Environmental Modelling & Software 19 (2004) 317–324www.elsevier.com/locate/envsoft

Multi-model integration in a decision support system: a technicaluser interface approach for watershed and lake management

scenarios

David Lama,∗, Luis Leonb, Stuart Hamiltonc, Norm Crookshankd, Derek Bonine,David Swayneb

a National Water Research Institute, Environment Canada, Burlington, ON, Canada L7R 4A6b University of Guelph, Guelph, ON, Canada

c Environment Canada, Vancouver, BC, Canadad Canadian Hydraulics Centre, Ottawa, ON, Canada

e Greater Vancouver Regional District, Vancouver, BC, Canada

Received 20 October 2002; received in revised form 11 March 2003; accepted 11 April 2003

Abstract

Computer simulations using mathematical models provide useful tools to investigate different scenarios based on watershedmanagement strategies and environmental conditions. They often require the combined knowledge of meteorological, hydrological,hydrodynamic and biochemical processes in air, soil and water. While existing models for individual processes are available,computational issues (e.g. software compatibility and consistency of model assumptions) on linking and integrating these modelsare challenging. To resolve these issues, we propose using a technical user interface approach based on expert system technologiesthat provide intelligent access to databases, models, scenarios and decision support output. As an example, we applied the multi-model integration approach to a watershed management study on Lake Seymour, BC, Canada, where sediment erosion due toprecipitation events or forest fires may lead to concerns of high turbidity conditions in a reservoir.Crown copyright 2003 Published by Elsevier Ltd. All rights reserved.

Keywords: Decision support system; Integrated models; Watershed management; User interface; Non-point source pollution

Software availabilityName of software RAISONContact address National Water Research Institute,

Environment Canada, P.O. Box 5050, Bur-lington, Ont., Canada L7R 4A6. Fax:+1-905-336-4430; e-mail: nwri.software@cciw.ca;website:http://www.nwri.ca/software/raison.html

Year first available 1993Hardware required IBM Pentium PC/equivalent with a

minimum of 16 MB RAMSoftware required MS Windows 95 or higher versionsProgram language C/C++/VB

∗ Corresponding author. Tel.:+1-905-336-4916; fax:+1-905-336-4400.

E-mail address: david.lam@ec.gc.ca (D. Lam).

1364-8152/$ - see front matter Crown copyright 2003 Published by Elsevier Ltd. All rights reserved.doi:10.1016/S1364-8152(03)00156-7

Availability/cost check website or email/write to con-tact for more information

Name of software ENSIMContact address Canadian Hydraulics Centre, National

Research Council, Ottawa, Ont., Canada K1A0R6. Website: http://www.chc.nrc.ca/English/Numerical/Numerical—models—e.html

Hardware required 450 MHz Pentium II microcomputeror better, 128 MB RAM, 6 GB hard drive, 8MB true colour graphics card, 3D OpenGLaccelerator strongly recommended

Software required Windows/NT version 4.0 (servicepack 6)

Program language C/C++/VBAvailability/cost write to contact for more information

318 D. Lam et al. / Environmental Modelling & Software 19 (2004) 317–324

1. Introduction

Environment Canada, in collaboration with the Canad-ian Hydraulic Centre at the National Research Council,Canada, has developed an environmental prediction anddecision support system for the Seymour Watershed,BC, Canada. This study considers sediments and nutri-ents generated from non-point sources in the watershed,including possible erosion and forest fires, and thenwashed off by overland flows during hydrologicalevents. When these sediments and nutrients enter thelake, they are subjected to transport and dispersion bylake currents, as well as affected by in-lake deposition,biochemical uptake and regeneration processes. Themain management concerns are the high turbidity andother water quality problems associated with theseinputs. The purpose of this paper is to describe a techni-cal user interface (TUI) that can link meteorological,hydrological, terrestrial and limnological databases withthe hydrological, hydrodynamic and water quality mod-els required to simulate these complex physical, chemi-cal and biological processes. The main goal of the TUIapproach is to use the data and models in a simple, step-by-step and effective decision support system that allowswatershed managers to evaluate the water turbidity andquality consequences of various proposed managementpractices in the watershed prior to implementation. Toachieve this goal, user consultation during the systemdesign and implementation stages is essential. As themain users of this system, the Greater VancouverRegional District (GVRD) and its partners have provideddata and advice in the system development. This paperuses the Seymour Watershed study as an example toillustrate this decision support system approach.

