Available online at www.sciencedirect.com

Environmental Modelling & Software 23 (2008) 650e659www.elsevier.com/locate/envsoft

Models, myths and maps: Development of the EXploratory ClimateLand Assessment and Impact Management (EXCLAIM) tool

Ian Calder a,*, James Garratt a, Philip James b, Ed Nash b

a Centre for Land Use and Water Resources Research, School of Civil Engineering and Geosciences, Newcastle University,Newcastle upon Tyne NE1 7RU, United Kingdom

b School of Civil Engineering and Geosciences, Newcastle University, Newcastle upon Tyne NE1 7RU, United Kingdom

Received 10 May 2006; received in revised form 12 September 2007; accepted 16 September 2007

Available online 19 November 2007

Abstract

For many years maps have been used to convey concepts and ideas in an easily understandable form. The advent of computer basedGeographic Information Systems (GIS) has allowed users to explore different scenarios using a variety of data. This paper describes the devel-opment of specialised GIS tools, via thin-client technology, to assist policy makers, donor organisations and Non-Governmental Organisations(NGOs) understand how the interactions between changing land use (particularly land uses involving forestry, irrigation and soil water conser-vation structures) and climate affect water resources and people’s livelihoods. The research brings together hydrological and socio-economicmodels with easy to use user interfaces. It is expected that the EXCLAIM tool will help to support the ‘‘Bridging Research And Policy’’ processand encourage the development of evidence based (rather than presently often myth based) land and water policies, especially in relation towatershed development projects.� 2007 Elsevier Ltd. All rights reserved.

Keywords: Water management; Web based modelling; Water policy; Geographical Information Systems; Hydrological modelling; Land use

1. Introduction watershed development projects, particularly those involving af-

In many parts of the developing world water is a scarceresource that must be managed to provide adequate suppliesfor basic needs such as drinking water and sanitation, butalso to provide water for agriculture, industry and the environ-ment. Hydrological models have been developed over the pastdecades which are parsimonious both in data requirements andmodel parameters but which can predict, well enough for mostoperational and water resource management purposes, thewater resource impacts of land use change within a catchment.It is usually possible to obtain long-term datasets (particularlydaily rainfall) and direct measurements or surrogate estimatesof potential transpiration for long time periods which makethese models applicable for most regions of the world.

The results of these models are often at variance with the per-ceived wisdom regarding the benefits of interventions in

* Corresponding author.

E-mail address: i.r.calder@ncl.ac.uk (I. Calder).

1364-8152/$ - see front matter � 2007 Elsevier Ltd. All rights reserved.

doi:10.1016/j.envsoft.2007.09.012

forestation programmes (Calder, 1999; Batchelor et al., 2003).Whereas in many parts of the world afforestation programmesare still being promoted on the basis that they will increase waterflows from catchments hydrological studies almost always (withthe possible exception of cloud forests) show the opposite to bethe case (Bruijnzeel, 1990; Calder, 2005). Overenthusiastic pro-motion of irrigation schemes and the ready availability of electricsubmersible pumps have resulted in huge increases in areas underirrigation in many parts of the world. Catchment closure, i.e. thecessation of flows from a catchment except in high rainfall years isbeing recorded more frequently now in many parts of Asia(Calder, 2005). This is one unwanted feature of some watersheddevelopment projects. When this occurs, downstream usershave no access to reliable water supplies and aquatic life maybe catastrophically affected.

There is clearly a need to better connect science with policyin the implementation of watershed development projects toavoid undesirable outcomes such as catchment closure. Deci-sion Support Systems (DSS) in support of Integrated Water

651I. Calder et al. / Environmental Modelling & Software 23 (2008) 650e659

Resource Management (IWRM) were seen as the tools whichwould help managers make more informed decisions aboutland and water resource options. These have been availablesince about 1996 but take-up has not been widespread (e.g.O’Callaghan, 1996; Elarabawy et al., 2000; Nauta et al.,2003). Perhaps part of the problem is that the tools havebeen developed without a clear understanding of potentialuser requirements and the necessary user skills. DSSs arenot used by policy makers, donors or NGOs who have interestsin land and water management because they normally wouldnot have the technical skills to operate or interpret the outputsof the tools. On the other hand water resource or land usespecialists, the technical specialists that might be found imple-menting policies in government ministries, would probablyprefer to work directly with the underlying hydrological,economic or ecological models supporting the DSS ratherthan working through the less immediate, and usually quiteconstrained and inflexible, DSS structure.

