mots clés: aménagement du territoire; productivité de l’eau; télédétection; analyse économique; indicateurs de l’eau
INTRODUCTION
Land and water resources in many of the world’s riverbasins are under unprecedented pressure resulting frompopulation growth, socio-economic development (e.g., theliberalization of the world food markets), socio-culturaldevelopments (e.g., changes in lifestyle and diet), andclimate change. These developments are leading to
* Correspondence to: Petra Hellegers, LEI, part of Wageningen UR, PO Box 29† Un outil interactif pour évaluer la planification des terres par des indicateurs lié
increasing competition for land and water resources. To dealeffectively with these competing claims, there must be goodcommunication between stakeholders in river basins. Thisapplies especially to large basins, because stakeholders arefrom various sectors, regions, and countries. Furthermore,the information that is communicated must be impartialand transparent.
703, 2502 LS the Hague, the Netherlands, E-mail: [email protected] à l’eau.
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144 P. J. G. J HELLEGERS ET AL.
Hydrological regimes and the availability of waterresources largely depend on land use and management inthe river basin. Land development in upstream areas im-pact on the availability and quality of water in down-stream areas, and may thus limit the developmentpotential of the latter areas. As land use is generally notplanned and managed at the river basin level, suboptimalconditions often emerge. That is, the favourable economicor ecological prospects of downstream areas are not beingfully utilized due to water scarcity or pollution, while lessfavourable areas located upstream use the water resourcessub-economically or sub-ecologically. This is especiallyvalid for transboundary river basins such as the Nile andKagera basins. Integrated water and land management atthe river basin scale is therefore imperative to deal effec-tively with competing claims on land and water. Althoughthe integration of land and water management is an impor-tant topic in the Comprehensive Assessment of WaterManagement in Agriculture (2007), it is dealt with mainlyin terms of water and agriculture. The broader scope of landand water management, namely incorporating both culti-vated lands and nature, has been less subject to integratedstudies.
The Water Evaluation and Planning (WEAP) tool (Yateset al., 2005) allows for the analysis of various water alloca-tion scenarios but not for the evaluation of water based landuse planning. More integrated land and water models (e.g.,SWAT) not only require large efforts in terms of data andmodel development, but also tend to have a strong hydro-logical approach. A common problem is that data and mod-els are not transparent and objective, which hinders theiracceptance by stakeholders; in land and water managementissues, such acceptance is generally more critical than thegeneration of accurate information.
This paper presents an interactive tool that can providerapid assessments of the impact of changes in land use onwater resources in river basins. The tool was developed tosupport discussions among stakeholders in river basins. Itcan be applied in multistakeholder meetings and workshopsand by individual stakeholders. The tool can instantly gener-ate key indicators for land and water management, and thiscan help stakeholders and decision makers identify develop-ment scenarios. Because the concept and assumptions arerelatively simple, the data are objective and transparentand the results can be easily verified (through own calcula-tions by the user); the tool is very suitable for applicationin meetings with stakeholders from various sectors, regions,and countries.
The tool has already been used in the Inkomati RiverBasin, which is a transboundary river basin shared by SouthAfrica, Swaziland, and Mozambique. The Inkomati RiverBasin was chosen to demonstrate the usefulness of the inter-active tool, as the basin is a typical example of one that is
experiencing water scarcity, over-exploitation of waterresources, population growth, economic development, andsocioeconomic reforms (which include the transfer of landto emerging farmers in South Africa under the National Wa-ter Act of 1998). It also has a wide applicability to land useand farming system, including subsistence farming, irrigatedsugar cane, pasture, natural vegetation, alien plants, KrugerNational Park, and commercial forest plantations.
The comprehensive basin wide Interim IncoMaputoAgreement (IIMA), which was signed in 2002, recognizesthe right of all riparian states to specific volumes of water.Water demand and use, however, are currently in excessof available water resources, certainly if the water require-ments of Mozambique and the Ecological Reserve are takeninto account. The Ecological Reserve is not met andthe cross-border flow to Mozambique is often less thanagreed upon in the IIMA. Moreover, water assurance tothe irrigation sector is very low in certain areas, especiallyin the lower reaches of the Crocodile River.
