Se

awater quality effects of urbanisation. In this review, ten existing stormw

LID. The models are all based on conventional methods for runoff generation and routing, but half of the models add a groundwater/baseflowcomponent and several include infiltration from LID devices. The models also use conventional methods for contaminant generation and treat-ment such as buildup-washoff conceptual models and first order decay processes, although some models add treatment mechanisms specific toparticular types of LID device. Several models are capable of modelling distributed on-site devices with a fine temporal resolution and contin-uous simulation, yet the need for such temporal and spatial detail needs to be established. There is a trend towards incorporation of more types ofLID into stormwater models, and some recent models incorporate a wide range of LID devices or measures. Despite this progress, there aremany areas for further model development, many of which relate to stormwater models in general, including: broadening the range of contam-inants; improving the representation of contaminant transport in streams and within treatment devices; treating baseflow components and runofffrom pervious surfaces more thoroughly; linkage to habitat and toxicity models; linkage to automated calibration and prediction uncertaintymodels; investigating up-scaling for representation of on-site devices at a catchment level; and catchment scale testing of model predictions. 2006 Elsevier Ltd. All rights reserved.

Keywords: Stormwater; Catchment; Model; Review; Urban drainage; Low impact

1. Introduction

Worldwide, there is a well documented decline in habitatand water quality of urban streams. Urbanisation is typicallyaccompanied by increases in impervious surfaces such as roofsand roads, construction of hydraulically efficient drainage sys-tems, compaction of soils, and modifications to vegetation.This results in increased flood flows (Leopold, 1968) andstream erosion (Hammer, 1972), and the potential fordecreased baseflow (Paul and Meyer, 2001; Schueler, 1994).Urbanisation also leads to water contamination from

suspended sediments, heavy metals, hydrocarbons, nutrients,and pathogens (Burton and Pitt, 2001; Hall, 1984).

In the last two decades, new urban water managementapproaches have been developed to deliver improved environ-mental, economic, social and cultural outcomes. We term suchan approachLID (low impact development), but alternative acro-nyms are SUDS (sustainable urban drainage systems), WSUD(water sensitive urban design), and LIUDD (low impact urbandesign and development, a term used inNewZealand). In this re-view, we focus on stormwater aspects of LID, with limited atten-tion to broader issues of integrated urban water cycleA review of models for low im

A.H. Elliott a,*,a National Institute of Water and Atmospheric Re

b Landcare Research, Private Ba

Received 3 April 2005; received in revised form

Available onlin

Abstract

Low-impact development urban stormwater drainage systems (LID)

Environmental Modelling & Softw* Corresponding author. Tel.: 64 (9) 8567026; fax: 64 (9) 8560151.E-mail address: s.elliott@niwa.co.nz (A.H. Elliott).

1364-8152/$ - see front matter 2006 Elsevier Ltd. All rights reserved.doi:10.1016/j.envsoft.2005.12.005pact urban stormwater drainage

.A. Trowsdale b

search, PO Box 11-115, Hamilton, New Zealand

g 92170, Auckland, New Zealand

2 December 2005; accepted 13 December 2005

3 March 2006

re an increasingly popular method to reduce the adverse hydrologic andater models are compared in relation to attributes relevant to modelling

are 22 (2007) 394e405www.elsevier.com/locate/envsoftmanagement. The scope is also limited to the effects of storm-water on water quality and quantity, rather than visual, socialand economic impacts.

LID devices are designed to detain, store, infiltrate, or treaturban runoff, and so reduce the impact of urban development

l(e.g. Wong et al., 2002; NZWERF, 2004). LID devices includestructural measures such as wetlands, ponds, swales, rainwatertanks, bioretention devices, vegetated filter strips, and filterstrips. LID approaches also include non-structural measuressuch as alternative layouts of roads and buildings to minimiseimperviousness and to maximise the use of pervious soils andvegetation, contaminant source reduction, and programmes ofeducation to modify activities. LID particularly emphasiseson-site small-scale control of stormwater sources. Manydesign guidelines for such devices are now available (e.g.,CIRIA, 2000).

Despite an increasing awareness and knowledge of these is-sues and potential solutions, the transition to more sustainableurban drainage design has been slow. This may reflect, amongother factors, a dearth of LID drainage design tools that oper-ate effectively at the necessary range of scales. The availabilityof effective LID modelling software could act to encouragewider uptake of LID principles (Beecham, 2002). Tools canmake design and application of LID more efficient, and dem-onstrate outcomes that can be used for education and policydevelopment. The challenge is to translate complex and highlyvariable natural processes into a computerised system or toolthat allows straightforward evaluation of LID drainage mea-sures at a range of scales applicable to urban management.

This paper explores the current range of LID assessmenttools, discusses their strengths and weaknesses and puts for-ward future research needs, with the aims of aiding model se-lection, increasing awareness of the available models, andencouraging model development.

1.1. Previous reviews

Zoppou (2001) reviewed both quantity and quality aspectsof urban stormwater models. He provided an overview ofstormwater modelling approaches, with a concise mathemati-cal description of common methods for flow routing and con-taminant generation and transport. He also described severalstormwater models. Burton and Pitt (2001, Appendix H) re-viewed catchment and receiving water modelling in relationto stormwater. They classified the catchment models primarilyaccording to the complexity, ranging from simple methods(based on export coefficients or event-mean concentrationsmultiplied by runoff volume) through to complex modelsthat are typically spatially distributed and processed based.McAlister et al. (2003) reviewed urban stormwater qualitymodels, and stressed the importance of using suitably smalltemporal resolution and continuous simulation over one ormore years. Beecham (2002) presented key features of fourmodels for water sensitive urban design, but did not compareand contrast the models or discuss their suitability. Other re-views of contaminant models (e.g. the review of sedimentmodels by Merritt et al., 2003) are not focussed on urbanstormwater or LID.