2. Models

In a broad sense, there are two modelling approaches:to build a new model for each application or to utilizeexisting models where possible. The first approach hasthe benefit of control in the model design and linkage,but requires longer development time. The secondapproach saves on development time, but requiresadditional work to link up existing models. Examples ofboth modelling approaches for reservoir managementand water resources planning can be found in the litera-ture (e.g. Loucks and da Costa, 1991). For the presentstudy, we adopted the second approach because therewere already models developed for the watershed analy-sis and hydrological simulation (Hamilton et al., 2001)and because the users at GVRD required a general mod-elling framework so that existing models could be used,with the flexibility that they could be replaced by bettermodels when available. It is with this design philosophythat we chose the following models for our study.

While individual summaries of these chosen modelsare given below, Fig. 1 shows their connections. First,a hydrological model (WatFlood) was used to model sur-face runoff in the watershed. The agricultural non-pointsource (AGNPS) model was then coupled with Wat-Flood to estimate runoff and sediment loads. A two-dimensional hydrodynamic model (Telemac-2D) wasused to simulate the lake currents. Transport and disper-sion models (SUBIEF and SedSim) were used to simu-late the nutrient and sediment transport in the reservoirand assess the turbidity at the water supply intake. Awater quality model (WQM) was then used to predictnutrient conditions in the lake. Fig. 1 also shows howthese models are connected to the input data for modelinput and calibration/verification, as well as howhydrological events and user-specified scenarios can beselected for some of these models.

WatFlood (Kouwen, 1999) is a distributed model thatcalculates flood flows in watersheds and was used forsome of the watersheds in the Seymour area. The modelemphasizes the optimal use of remote sensed data. Radarrainfall and land cover data from satellite imagery canbe directly incorporated in the model. It uses the groupedresponse unit method (Kouwen et al., 1993) whichassumes that the hydrological response from similarland-use, soil and topography will be identical given thesame meteorological forcing.

AGNPS (Young et al., 1986) is an event-based modelthat simulates surface runoff, sediment, and nutrienttransport from watersheds. The model has the ability tooutput water quality characteristics at intermediatepoints throughout the watershed network. Runoff vol-ume and peak flow rate are estimated using the runoffcurve number method. Because it is also a distributedmodel, it can use the same grid system as WatFlood forconsistency. The sediment is routed from grid cell to gridcell through the watershed to the outlet using a transportcoupling between WatFlood and AGNPS.

Telemac-2D is a hydrodynamic model developed bythe Laboratoire National d’Hydraulique of Electricite deFrance. The model provides 2D simulations of currents,elevations, contaminant dispersion, transport and depo-sition of sediments. As a finite-element model, the com-putational grids can be optimally fitted to domain bound-aries, where local refinements are possible to increaseresolution in areas of special interest (Hamilton et al.,2001). WatFlood generates inflow conditions for Tele-mac-2D.

SUBIEF is a transport and dispersion model for nutri-ents and sediments, as part of the Telemac system, withthe resulting flow regime calculated by Telemac-2D.SedSim (Davies et al., 2000) is a Lagrangian, parcel-based sediment transport model initially developed tomodel the fate of sand grains or particles. SedSim hasbeen modified to predict the fate of fine clay and siltparticles typically found in the Seymour reservoir.