An alternative approach is to develop an easily under-standable interface to the output of sophisticated numericalmodels via an accessible medium. This approach can makeuse of the flexible structure of modern web based GIS (Geo-graphic Information System) technology. In this way, non-specialists can explore for themselves the effects of changesin a variety of factors and how it impacts on the available re-sources. This means that the user should be able to work withthese models and explore the outputs without having to bea specialist in hydrological modelling. Such a tool hasbeen described by Lanini et al. (2004), in which the roleof the model is described as ‘‘not to deliver predictive resultsbut much more to describe alternative scenarios using a widerange of indicators corresponding to the concerns of thestakeholders’’.

A tool with similar properties is described in this paper. The‘‘Exploratory, Climate, Land Impact and Management’’ (EX-CLAIM) GIS tool was developed to present hydrological in-formation to land managers and decision-makers and supportthe "Bridging Research And Policy" process (GDN, 2003).The development of EXCLAIM is intended to meet the needfor a tool to apply our understanding of the environment inpractical situations.

EXCLAIM is demonstrated through the example of an im-plementation for the Luvuvhu catchment in South Africa. Thiscatchment was the study catchment for the CAtchment Man-agement and Poverty (CAMP) project (Calder, 2004) whichaimed to understand how changes in land use arising fromthe implementation of different policy instruments would im-pact on water resources, economics and people’s livelihoods.In the example, the effects of land use change on hydrologicaland socio-economic indicators have been explored.

2. Architecture of EXCLAIM

The EXCLAIM tool is written in Java and is currentlyavailable as an applet, allowing use in a web browser bothlocally and via the internet, giving a wide potential audience.It has an extendable plug-in style architecture allowing new

models and Graphical User Interface (GUI) elements to be in-corporated with a minimum of code modifications. The keycomponents are the applet class itself, the land use databaseand the model datasets. These are complemented by special-ised classes providing management of overlays, GUI elementssuch as the toolbar, model output panel, slider panel, etc.

Each model is managed by a specialised class, or set ofclasses, which handle both the data management and aggrega-tion to subcatchment and total areas and much of the requiredcalculations, with the output data being gathered by the appletclass itself before being passed to the model output panel fordisplay. Thus, adding an additional model requires only theclasses to handle the particular data requirements of thatmodel and minor modifications to the applet and GUI codeto enable the collation and display of outputs.

The input files are loaded into a simple Hypertext MarkupLanguage (HTML) page. An Extensible Markup Language(XML) configuration file defines the files from which the data-sets are to be loaded, as well as giving metadata about these toallow flexibility as to their format. The same file is also used toconfigure the GUI, either by directly including relevant XMLor by linking to further XML files. This arrangement allowsre-use of GUI definitions, meaning that a set of applications(e.g. neighbouring catchments) can be presented with a com-mon interface. The actual data files to be loaded are in a varietyof formats according to the type of data.

3. Data requirements

3.1. GIS data

Exclaim requires catchment boundary and land use data.The land use data, and subcatchment boundaries, arecontained in a pre-processed compressed Java object streamfile to minimise download and startup time for the tool. Thisfile is generated from two GIS layers (currently only ESRIShapefiles are accepted, although other formats may be imple-mented), one containing the current land use regions, thesubcatchments into which they fall, and information relatingto how these may be changed (see section on ‘Logical informa-tion’), and one containing the subcatchment boundaries andnames. Generation of these layers requires some work usinga standard desktop GIS, e.g. in intersecting land use and sub-catchment layers, but this reduces the geoprocessing require-ments of the viewer, speeding up its operation.

Other spatial information (e.g. of the river network or urbanareas) may also be loaded from compressed object streamsgenerated from GIS layers (‘Other geometry’ in Fig. 1).Grid data (e.g. grids of mean annual precipitation or altitude)may be included to allow flexibility in managing land usescenarios (see section on ‘Logical information’).

3.2. Model data

At the heart of EXCLAIM is the database of model outputs.There is no fundamental reason why any model cannot be used

Fig. 1. EXCLAIM process framework.

652 I. Calder et al. / Environmental Modelling & Software 23 (2008) 650e659

within the EXCLAIM framework, as long as it is able toproduce outputs at the appropriate scale and time-frame.