These previous reviews provide a valuable background onthe features of a range of models, methods for representing

A.H. Elliott, S.A. Trowsdale / Environmentakey processes, and categorisations of the models. However,none of them focus specifically on the ability of the modelsto represent LID. In this review the focus is urban storm-water models and LID.

1.2. Review process and structure

We identified approximately 40 models for urban storm-water from previous published reviews, journal abstractingservices, internet searches, conference proceedings, and mod-elling practitioners. We then selected 10 models that are cur-rently available and have not been superseded, havesufficient documentation in English, and are more than a con-ventional stormwater drainage/hydrology model. Our assess-ment is based on versions of the models available inFebruary 2005, and the range of models and the features ofthe models may have changed since that time.

The ten models (Table 1) were compared in relation tothe following attributes:

e The intended uses of the model including research, publiceducation, developing device sizing rules, catchment plan-ning, and conceptual to detailed design. All these levels ofmodel use are relevant to LID.

e Temporal resolution and scale. The temporal resolution re-fers to the smallest computational timestep of the model.We also distinguish between models intended only fora single rainfall event and those intended for simulationof a long-term sequence of events (continuous simulation)as discussed in Singh (1995).

e Catchment and drainage network representation, andspatial resolution and scale. The catchment and drain-age representation refers to the types of element thatare used to represent the catchment, soil column andgroundwater, drainage network, and treatment or flowcontrol devices. We categorise models according towhether they are lumped (a single catchment element),quasi-distributed (where the model is broken intoa number of elements such as subcatchments), or fullydistributed (usually grid or mesh-based) as discussed inSingh (1995). In each of these categories, we includecases where the catchment element is broken downinto a number of land uses, surface types or stormwatertreatment categories. Spatial scale refers to the size ofthe modelled area.

e Representation of runoff generation, routing to the drain-age network, routing within the drainage network, andgroundwater movement.

e Types of contaminant included in the models, and methodsused to represent processes of contaminant generation,transport and treatment.

e LID devices or technologies specifically included in themodel, or able to be simulated indirectly using the model.The devices assessed range from on-site non-structuralcontrols such as reduction of imperviousness, to regionalscale wetlands.

395Modelling & Software 22 (2007) 394e405e User interface and integration with other software such asautomated calibration software or receiving-water models.

Primary intended use

e.

th

s

Detailed simulation of urban drainage.

Widespread use outside USA

Conceptual design for drainage systems,

with emphasis on treatment devices.

Popular in Australia

Estimation of urban stormwater

pollutant load

Single site water use model. Originally

for research but now includes commercial

users, especially for rain tanks

Preliminary planning or education

Planning tool for load of contaminants

Management of lake catchments and

conceptual design of stormwater

treatment. Applied in Scandinavia

Detailed model for planning and

preliminary design. Widely used

Integrated water cycle, water re-use,

Used mainly for research in Australia

: Planning-level assessment of

water quantity. Strong support in British

Columbia

396

A.H.Elliott,

S.A.Trow

sdale/Environm

entalModelling

&Softw

are22

(2007)394

e405Table 1

Name and introductory information for the selected models (unless stated otherwise, the source code is not available)

Model Versions References Primary author or

organisation

Cost (USD)

MOUSE First: 1985.

Latest: MOUSE 2004

DHI, 2002aed; http://www.

dhisoftware.com/mouse

DHI Water and

Environment

w5000 for basic flow modulFurther modules comparable.

MIKE STORM, a version wi

reduced capabilities, costs les

MUSIC (Model for

Urban Stormwater

Improvement Conceptualisation)

First: 2000. Latest:

Version 2.0, 2003

Chiew and McMahon, 1999;

MUSIC Development

Team, 2003;

Wong et al., 2002; http://www.

toolkit.net.au/music

Monash University and

the CRC for Catchment

Hydrology, Australia

w300

P8-UCM First: 1990. Latest:

Version 2.4, 2002

Palmstrom and Walker, 1990;

http://wwwalker.net/

William W.

Walker Jr.

Free

PURRS (Probabilistic

Urban Rainwater and Wastewater

Reuse Simulator)

First: c. 1999. Latest:

Version 6.5, 2004

Coombes, 2002;

http://rambler.newcastle.edu.

au/wcegak/Coombes/

Peter Coombes, Newcastle

University, Australia

w800

RUNQUAL Latest 1999 http://wri.eas.cornell.edu/

products/software/runqual/

Douglas Haith, Cornell

University

Free, including

source code

SLAMM (Source

Loading and Management Model)

Latest: Winslamm 8.7,

2004

Pitt, 1998; PV & Associates Bob Pitt, University of

Alabama.

200

StormTac Latest: 2004 Larm, 2000, 2003; http://

www.stormtac.com

Thomas Larm, SWECO

VIAK

2500

SWMM (Storm Water

Management Model); XP-SWMM;

PCSWMM; MIKESWMM

First: 1970. Latest:

SWMM5 in 2004

Rossman 2004; Huber and

Dickinson 1988.

Proprietary versions are XP-

SWMM

(http://www.xpsoftware.com.au/

products/xpswmm.htm),

PCSWMM (http://

www.computationalhydraulics.

com/) and MIKE-SWMM (http://

www.dhisoftware.

com/mikeswmm/)

Various for USEPA. USEPA version is free,

including code

UVQ (Urban

Volume and Quality)

First: 2000 Mitchell et al. 2003;

Mitchell and Diaper (2006)

CSIRO and Monash

University, Australia

Available for a

small charge

Water Balance

Model (WBM)

First: 2004 http://www.waterbalance.ca Greater Vancouver Regional

District

Web-based. Basic model free

ongoing licence payment

for full model

ning or preliminary design, which may reflect an attempt toencourage LID by targeting the level of use in which broadprinciples start to be converted to designs or planning mea-sures for specific catchments or sites. MUSIC, P8 and WBMare best suited for conceptual or preliminary design at eithera subdivision or catchment scale.