The tool was used in stakeholder meetings to identifypotential policy options, one of which is the current planto convert 25 000 ha of bushland into sugar cane for bio-fuel production in Mozambique. The tool allows for theassessment of the impact on water productivity, waterconsumption, and water availability for downstream uses.The tool can also be used to track strategic adjustmentsin land use or farming systems (cropping pattern) to com-ply with the tripartite water allocation agreements. To em-bark on a water reallocation process, either among thethree states or in accordance with the water supply objec-tives and priorities laid down in the National Water Act(Act 36 of 1998) and the National Water Resource Strat-egy, a better understanding of current water use and avail-able water resources at a regional (river basin) level isrequired. The IWAAS study (2008) provides insight intowater availability but only limited insight into actual wateruse by land use types. This paper explains the conceptsbehind a new, interactive water-based land use planningtool and shows its application in strengthening of stake-holder discussions. The tool is used to elaborate twoscenarios:
1. Conversion of 25,000 ha of bushland into sugar-canefor biofuels in Mozambique;
2. Prioritization of areas for zero replant of forest planta-tions in the upstream areas.
The first scenario was proposed by the stakeholdersduring an interactive workshop. The second was added toillustrate differences among areas in the cost-effectivenessof streamflow enhancement. The results of the tool’s appli-cation are presented. The accuracy of the various variableswill be discussed and some conclusions will be drawn.
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145WATER INDICATOR ASSESSMENT TOOL
METHOD AND MATERIALS
The interactive tool builds upon earlier studies in which re-mote sensing and economic analysis were combined to sup-port decision making in the Inkomati River Basin in SouthAfrica (Soppe et al., 2006; Hellegers et al., 2009, 2010)and in the Krishna River Basin in India (Hellegers andDavidson, 2010). The land and water indicators in the deci-sion making process will be elaborated as well as data toquantify these indicators and details concerning the setupand functionalities of the tool.
Indicators
The tool quantifies key land and water management indica-tors. These indicators can help identify and evaluate land de-velopment options that best serve policy objectives andpriorities. Discussions on future land uses can be betterstructured and more to the point by using water related indi-cators for existing and alternative land uses and by evaluat-ing tradeoffs between various land use options. The toolenables the assessment of four indicators, each of whichaddresses a specific policy objective as follows:
The agricultural production per unit of water is an importantindicator for the allocation and management of scarce waterresources (Kijne et al., 2003; Molden et al., 2007). The con-cept has been discussed extensively in the literature, espe-cially within the framework of the challenge of producingmore food with less water (Molden et al., 2010). The bio-physical crop water productivity (CWP) (kgm�3) is calcu-lated by dividing the beneficial biomass (yield) by thevolume of consumed water (Eq. 1). The yield of a crop iscalculated by multiplying the gross biomass production bythe crop’s harvest index (Eq. 2). CWP is relevant only foragricultural land uses and forest plantations.
CWPi ¼ Yi=10 � ETacti (1)
Yi ¼ ki �Mi (2)
with Yi, beneficial biomass or yield of crop i (kg ha�1);
ETacti, actual evapotranspiration of crop i (mm); ki, harvestindex of crop i (�); Mi, gross biomass of crop i (kg ha�1).
The actual evapotranspiration and gross biomass produc-tion can be quantified through remote sensing techniques.The harvest index is generally determined based on histori-cal yield data and/or the literature. As with evapotranspira-tion and biomass production, the harvest index can varyspatially, as certain areas are more suitable for specific cropsthan others. The harvest index may also vary between years,as climatic conditions and related yields vary from season toseason.
Economic water productivity
Economic water productivity (EWP) expresses the monetaryreturns on water, namely the monetary value of the pro-duced product per unit of water. EWP has been used instudies by Hellegers and Perry (2006), Soppe et al. (2006),and Hellegers et al. (2009, 2010). Here, the South Africanrand (ZAR) is used as the monetary unit. EWP can becalculated if the prices of commercial (agricultural andforestry) inputs and outputs are known. It is calculated bymultiplying the beneficial biomass (yield) by the marketprice, subtracting the financial production costs of all inputsexcept water, and dividing the figure by the volume of con-sumed water (Eq. 3). A negative EWP means that the finan-cial costs of production exceed the gross production value(benefits). This approach, which is known as the residualmethod (Young, 2005), relies on the principle that the valueof a good (its price times its quantity) is equal to the sum ofthe quantity of each input multiplied by its average value.The value of the consumed water (or the ‘value of water’or ‘net return to water’) can be calculated if the other inputsand outputs and their values are known (Hellegers andDavidson, 2010).