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Fig. 1. Design schematic of the TUI showing input data and scenario generation (e.g. forest fire) and their connection to model linkages and output.

AGNPS provides nutrient and sediment loading inputto SUBIEF.

WQM is a water quality model that simulates nutrientprocesses for dissolved oxygen, nitrogen and phosphorusin the reservoir (Hamilton et al., 2001). It is coupled toSUBIEF and utilizes the nutrient loading input fromAGNPS.

Acres Watershed model is a spreadsheet modeldeveloped by Acres Consultants Ltd. and is based onthe classification of watershed geochemistry and forestryecology and estimates potential fire hazard areas(Hamilton et al., 2001). It was developed specifically forSeymour and adjacent watersheds. It is mainly used toguide scenario generation (e.g. forest fires) for decisionsupport in the TUI.

2.1. Technical challenges

There were many technical challenges faced by theresearch team. For example, all the necessary data hadto be collated into databases accessible by the modelsand to support scenario selection. They had to be sum-marized or processed in order to be useful for the modeland for easy viewing. In most cases, both the data andmodel results required special temporal and spatial align-ment methods to make meaningful comparison amongthem. For the models, some such as Telemac-2D mustbe implemented to accept as input the output of anothermodel (e.g. WatFlood) sequentially, i.e. in the so-called“ transformal” mode (Budd, 2002). In other cases, themodel (e.g. AGNPS) was implemented in a “ reactive”mode (Budd, 2002), meaning that the user may alter theinput (e.g. land-use data) in an arbitrary manner (e.g.

the shape and size of hypothetical forest fire areas). Inaddition, these models were originally implemented withdifferent programming languages and software platformsand required a program control that could understandand communicate with all of them. Sometimes, modelassumptions and computational schemes were not com-patible with each other. For example, WatFlood is atime-dependent model, while AGNPS, which linkedwith it, is an event-driven or steady-state model. Tele-mac-2D and SUBIEF are finite element models special-ized for the simulation of horizontal distributions,whereas WQM is based on vertical interactions betweenair, water and sediment in a vertical column.

The most difficult challenge was that the end-user, dueto software license conditions and strong interests ingraphical presentation of results for decision support,required not only that the model structure be essentiallyunmodified, but also that it should exhibit a commonlook and feel in the visualization and animation of theinput and output. As a result, while the appearance ofthe model results seemed the same and the model codesremained intact, significant effort was required both tohide information not alterable by the user, and to high-light model input parameters that the user may change.Cautions and guards were required to guide the input bythe user to satisfy model assumptions and restrictions.The user also expected the execution of model runs tobe seamless and smooth, with the flexibility to add orsubstitute models as required. These technical challengespointed to the need for a novel approach to design sucha system.

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3. Decision support

In designing decision support systems, we can developthe interface for two different types of users: the techni-cal user and the public user. In the present study, a tech-nical user interface needs to be built before the publicuser interface and, because of special requirements bythe user, there are not too many alternative approaches.For example, one of the main requirements is that thetechnical user interface must understand and communi-cate with databases and models from different program-ming platforms and languages. The common look-and-feel feature requires conversion of data formats and stat-istical computations to align properly the data and modelresults (e.g. coinciding snapshots of simulated sedimentsmovement in the lake with moving markers on precipi-tation graphs). This precludes the use of conventionaloff-the-shelf software systems that allows only one ortwo main types of data file formats or modelinputs/outputs. The requirement for both transformal andreactive modes (Budd, 2002) of operating models andthe demand for timely and simultaneous display of inte-grated model results preclude the simple manualapproach of linking models through database files.Instead, we adopt a TUI approach by using object ori-ented programming methodologies (Budd, 2002) asdescribed in the next section to overcome the difficulties.