3.2.1. Hydrological dataA key concept in the development of the hydrological com-

ponent of EXCLAIM was the requirement to display thepartitioning of rainfall into the portion that runs out of thecatchment (‘blue water’) and the portion that evaporates(‘green water’) (Falkenmark, 1995). EXCLAIM depends ona series of hydrological response units (HRU’s), each of whichconsists of an area under a particular land use served by a par-ticular set of meteorological data. In order to calculate thehydrological summary statistics of runoff and evaporation,data on rainfall and evaporation must be introduced for eachHRU. Multiple rainfall or evaporation datasets may be usedwithin a single EXCLAIM application, allowing comparisonsof, for example, year-on-year variability in water resources.

Under the EXCLAIM framework, a hydrological model isused to provide a measure of evaporation. The timescale ofthe outputs can be chosen by the person developing theEXCLAIM application. However, the time period should beat least long enough to ensure approximate validity of theblue water calculation. For the current version of EXCLAIM,this means that the inputs should be presented at a timescaleno finer than annual averages.

The model data are in either plain text files or structuredXML, which may be compressed in ZIP format to minimisedownload time.

3.2.2. Socio-economic dataIn the current version of EXCLAIM, socio-economic indi-

cators can be calculated. The data required for this can comefrom any suitable economic model, as long as it is able to

provide information on the productivity and employment op-portunities offered by each land use. These data must be pre-sented in ‘per hectare’ form, e.g. $/ha and person-years/ha.The data may be disaggregated into more than one economicgroup. Later in this paper, we describe a distinction drawn be-tween ‘commercial’ and ‘informal’ use of land.

3.3. Logical information

Finally, the logical aspects of the tool must be included.These comprise the information on how land use might change(‘Land use change rules’, ‘Model change parameters’ and‘Rainfall data grid’ in Fig. 1). The potential ways in whichthe land use may change must be determined in advance.The key to allowing the land use in the catchment to be con-trolled is the inclusion in the land use table of ‘variable’values, which may be of two sorts, ‘buffers’ and ‘grids’.

With buffers, the regions into which a land use will expandor contract has been pre-determined and a number assigned,e.g. 1 for the first set of regions into which the land use willexpand, 2 for the second set, �1 for the first regions fromwhich it will contract, and so on. The user may then directlychoose a value and thus control which regions are coveredby that landuse. The rules regarding the expansion and con-traction of the land uses must be pre-determined whenpreparing the GIS data files, so that the necessary numberingof the regions may be introduced into the attribute files.

Grids allow an external factor such as rainfall or altitude tobe used to determine the expansion or contraction of a landuse.For each grid, either an individual value or a maximum andminimum pair of values may be assigned to each region.Each land use may then expand or contract into regions basedon these grid values and a given behaviour type as to whether

653I. Calder et al. / Environmental Modelling & Software 23 (2008) 650e659

this will occur from the maximum, the minimum, the middleor the extremes. The user then sets a change value for theland use (positive for expansion, negative for contraction),which is used with the defined behaviour to determine whichregions will be affected. One grid may therefore be usedwith many land uses in different ways, giving enormousflexibility as to how land use change is implemented.

3.4. Additional configuration options for the interface

The EXCLAIM tool is intended for a wide audience of bothexpert and non-expert users, and as such it is important that theGUI is suitable for both groups. However, the limited amountof screen space available within the applet context and thelarge amount of possible controls and model outputs meansthat the interface could become cluttered. The core of theGUI is the central map display area, with other components fit-ting around this. A great deal of flexibility has been built in asto which components are displayed, and their contents, withcontrol being possible both through the XML configurationfiles and through the GUI in the form of a configuration dialog.For each application it can therefore be defined in XML whichGUI elements are available and what controls are included ineach element (e.g. the buttons available in the toolbar and thesliders available in the sliderbar). These elements can then beconfigured further by the user where appropriate, and is alsopossible to remove the configuration options so that basicusers are given a simpler tool.

Toolbar allowing GISfunctionality (zoom/

pan/select) andaccess to

configuration dialog

Rainfallpercentile slider -

allows user toeasily explore

climatic changeand variation

Landuse sliders - allow user to control the eeach landuse and explore the results of l

Statusbar givinginformation oncurrent settings

‘GIS’ view on chosen landuse state, together withoverlays of subcatchment boundaries and

additional information (e.g. rivers, settlements)

Fig. 2. Screenshot of the EXploratory Climate Land Assessment and Impact Manag

annotations showing the use of climate and land use sliders.