EWPi ¼ Pi � Yi - Bi � Yi - Cið Þ=10 � ETacti (3)
with Yi, beneficial biomass or yield of crop i (kg ha�1); Pi,market price of crop i (ZAR kg�1); Bi, variable financialproduction cost of crop i (ZAR kg�1); Ci, fixed financialproduction cost of crop i (ZAR ha�1); and ETacti, actualevapotranspiration of crop i (mm).
In this paper, EWP is applied only to commercial landuse. The EWP of Kruger National Park, which generatesrevenue from tourism, is not considered, as the relation be-tween water consumed by nature and monetary returns fromtourism is much more ambiguous than the relation betweenwater consumed by agriculture and forestry and the mone-tary returns from these sectors.
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146 P. J. G. J HELLEGERS ET AL.
Job water productivity
Job water productivity (JWP) (jobs m�3) is less extensivelydiscussed in the literature, yet is very relevant to SouthernAfrica. It can be calculated by dividing the number of jobs(employment) per ha of a certain land use by the volumeof water consumed by that land use (Eq. 4):
Copy
JWPi ¼ Ji=10 � ETacti (4)
with Ji, number of jobs required to manage the land use i(jobs ha�1) and ETacti, actual evapotranspiration of landuse i (mm).
Here, JWP is applied only to commercial land uses.
Water availability for downstream uses
Water availability for downstream use is an important indi-cator for the ecological reserve (environmental flow require-ments), water assurance commitments (water rights) orlicenses for certain water uses, and international agreements.Water availability for downstream use is determined byassuming that water resources are ultimately representedby precipitation and that water consumption is representedby actual evapotranspiration. Inter-basin transfers were notincorporated in the tool, but can be easily accounted for.Water availability is then assumed to equal the rainfall sur-plus (rainfall minus actual evapotranspiration). Using thetool in any area or sub-area, water availability for down-stream use is calculated as:
Qout ¼ Qin þ 10�X
P 0:5em- ETactið Þ�Ai� �
(5a)
for Qin þ 10�P P 0:5em- ETactið Þ�Ai
� �> 0 and
Qout ¼ 0
(5b)
for Qin þ 10�X
P 0:5em- ETactið Þ�Ai� �
< 0
with Qout, water availability for downstream areas (m3); Qin,
water available from upstream areas (m3); P, rainfall (mm);ETacti, actual evapotranspiration of land use i (mm); andAi, area of land use i (ha).
The tool assesses periods of one year, thus covering a hy-drological cycle. Equation 5b makes a provision for the tem-porary use of water from storage, for example in dry years.The calculated water availability for downstream use shouldnot be misinterpreted as river discharge. Part of the rainfallsurplus is stored in the soil profile, aquifers, and reservoirs(dams), and is therefore not immediately available. For rela-tively long periods, changes in storage are relatively small incomparison with the groundwater and surface water dis-charges; however, these changes in storage should not be
overlooked due to the large interannual variability of rain-fall. Percolation losses (e.g., from irrigation systems) anddomestic and industrial waste waters are regarded as internal(recoverable) flows and volumes, as they remain within thesystem. The actual domestic and industrial consumptivewater uses can be ignored, as most domestic and industrialuses are non-consumptive recoverable uses (Perry, 2007).
Data
Land use. A reliable land use map is critical to relategeographically the actual evapotranspiration and biomassproduction data from remote sensing to the different landuses. The land use map was created using NLC2000.
Rainfall. Rainfall data were retrieved from the TropicalRainfall Measurement Mission (TRMM), which carries aprecipitation radar. Data are available at 3-hour intervals.The spatial resolution of the data is 0.25�, which corre-sponds with a pixel size of approximately 25 km2. TheTRMM satellite rainfall model can have accuracies ofbetween 70% and 99% (Huffman et al., 2007). The accuracyof rainfall radar technologies was recently tested bySchuurmans et al. (2007). Detailed background informationabout the retrieval of rainfall data from satellites is providedby Barrett (1988), Barrett and Beaumont (1994), Petty(1995), Petty and Krajewski (1996), Kummerow et al.(1996), Smith et al. (1998), Kidd (2001), and Huffmanet al. (2007). The major advantage of using TRMM rainfalldata is that the data are impartial (they can be applied with-out spatial processing, which can sometimes be ambiguous)and are free of charge.