3.1. TUI approach

The Seymour reservoir management system (SRMS)is designed for technical users. The first main task of theTUI is to ensure communication among differentsoftware tools. As shown in Fig. 2, we use the RAISONObject System (ROS) software (Lam et al., 1994), pro-

Fig. 2. Software linkage in the TUI.

grammed with Visual Basic , to form the core of thelinkage with other systems such as Access for databasemanipulation, Excel for the Acres Watershed model,ArcInfo for GIS maps and AGNPS.

The EnSim system, which offers visualization andanimation tools for the results from Telemac-2D, SUB-IEF and SedSim, is a vital part of the TUI and is connec-ted to ROS via component object model (COM) techno-logies in the software design. The COM technologiessupport the development of programs that can be writtenin any language under the Windows environment andused dynamically by any application in the system,allowing a high degree of interconnectivity among data-bases and modelling software. In addition, by using theexpert system technologies available in ROS (Lam et al.,1994), we can control the transformal and reactivemodes (Budd, 2002) of operating models (i.e. Telemac-2D and WatFlood run independently outside the TUI andthe results are archived in the TUI database, but AGNPS,SUBIEF, SedSim and WQM run interactively within theTUI). The connections among the latter four models arehighlighted in Fig. 1. Thus, the AGNPS model acceptsthe computed runoff from WatFlood and uses themeteorological and soil type and other watershed data.These are passed as database and geographical infor-mation system (GIS) files. The interactive component ofAGNPS is activated by the scenario generation. The usercan select landslide or forest fire scenarios, which canautomatically alter the values of the model coefficientsaccordingly, and then the model can be re-run. Thus,each time a scenario is generated, new model results willbe obtained interactively. Similarly, SUBIEF uses thecomputed lake circulation from TELEMAC (Fig. 1). Itis affected by the sediment yield at the river outlets com-puted by AGNPS. When AGNPS results change, SUB-

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IEF results change accordingly. Similar interactive com-putational connections, through different software andobject oriented programming techniques (Budd, 2002),are designed for SEDSIM and WQM, which also dependon AGNPS.

The TUI can dispatch various visualization and ani-mation displays of model input and output as the userchooses. It also controls special programs written to dothe temporal and spatial aggregation or proratingschemes required to compare data and model results, andto ensure model input satisfying model assumptions(Hamilton et al., 2001). The TUI controls other specialmodules dealing with the automatic alteration andextraction of map data for the definition of the values ofmodel coefficients (Leon, 1999).

Using all the above techniques, we manage to bringthe TUI into a working and coherent system, with com-mon look and feel in its operation. Essentially, theSRMS interface consists of four main sections (Fig. 1):(i) information-database, (ii) models, (iii) scenario, and(iv) output display. By accessing the information-data-base, the user can find information on the project or viewa demo of the system. The user can select, in any orderbut always with the same common look and feel, dataon meteorology (precipitation, temperature, wind speed),flows (observed and computed runoffs for thetributaries), water quality (dissolved oxygen, nitrogen,etc.), sediments (rivers and lake) and GIS maps(elevation contours, ecosystem units, land-use, soiltype).

Fig. 3 shows an example of the TUI. The four compo-

Fig. 3. The TUI for the Seymour reservoir management system with four components (icons at top: information/databases, models, scenarios,output) showing control panel for output (leftmost panel) and the simulated hydrodynamic currents in the lake (left displaying panel) and the hourlyprecipitation data used by AGNPS model and the spatially interpolated precipitation distribution as a snapshot of simultaneous animation for Event2 in both displaying panels.

nents (database, models, scenarios and output) areaccessed through the top buttons. For example, if theuser chooses the “model” button, the user can gainaccess to information of the models used in the SRMS,such as model description, assumptions and calibrationresults. For AGNPS, SedSim, SUBIEF and WQM, theinterface can be used to change model parameters andrun them. On the other hand, as shown in Fig. 3, the usercan view, with a moving bar on the time series graph forthe precipitation data used by the AGNPS model andsynchronize the animation over time and space of thespatially interpolated precipitation data over the water-shed as well as the hydrodynamic model results (lakecurrents) from the Telemac-2D model. The user can con-trol the time step used in the simultaneous animation ofthese three windows and can select and place, by usingthe pull-down menu and button provided with the system(leftmost column), any two sets of the data and/or modeloutput including scenario results on the two displaypanels for comparison as shown in Fig. 3.