The fundamental purpose of the tool is to allow the effectsof land use change and climatic variation to be explored. Toenable this in a straightforward way, the chosen land usesand the rainfall percentile can be chosen by means of sliders(see Fig. 2). These are defined for each dataset throughXML, with the choice of which sliders to use also beingavailable through the GUI. The order of precedence of landuses (i.e. which should take priority in the event of conflict,such as both set to expand into the same region) is definedby the order in which the land use sliders appear in the GUI.

3.5. Model outputs

EXCLAIM calculates the overall evaporation, runoff andsocio-economic indicators for each subcatchment for a givenland use configuration. An area-weighting function is used:for each subcatchment, the outputs for each land use aresummed according to their proportional area.

For each configuration of land use and rainfall set throughthe sliders, the model output panel indicates the results of thehydrological and socio-economic models, and the magnitudeof the change from a base state. The user may choose whetherchanges are compared within the chosen rainfall dataset orto an alternative dataset. It is possible to assess the effects ofeither land use change or climatic variation individually orto assess both together. To give a broad indicator as to whethera change will have a positive or negative impact, a ‘smiley’ (ahappy, sad or impassive face) shows when the magnitude

xtent covered byanduse change

Hydrological modeloutput showing the

levels of rainfall,evaporation and

runoff for the wholecatchment and thecontribution of the

selected sub-catchment under thechosen landuse and

rainfall conditionsand the change inthese from a base

state

Socio-economic output data showing the commercialand informal productivity and employment in the sub-

catchment under the chosen landuse and rainfallconditions, and the change in these from a base state

Indicator icons toenable a rapidassessment of

whether the chosenscenario results in a

beneficial ordetrimental change

from the base state ineach available output

ement (EXCLAIM) tool set up for the Luvuhu catchment in South Africa with

654 I. Calder et al. / Environmental Modelling & Software 23 (2008) 650e659

change from the base state is greater than a pre-determinedpercentage.

The amount of blue water is calculated within EXCLAIM bysubtraction of evaporation from the rainfall for each HRU. Thevalues of rainfall, evaporation and runoff are displayed on thescreen with variably sized arrows. If socio-economic indicatorsare used, EXCLAIM calculates the area-weighted sum of theproductivity and employment values for each HRU. When thehydrological and economic components are combined, EX-CLAIM calculates the value of water per-mm, i.e. the produc-tivity and employment divided by the amount of runoff.

The range of outputs from EXCLAIM obviously depend onthe inputs. In the current version, it is possible to explore twocategories of model output: hydrological and socio-economic.There is no technological reason why any number of informa-tion sets could not be included in future versions of EXCLAIM,as long as there is a dependency on land use, hydrological and/or climatic data.

4. Example application of EXCLAIM

4.1. GIS data

Table 1

Characteristics of weather years used for HYLUC outputs in EXCLAIM for

quaternary catchment A92a

The area of the Luvuvhu catchment in South Africa isapproximately 6000 km2. The direction of flow is roughly westto east, and it drains into the Limpopo river by the border withZimbabwe. The Luvuvhu catchment is divided into 14 subcatch-ments (named quaternary catchments to represent their order ina hierarchy). The quaternary catchment A92a (approximately500 km2) in the upper reaches of the Mutale river was selectedfor close examination, on the basis of its extended runoff recordand the wide range of land uses within the area. The land usedata for the Luvuvhu catchment came from 1996 Landsat imag-ery which was classified into a large number of categories by theCouncil for Scientific and Industrial Research (CSIR). These datawere then re-classified into six land use categories:

� Forestry� Rangeland� Dryland agriculture� Irrigated agriculture� Water bodies� Urban and peri-urban

The purpose of the modelling exercisewas to investigate the ef-fects of changing the amount of irrigated agriculture and forestryon the water resources in the catchment. Therefore the scenarioswere set up in EXCLAIM to alter the proportions of the first 4land uses. The total area under water bodies and urban/peri-urbanwas around 0.5% in the A92a quaternary catchment, and so did notgreatly influence the hydrological predictions of the model.

Percentile Description Year Rainfall (mm)

5 3rd driest 1982 420

25 12th driest 1991 572

50 Median 1973 826

75 12th wettest 1974 1032

95 3rd wettest 1953 1429

4.2. Model data

4.2.1. Hydrological dataEXLAIM was applied in the area of water resources man-

agement, and so inputs were prepared on the basis of annual

averages, in order to obtain annualised model results. The rain-fall and the total evaporation (i.e. the sum of soil evaporationand transpiration) were determined for each HRU within theLuvuvhu catchment.