2.2. Temporal resolution and scale

The temporal resolution of the models ranges from annualaverage to sub-hourly (Fig. 2). Models with the capability forsmall timesteps can also usually be run with longer timesteps.If dynamic-wave flow routing is used, timesteps in the order ofa second may be required to maintain numerical stability, butthis is probably finer than required for representing the runoffgeneration, contaminant generation, or contaminant transportand treatment processes.

MOUSEMUSIC

P8

PURRS

RUNQUALSLAMM

StormTacSWMM

UVQWBM

Public

educ

ation

Plann

ing of

landu

se

Rese

arch

Prel

Deve

loping

sizing

rules

for d

evicesFig. 1. Potential uses for the selected models. Grey shadinwhile MUSIC (with its smallest timestep of 6 min) is margin-ally suited. On the other hand, for the purpose of establishingcontaminant loads and annual water balance (rather than thetiming of loads and flow rates), longer timesteps may be ade-quate. This aspect of temporal resolution requirements war-rants further systematic evaluation. In the absence of suchstudies, there is likely to be a trend to the use of small time-steps, even though small timesteps may not actually berequired to adequately address a particular management issue.

2.3. Catchment and drainage network representation,and spatial resolution and scale

Four models (MOUSE, MUSIC, SWMM and P8) are spa-tially distributed with a link-node drainage network. Each ofthe catchment elements in these models is associated witha node of the network, and treatment or flow control devicesare also placed at nodes. The nodes are linked by drainage

Detai

led de

sign o

f regio

nal dr

ainag

e syst

em

in catc

hmen

ts/citie

s

Site la

yout a

nd m

ateria

ls sele

ction

imina

ry de

sign o

f regio

nal co

ntrols

Detai

led de

sign o

f subd

ivision

or sit

e

Prelim

inary

desig

n of a

subd

ivision

or sit

e2. Comparison of models in relation to selected attributes

Basic information on the models (such as cost and avail-ability) is given in Table 1. In this section we compare themodels in relation to the set of attributes described aboveand discuss how this relates to representation of LID, but weleave a discussion of the collective limitations of the modelsuntil Section 3.

2.1. Potential uses of the model

The range of uses for each of the selected models is sum-marised in Fig. 1. Two of the models (MOUSE andSWMM) are suitable for a wide range of uses, yet they aretoo complex to be used by the general public or non-modellingplanners. Other models (StormTac and PURRS) have a com-paratively restricted range of uses. The remaining six modelshave a moderate range of uses, mostly clustered around plan-

All the models are capable of long-term continuous simula-tion (with the exception of StormTac which is based on meanannual average values). Simulations covering 10 years or moreare computationally feasible, provided that the level of spatialdetail is not excessive (say, less than 200 spatial elements) andprovided that stability constraints do not necessitate very smalltimesteps (in the order of one second).

MOUSE, SWMM, and MUSIC are most suited for predic-tion of flow rates from small catchments, while the daily or an-nual models (RUNQUAL, SLAMM, StormTac and UVQ) areunsuited for this purpose. MUSIC has a smallest timestep of6 min, so it has limited applicability for predicting flow ratesfrom areas smaller than about 0.01 km2.

For modelling of small on-site LID devices and smallcatchments, sub-hourly timesteps may be required as the time-scale of variation in the runoff and associated treatment pro-cesses is likely to be in the order of minutes (McAlisteret al., 2003). MOUSE and SWMM are suited for this purpose,

397A.H. Elliott, S.A. Trowsdale / Environmental Modelling & Software 22 (2007) 394e405g indicates that the model is marginally suited to that use.

Runoff generation

Routi

ng th

rough

devic

es

Hydro

logic r

outing

in dra

inage

netwo

rk

Hydra

ulic ro

uting

Grou

ndwa

ter/ba

seflow

Routi

ng to

drain

age n

etwork

Runo

ff coe

fficien

t

Conce

ptual r

ainfall

-runo

ff

SCS C

urve N

umbe

r

Furth

er run

off ge

nerat

ion op

tions

(e.g. G

reen-A

mpt)

Routing

MOUSEMUSIC

P8PURRS

RUNQUALSLAMM

StormTacSWMM

UVQWBMelements (pipes or channels). In MOUSE, the catchment ele-ment is divided into a number of different contaminant-generatingsurfaces or land uses, whereas in the other link-node models thecatchment element is taken to be homogeneous in relation tocontaminant generation. UVQ has a novel representation ofthe catchment, using three nested spatial components (propertyor unit block, neighbourhood or land use, and catchment) so thata range of scales and associated types of water management canbe addressed. These quasi-distributed models allow for explicitrepresentation of the spatial distribution of LID devices.

The remaining models (PURRS, RUNQUAL, SLAMM,StormTac and WBM) treat the catchment in a lumped fashionwith no drainage network, except that the catchment may bebroken into a number of land uses or surface classes (withthe exception of PURRS).

All the models except for StormTac divide the catchmentelements (such as subcatchments) into pervious and impervi-ous components for runoff generation.Fig. 3. Runoff generation and routinOver half of the models (MOUSE, MUSIC, PURRS,SWMM, UVQ and WBM) include soil moisture stores (upto three) in each catchment element, and five models includea groundwater store in each catchment element (Fig. 3).

