a gis based decision support system for the implementation of sw bmps.pdf

7/27/2019 A GIS based decision support system for the implementation of SW BMPs.pdf

1/9

11th

International Conference on Urban Drainage, Edinburgh, Scotland, UK, 2008

Viavattene et al. 1

A GIS based decision support system for the implementation of

Stormwater Best Management Practices

C.Viavattene1*, L.Scholes

2, D.M. Revitt

2, J.B. Ellis

2

1Flood Hazard Research Centre Middlesex University, Queensway Enfield Middlesex

EN3 4SA2Urban Pollution Research Centre Middlesex University, Queensway Enfield Middlesex

EN3 4SA.

*Corresponding author, e-mail [email protected]

ABSTRACTWhilst there is increasing interest in the use of stormwater Best Management Practices

(BMPs) amongst policy makers, concern is expressed that a lack of shared knowledge by

stakeholders unfamiliar with these systems could negatively influence the decision making-

process in public participation sessions. To facilitate understanding and to enhance

transparency relating to the development of sustainable urban drainage strategies, a widerange of technical, environmental and socio-economic criteria have previously been identified

(together with supporting indicators and benchmark values) to assist practitioners in the

selection of BMPs. This paper addresses the issue of the communicability of this work by

demonstrating how these methodologies can be integrated into a decision support system

based on a Geographic Information System (GIS) platform. This adds considerable value to

current approaches; allowing the integration of layers containing pertinent information,

facilitating knowledge transfer by enhancing communication through a user-friendly map

interface and also offering the opportunity to link directly with more technical stormwater

models. The potential operational utility of the developed approach is illustrated through its

application to the incorporation of BMPs within a case study site.

KEYWORDSStormwater Best Management Practices; Decision Support System; GIS; Multi-criteria

approach; Urban scale

INTRODUCTIONThe contribution that stormwater BMPs (also known as Sustainable Urban Drainage Systems

; SUDS) can make to sustainable urban development through their potential to address the

needs and concerns of a diverse group of stakeholders, has been widely recognised (Revitt et

al., 2003). These systems include a wide range of structures with different impacts on water

quantity and quality, posing different technical constraints and entailing variable costs.However, unfamiliarity with these techniques, and in many cases, the lack of technical

knowledge held by stakeholders could influence the decision-making process when selecting

appropriate systems.

Urban stormwater models such as SWMM, MIKE II, MOUSE, Hydroworks or STORM (for a

review of these models see Balmforth et al., 2006; Elliott et al., 2007) are now widely used to

assess the impact of control devices on the urban drainage system. Such models provide a

good representation of the physical phenomena but, because of their complexity, they are


2/9

11th


2 A GIS based decision support system for the implementation of BMPs

usually non-user friendly and are generally limited to technical issues (Balmforth et al.,

2006). Geographic Information Systems (GIS) are also commonly used to collect and manage

the spatial data required as an input for such models. More recently they have also been used

as post-processors to accept the output and enable a user-friendly representation of the results

(Heaney et al., 2001). In the context of a typical urban development scenario of multiple

stakeholders from a wide variety of backgrounds, there is clear potential for the use of such a

central data integration and communication tool and as a precursor to analytical modelling.The development of this type of specific GIS tool which will enable stakeholders to identify

possible sites for the location of urban BMPs on a catchment-scale represents an obvious step-

forward. Currently there are only a few examples of such dedicated tools (Makropolous et al.,

2001; Cappiella et al., 2005).

Previous approaches, such as that by Scholz et al. (2006), have principally considered the

physical characteristics of a site within the framework of a decision matrix with an output in

the form of a recommendation for a particular BMP or design configuration. An example of a

more interactive approach is that by Jin et al. (2006) involving the development of a GIS-

based expert system (known as FLEXT) which enables users to apply a series of rules and

conditions within a large database containing detailed site-specific information. Although the

transfer of data between GIS software and FLEXT is possible, the tool is not yet fullyintegrated into a GIS platform. The need to include a wider range of issues was addressed by

the development of the DayWater Multi-Criteria Comparator; MCC (Ellis et al.,2008) which

in addition to site characteristics, also benchmarks the performance of BMPs against a range

of technical, environmental, economic, operation and maintenance, social and legal criteria.