3.2. Multi-model interactions in the TUI

To illustrate model interactions in the TUI, we outlinethe steps to answer one of the main target questions forthis study: what is the sediment concentration in Seym-our Lake at a given location and time during a givenprecipitation event before and after a hypothetical forestfire for certain user-selected, hypothetical burn areas? Toanswer the question, we first need the model resultsbefore the hypothetical forest fire takes place, i.e. the

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Table 1Estimated total/average daily sediment yield for the five selected rain-fall events and for the hypothetical burn scenario (Fig. 4) for Event 2

Total Average daily(ton) (ton/day)

Weather events1) 17 September 1997—low: none 3369 1402) 01 October 1997—mid: none 4215 883) 30 October 1997—high: none 4099 1024) 13 October 1998—low: none 1622 415) 13 November 1998—low: none 4620 94

Burn scenario2) 01 October 1997—Mid: 0004—BnSc 5619 117

base case. For the base case, there are five rainfall events(Table 1) identified by the main user (GVRD) to be ofinterest for this study. The models are calibrated withthe available observed data for these events. The modelresults for each of these events are then stored in the

Fig. 4. The TUI approach to create scenario and re-run models: (top) draw polygons to define hypothetical forest fire areas using fire hazardrating map; (right) re-run the AGNPS model using new model input generated from the forest fire scenario; (bottom) estimated sediment yield atspecified locations as well as total yield for the new AGNPS model run; (left) re-run SEDSIM model to simulate the movement of sediment inthe lake due to input from the scenario.

system so that the user can view and compare the out-puts. This requires a proper sequence of execution of themodels. The starting point is with the rainfall data whichare used as input to the WatFlood model, which pro-duces the flow results used by the AGNPS model, whichin turn computes the sediment yield, and nutrient loads.The output of AGNPS is then used as input (sedimentsources) to the SedSim model (for lake sediment trans-port simulation) and the SUBIEF/WQM model (for lakenutrient transport simulation). The SedSim and theSUBIEF/WQM models also use as input the output ofthe Telemac-2D model. The Telemac-2D in turn uses asinput the output of WatFlood. Fig. 1 shows these modellinkages and data access paths.

For the burn scenarios, we need to create or modifyburn area and to communicate the required changes inthe input data to the models to re-compute the results.The main difference in the system design is that the TUIwill be interactive (i.e. the user can input interactivelythe burn areas on the screen and then re-run the relatedmodels). Using the “Scenarios” button (Fig. 3), the user

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can create or modify scenarios and re-run the models.Fig. 4 shows, as an example, the sequence of steps usedin the TUI to obtain the model results for the scenariocase. First, to assist the user in the selection of the burnareas, a map (Fig. 4) showing the projected fire hazardrating for the different ecozones obtained by the AcresWatershed model (Lam et al., 1999) is displayed. Theuser specifies the desired area by supplying a polygonor several polygons on the screen and defining the hypo-thetical percentage of burned areas. The hypotheticalchanges on the map will cause changes in the land-usedata, which will affect the results of the AGNPS model,as the sediment yield from the burn area will differ fromthe original conditions. The TUI then proceeds to theAGNPS model interface (Fig. 4) and the user can selectany one of the five hydrological events and apply theburn scenario to change the input files in the model andre-run the model. The new AGNPS model results canbe displayed as a summary table (Fig. 4). The user canthen re-run the SEDSIM model with this new AGNPSresults as input to simulate the sediment transport in thelake (Fig. 4) and the SUBIEF model to simulate thenutrient transport in the lake. The new model results arestored in the database and can be retrieved to comparewith the base case results as tabulated values, graphs,maps or animated snapshots, by using the “Output” but-ton in the TUI (Fig. 3). Table 1 shows the total andaverage daily sediment yield for the burn scenario usingEvent 2 data, as well as the base case result for the fiveevents. For example, for the particular burn scenario cre-ated by the user as shown in Fig. 4, the estimated totalsediment yield is shown to be increased to 5619 ton fromthe original yield of 4215 ton for the same event for thebase case.