Actual evapotranspiration and biomass produc-tion. The actual evapotranspiration and biomass productionare calculated using the surface energy balance algorithmfor land (SEBAL) applied on MODIS images. Theseimages have a spatial resolution of 250 x 250m. SEBAL(Bastiaanssen et al., 2002, 2005) has been in use for20 years. The model uses remote sensing data and the phys-ics of the energy balance to estimate actual and potentialevapotranspiration (ETact, ETpot) from net available energy.In periods of water stress, the actual evapotranspiration isless than the potential evapotranspiration. The model wasextended to produce estimates of crop biomass production(Bastiaanssen and Ali, 2003), so that crop yield and cropwater productivity could be obtained on a pixel by pixel ba-sis. Energy balance and biomass production are calculatedapproximately twice a month. If land use maps are available,the consumptive water use can be calculated for each landuse. The geographical distribution of water consumptionfor particular land uses can also be determined. Field mea-surements of ETact over natural vegetation surfaces and
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147WATER INDICATOR ASSESSMENT TOOL
irrigated mango plantations in Brazil recently showed thatthe annual ETact values of SEBAL deviated 4.4% and0.5%, respectively, from the eddy correlation measurements(Teixeira et al., 2009).
Publications on the accuracy of crop yield estimates areless common. Zwart and Bastiaanssen (2007) showedthat reported wheat yields in the Yaqui irrigation district(Mexico) were on average 10% lower than remote sensingestimated yields. With the installation of GPS systems onharvesters, it will soon be easier to validate remotely sensedmaps of crop yields. The role of remote sensing algorithmsin estimating ETact has been reviewed by Moran andJackson (1991), Kustas and Norman (1996), Couraultet al. (2005), Kalma et al. (2008), and Verstraeten et al.(2008). The applicability of a satellite based energy balancefor mapping evapotranspiration has been assessed by Allenet al. (2005, 2007). The usefulness of remote sensing datato provide spatial information about water resources hasalso been demonstrated by Chowdary et al. (2008)and Casa et al. (2008). The latter applied a spatially distrib-uted simple water balance model, which allows the estima-tion of temporal and spatial variation of crop waterrequirements.
Harvest and socio-economic data. Biophysical cropcharacteristics such as harvest indices and yields, and so-cioeconomic data such as fixed and variable financialproduction costs of crops and the market prices of crops
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16
15
14
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12
2120
19
18
17
2423
Figure 1. Land management areas. This figure is available
(including commercial forestry), largely determine the out-comes of the tool. A main difference between these vari-ables and the ET is, however, that the user can specify thesocioeconomic variables and thus has direct control overtheir accuracy.
Tool setup and functionalities: spatial resolution. Anumber of geographical land management areas were identi-fied to allow for the spatial assessment of changes in landuse. Land use planning occurs at the level of these land man-agement areas and the land and water indicators are calcu-lated for these units. In the current version of the tool, theInkomati River Basin was subdivided into 24 land manage-ment areas (Fig. 1), of which 18 are located in South Africa,one in Swaziland and five in Mozambique. A total of 15land uses are distinguished. These include nine commercialland uses (cultivated areas and commercial forestry, inwhich consumptive use of water produces beneficial bio-mass) and six other uses (nature and built areas). The landmanagement areas do not refer to existing administrativeunits but were created to visualize the spatial variability ofland and water indicators over a perceivable number of spa-tial units.
Temporal resolution. To facilitate dynamics in landuse planning, the tool was developed to assess a recent aver-age year (2003–2004), a relatively dry year (2002–2003),and a relatively wet year (2005–2006). These years were
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148 P. J. G. J HELLEGERS ET AL.
selected on the basis of rainfall data covering the past10 years. The use of older climatic data is not desirable,as the utilized land use data refer to 2000. Combining dataof the year 2000 with old climate data could introduce sig-nificant errors.
Functionalities. The current version of the tool caninstantly show for each land management area the implica-tions of land use changes anywhere in the river basin for:
• crop water productivity;• economic water productivity;• total water production value (in million ZAR);• water use related jobs;• volume of water available from upstream areas;• actual evapotranspiration (consumptive water use);• volume of water available to downstream areas;• water taken from storage (in the case of a negativerainfall surplus).
In addition, rainfall, total area under commercial land use,biomass production, socioeconomic background data, andother general data are presented. The average actual evapo-transpiration and biomass production is calculated for eachof the 15 land uses in each of the 24 land management area,and for each of the three years. If a certain land use does notoccur in any of the land management areas, values from theneighbouring land management area are taken. These aver-age values (ETacti and Mi in equations 1–5) are consideredcharacteristic (non-variable) data of a land managementarea. If any change in land use is introduced in a land man-agement area (in a certain year), the actual evapotranspira-tion (consumptive water use) in that area is recalculated to:P15
i¼1ðETacti�AiÞ . Thereafter, CWP, EWP, and JWP arerecalculated as previously described.