The research described in this paper integrates the DayWater MCC approach within a GIS

platform as part of the EU FP 6 SWITCH (Sustainable Water Management Improves

Tomorrows Cities Health) project (www.switchurbanwater.eu). The aim of this approach is

the development and application of a GIS decision support tool which facilitates the

integration of data from a variety of sources to investigate the potential benefits of BMPs. On

a catchment-wide basis, this model allows the user to identify potential areas which are

appropriate for the installation of different types of BMPs in relation to site-specific criteria aswell as to predict the most appropriate types of BMP for a specific site. The involvement of a

wider range of stakeholder interests is then facilitated by the incorporation of the MCC tool

with the inclusion of an up-dated methodology to assess the comparative pollutant removal

potential of different BMPs (Scholes et al., 2007). Following a description of the development

of the model, this paper demonstrates its potential application within the Eastside

development in Birmingham (UK), an urban area currently undergoing intensive re-

development.

METHODOLOGY

In developing a GIS-based decision support system for the identification of appropriateBMPs, the focus has been based on the integration of three relevant components; site

characteristics, BMP pollutant removal performance and the inclusion of end-user

preferences.

Development of GIS platformThe Decision Support system has been developed using the Visual Studio.net 2003

development environment with the support of ESRI

Arcgis library 9.1

. It is composed of

two main interfaces which are viewed simultaneously: the GIS interface and the user-friendly


3/9

11th


Viavattene et al. 3

interface (Figure 1). The GIS interface consists of a screen where different shapefiles and

raster layers can be viewed (see left-hand side of Figure 1). The GIS interface utilises current

map tools (e.g. zoom, pan, refresh, up and down layer, add and remove layer) to enable users

to interact with the map. The user-friendly interface is a multiple-page dialog box (right-hand

side of Figure 1) enabling users to access information, databases and pictures relating to 15

different stormwater BMPs.

Figure 1. Snapshot from the SWITCH BMP decision support system showing both the GIS

and user-friendly interfaces.

BMP assessment componentsSite criteria approach.A variety of site-specific aspects with the potential to influence the use

of various BMPs have been widely reviewed in the literature (CIRIA, 2007; Daywater, 2005;Jin et al., 2006; Scholz et al., 2006; WoodsBallard et al., 2007). Based on a consideration of

their ease of utilisation within a GIS format, the following indicators have been selected: type

of land use (open space, railway, car park, building, pavement, road, verge, water body,

other), soil type (clay, silt, loam, sand, gravel), slope (%), depth to groundwater (m) and the

presence of flat roofs. Default values which relate BMP type to the indicators are defined,

effectively establishing a set of rules which determine which BMPs can be located at a

particular site. However, the user is able to change these default settings based on their own

knowledge and requirements.

BMP pollutant removal potential.To address concerns relating to water quality aspects, the

systematic BMP pollutant removal assessment approach developed by Scholes et al.(2007)

has been incorporated within the decision support system. This BMP pollutant removalassessment framework involves the combination of field data and expert judgement to assess

the potential for seven pollutant removal processes (adsorption, settling, microbial

degradation, filtration, plant uptake, volatilisation and photolysis) to occur within a range of

BMPs, together with an assessment of the potential for the identified processes to remove

pollutants of concern. These two sets of information are then combined to develop a single

unit value which identifies the relative potential for a particular pollutant or pollutant group to

be removed by specific BMPs.


4/9

11th



Multi-criteria comparator. Using this tool, stakeholders are able to assess the performance of

BMPs against the criteria listed in Table 1. The performance of each of 15 BMPs is

benchmarked against each indicator using default scores (developed during the DayWater

project (Ellis et al.,2008)) or alternatively the user can enter their own scores. Users then

apply weightings which are combined with the scores to generate a BMP order of preference.

Table 1. An example of the use of multi-criteria comparator approach showing (a) itsapplication to swales and (b) the ranked order of BMPs predicted using the same criteria and

indicator weightings

a) b)Criteria Criteria

weighting

Indicators Indicator

weighting

Swales

Technical 15 Flood control 5 2

Pollution

control

5 3

System

adaptability to

urban growth

5 4

Environmental 50 Receiving

water volume

impact

25 4

Receiving

water quality

impact

25 4

Receiving

water

ecological

impact

0 3

Operation and

Maintenance

10 Maintenance

and servicing

requirements

5 3

Systemreliability and

durability

5 4

Social and

Urban

Community

Benefits

10 Public heath

and safety

risks

2 3

Sustainable

development

2 3

Public/commu

nity

information

and awareness

1 2

Amenity and

aesthetics

5 3

Economic 5 Life cyclecosts

5 4

Long term

affordability

0 4

Legal and

Urban Planning

10 Adoption

status

5 5

Building

development

issues and

stormwater

regulations

5 3

Total (sum of

score x weight)