Most of the models have no inherent limit on the spatialextent of the modelled area, and could be set up for a rangeof spatial scales encountered in urban areas, ranging froma single site (w100 m2) up to medium catchments(w10 km2). An exception is PURRS, which is only intendedfor single sites. However, the timestep in some of the models(such as P8) means that predictions of flow rates would not bereliable for small catchments.

The maximum number of elements in the quasi-distributedmodels is also of interest for those cases where the modellerwishes to incorporate considerable spatial detail or complexity(as may occur for modelling large catchments or on-site LID).P8 has a limit of 192 catchment elements. MUSIC would beimpracticable to use with more than about 100 catchmentLump

ed da

ily or

even

t

Lump

ed ho

urly o

r sub

-hourl

y

Distrib

uted h

ourly

Lump

ed an

nual

avera

ge

Distrib

uted d

aily

Distrib

uted s

ub-ho

urly

MOUSEMUSIC

P8

PURRS

RUNQUALSLAMM

StormTacSWMM

UVQWBM

Fig. 2. Spatial and temporal resolution of the selected models.

398 A.H. Elliott, S.A. Trowsdale / Environmental Modelling & Software 22 (2007) 394e405g methods for the selected models.

elements, as the data need to be entered manually and largefiles are created. The level of detail in SWMM and MOUSEmay be limited by computational constraints, especially forlong-term simulation and dynamic flood routing. UVQ canpotentially be used for spatially complex models, due to thehierarchical spatial configuration and daily timestep.

2.4. Runoff generation

Most of the models are similar in the way that runoff fromimpervious areas is generated, and this is the dominant effectof urbanisation on runoff generation. The models mostly usesimple conventional rainfall-runoff methods for generatingrunoff from pervious areas (Fig. 3). MOUSE includes an ini-tial-and-continuing loss option while SWMM includesa Green-Ampt infiltration option. MUSIC uses daily calcula-tions to determine the volumes of runoff for each runoff com-ponent, then temporal disaggregation based on the rainfallpattern to break each of these components into a sub-dailytime distribution. There is no clear advantage of one of therunoff generation methods over another in relation to model-ling of LID. They are all likely to need calibration or develop-ment of suitable regional parameters, and all are somewhatcoarse in relation to treatment of the effects of vegetation(on soil moisture and interception).

Several models also include a baseflow runoff component,which is relevant to LID because maintenance of the baseflowis often a goal of LID. MOUSE, MUSIC, P8 and UVQ usea single linear lumped groundwater reservoir in each subcatch-ment, while SWMM has an additional unsaturated zone andthe groundwater reservoir is non-linear.

2.5. Flow routing

Eight of the models have no routing of flow between thepoint of runoff generation and the modelled drainage network(Fig. 3). This is appropriate for six of the models which are notintended to resolve fine-scale temporal flow variations.MOUSE and SWMM do include routing of runoff to the drain-age network, including a range of conventional methods suchas reservoir routing, unit-hydrographs, and time-area routing.In MUSIC, such routing would have to be represented approx-imately using a drainage link, and the minimum timestep of6 min would have the effect of smoothing of flows for smallcatchments. PURRS does not include routing, but the user isadvised to select a timestep comparable to the on-site timeof concentration which partially accounts for runoff attenua-tion. Such lags could be important in relation to modellingthe flow rates from small or medium size catchments, whichis particularly relevant to modelling of on-site LID devices.However, resolving such lags and temporal detail in the flowsis probably of secondary importance in relation to predictingthe effects of LID on contaminant loads. In SWMM5, over-land flow can also be routed between sub-areas within a sub-

A.H. Elliott, S.A. Trowsdale / Environmentalcatchment or between subcatchments, and this capabilitycould be useful for representing LID (for example, by allowingrunoff from roofs to pass over a pervious depression storagearea).

All the models bar one (Stormtac) route flow throughdevices (Fig. 3). Simple level-pool routing is used for routingflows through devices in all the models, but the models vary inthe details such as the types of outflow, specifications of theoutflow rates, and specification of the device dimensions.Models such as SWMM and MOUSE are the most flexiblein this regard. MUSIC allows for flow to bypass devices, butreservoirs must have vertical sides and the outlets have a sim-ple configuration. In SWMM and MOUSE, the outflow can becontrolled by downstream water levels if the hydraulic flowrouting option is used. MUSIC, PURRS, and UVQ allow fortime-varying abstraction of water from devices for irrigationor household use. These capabilities are of direct relevanceto modelling particular types of LID device.

MUSIC and P8 use hydrologic routing in the drainage net-work (time-lag, linear reservoirs, or MuskinghameCungerouting). Two models (MOUSE and SWMM) are capable ofdynamic-wave hydraulic routing, and they are also capableof simpler routing methods such as kinematic wave routingor hydrologic routing. For representation of LID, fully dy-namic flood routing would often not be necessary, except per-haps in the lower reaches of a catchment where backwatereffects are more likely or for off-line detention facilites.

2.6. Contaminant range, generation, transport,and treatment

2.6.1. Range of contaminantsThe contaminants included in each of the models are shown

in Fig. 4. Two of the models (PURRS and WBM) deal onlywith flow. The remaining models can be used to model sedi-ment, nutrients, heavy metals, and other sediment-related toxiccontaminants, although heavy metals are included explicitly inonly half of these models. In some models (such as P8) themain emphasis is on sediment, while other contaminants aremodelled through their association with sediments plus a dis-solved fraction. Only MOUSE has the capability to addressdissolved oxygen in streams, and only MOUSE deals withpathogenic organisms or associated bacterial indicators (buteven then only in a generalised and simple fashion).

In many cases, a given model is not set up to simulate a par-ticular contaminant explicitly, but can be used to represent thatcontaminant either by using generic contaminant generationand treatment options, modelling another contaminant thathas similar behaviour, or by specifying the association of thecontaminant with sediment.