It is important to note that ETact is not only dependent onland use but also on the prevailing climatology of an area.Hence, the tool has a deficiency when sugar cane is plantedin areas that are climatologically different then the referenceareas for sugar cane that are used to determine the spectrumof ETact values. This discrepancy in atmospheric conditionscould create a systematic deviation from the average ETact
value found for existing sugar cane areas if sugar cane isnot cultivated in nearby areas. One way to solve this issuein the next version of the model will be to include the conceptof reference ET and a crop coefficient. Another limitation is thatETact also depends on agricultural practices. Water produc-tivity can, for example, be increased through efficient irriga-tion systems that minimize evaporation losses. By analyzingthe statistical characteristics of water productivity for eachland use in a certain area, the scope for more efficient wateruse and saving can be assessed. The option of water savingmight be included in the next version of the tool.
Water availability to downstream areas is calculated with arouting procedure that takes into account the hydrologicalstructure of the river basin. Water availability to downstreamareas is calculated as the sum of water availability from up-stream areas plus rainfall surplus in the area. In the case ofa calculated negative water availability to downstream areas(due to rainfall deficit), it is assumed that the water debit istaken from storage and that water availability to downstreamareas is nil. The conversion of land towards even more waterconsuming land use in upstream areas that have already anegative rainfall surplus is not restricted by the tool. The tool,thus, does not consider biophysical system limitations.Details are also given in the online tool manual.
Analysis and interactive use
The current version of the tool consists of a viewer and in-teractive mode. The viewer mode enables the display of allbasic data on thematic pixel maps: land use, biomass pro-duction, actual and potential evapotranspiration, and rainfall(mostly at a spatial resolution of 250m). The viewer modecan also show the indicators and the basic data aggregatedfor the land management areas. Data are presented in theform of both tables and maps. In the interactive mode, theuser can introduce and assess land use changes in each ofthe 24 land management areas and for each of the threeyears. Market prices, production costs, and harvest indicescan be specified and altered. After each adjustment, the toolinstantly recalculates the land and water indicators, displaysthem in tables and maps, and compares them with the cur-rent (reference) situation.
To allow for the application of the tool at any time and any-where, it has been developed as a web-based application. Forinteractive use and for defining, saving, and reopening scenar-ios, the user needs to log in. The tool works in a GIS environ-ment. It uses open source software to enable license freehosting, and application and open standards to ensure compat-ibility, easy further development, maintenance, and any futureextension of functionalities without being dependent on devel-opers or vendors. Although the interactive tool is accessibleonly to authorized users, non-authorized users may browsethrough the existing data presented in the tool. The viewermode contains hundreds of base maps, while a virtual unlim-ited number of additional maps with land and water indicatorscan be generated (online) in the interactive mode. Maps arecontinuously updated while the user works with the tool.
INTERACTIVE PLANNING AND EVALUATIONOF SCENARIOS
Scenarios of land use planning can be identified and evalu-ated either interactively (e.g., in stakeholder meetings) or in-dividually. In this section, two potential land development
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149WATER INDICATOR ASSESSMENT TOOL
scenarios in the Inkomati River Basin in Southern Africawere evaluated to demonstrate the usefulness of the tool.
The Inkomati River Basin
The Inkomati River Basin incorporates six sub-basins: theKomati, Crocodile, Sabie Massintonto, Uanetze, andMazimchopes rivers (Fig. 2). The Komati River originatesin the southwest of the basin, flows from South Africa toSwaziland, then re-enters South Africa before crossing intoMozambique at Komatipoort and Ressano Garcia. TheCrocodile River is located in the centre of the basin. It joinsthe Komati River just before it flows into Mozambique,where the river is called the Incomati. The Sabie River ori-ginates in the northwest of the basin. It flows throughKruger National Park towards Mozambique, where it even-tually joins the Incomati River. In the north, three relativelysmall rivers (Massintonto, Uanetze, Mazimchopes) alsocross Kruger National Park and flow towards Mozambique.As the discharges of these three rivers are very limited, landand water planning and management mainly concern thearea covered by the Komati, Crocodile, and Sabie basins.