The hydrological model HYLUC was used to calculate thetotal evaporation (i.e. soil evaporation plus plant transpira-tion). HYLUC is well suited to producing data at the correctspatial and temporal scale, and has been shown to be a robustdescriptor of the hydrological response of catchments witha relatively parsimonious data requirement (Calder, 2003;Calder et al., 2003). The original modelling study (includinga limited validation) is described in Jewitt et al. (2004). HY-LUC demands data at a daily time step, and the appropriatemeteorological data were obtained from the School of Biore-sources Engineering and Environmental Hydrology at theUniversity of KwaZulu-Natal. The data consisted of a 44-year record of daily rainfall, and an estimate of dailypotential transpiration, derived from the long-term monthlymaximum and minimum temperature using the Linacre equa-tion (Linacre, 1977) (repeated annually) for each quaternarycatchment. Although daily measurements of potential transpi-ration would be preferred it has been shown that the calcula-tion of actual evaporation and the prediction of runoff inrainfall runoff models is remarkably insensitive to the formof potential evaporation function employed (Calder et al.,1983; Oudin et al., 2005).

To provide the information needed for the analysis ofclimate variability in EXCLAIM, individual weather yearswere selected as representative of particular climate condi-tions. Each year of the 44 weather years was ranked accordingto the total rainfall within that year. From the ranked years,a range of weather years were selected to represent a 1-in-20 year drought (5th percentile); 1-in-4 year drought (25thpercentile); average (median); 1-in-4 year inundation (75thpercentile); and 1-in-20 year inundation (95th percentile).The actual years chosen for A92a are shown in Table 1.

Total evaporation was calculated for each HRU for eachpercentile weather year. The predictions of the total evapora-tion in each year for each HRU within quaternary catchmentA92a are shown in Table 2. The rainfall and evaporationdata from Tables 1 and 2 were used by EXCLAIM to calculatethe runoff from the catchment.

4.2.2. Socio-economic dataThe CAMP project aimed specifically to understand the

implications, with regard to water resources, economics andpeoples livelihoods, of changes in land cover brought about

Table 2

HYLUC predictions of evaporation (green water) from individual land covers in quaternary catchment A92a

Evaporation (mm)

Land use 5 Percentile 25 Percentile 50 Percentile 75 Percentile 95 Percentile

Forestry 432 567 476 809 903

Rangeland 412 480 470 742 826

Dryland agriculture 367 386 412 610 673

Irrigated agriculture 1061 1061 1061 1061 1061

Water bodies 1772 1772 1772 1772 1772

Urban and peri-urban 367 386 412 610 673

655I. Calder et al. / Environmental Modelling & Software 23 (2008) 650e659

by the implementation of two different land and water relatedpolicy instruments, the Working for Water (WfW) programme(Department of Water Affairs and Forestry, 1996) and theStream Flow Reduction Activity (SFRA) policy instruments(Department of Water Affairs and Forestry, 1999). As part ofthis research, socio-economic data were collected on theproduction values ($/ha) and job opportunities (man years/ha) associated with different land uses in one of the subcatch-ments of the Luvuvhu, the Tengwe subcatchment (Olbrich andHassan, 1999). In an attempt to determine impacts on thepoorest people the data were disaggregated between groupsthat were in the ‘‘formal’’ or paid economy as comparedwith those in subsistence or the ‘‘informal’’ economy. Thisdistinction is not clear, and so it is not straightforward toobtain reliable input data. In this example, the input valueswere based on the opinions of experts in CSIR. Values wereestimated for 4 land uses and are shown in Table 3: futurework should aim to clarify reliability and sensitivities associ-ated with these numbers.

4.3. Logical information

Two variables were defined, a buffer for irrigated agricultureand a grid based on rainfall for forestry. The irrigated agriculturebuffer was produced in ArcGIS by generating successive buff-ered regions from the present irrigated areas. These bufferedregions were then intersected with the land use layer to producea suitable field in the land use shapefile. The rainfall grid (alsofrom CSIR) was then intersected with the land use layer.

For the model output icons, a significant change wasdefined as being a 10% change from the outputs based onthe land uses from 1996 within the current rainfall percentile.Thus in this paper, the output icons indicate only the result ofland use change, not the result of climatic variability.However, the interaction between weather and land use caneasily be modelled by simply changing the configuration ofEXCLAIM.