2.6.2. Contaminant generationThe models use a range of methods for contaminant gener-

ation, which are discussed in Zoppou (2001). The methods in-clude: buildup-washoff (MOUSE, RUNQUAL, SLAMM, P8and SWMM5); characteristic concentrations (MUSIC, Storm-Tac, UVQ, SLAMM, RUNQUAL and XP-SWMM), some-

399Modelling & Software 22 (2007) 394e405times with a stochastic component (MUSIC, SLAMM andXP-SWMM); empirical power rating curves for concentration

are calculated as fixed (hard-coded) functions of hydraulic load-

2.6.3. Contaminant transport and treatment processes

In MOUSE, SWMM, and P8 contaminants are transportedthrough the network by treating the links as well-mixed reser-voirs with first order decay, except that MOUSE can also usethe advection-dispersion equation and P8 allows for second or-der decay. For dissolved oxygen and biological oxygen demand,MOUSE allows for re-aeration and interaction with bed sedi-ments. In UVQ, contaminants are transported conservativelyin the links with no lags (the timing is not relevant as only dailycalculations are performed). InMUSIC, contaminants are trans-ported conservatively through links but with either a time lag ordispersion based on MuskinghameCunge routing. MOUSEincludes a sediment erosion component intended to representsediment deposits in pipes. Formost contaminants, simple trans-port methods are likely to be adequatewhen the drainage systemis dominated by pipes.

In those models with infiltration devices (see Section 2.7),

ing. The filtration efficiency of bioretention filter media is deter-mined using fixed empirical relations based on the retention timein themedium and particle size of themedium. The user can alsodefine a concentration rating curve for any device.

Some other models include treatment in LID devices andmeasures apart from ponds and infiltration. In RUNQUAL,vegetated filter strips are modelled by assuming completeremoval of sediment for strips of 30 m length with performancereduced in proportion to the length for shorter filters, while dis-solved contaminants are not removed. In SLAMM the removalof sediment through street sweeping and catchbasin cleaning iscalculated from empirical equations. In UVQ the user specifiesa removal efficiency or required output quality for each device.

2.7. LID devices or practices

The ability of the models to incorporate LID devices andas a function of flow rate (P8 and SWMM5); and unit arealoadings (StormTac). In some models the method dependson the contaminant, and some models include a range ofmethods. SWMM5 allows for a user-defined BMP reductionefficiency to be applied to the contaminant sources, separatefrom the treatment that occurs in devices. P8 and MOUSEmodel two or more sediment fractions plus a dissolved frac-tion, and other contaminants are modelled through their asso-ciation with each of the size fractions. In SWMM and MUSIC,the concentrations in baseflow can be specified separatelyfrom stormflow concentrations.

All the methods for representing contaminant generationrely on empirical parameters relating to concentrations, yields,or buildup-washoff processes. This reflects the limited knowl-edge of the processes and process rates for contaminant gener-ation. The particular method has little bearing on thesuitability of the models to represent LID, except that methodswith a range of particle sizes permit more detailed representa-tion of contaminant removal processes in devices.

MOUSEMUSIC

P8

PURRSRUNQUAL

SLAMMStormTac

SWMMUVQWBM

Sedim

ent

Nutrie

nts

Heav

Fig. 4. Contaminants included in the selected models. Grey shading indicates

400 A.H. Elliott, S.A. Trowsdale / Environmentalthe removal of contaminants due to infiltration is determinedfrom the product of the infiltration rate and the concentrationin the device. This removal processes is very relevant toseveral LID devices. The infiltrated contaminants do not re-emerge into the drainage system and the groundwater contam-ination is not considered, except that in P8 a removal effi-ciency in groundwater can be applied.

Most of the models include contaminant treatment in ponds,determined using sediment settling theory (SLAMM, P8,MOUSE, and in a simple manner, RUNQUAL), first or secondorder decay (MUSIC and P8), removal fractions or output con-centrations (UVQ and StormTac), or user-specified functions ofvariables such as flow rate (SWMM). All these methods rely onuser inputs for rate parameters or sediment settling rates.

In MUSIC, a number of devices apart from ponds can bemodelled. Treatment in biofilter storage areas and swales ismodelled using a series of well-mixed reactors with first orderquasi-steady removal kinetics, plus removal with infiltration.Treatment in gross pollutant traps is modelled with a concentra-tion rating curve (inflow concentration versus outflow concen-tration). For buffer strips, concentration reduction efficiencies

y meta

ls, oth

er tox

ics

Patho

gens

Temp

eratur

e

BOD,

Dissol

ved ox

ygen

models where the contaminant can be modelled only coarsely or indirectly.

Modelling & Software 22 (2007) 394e405measures, a key consideration in this review, is summarisedin Fig. 5. In many cases a model can be used to represent

cO

n

lgeneration sub-model (e.g. Department of EnvironmentalResources, 1999; Guther et al., 1996; Kandasamy andOLoughlin, 1995).

All of the models in this review can be used to investigatethe effects of reducing imperviousness. They can also be usedto represent the effects of soil protection or improvement, byaltering infiltration parameters.

All the water quality models can be used to represent thereduction of contaminant generation by altering the storm con-centrations or yields, or mix of land uses. However, none ofthe models deal specifically with contaminant reduction dueto the use of source-reduction practices such as altered con-struction or vehicle emissions controls to reduce contaminantinputs to the urban system, which is part of the LID philoso-phy. Hence some major opportunities to limit contaminantgeneration may not be able to be simulated explicitly.