Scenario development. Approximately 12% of the ba-sin (638 000 ha) is used for rainfed agriculture, forest planta-tions, and livestock (grazing areas), and about 5% (260000 ha) is used for irrigated agriculture. Thus, 17% of theland is managed while 83% is not. Some of the unmanagedland could be converted into managed land; for example,
Figure 2. Inkomati River Basin with sub-basins. This figure is ava
bushland and natural grassland could be converted into agri-cultural areas. The scope for land use adaptation, however,is limited. Conversion depends not only on the availabilityof water resources but also on the agricultural potentialand the existing and planned economic and ecologicalfunctions. For example, it is not realistic to convert part ofKruger National Park into irrigated agricultural land. Landuse planning should, of course, involve both regional andlocal knowledge from planners and stakeholders.
As a showcase, two scenarios are evaluated and discussedin this section:
• conversion of 25 000 ha of bushland into cultivatedarea for sugar cane for biofuel production inMozambique;
• prioritization of areas for zero replant of forest planta-tions in the upstream areas on the basis of, for example,the cost-effectiveness of streamflow enhancement.
Development of sugar cane in Mozambique
During an interactive workshop, stakeholders proposedassessing the conversion of 25 000 ha of bushland into agri-cultural land for the cultivation of sugar cane. The proposedarea is located in Mozambique, in the area where the Inco-mati and Sabie rivers join. The 25 000 ha represents 9% ofthe total area (Fig. 3). Table 1 shows that in an average year,this land conversion would cause a 52 million m3 decreasein the rainfall surplus (from 62 to 10 million m3), as sugar
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Figure 3. Land cover in the baseline situation (before conversion) in area 5
150 P. J. G. J HELLEGERS ET AL.
cane consumes 867mm of water and bushland only639mm. Water availability to downstream areas wouldtherefore decrease by 3% (from 1730 to 1680 million m3
per year).In a dry year, there is already a rainfall deficit of
479 million m3. The development of sugar cane wouldincrease the deficit by 85 million m3 (towards a deficit of564 million m3). As in a dry year there is no water available
Table I. Situation before and after conversion of 25 000 ha of bushland
Area 5 Dry year
BeforeCWP (kg/m3) 0.016EWP (ZAR/m3) 0.002Production value (million ZAR) 6Water use related jobs 1090 18Rainfall (mm) 374ETact (mm) 547Gross area (ha) 277 000 277Commercial area (ha) 2450 27Water available from upstream areas (million m3) 0Rainfall surplus (million m3) �479 �Water availability to downstream areas (million m3) 0Deficit/water from storage (million m3) 479
Zero replant of forest plantations in the upstream area.
from upstream areas, this scenario is only feasible if provi-sions are made to cover the water shortage in the form of,for example, surface water reservoirs or boreholes, orarrangements with upstream water uses to release more wa-ter. Both CWP and EWP of the area would, however, in-crease considerably. The production value of the areawould increase from 6 million to 283 million ZAR/year ina dry year and to 321 million ZAR/year in an average year.
into sugar cane in Mozambique
Average year Wet year
After Before After Before After0.141 0.023 0.164 0.018 0.1460.102 0.003 0.116 0.002 0.105
The cultivation of sugar cane would also create about 17 000additional jobs in the area. These economic and social bene-fits could provide space for negotiations and compensationschemes with less productive upstream water uses.
In this example, the EWP in a dry and wet year are lowerthan in an average year. Possible explanations are loweryields in dry years, insufficient use of water in wet years,low market prices in wet years, high seasonal labour costs,etc. Such results add to the discussion and stakeholders fromthe area should be able to explain the results. The water re-lated jobs do not change since with unchanged land use, thesame number of people will work during a dry, average, andwet year. The job water productivity (not shown in the table)will however be different. The water related jobs do changewith land use changes.
The water consumption (ETact) of forest plantations is rel-atively high compared to other land uses. Limited or zero re-plant of commercial forests would therefore enhance wateravailability to downstream areas. In South Africa, commer-cial forests have been planted in various upstream areas. Thetool can help prioritize areas for zero replant on the basis of,for example, the lowest decrease in economic productionvalue per m3 of water, which would then become availablefor downstream areas.