Table 3

Socio-economic indicator input values used in HYLUC for the 4 land uses used i

Land use Proportion

commercial

Productivity

commercial ($/ha)

Forestry 1.0 100

Rangeland 0.5 4

Dryland agriculture 0 378

Irrigated agriculture 0.5 3417

a Person-years/ha.

5. Results

Fig. 2 shows the whole Luvuvhu catchment with thequaternary catchment A92a highlighted. This figure hasbeen annotated to indicate the information available withinEXCLAIM.

An example of the output from the EXCLAIM tool for theA92a quaternary catchment within the Luvuhu, selected forthe set of land uses from 1996, and for a median rainfallyear, is shown in Fig. 3. All the indicator ‘smiley’ icons areimpassive, as this is the baseline scenario for comparison.

A changed land use scenario, selected by moving theforestry and irrigation sliders, to expand the areas under theseland uses is shown in Fig. 4. This scenario, with a change inland use but with the median climate, shows that the amountof runoff will be reduced, but not by more than 10%. Thedisplay also shows how, using the socio-economic data associ-ated with each land use, productivity and job opportunitieswill change with the change in land use. The employmentpossibilities are likely to increase under this land use scenario,but the total productivity is likely to decline.

The impact of changing land use, together with a differentclimate scenario, is shown in Fig. 5. Here the land use changeis the same as for Fig. 4 but the climate slider has been movedto represent a dry year (5th percentile, i.e. once every 20 yearswill be at least this dry). Here we see that the catchment wouldhave been in a ‘‘closure’’ condition, that is, there would havebeen no runoff out of the catchment, for such a dry year. Thenegative flow would indicate a reduction in water storagewithin the catchment during the year, made up of changes insurface, soil and groundwater storage.

5.1. Conclusions

The purpose of this paper is to describe a computerisedsystem that can be used by a range of stakeholders to helpevaluate the effects of land-related interventions within

n this analysis

Employment

commercial (py/ha)aProductivity

informal ($/ha)

Employment

informal (py/ha)a

0.03 0 0

0.001 100 0.003

0.04 200 248

0.18 1500 0

Fig. 3. Screenshot of the EXCLAIM tool with the Tengwe (A92a) catchment selected for a 1996 land use and a median rainfall climate scenario.

656 I. Calder et al. / Environmental Modelling & Software 23 (2008) 650e659

a catchment. EXCLAIM shows how such interventions affectthe partition of rain falling on the catchment into blue water(liquid) flow and green water (vapour) flow out of the catch-ment (Falkenmark, 1995). Where the appropriate socio-economic data are available, the tool can also demonstratehow spatial changes in land use affect job opportunities andeconomic production values.

EXCLAIM has minimal data requirements, as the model-ling per se is performed outside of the GIS tool. The minimaldata requirements facilitate the construction of ‘‘bespoke’’systems which can be tailored to a particular catchment orcountry’s needs. However, a variety of inputs and outputscan be used to enhance the model. In the example given inthis paper, the hydrological component is linked to a socio-economic component, to demonstrate how land use changealters the number of jobs and the levels of productivitytogether with the availability of water resources.

EXCLAIM allows the impacts of the land use changescenarios to be investigated for not only an average rainfallyear, but also, through the use of a slider, a range of rainfallyears. The slider allows the selection of the driest to the wet-test years in an historical record by moving the slider over therange of dry to wet.

The EXCLAIM viewer is intended to be flexible and capableof being used with a wide variety of datasets, models and inter-faces. Since the derivation of hydrological parameters is per-formed separately from the data entry for the EXCLAIM tool

itself, then the only limitation on the choice of hydrological modelis the ability to generate outputs at the appropriate scale. In orderto test EXCLAIM with another model, the only additional effortrequired is to enter a relatively small number of summary statis-tics into the EXCLAIM database. An example of this is found inJewitt et al. (2004), in which two models were compared undera system that is a fore-runner to EXCLAIM.

The use of XML for input of model data and applicationconfiguration means it can be easily customised without need-ing to make code changes, and the plug-in architecture of thecode means that incorporating additional models is relativelystraightforward. The simple user interface allows non-expertsto easily explore the effects of changing land use and climaticconditions and gives a rough indication as to whether thesechanges will have a positive or negative impact based uponthe available models.

