a long
period of dry weather, the runoff coefficient is low, whereas it is high for periods with a lot of
rainfall. Saturation of the soil can lead to pervious area runoff occurring which might explain
the varying coefficients. Coefficients between 0.25 and 0.40 seem likely for this kind of land
use during storm events (Urban Drainage and Flood Control Dictrict, 2007).

Total amount of recorded rainfall

350
300
rainfall (mm)

250
200
150
100 Rainfall Frederick St.
50
0 Rainfall Morphett Arms
Difference

Time & Date

Figure B-3: Difference between the amounts of recorded rainfall.

By looking at the total volume of water generated by the events and the predicted and actual runoff
volumes, it became clear that the model didn’t function well anymore and needed further calibration.
A remarkable finding was that the model, based on data in 1993 to 1994, seemed to have a stable
volumetric runoff coefficient (roughly between 0.25 and 0.30 for the 12 selected rainfall events) while
in reality the runoff coefficient proved to me more variable. One possible explanation for this is that

35
the old model overestimated the impervious area for the catchment, and underestimated the
influence of the soil/pervious area in predicting the flows.

Table B-1: Characteristics of the 12 storm events

36
Appendix C: Decision process flowchart

The decision making process is not only a matter of choosing

the most effective measure. A successful application of
WSUD requires input from a range of professions including
engineering, ecology, landscape architecture, legislative and
other interdisciplinary considerations such as the
community or residents (Government of South Australia,
2013).

The decision process for selecting appropriate WSUD

measures is represented in the flowchart on this page. It
becomes clear that already very early in the process
government authorities need to be involved with the
project.

For this project some relevant steps will be further

explained below. Especially the earlier steps in the process
are relevant to this research.

 Step 2: Identify Objectives & Targets

There is a wide range of objectives related to WSUD, for

example water quality, water quantity, integrated water
cycle management, biodiversity, amenity and social
outcomes. The focus of this project is on water quantity,
however other possible good and bad side effects of the
proposed WSUD measures should be taken into account.

Figure C-1: The WSUD selection process.

 Step 3: Identify suitable WSUD measures (Government of South Australia, 2013)

Out of the overview provided in appendix A, a number of most suitable measures were chosen. It is
important that the effects these measures have on other targets than just water quantity are also
taken into account.

 Step 4: Meet with council and relevant authorities

Local governments need to be involved in the process in an early stage. The most important fact is
this step is that the City of Marion (the location of the Frederick street catchment) already has
experience with rainwater tanks and bioretention basins, and therefore it is expected that the
council is willing to cooperate for at least these WSUD measures.

Step 6-8 of the decision process flowchart are the main focus of this report. In some ways, the
conclusion of this report can be seen as the objectives check (step 9).

37
Appendix D: Simulated vs. Actual runoff

Event 1
0,700

0,600

0,500
Flow (m3/s)

0,400
Prediction - 1993 model
0,300 Prediction - 2013 model
Actual flow
0,200

0,100

0,000
0 150 300 450
Time (minutes)

Event 2
0,700

0,600

0,500
Flow (m3/s)

0,400
Prediction - 1993 model
0,300 Prediction - 2013 model
Actual flow
0,200

0,100

0,000
0 150 300 450 600
Time (minutes)

38
 Event 3
0,600

0,500

0,400
Flow (m3/s)

0,300 Prediction - 1993 model

Prediction - 2013 model
0,200 Actual flow

0,100

0,000
0 150 300 450 600
Time (minutes)

Event 4
0,500

0,450

0,400

0,350
Flow (m3/s)

0,300

0,250 Prediction - 1993 model

0,200 Prediction - 2013 model

0,150 Actual flow

0,100

0,050

0,000
0 150
Time (minutes)

39
 Event 5
0,700

0,600

0,500
Flow (m3/s)

0,400
Prediction - 1993 model
0,300 Prediction - 2013 model
Actual flow
0,200

0,100

0,000
0 150 300 450 600
Time (minutes)

Event 6
0,400

0,350

0,300

0,250
Flow (m3/s)

0,200 Prediction - 1993 model

Prediction - 2013 model
0,150
Actual flow
0,100

0,050

0,000
0 150 300 450
Time (minutes)

40
 Event 7
0,300

0,250

0,200
Flow (m3/s)