Table 2 shows the change in the land and water indicatorsshould forest plantations be converted into bushland. Threeupstream areas were assessed for an average and a dry year.In areas 9, 10, and 12, 6130, 81 900 and 18 700 ha (repre-senting respectively, 5.7%, 33.8%, and 12.3% of the totalarea) were converted. The difference in ETact between forestplantations and bushland that re-establishes on the site was350, 168 and 191mm, respectively. The resulting increasein rainfall surplus per ha converted was consequently high-est in area 9, while the increase in the total rainfall surplus
Table II. Change in land and water indicators due to conversion of forestyear
Area 9 (yea
Dry y AΔ CWP of the area (kg/m3) �0.137Δ EWP of the area (ZAR/m3) �0.014Δ Production value (million ZAR) �15Δ Water use related jobs �257 �Δ ETact (mm) �18Δ Commercial area (ha) �6130 �6Δ Water available from upstream areas (million m3) 0Δ Rainfall surplus (million m3) 20Δ Water availability to downstream areas (million m3) 0Δ Deficit/water from storage(million m3) �20
Area 9 shows the lowest decrease in CWP and EWP and the lowest decrease in totarget area 9, 10, or 12 for zero replant also depends on the change in the land andthere.
was highest in area 10 (due to the low share of forest plan-tation in the total area of area 9).
DISCUSSION
The ET values of the Incomati River Basin are computed bymeans of the SEBAL model. This model has been validatedfor energy balance measurements in various parts of theworld and also inside South Africa. A summary of compar-isons with field measurements can be found in Soppe et al.(2006). A validation with grapes in the Western Cape hasbeen published by Jarmain et al. (2007), which revealed thatthe deviation of ET from field water balances and SEBALsurface energy balances were within the limitations of fieldmeasurement technologies.
The overall accuracy of accumulated values for ET inlandscapes with pastures, bushland, sugar cane, and orchardplantations is 90 to 95%. This value typically pertains to aparticular field within a certain land use class. The planningtool described in this paper considers the full spectrum ofET within a given land use class. While for certain pixels,the accuracy might be 90 to 95%, the accuracy of the landuse as a total group of pixels is 95% or higher. The averageET value is thus rather accurate. Further to the validation ofSEBAL against field measurements, ET data could be pre-sented on a month-to-month basis for diverging types ofland use classes. While the ET of mountainous forestremains moderate and constant throughout the year, the tem-poral variability of ET in the pastures exhibit a distinct sea-sonality. ET data does seem to be robust and consistent forthe sake of land use planning.
The spatial resolution of the TRMM rainfall data was0.25º, which corresponds to approximately 25 kilometres.The spatial resolution of the MODIS images used for the
plantations into bushland in areas 9, 10, and 12 in a dry an average
r, y) Area 10 (year, y) Area 12 (year, y)
verage y Dry y Average y Dry y Average y�0.148 �0.826 �0.899 �0.287 �0.338�0.015 �0.083 �0.090 �0.029 �0.034�15 �200 �218 �44 �52257 �3,440 �3,440 �785 �785�18 �86 �56 �24 �25130 �81 900 �81 900 1870 �18 7000 0 0 0 019 208 136 35 3819 0 0 0 380 �208 �136 �35 0
tal production value (15 million ZAR, which is 0.75 ZAR/m3). Whether towater indicators in the downstream areas and the policy priorities that exist
Irrig. and Drain. 61: 143–154 (2012)
152 P. J. G. J HELLEGERS ET AL.
calculation of the actual evapotranspiration was 250m. Wa-ter availability was calculated as rainfall surplus, subtractingthe annual actual evapotranspiration as determined bySEBAL from the annual rainfall from TRMM. Especiallyin relatively water scarce areas, this could result in signifi-cant inaccuracies, as the absolute value of water availabilitywill be low. It should be noted that the TRMM rainfall dataare calibrated in the Americas whereas in Africa, this is gen-erally not the case. In the Inkomati River Basin, TRMMseems to underestimate the rainfall. The accuracy can be in-creased by calibrating the TRMM data, for example with to-pography, wind direction, land cover, and recorded rainfall.A preliminary assessment showed that calibration withmeteo stations alone is not sufficient. To further increase ac-curacy, a more detailed downscaling method for the TRMMdata needs to be developed.
As previously stated, water availability should not beinterpreted as river discharge. For 13 hydrological stations,the accumulated upstream rainfall surplus was calculatedbased on 250 x 250m pixels and compared with therecorded river discharges, showing low correlation. This ac-cumulated rainfall surplus was also calculated with variousdownscaling methods for the TRMM data, which alsoshowed little correlation. Obviously, the changes in storagecould not be neglected over periods of one year. If reliableriver discharges need to be calculated, a hydrological ap-proach is required. For the sake of transparency and verifi-ability, the original non corrected TRMM data are used inthe tool. As the tool does not provide detailed results, furthermore in-depth investigations should be carried out after therapid assessments. In addition, as the results largely dependon the quality of the underlying data, particularly basic eco-nomic data and land use map, it is imperative to have reli-able data on current land use, market prices, andproduction costs. It should also be taken into account thatlarge changes in land use can affect market prices, especiallyif crops are produced for the local markets, since the supplywill change.