All the models except PURRS include ponds or wetlands,reflecting the widespread use of these devices. The modelsdo vary in the details of flow routing and contaminant treat-ment in such devices (Sections 2.5 and 2.6), which is a factor

Runon (passing runoff from an impervious area to a pervi-ous area) is allowed for explicitly in four of the models,although only two of those models are water quality models.In MUSIC, P8, SLAMM, and RUNQUAL, infiltration throughrunon could be modelled approximately using a buffer strip orinfiltration device. MUSIC could also address contaminantremoval approximately through the buffer strip removal equa-tion. In other models, runon could be represented coarsely byreducing the impervious area.

Three models (MUSIC, PURRS and UVQ) are set up tomodel rain tanks. PURRS gives tanks special attention, whileUVQ focuses on water budget aspects rather than flow rate.Other models could be used to represent rain tanks usingdetention tanks with a constant withdrawal rate.

Bio-retention devices or filtration devices are included onlyin MUSIC and WBM, and WBM is limited to water quantityaspects. Other flexible models such as MOUSE and SWMMcould model flow aspects of these devices indirectly and ap-proximately using storage/infiltration devices. Bioretentiondevices of the type that rely predominantly on infiltration intoa device indirectly, even though it does not cater explicitly forthat type of device. For example, a rain tank with constantwithdrawal, an orifice outlet, and an overflow can be modelledwith MOUSE by using suitable combinations of devices andoutlet types (Kettle et al., 2004). Many standard hydrologic/hydraulic models can be used to model the hydrological impli-cations of LID, particularly the storm flow implications: theycan predict the effect of changes in imperviousness on stormflows; most of them include detention ponds; they can repre-sent the flow-retarding effects of swales either explicitlywith a detailed drainage network or in an approximate wayby adjusting the catchment routing parameters; and on-sitedetention can be modelled either as small ponds or approxi-mately by increasing the depression storage in the runoff

MOUSE

MUSICP8

PURRS*RUNQUAL

SLAMMStormTac

SWMMUVQ

WBM*

Impe

rviou

snes

s red

uctio

n

Redu

ction o

f

conta

mina

nt ge

nerat

ion

Infiltr

ation

tren

Pond

s and

wetla

nds

Soil p

rotect

ion

Fig. 5. LID devices and measures included in the selected models. Grey shading i

model the device. Models with an asterisk do not address water quality.

A.H. Elliott, S.A. Trowsdale / Environmentato consider when selecting a model in catchments where pondsand wetlands are an important component.Most of the models can be used for infiltration devices, butusers of SWMM and MOUSE would need to represent theinfiltration by an outlet in a tank (rather than infiltration intothe soil), and StormTac does not include infiltration devices at all.

Sevenof themodels represent on-site detention tanks explicitlyalthough P8, RUNQUAL, WBM, and UVQ would only be suit-able for assessing the volume effects of the tanks (not flow rates)due to the fairly coarse timestep use in these models.

The water quality, infiltration, storage, and hydraulic as-pects of swales are addressed by MUSIC, while WBM andSLAMM model only the infiltration function of swales. Thehydraulic aspects of swales can also be modelled using linksin P8, MOUSE, and SWMM, but without infiltration (unlessit is represented as a throttled pipe outflow).

Gree

n roo

fs

Bio-re

tentio

n, rai

n gard

ens

Filtra

tion d

evice

s

Runo

n

hes/b

ores

Swale

s

Rain

tanks

n-site

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Perm

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pavin

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dicates that the model does not explicitly address the device, but could be used to

401Modelling & Software 22 (2007) 394e405the soil (without underdrains or significant evapotranspiration)could be modelled as infiltration devices.

None of the models include permeable paving explicitly,but four of them could be used to represent permeable pavingby adjusting the parameters of a pervious sub-area.

Only WBM addresses green roofs specifically. Somemodels could represent green roofs indirectly by changingthe soil and subsoil properties in a given area. This limitedtreatment of green roofs reflects their relatively recent intro-duction into the range of LID devices.

2.8. User interface and model integration

The user interfaces of the models cover a range of sophis-tication. PURRS uses text input/output files, while P8 andRUNQUAL add a text-based interface including menus.SLAMM and UVQ are also essentially based on menus andtext entry, but are based on Microsoft Windows rather thanDOS. WBM also uses text-based input with menus, but isdriven with an internet-based forms/database system. Storm-Tac is based on a Microsoft Excel spreadsheet with graphicalelements. The interfaces for SWMM, MOUSE, and MUSICare centred on a spatial editor, with forms-based input of infor-mation for user-selected objects representing components ofthe catchment, devices, and drainage elements. MOUSE andSWMM input files can also be edited manually. Such sophis-ticated and attractive interfaces are likely to promote the use ofthe models in mainstream engineering and planning practice,which could influence the uptake of LID.

Most of the models allow for a range of state and flux vari-ables to be output in text files, along with statistical summa-ries, while some of the models (MOUSE, MUSIC, SWMMand WBM) also display graphs of results. In MUSIC,MOUSE, and SWMM, the simulation results can be accessedthrough the spatial editor (by clicking on the relevant object).

Few of the models incorporate or are linked to calibrationor prediction-uncertainty models. MOUSE and PC-SWMMincorporate automated calibration routines, although this isfor the hydrograph only. Other models allow the user toview measured hydrographs against predicted hydrographs,to assist with manual calibration of the flow components.Those models with text-based input files could be optimisedwith third-party software such as PEST (Watermark Numeri-cal Computing).