0,150 Prediction - 1993 model

Prediction - 2013 model
0,100 Actual flow

0,050

0,000
0 150 300 450 600
Time (minutes)

Event 8
0,400

0,350

0,300

0,250
Flow (m3/s)

0,200 Prediction - 1993 model

Prediction - 2013 model
0,150
Actual flow
0,100

0,050

0,000
0 150 300 450 600
Time (minutes)

41
 Event 9
0,160

0,140

0,120

0,100
Flow (m3/s)

0,080 Prediction - 1993 model

Prediction - 2013 model
0,060
Actual flow
0,040

0,020

0,000
0 150 300
Time (minutes)

Event 10
0,120

0,100

0,080
Flow (m3/s)

0,060 Prediction - 1993 model

Prediction - 2013 model
0,040 Actual flow

0,020

0,000
0 150
Time (minutes)

42
 Event 11
0,100

0,090

0,080

0,070
Flow (m3/s)

0,060

0,050 Prediction - 1993 model

0,040 Prediction - 2013 model

0,030 Actual flow

0,020

0,010

0,000
0 150
Time (minutes)

Event 12
0,180

0,160

0,140

0,120
Flow (m3/s)

0,100
Prediction - 1993 model
0,080
Prediction - 2013 model
0,060 Actual flow

0,040

0,020

0,000
0 150 300 450
Time (minutes)

43
Appendix E: Antecedent rainfall vs. Volumetric runoff coefficient
Antecedent rainfall vs. Volumetric runoff coefficient (48 hours)
60,0
R² = 0,1644
Volumetric runoff coefficient

6
50,0

5
40,0

30,0 7 11 2
12
20,0 8

10,0 9

0,0 3
1104
0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0 45,0
Rainfall in previous 5 days (mm)

Antecedent rainfall vs. Volumetric runoff coefficient (5 days)

0,450
12 11 R² = 0,3643
0,400
Volumetric runoff coefficient

7 2 5
0,350 1
6
9
0,300 8
4
0,250 10
3
0,200
0,150
0,100
0,050
0,000
0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0 45,0
Rainfall in previous 5 days (mm)

Antecedent rainfall vs. runoff coefficient (7 days)

0,450
12 11 R² = 0,3838
Volumetric runoff coeffcient

0,400
7 2 5
0,350 1
9 6
0,300 8
4
0,250 10
3
0,200
0,150
0,100
0,050
0,000
0,0 10,0 20,0 30,0 40,0 50,0 60,0
Rainfall in previous 14 days (mm)

44
 Antecedent rainfall vs. runoff coefficient (10 days)
0,450
11 12 R² = 0,4425
0,400
Volumetric runoff coeffcient

2 5 7
0,350 1
6
9
0,300 8
4
0,250 10
3
0,200
0,150
0,100
0,050
0,000
0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0
Rainfall in previous 14 days (mm)

Antecedent rainfall vs. Volumetric runoff coefficient (14 days)

0,450
11 12 R² = 0,51
0,400
Volumetric runoff coeffcient

2 5 7
0,350 1
6
9
0,300 8
4
0,250 10
3
0,200
0,150
0,100
0,050
0,000
0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0 80,0
Rainfall in previous 14 days (mm)

Antecedent rainfall vs. runoff coefficient (21 days)

0,450
11 12 R² = 0,3191
0,400
Volumetric runoff coeffcient

2 7
0,350 1 5
6
9
0,300 8
4
0,250
3 10
0,200
0,150
0,100
0,050
0,000
0,0 20,0 40,0 60,0 80,0 100,0 120,0
Rainfall in previous 14 days (mm)

45
 Statistical analysis
0,6

Coefficient of determination (R2)

0,510
0,5 0,443
0,409
0,384
0,4 0,364

0,3

0,2

0,1 0,061

0
0 5 10 15 20 25
Days before storm event taken into account (API)

46
Appendix F: Legislative requirements and approvals for rainwater tanks and
bioretention basins
Before undertaking a concept design of a rainwater tank system it is important to check whether there
are any planning regulations, building regulations or local health requirements that apply to the
possible installation of new rainwater tanks in the Frederick St. catchment. The most important
legislation for rainwater tanks in South Australia is listed below:

The legislation which is most applicable to the design and installation of rainwater tanks and
bioretention basins includes:

 Development Act 1993 and Development Regulations 2008

 Waterworks Act 1932 and Waterworks Regulations 1996
 Natural Resources Management Act 2004
 Environmental Protection Act 1993
 Public and Environmental Health Act 1987

The following standards apply as well:

Standard Title Purpose

AS/NZS 3500 2003 Plumbing and Drainage
Standards and the South
Australian Variations
AS/NZS 3500.1.2 Water supply – Acceptable Provides guidance for the
solutions design of rainwater tanks with
dual water supply (rainwater
and mains water)
AS/NZS 4020 Testing of Products for Use in Any materials in contact with
Contact with Drinking Water water to be used for drinking
must comply with this
standard.
AS 2179 Rain Water Storage Tanks – If a metal rain water tank is to
Metal (Rain Water) be used, it shall comply with
specifications this standard.
AS/NZS 1170 Loads on Rainwater tanks
AS/NZS 4766 Polyethylene Storage Tanks for Polyethylene rainwater tanks
Water and Chemicals shall comply with this
standard.
(Local Government Association of South Australia, 2009)

For this research, which is mainly focussed on peak flow reduction, the following requirement is the
most important:

 “Since 1 July 2006, new houses and house extensions greater than 50 square metres are
required to have an additional water supply to supplement mains water. The additional water
supply must be plumbed to a toilet, to a water heater or to all cold water outlets in the laundry.
All water sources must be connected before the house is occupied. If a rainwater tank is used
to meet the requirement for additional supply, it must have a storage capacity not less than 1
kilolitre.” (Development Act 1993 and Development Regulations 2008)

47
Appendix G: Peak flow simulation results using various WSUD measures

2040 – 1 kL new houses

Event # Intensity Date 2013 peak flow(m/s) 2040 peak flow (m/s) Change
1 High 29-04-14 0,680 0,750 10%
2 High 2-05-14 0,680 0,740 9%
3 Medium 12-09-13 0,490 0,530 8%
4 Medium 13-02-14 0,860 0,960 12%
5 Medium 14-02-14 0,660 0,690 5%
6 Medium 5-05-14 0,330 0,360 9%
7 Medium 9-05-14 0,260 0,280 8%
8 Low 21-08-13 0,410 0,450 10%
9 Low 2-10-13 0,170 0,180 6%
10 Low 8-04-14 0,130 0,130 0%
11 Low 2-05-14 0,100 0,110 10%
12 Low 9-05-14 0,140 0,150 7%

Average:
+8%
2040 – 1 kL all houses

Event # Intensity Date 2013 peak flow(m/s) 2040 peak flow (m/s) Change
1 High 29-04-14 0,680 0,720 6%
2 High 2-05-14 0,680 0,690 1%
3 Medium 12-09-13 0,490 0,480 -2%
4 Medium 13-02-14 0,860 0,960 12%
5 Medium 14-02-14 0,660 0,690 5%
6 Medium 5-05-14 0,330 0,310 -6%
7 Medium 9-05-14 0,260 0,230 -12%
8 Low 21-08-13 0,410 0,380 -7%
9 Low 2-10-13 0,170 0,150 -12%
10 Low 8-04-14 0,130 0,110 -15%
11 Low 2-05-14 0,100 0,090 -10%
12 Low 9-05-14 0,140 0,150 7%

Average:
-3%

48
2040 – 2 kL new houses

Event # Intensity Date 2013 peak flow(m/s) 2040 peak flow (m/s) Change
1 High 29-04-14 0,680 0,720 6%
2 High 2-05-14 0,680 0,720 6%
3 Medium 12-09-13 0,490 0,520 6%
4 Medium 13-02-14 0,860 0,960 12%
5 Medium 14-02-14 0,660 0,690 5%
6 Medium 5-05-14 0,330 0,350 6%
7 Medium 9-05-14 0,260 0,280 8%
8 Low 21-08-13 0,410 0,440 7%
9 Low 2-10-13 0,170 0,180 6%
10 Low 8-04-14 0,130 0,130 0%
11 Low 2-05-14 0,100 0,110 10%
12 Low 9-05-14 0,140 0,150 7%