364

BMP Rank

Infiltration basin 1

Porous paving 2

Swales 3

Infiltration trench 4

Retentions pond 5

Constructed

wetland

6

Detention basin 7

Extended

detention basin

8

Green roofs 9

Filter strip 10=

Filter drain 10=

Soakaway 12

Lagoon 13

Settlement tank 14

Porous asphalt 15


5/9

11th


Viavattene et al. 5

Interactive map functionalitiesIn the decision support system, the assessment method is applied to a vector database (a layer

in a shapefile format; polygon type). The layer database contains site characteristic values for

each area of land under consideration (i.e. land use type, slope, soil type etc). The site

criterion rules are applied to this database to assess the potential for using BMPs, and the

results generated can be viewed in three different ways.

Potential Areas tool. This tool allows users to identify all the areas within a development site

where a particular stormwater BMP may be located, with the results shown on a map (Figure

2 A). The tool helps the user to develop an overview of the opportunities for locating BMPs

throughout the studied area. The addition of other layers to the map containing information on

water quality or quantity problems could then support the identification of key sites for BMP

implementation.

Site-by-Site assessment tool. The aim of this tool is to allow users to assess the potential for

using all 15 BMPs at a selected location. By pointing the mouse at a specific area on a map,

the tool identifies which BMPs could be implemented (Figure 2 B). Additional information is

offered to the end user to assist his selection. For example having identified which BMPs may

be utilised based on site constraints, the list of possible BMPs can be ranked using thepollutant removal methodology and/or the multi-criteria comparator approach.

ADD BMP tool. As with the previous tool, the ADD BMP tool supports users in identifying

potential areas for a specific type of BMP. The tool interacts with the map through the use of

a mouse (Figure 2 C) such that once a particular type of BMP is selected, the mouse cursor

changes into a symbol indicative of the BMP being considered. As the user moves the cursor

across the screen, the cursor image changes automatically in relation to whether the area is

suitable for the particular BMP being considered. The user can then add the BMP to a

dedicated layer which georeferences existing and new BMPs for further use in hydrological

stormwater models.

DISCUSSIONThe key drivers behind the development of the decision support tool are firstly, the

development of a GIS tool which enables stakeholders to identify potential sites for the

location of BMPs, and secondly the integration of multi-criteria analysis approach to support

wider considerations involved in urban decision processes. In relation to the first objective,

the user can use the tool to effectively assess the potential locations for the siting of BMPs

through the use of three tools within a GIS interface (Potential Areas tool, Site-by-site tool

and the ADD BMP tool). These three options are based on generic site characteristics rules

which are applied to site-specific information.

Difficulties associated in the collection of field data are identified as a barrier limiting theimplementation of decision-support systems in general and the integration of data within a

GIS format in particular. To assess the use of this decision support system under such

circumstances, the tool has been applied to the Eastside Urban Development for which only a

limited amount of data has been accessed. Eastside is a 170 ha area close to the centre of

Birmingham which has been undergoing major regeneration over the last ten years. It is

planned to become a new learning, technology and heritage quarter for the city and should

provide citizens with learning and employment opportunities (Birmingham City Council,

2008). There is a common will, shared by stakeholders, to incorporate sustainable


6/9

11th



Figure 2. Snapshot of the three BMP site selection tools (A: Potential Areas tool, B: Site-by-

Site tool and C: ADD BMP tool)


7/9

11th


Viavattene et al. 7

development into the regeneration programme. According to the Eastside Sustainable Vision

(2002), the regeneration programme, as a minimum, must address the European Directives on

sustainability in order to meet the criteria of Advantage West Midlands and the European

Regional Development Fund. From a water perspective, the city has to manage major issues

on water quantity and quality. In particular, the area is subject to rising water tables resulting

from a decline in the areas industry and the greater part of the run-off from Birmingham city

centre flows towards the River Rea (Eastside Sustainable Vision, 2002). Severn Trent WaterLtd is facing increasing sewer network surcharging problems within its region much of which

is related to surface water flooding. For example, Foster et al.(2007) have shown that a large

component of the Eastside sewerage network is susceptible to surcharging during a 5 year 60

minute design rainfall event.