4. Discussions and conclusions

The results shown in this paper are a preliminaryattempt at sediment transport and water quality model-ling for the Seymour reservoir. The models have beenindividually calibrated with the best available data at thistime. As an example, Fig. 5 shows the comparison

Fig. 5. Distributions of measured data and computed results for stream sediment concentration (ppm) at three sampling stations in the Seymourwatershed.

between the computed and observed sediment yield atthree river outlets to the lake. The sediment yield com-puted from the AGNPS model fits well with the obser-vations. Comparison of other model results (not shownhere) produced similar agreement (Hamilton et al.,2001).

From this preliminary attempt, some insight wasobtained from the integrated results. For example, Fig.6 shows the precipitation and the computed ammoniaand nitrate concentrations in the lake at the inlet (node279 in the finite element grid) and at the outlet (wherewater intake is located). For this rainfall episode, it isshown that the peak nutrient concentrations for bothammonia and nitrate at the lake inlet lag behind the peakof the precipitation event by about 6 h. However,ammonia and nitrate concentrations behaved differentlyat the intake with a minimum for ammonia lagging afterthe peak of the precipitation event and with a prolongedmaximum for nitrate.

Had the models been run by other approaches (e.g.

Fig. 6. Time series for (from top) observed precipitation, computedammonia and nitrate concentrations at intake and at node 279 near thelake inlet for Event 1.

324 D. Lam et al. / Environmental Modelling & Software 19 (2004) 317–324

the simple manual approach), these integrated resultsmight not be obtained so readily. It was through theautomation of the management scenarios and interactiveruns of the models with the TUI that we were able toobtain new insights with reasonable computational timefor simultaneous display of precipitation, water quantityand quality results. Results such as shown in Fig. 6 areimportant to the operation and planning of the reservoir.By manipulating the available model input throughhypothetical alteration of land-use, lake level and otherinput, the end-user was able to produce integrated resultsrequired for operation and planning in a timely andorganized manner. Through this exercise, we found thatnew models and data can be implemented and linked toexisting modules in the TUI approach much easier thanother conventional approaches. This is due to the use ofthe object oriented programming approach in the TUIthat effectively hides the unnecessary informationamong the modules and focuses on the necessary inputand output. The use of logged information for differentscenarios and storing the model results as versions basedon these scenarios has led to effective retrieval of dataand model results for comparison. The use of tables,graphs, maps and animated snapshots was found to beeffective for such comparisons.

More data are needed for verifying model calculationsfor various hydrological and hydrodynamic conditionsand for verifying the water quality simulations in thelake. The scenario results are preliminary and representthe state of scientific knowledge and the data availableat this stage. The forest fires and landslide scenarios mayalso have long-term effects that require long-term epi-sodes and further confirmation with observations. At thisstage, user feedback is also required to improve the sys-tem.

Acknowledgements

We thank the support and advice from David Dunkleyand Lorne Gilmour at GVRD. Thierry Faure and Martin

Serrer at the NRC/CHC provided technical support andtraining for the SUBIEF model; Sebastien Bourban pro-vided advice. Patricia Chambers at NWRI providedadvice on nutrient conditions during forest fires and har-vest. Craig McCrimmon at NWRI provided program-ming support. Jocelyn Neysmith and Phil Fong at NWRIand Ken Brown and Alex Storey at the University ofGuelph assisted in beta testing and maintenance of thesystem.

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