Average:
+7%

2040 – 2 kL all houses

Event # Intensity Date 2013 peak flow(m/s) 2040 peak flow (m/s) Change
1 High 29-04-14 0,680 0,610 -10%
2 High 2-05-14 0,680 0,610 -10%
3 Medium 12-09-13 0,490 0,440 -10%
4 Medium 13-02-14 0,860 0,940 9%
5 Medium 14-02-14 0,660 0,690 5%
6 Medium 5-05-14 0,330 0,300 -9%
7 Medium 9-05-14 0,260 0,230 -12%
8 Low 21-08-13 0,410 0,370 -10%
9 Low 2-10-13 0,170 0,150 -12%
10 Low 8-04-14 0,130 0,110 -15%
11 Low 2-05-14 0,100 0,090 -10%
12 Low 9-05-14 0,140 0,120 -14%

Average:
-8%

49
2040 – 5 kL new houses

Event # Intensity Date 2013 peak flow(m/s) 2040 peak flow (m/s) Change
1 High 29-04-14 0,680 0,720 6%
2 High 2-05-14 0,680 0,720 6%
3 Medium 12-09-13 0,490 0,510 4%
4 Medium 13-02-14 0,860 0,940 9%
5 Medium 14-02-14 0,660 0,680 3%
6 Medium 5-05-14 0,330 0,350 6%
7 Medium 9-05-14 0,260 0,270 4%
8 Low 21-08-13 0,410 0,440 7%
9 Low 2-10-13 0,170 0,180 6%
10 Low 8-04-14 0,130 0,130 0%
11 Low 2-05-14 0,100 0,110 10%
12 Low 9-05-14 0,140 0,150 7%

Average:
6%
2040 – 5 kL all houses

Event # Intensity Date 2013 peak flow(m/s) 2040 peak flow (m/s) Change
1 High 29-04-14 0,680 0,600 -12%
2 High 2-05-14 0,680 0,600 -12%
3 Medium 12-09-13 0,490 0,430 -12%
4 Medium 13-02-14 0,860 0,860 0%
5 Medium 14-02-14 0,660 0,640 -3%
6 Medium 5-05-14 0,330 0,290 -12%
7 Medium 9-05-14 0,260 0,230 -12%
8 Low 21-08-13 0,410 0,370 -10%
9 Low 2-10-13 0,170 0,150 -12%
10 Low 8-04-14 0,130 0,110 -15%
11 Low 2-05-14 0,100 0,090 -10%
12 Low 9-05-14 0,140 0,120 -14%

Average:
-10%

50
2040 - Bioretention

Event # Intensity Date 2013 peak flow(m/s) 2040 peak flow (m/s) Change
1 High 29-04-14 0,680 0,770 13%
2 High 2-05-14 0,680 0,520 -24%
3 Medium 12-09-13 0,490 0,540 10%
4 Medium 13-02-14 0,860 0,950 10%
5 Medium 14-02-14 0,660 0,680 3%
6 Medium 5-05-14 0,330 0,150 -55%
7 Medium 9-05-14 0,260 0,190 -27%
8 Low 21-08-13 0,410 0,160 -61%
9 Low 2-10-13 0,170 0,050 -71%
10 Low 8-04-14 0,130 0,020 -85%
11 Low 2-05-14 0,100 0,020 -80%
12 Low 9-05-14 0,140 0,130 -7%

Average:
-31%
2040 – No WSUD

Event # Intensity Date 2013 peak flow(m/s) 2040 peak flow (m/s) Change
1 High 29-04-14 0,680 0,760 12%
2 High 2-05-14 0,680 0,750 10%
3 Medium 12-09-13 0,490 0,540 10%
4 Medium 13-02-14 0,860 0,970 13%
5 Medium 14-02-14 0,660 0,690 5%
6 Medium 5-05-14 0,330 0,370 12%
7 Medium 9-05-14 0,260 0,290 12%
8 Low 21-08-13 0,410 0,460 12%
9 Low 2-10-13 0,170 0,190 12%
10 Low 8-04-14 0,130 0,140 8%
11 Low 2-05-14 0,100 0,110 10%
12 Low 9-05-14 0,140 0,160 14%

Average:
11%

51
Appendix H: Maps and statistics

(Source: Australian Bureau of Meteorology)

(Source: Australian Bureau of Meteorology)

52
(Source: Australian Bureau of Meteorology)

53