As a contribution to addressing these issues, the use of BMPs within Eastsides ongoing and

future regeneration projects is being considered. With respect to using the developed decision-

support system, sufficient data has been collected to construct a viable tool (although it is

anticipated that additional future refinements will improve the operational aspects of the

system). The topographic layer of Master Map data has provided initial information on

urban land use types. Further refinement to discriminate between specific land use areas e.g.

car parks, other impermeable areas, open spaces, and verges has been achieved using imagesobtained from Google Earth 2007 and by referring to 2008 Infoterra Ltd & Bluesky. Soil

data were obtained from the relevant Ordnance Survey of Great Britain geological map and

from the SOILSCAPETM

Website (Cranfield University, 2008). Surface slopes have been

calculated using the Digital Terrain Model available through the Ordnance Survey/EDINA

supply service. The current existence of flat roofs was the most problematic aspect, and initial

allocations were achieved by analysing the remote sensing data available within Google

Earth. This will be confirmed through on-site investigations. Data collection with regard to

groundwater levels across the site is ongoing and will be included together with the

incorporation of future development plans as these become available.

The current lack of data on site-specific sources and loadings of pollutants, their impact on

receiving waters and the preferences of the stakeholders limit the potential to field-test theapplication of the multi-criteria comparator and the BMP pollutant removal potential

components. However, it is possible to demonstrate the potential benefits of the decision-

support system using a theoretical example.

Considering the case of an existing open space (e.g. roundabout or park), the Site-by-Site

tool allows the user to assess which of the 15 BMPs could be utilised (see Figure 2B). A user

could then refine this list of possible BMPs using both the BMP pollutant removal and/or

the MCC comparator components. For example, if a user identified nitrates as a key pollutant,

the decision-support tool can be used to generate an order of preference of BMPs which offer

the greatest potential to remove nitrate (see column 2 of Table 2 for the 5 most highly ranked

BMPs). An example of an order of preference of BMPs for the removal of total suspended

solids (TSS) is also presented in Table 2 (column 3) as a comparison. As can been seen in

Table 2, if the main pollutant of concern is nitrates then a sub-surface flow (SSF) constructed

wetland presents the higher score. If the main pollutant is TSS, then an infiltration basin is

recommended as offering the greatest potential for removal. In relation to the 5 most highly

ranked BMPs, it is noticeable that infiltration basin and constructed wetland score well for

both nitrates and TSS. In contrast, certain BMPs (e.g. soakaways and swales) are present in

one list and not the other.


8/9

11th



In relation to the incorporation of user preferences, the final two columns show the scores

obtained when two different preferences were expressed using the MCC matrix component.

The first preference involved an application of a higher weighting on the environmental

criterion. In the second preference, higher weightings were applied to criteria linked to project

appraisal objectives (i.e. technical, operation and maintenance and economic criteria). The

impact of altering the weightings is evidenced by differences in the order of preferences

generated. In both cases swales, infiltration basins and retention basins score most highly,although their ranked order varies offering scope, for informed negotiation.

One approach to utilising the generated results would be to identify which BMP best meet the

needs of all considered aspects. For this particular example, the use of an infiltration basin is

shown to offer the best overall performance.

Table 2. Overview of the BMP orders of preference generated with respect to differing

priorities.Ranked

position

Nitrates TSS MCC Preference 1 MCC Preference 2

1 Constructed WetlandSSF Infiltration basin Infiltrationbasin 393 Swale 354

2 Infiltration basin Constructed Wetland

SSF

Swale 364 Retention basin 344

3 Constructed Wetland

SF

Soakaway Retention basin 344 Infiltration

basin

343

4 Swale Extended Basin Constructed

Wetland

342 Filter strip 335

5 Filter strip Constructed Wetland

SF

Extended

detention basin

310 Extended

detention basin

305

CONCLUSIONS

A modelling approach based on GIS has been shown to be capable of handling data from avariety of different tools to form the basis for a user-friendly decision support process which

assist stakeholders in understanding and communicating alternative options for the inclusion

of BMPs into urban areas. The described tool simultaneously presents the output of three

different approaches for identifying appropriate BMPs, offering the end-user information

from the specific perspective of site characteristics and pollutant removal as well as from a

more holistic consideration of a broader range of social, environmental and economic

perspectives (MCC). The next stage in the development of this integration tool is the

incorporation of a dialogue with a hydrodynamic stormwater model.