3. Trends in model development and gapsin model capabilities

There is a trend towards introducing LID devices into con-ventional stormwater drainage models, either by modifyingconventional models, building new models based on conven-tional modelling approaches, or documenting how methodsto model LID devices indirectly. For example, infiltrationsource control devices have been recently incorporated intoWinDes (http://www.microdrainage.co.uk), and there are plansto incorporate more types of distributed stormwater controlsinto SWMM5 (personal communication, Lewis Rossman,

402 A.H. Elliott, S.A. Trowsdale / EnvironmentaCDM). This trend is expected to continue given the institu-tional investment in existing conventional models.We also expect that more types of LID devices will beincorporated into stormwater models as information on theirperformance becomes available and as new types of deviceare developed. Representation of LID devices is likely to berefined as more performance monitoring data becomes avail-able and as the understanding of processes increases.

There is a trend to make existing models easier to use. Forexample, the USEPA version of SWMM has recently beenupgraded to include a spatial editor. Database-orientedmanagement of model inputs and metadata, and use of GIS(either incorporated within the main model software or linkedto the models) is growing. For example, DHI are developinga modelling framework, MIKE-URBAN, which will use GIScomponents and will drive models such as MOUSE andSWMM. Similarly, there are plans to move MUSIC into anintegrated modelling environment with a GIS basis (personalcommunication, Tim Fletcher, Monash University). As themodels become easier to use, it can be expected that their pop-ularity will increase which may in turn promote the use ofLID. As LID components are included explicitly in suchmodels, LID will be considered more frequently as a main-stream design component for urban stormwater systems.

There is a trend towards the use of continuous long-termsimulation. This is in part because computers now have thespeed and storage capacity to allow long-term simulationwith reasonable run-times. It is also in part due to a realisationof the importance of antecedent moisture conditions for smallstorms, which is accommodated by continuous simulation. In-deed, most of the models we reviewed include continuousmodelling capability. We expect, however, that a need for sim-pler annual average models and device sizing guidelines willre-emerge as a convenient way to encapsulate the knowledgeand results from more complex detailed models.

Management and ecosystem components are likely to beadded to core hydrology and water quality components. Forexample, life-cycle costing and ecosystem effects models arebeing incorporated into MUSIC (personal communication,Tim Fletcher, Monash University).

Despite the considerable number of stormwater models thatcan be applied to LID, and a commonality in process represen-tation and model interfaces suggesting a maturing of the soft-ware in this area, several significant gaps in the capabilities ofthe models remain. In our opinion, these limitations precludecomprehensive predictions of the effects of LID on hydrologyand water quality and the resulting ecosystem effects. Whileall models involve a degree of approximation and specialisa-tion, it is important for the stormwater modeller to understandthe limitations of the models. Highlighting these limitationsalso points to opportunities for further research anddevelopment.

The models we reviewed do not address some key waterquality parameters of interest. None of the models includetemperature, despite this being an important stressor in urbanstreams (Burton and Pitt, 2001), although some specialistmodels for urban stream temperature have been developed

l Modelling & Software 22 (2007) 394e405recently (e.g., ul Haq and James, 2002). Only one of thereviewed models (MOUSE) addresses dissolved oxygen

depletion, and even then the emphasis is on wastewater dis-charges rather than stormwater. Most of the models have lim-ited or no ability to predict pathogenic micro-organisms orbacterial indicators, yet these are of major concern even forseparated stormwater systems. None of the models are wellsuited for the prediction of sediment loads during the earth-works phase of development.

The models we reviewed are not well suited for site or sub-division fingerprinting to maximise the use of absorbent soilsand natural features and to minimise imperviousness, or forthe selection of construction materials on a site and otheremissions controls to reduce the production of contaminants,yet this is surely where low-impact development approachesshould start. At present such source controls must be modelledby adjusting soil properties or contaminant load parameters.

The models are not integrated with ecosystem effectsmodels, limiting their ability to predict the benefits of LIDon the stream ecosystem, which is a key purpose of LID.None of the models are linked to habitat models such as ero-sion or baseflow habitat models, none of them predict contam-inant accumulation in streams or estuaries (effects are judgedfrom water column concentrations or load reduction percent-ages), and none are linked to bioaccumulation models for toxiccontaminants.

There is scope for improving the representation of contam-inant transport and removal processes. For example, the effec-tiveness of various filter media on contaminant removal couldbe included. There is no explicit modelling of the effects ofvegetation on settling or sorption of contaminants. The modelsincorporate few, if any, chemical or biochemical processessuch as sorption/desorption and complexation, particle interac-tions, biological uptake reactions, or generation of organicsediments. None of the models attempt to represent the contri-bution to sediment load from erosion in streams, yet this canbe a major contributor to sediment loads (Trimble, 1997).None of the models (except MOUSE) account for storageand release of contaminants in sediments (especially instreams) and the associated effects on baseflow concentrationsand timing of storm loads. Incorporation of such processwould certainly increase the number of parameters in themodel, yet without such modelling the representation of trans-port and treatment processes remains highly empirical.

Most of the models are somewhat limited in relation to pre-diction of baseflow, reflecting the traditional emphasis on im-pervious areas and flooding. In MUSIC, SWMM, andMOUSE, infiltration from devices such as swales or infiltra-tion trenches is not added to the soil or groundwater moisturestores, which somewhat limits the utility of these models forassessing baseflow enhancement. All the models excludesome factors that can affect baseflow, such as leakage fromthe water supply network, groundwater interception by storm-water and wastewater drains, the effect of vegetation type onevapotranspiration or interception, and regional groundwaterflows. Hence the predictions of the effects of urbanisation onbaseflow may be unreliable. Moreover, predictions of changes

A.H. Elliott, S.A. Trowsdale / Environmentain baseflow have rarely been tested. This is relevant to LID, asmaintenance of pre-development baseflow is often a key goal.The models do not incorporate more sophisticated hydro-logical processes for prediction of storm flow from perviousareas, such as variable source areas or macropore flow. Thispotentially limits the reliability of the models for predictionof storm runoff from pervious areas, which is of interest asLID aims to mimic pre-development hydrology. Also, thereis a heavy reliance on calibration of conceptual parameters,so that for applications at the development scale or smallerwhere data collection for calibration would be too expensive,the modeller must resort to experience or regional parameter-isation to obtain parameter values.