CONCLUSIONS AND RECOMMENDATIONS
The tool presented in this paper enables stakeholders toevaluate the impact of alternative land development scenar-ios based on a number of water related indicators. The toolgenerates spatially distributed information about changesin water consumption, water productivity, and wateravailability, based on a consistent method and impartial,transparent, and verifiable information. The method is con-sistent in that it is applied to the entire river basin and thelevel of accuracy is maintained. The generation of the basicdata on water resources, rainfall, evapotranspiration, andrainfall surplus excludes potentially subjective human
interpretations. The tool can therefore play a role in confi-dence building and promote open discussions among stake-holders. It can help stakeholders evaluate tradeoffs betweenalternative land development options and courses of socialaction that could impact water resources and water use. Byevaluating water related indicators, users can identify themost preferable land uses and their spatial distribution overthe basin from a water resources perspective. The tool isintended for interactive use. Stakeholders can instantly in-vestigate the impacts of changes in land use, which makesthe tool particularly suitable for use in workshops and meet-ings. To ensure the identification of realistic land develop-ment scenarios, the tool should be used in collaborationwith spatial planners. Land conversion scenarios should fo-cus on manageable land uses.
The usefulness of the tool was demonstrated in stake-holder meetings in the Inkomati River Basin. Stakeholdersbecame more aware of the impact of changes in land useon water resources and this resulted in lively discussions.It was also shown that the EWP is not equal among thecrops, as suggested in theory. Spatial variations in waterproductivity can be due to management practices, randomevents (which cannot be controlled), and the natural produc-tivity of the farm resources (Hellegers et al., 2010). Exam-ples of management practices are irrigation application(e.g., excessive deliveries causing non productive evapora-tion from wet soil), weed control, seed selection, and theuse of nutrients and pesticides. Examples of random eventsare droughts, storms, and pest attacks. The natural produc-tivity of farms depends on the climate, local hydrology(e.g., water tables), and soil characteristics. Because the toolalso generates information on biomass production, it can beused to assess carbon sequestration policies. As some typesof land use can capture and store more carbon dioxide thanothers, the area under such crops as trees could be expandedto reduce the accumulation of greenhouse gases in the atmo-sphere. Another of the tool’s potential applications is the pri-oritization of areas for the removal of invasive alien species,thus supporting the Working for Water programme in SouthAfrica. For this purpose, areas should be identified whereexcessive evapotranspiration rates are observed for certainland uses. Dye and Jarmain (2004) reported reductions inevapotranspiration of up to 600mm following the removalof black wattle from indigenous grassland. The tool can befurther developed by adding an ecological water productiv-ity indicator, which could be used to evaluate policy priori-ties aimed at securing the ecological integrity of an area.
The current tool is static: it provides annual data that canpromote strategic land planning. It is not designed for oper-ational land and water management (e.g., to respond todroughts and floods), nor does it incorporate options to im-prove water management and water saving. To incorporatesuch functionalities, the calculation of the rainfall surplus
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153WATER INDICATOR ASSESSMENT TOOL
in the land management areas should be replaced by moredetailed hydrological calculations derived from, for exam-ple, a hydrological model. With a dynamic hydrologicalmodel, critical hydrological components such as surfaceand groundwater flows and changes in the soil moisture con-tent can be quantified in time, which enables assessments forshort periods during the year. Options for management prac-tices and water saving can be evaluated by investigating thestochastic characteristics of the indicators. For example, ahigh standard deviation of water productivity in an area indi-cates that there is scope for improvement by, for example,training farmers or introducing more modern agriculturaland on farm water management practices. Differences be-tween various areas might also be investigated in more de-tail. This would help identify target areas to supportemerging farmers, for example. In addition, location specificcrop production functions (with yield as a function of ETact)can be derived from data on biomass production and waterconsumption, which can help optimize water allocationstrategies and develop strategies for fractional irrigation intimes of scarcity. As operational water management, onfarm water management, water saving, and water allocationare key issues in the Inkomati River Basin, it is recom-mended to extend the tool by adding these functionalities.
ACKNOWLEDGEMENT
This paper was written in the framework of the DGIS–Wageningen UR Partnership programme Competing Claimson Natural Resources, the aim of which is to provide guidancein dealing with potentially conflicting multiple uses of naturalresources.
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