Since the original implementation of EXCLAIM for theLuvuvhu catchment there have been a number of furtherdevelopments and implementations (see the web link at theend of the paper) which have demonstrated the flexibility ofthe approach. These include the investigation of the impactsof water retention measures (farm reservoirs and soil waterconservation structures) which has entailed the separatevisualisation in EXCLAIM of surface and groundwater flows.

From a scientific point of view, it would be quite feasible toreplace historical climatic data with data generated for a rangeof future climate change scenarios. These climate change

Fig. 4. Screenshot of the EXCLAIM tool with the Tengwe (A92a) catchment selected for an increased forestry and irrigation scenario under a median rainfall

climate scenario.

657I. Calder et al. / Environmental Modelling & Software 23 (2008) 650e659

scenarios could include the use of weather generators calibratedagainst GCM predictions (such as those from Kilsby et al.,2007), which might include not only rainfall changes butchanges in temperature and other climate variables related topotential evaporation. This would allow the combinedimpacts of future climate and land use changes to be exploredin relation to effects on water flows, economics and people’slivelihoods. A more robust calculation of blue water productionwould allow the display of the outputs at shorter timescales, andcould also allow the estimation of the effect of other manage-ment activity such as water harvesting. Water quality issuescould also be incorporated in addition to water quantity.

From a software point of view, the EXCLAIM tool iscurrently limited by requiring the user to download both theJava applet program and the data onto their local system. Thiscan cause issues on low bandwidth connections and could bea problem with larger catchments where the data needs aregreater. However, using server-side GIS technology such asArcGIS Server engine from ESRI (ESRI, 2004) it should bepossible to implement EXCLAIM as a server-based service.This would remove the need for substantial downloads andopen up the possibility of demonstrating the effects over largescales or incorporating the models themselves into the software.

EXCLAIM is currently being used as teaching tool, asa tool for Negotiation Support (NS) and as a means for dissem-inating knowledge of land and water interactions to policy

makers. The tool development was largely funded under theUK Department for International Development’s ForestryResearch Programme in support of a cluster of projects inIndia, South Africa and Central America dealing with forestand water issues. The tool has been applied to demonstratethe impacts of catchment interventions including changes inforest cover, irrigation and soil water conservation structuresin these countries. The tool has also been used under new pro-grammes of work relating to Bridging the gap between Re-search and Policy (BRAP) in India, China and Vietnam andhas proved very effective in communicating to policy makersthe concepts, issues and trade-offs associated with decisionsrelating to land use.

The development of EXCLAIM is not an alternative tohydrological or economic modelling. EXCLAIM is justa tool for technical modellers with a sophisticated under-standing of hydrology or economics to present clearly theirresults to the people who need to know. Of course, as inany modelling system, there is the danger that model uncer-tainty, or the introduction of spurious input data, might resultin inaccurate predictions. Whilst recognising that uncer-tainties in model predictions do exist, planning decisionsnevertheless need to be taken, and should be taken basedon the best available science. Tools such as EXCLAIM canhelp to make this best available knowledge more accessibleto non-specialists.

Fig. 5. Screenshot of the EXCLAIM tool with the Tengwe (A92a) catchment selected for an increased forestry and irrigation scenario and selected for a dry (5

percentile) rainfall year, showing ‘‘closure’’ conditions of negative flow e equivalent to negative water storage (soil, groundwater, surface water) over the year.

658 I. Calder et al. / Environmental Modelling & Software 23 (2008) 650e659

It is expected that with economic, environment and waterresource components built into the underlying models, thistype of tool will be of real value to decision-makers who aretrying to interpret both the biophysical and socio-economicimpacts of catchment interventions. Watershed managers,catchment planners, or agencies responsible for planning de-velopments, together with donor organisations, will have thetools in hand to challenge the current myths surrounding waterresources and thus assist with the implementation of theUnited Nations Conference on Environment and Development(UNCED) principles (United Nations Conference on Environ-ment and Development, 1992) and meeting the MillenniumDevelopment Goals (United Nations, 2000).

5.2. Web link

The most recent version of EXCLAIM can be obtained andviewed from http://www.needs.ncl.ac.uk/exclaim.

Acknowledgements

The development of the EXCLAIM tool was supportedunder the Forestry Research Programme (ZF0176) of the De-partment for International Development. Opinions expresseddo not necessarily reflect the views of the Forestry Researchprogramme.

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