Even if suitable data is available for calibration, most of themodels do not incorporate calibration techniques and method-ologies, except occasionally for flow components. None of themodels are set up for automated calibration of water qualityparameters. When calibration is incorporated, the techniquesdo not allow for calculation of parameter or prediction uncer-tainty (beyond simple sensitivity analysis).

None of the models integrate the hydrologic and waterquality predictions with costing modules, environmental riskanalysis or receiving-water models, except that StormTac in-corporates a simple lake concentration model and MUSICcompares the predicted frequency distribution of concentra-tions with concentration criteria.

None of the models are integrated with drawing softwarefor the preparation of construction drawings or site layout.We see a role for models that allow visualisation of low-impact development measures such as rain gardens or narrowroads into the site layout and landscaping.

There are some unresolved questions about how much spa-tial detail is needed to represent on-site LID at a catchmentscale. For example, the degree to which models of on-sitedevices can be scaled up to the catchment scale using lumpedrepresentations of the devices has not been demonstrated: thealternative is to represent each device separately. There isa need for systematic work on the suitability of, and methodsfor, such up-scaling. It may be that such distributed systemsare best modelled with a detailed representation of the systembut also by re-using model components to save on setup timeand computational effort (as in the UrbanCylce model beingdeveloped by Kuczera and others at Newcastle University,Australia).

There are very few documented tests of the ability of storm-water models to predict the actual effect of LID at a subdivi-sion or catchment scale, mainly because there are difficultiesin setting up a suitable study site, especially one includinga spatial control.

Several approaches can be taken to address these limita-tions. Research into flow and contaminant generation andtransport processes and development of mathematical repre-sentation of these processes will improve the fundamental orempirical representation of processes in the modes. Testingof the performance of existing or new devices will also leadto improvements in their representation within models. Somegaps will require the development of new models (both sophis-

403l Modelling & Software 22 (2007) 394e405ticated research-level models and simple models), but manylimitations can be overcome through refinement of existing

models. Further application and testing of existing models willalso help address some of the research gaps, and this is likelyto occur as modelling of LID devices becomes morewidespread.

4. Summary and conclusions

A wide range of existing models, including conventionalstormwater models, is available for predicting at least someof the water quality and flow effects of LID. None of the tenmodels we reviewed are intended for the full spectrum ofuses that could be demanded of a model in relation to LID.The models most commonly address the middle ground ofplanning and preliminary design levels of use.

The models use a wide range of temporal resolution, fromaverage annual to sub-hourly. All but one of themodels are capa-ble of long-term simulation. Half of the models use lumpedcatchments, while the remaining models are quasi-distributed.

The models use similar methods for generating runoff fromimpervious areas, and a range of conventional methods is usedfor generating runoff from pervious surfaces. Half of themodels include a groundwater component, which is relevantfor assessing effects of LID on baseflow, but the representationof groundwater is simplified and generally untested.

Several models are limited in their ability to predict theflow rates from small catchments incorporating LID due tothe large timestep or limited flow-routing capabilities. Suchmodels may still be suitable for predicting water budgets orcontaminant modelling. All but one of the models route flowsthrough devices.

Most of the contaminant models include sediment andnutrients specifically, and half of them also include heavymetals explicitly. In many cases, contaminants that are notincluded explicitly in the model can be represented eitherby using generic transport and treatment options, by model-ling another contaminant with a similar behaviour, or byspecifying the association of the contaminant with sediment.The models use a limited range of methods for contaminantgeneration, all of which rely heavily on empirical parameters.The models either have no contaminant routing in the drain-age network, or use simple representation of contaminantrouting and decay.

The models differ in the types of LID device that are in-cluded explicitly. All the models can represent the effects of re-ducing imperviousness or improving soil infiltrationproperties, all but one can model ponds, all the contaminantmodels can represent reduction of contaminant generation,most of the models can be used for infiltration devices, andthe majority of the models can represent on-site detentiontanks. Half of the models can represent some of the functionsof swales, MUSIC being the most comprehensive in this re-gard. Runon is included explicitly in four models, rain tanksare included in three models, and only two models includerain gardens, bio-retention devices or filtration devices. Onlyone model includes green roofs explicitly, and none of them in-

404 A.H. Elliott, S.A. Trowsdale / Environmentalclude permeable pavements. In many cases, a device which isnot represented explicitly in the model can still be modelledindirectly by altering the parameters of other devices or com-bining other devices. Conventional stormwater drainagemodels can be used to approximate the hydraulic aspects ofseveral types of device. We expect to see more LID devicesbecoming incorporated into conventional stormwater models,gradual refinement of the algorithms for representing LID de-vices, and extension of the range of devices as new types ofdevice are developed and better data are collected.

There is a trend towards incorporation of spatial editors,GIS, and other graphical interface features into stormwatermodelling systems. Such features will likely encourage theuse of models that incorporate LID, which in turn couldencourage the uptake of LID.

There is considerable scope for improving the capabilities ofthe models including: improvement of runoff generation andgroundwater components; extending the range of contaminants;incorporation of more contaminant biochemical and physicalprocesses; more integration with receiving-water and ecosys-tem effects models; incorporation of more non-structural storm-water control measures; more linkage to calibration techniques;testing of model predictions against field data; and investigationof methods for and suitability of spatial and temporal aggrega-tion methods. Such gaps and deficiencies are likely to be ad-dressed in future model development, as the use of LID andassociated modelling becomes more commonplace.

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