It is important to point out that the tool is still in the development phase and that it has not yet

been fully trialled with relevant stakeholders. This work is scheduled to take place within the

SWITCH project, and will enable an assessment of the potential interest in the approach to beassessed as well as providing constructive comments and suggestions relating to the usability

of the approach and its format. It is also hoped that this process will assist with the collection

of additional relevant data. In addition to applying this tool within the Eastside development

of Birmingham (UK), it will also be trialled in Belo Horizonte (Brazil), Lodz (Poland) and the

Emscher region (Germany). These are all case study cities participating in the ongoing

SWITCH project. Completion of these field trials will enable the theoretical and analytical

limitations of operationally applying this tool to be evaluated.


9/9

11th


Viavattene et al. 9

ACKNOWLEDGEMENTWe wish to acknowledge the support of the EU FP6 SWITCH (Sustainable Water

Management Improves Tomorrows Cities Health) project which contributes to the current

research described in the paper. We are also grateful to the previous EU FP5 DayWater

project which has provided some of the basic methodologies to be used in the GIS tool.

REFERENCESBalmforth D., Digman C.J., Butler D., Shaffer P. (2006). Integrated Urban Drainage Pilots: Scoping Study.

DEFRA.London

Birmingham City Council (2008).Internet website: http://www.birmingham.gov.uk/eastside.bcc. Visited 25th

of

February 2008.

Capiella K., Wright T., Schueler T. (2005). Urban Forestry Watershed Manual Part1: Methods for increasing

forest cover in a watershed. US Department of Agriculture.

CIRIA (2007).Internet site.http://www.ciria.org.uk/suds/. Visited 25th

of February 2008.

Cranfield University (2008). National Soil resources institute : SoilscapesTM

. Internet Website.

http://www.landis.org.uk/soilscapes/.Visited 25th

of February 2008.

DayWater (2005). An Adaptive Decision Support System (ADSS) for the Integration of Stormwater SourceControl into Sustainable Urban Water Management Strategies. Internet Website.

http://www.daywater.org. Visited 25thof February 2008.

Eastside Sustainable Vision (2002). Sustainable Eastside: a vision for the future. 102 p. http://www.sustainable-

eastside.net/. Visited 25th

of February 2008.

Ellis J.B., Deutsch J-C., Legret M., Martin C., Revitt D.M., Scholes L., Seiker H., and Zimmerman U. (2008).The DayWater decision support approach to the selection of sustainable drainage systems. Water practice

and technologyVol 1 No 1.

Elliott A.H., Trowsdale S.A. (2007). A review of models for low impact urban stormwater drainage.

Environmental Modelling & Software- Vol 22. Pp 394-405

Foster L., Bellringer M., Pardoe P. (2007). Green roofs for Eastside: saving developers money through managing

surface water. Groundwork Birmingham & Solihull. Report no: 5001-BM01303-BMR-03

Heaney J.P., Sample D., Wright L. (2001). Geographical Information Systems, Decision Support Systems, and

Urban Management. US Environmental Protection Agency.

Jin Z., Sieker F., Bandermann, Sieker H., 2006. Development of a GIS-based expert system for on-site storm

water management. Water practice and technologyVol 1 No 1.

Makropolous, C., Butler, D and Maksimovic, C. (2001). GIS-supported stormwater source control

implementation and urban flood risk mitigation. 95 105 in Marsalek, J (Edit): Advances in UrbanStormwater and Agricultural Runoff Source Controls. Kluwer, London. ISBN 1402001533.

Revitt DM, Ellis JB, Scholes L. (2003) Review of the use of stormwater BMPs in Europe DayWater

Deliverable 5.1, 98 pp. http://www.daywater.org.Visited 25th

of February 2008.

Scholes L., Revitt D.M., Ellis J.B. (2007). A systematic approach for the comparative assessment of stormwater

pollutant removal potentials. Journal of Environmental Management;

doi:10.1016/j.jenvman.2007.03.003.

Scholz M. (2006). Decision-support tools for sustainable drainage. Engineering sustainability 159 issue ES3.

117-125

Scholz M., Corrigan N.L., Yazdi S.K. (2006). The Glasgow Sustainable Drainage System Management project:

Case studies (BELvidere Hospital and Celtic FC Stadium Areas). Environemental Engineering Science-

Volume 23, Number 6, 2006. Pp 908-922

Woods-Ballard B., Kellagher R., Martin P., Jefferies C., Bray R., Shaffer P. (2007). The SUDS manual. CIRIA.

606 p.

a gis based decision support system for the implementation of sw bmps.pdf

Documents