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Agricultural Water Management 108 (2012) 3951

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Agricultural Water Management

j o u rn a l h om e page : www.e l sev i e r. com/ loca t e / agwa t

Improved indicators of water use performance and productivity for sustainablewater conservation and savingLuis S. Pereira a,, Ian Cordery b , Iacovos Iacovides ca CEER Biosystems Engineering, Institute of Agronomy,Technical University of Lisbon, Tapada da Ajuda, Portugalb School of Civil and Environmental Engineering, University of NewSouth Wales, Sydney, Australiac I.A.CO Ltd., Environmental and Water Consultants, Nicosia, Cyprus

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Keywords:Benecial water useWater wastages and lossesWater productivityEconomic water productivityWater conservationWater savingEfcient water use

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Water use concepts and performance descriptors that may be useful in dening conservation and savingof water are discussed with the aim of improving the overall performance and productivity of water use.New indicators are proposed which include consideration of water reuse and aim to assist in identifyingand providing clear distinctions between benecial and non-benecial water uses. An analysis of produc-tivity concepts useful both in irrigation and elsewhere is provided together with suggestions for wherecommonly used terms, such as the broadly used water use efciency among others, would be betteravoided in irrigation engineering and given much more narrowly dened meanings in agronomy andbiological sciences. Particular attention is given to economic issues in water productivity. The analysis iscompleted with various case study applications at irrigation farm and system scales. It is recommendedthat a set of terms (not necessarily those developed here) be widely adopted that will provide a basis foreasy, certain communication and provide widespread common understanding of the issues which mustbe faced to develop approaches to achieve efcient water use.

2011 Elsevier B.V. All r ights reserved.

1. Introduction

For millennia, civilizations developed in water scarce envi-ronments, however where scarcity was less stringent than thatwe know today. The respective cultural skills, particularly withrespect to water use are an essential heritage of those nationsand peoples, and of humanity generally. However, progress in theXXth century questioned traditional know-how, which has oftenbeen replaced by modern technologies and management importedfrom different environments and cultures. A culture of economis-ing water is following the technical one, which was introducedwhen large irrigation schemes were built and water scarcity wasnot yet a challenge. Both technologies and management weregenerally imported from different cultural and institutional envi-ronments, and their adaptation to local conditions has not alwaysbeen successfully adopted or accepted by farmers. Managementtherefore faces difcult challenges arising from the fact that irri-gators perceive problems, practices and objectives different fromthose perceived by the non-farmer water and nancial managers.Despite its great importance, a discussion on differences of per-ception of water management and efciency objectives between

Corresponding author. Tel.: +351 213653480; fax: +351 213653287.E-mail address: [email protected] (L.S. Pereira).

farmers and policy- and decision-makers is out of the scope of this paper. For example, an analysis of UK farmers perception of irrigation efciency is addressed in this issue ( Knox et al., 2011 ).

Thelast century hasknownan increasedinterventionof govern-mental and state institutions in water management following theenormous investments made. Traditional institutions lost impor-tance and new centralized institutions were created to manageand operate the introduced investments and technologies. Eventhough in many places there is already 100% commitment of waterresources there remains ongoing increasing demand. As a result of lack of success of existing institutional arrangements a number of variations of participatory irrigation management are now beingconsidered to solve the resulting problems. Related challenges andsuccessful issues for Asian irrigation communities are analysed inShivakoti et al. (2005) . Self-governing irrigation systems are advo-cated by many authors. The classical analysis on this subject bythe 2009 Nobel Prize winner deserves attention ( Ostrom, 1992 ).A reconsideration of traditional irrigation practices is starting anda new appreciation of the advantages of traditional know-howis beginning to appear. However, pressures on irrigating farmersare continuing to require them to increase irrigation efciency,achieve higher water productivity and use less water. Yet there isoften a lack of assistance for them to develop and adopt improvedapproaches and techniques appropriate to these changing farmingobjectives, however keeping farmers objectives of nancial and

0378-3774/$ see front matter 2011 Elsevier B.V. All rights reserved.

doi: 10.1016/j.agwat.2011.08.022
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40 L.S. Pereira et al./ Agricultural Water Management 108 (2012) 3951

social nature. In addition, perceptions of an urban society that veryhighly prioritisesenvironmental preservation for futurewater allo-cation are also challenging farmers attitudes and requiring newapproaches.

A new communication model has to be developed that couldlead to a better understanding of water use in agriculture anddemonstrate why performance improvement must occur withinthe context of the needs of the societies and the objectives of farm-ing ( Clemmens and Molden, 2007; Perry, 2007; Lankford, in thisissue ). Newapproaches arerequiredto properlydene andaccountforeachitemof wateruse andproductivitywithwaterconservationandsavingbeing theprimarydrivers to achieve higherperformance(Fosterand Perry,2010;Moldenet al., 2010 ). Fromthis perspective,the performance concepts need to be differently dened, under-stood and applied. In other words, we need a new model in termsof conceptualization of water use performance that can be under-stoodby users,managersand decision-makers alike. This improvedconceptualization can then provide a common framework aroundwhich actual water use (hopefully monitored water use debateover words isnotvery usefulif theactual volumes involved areonlyapproximate) canbecomesustainable forlarge andsmallfarmersorother users, in allclimates and in societieswith different degrees of development, utilising a wide range of technologies (see for exam-ple Rockstrm et al., 2010 , calling for a paradigm shift to watermanagement in rainfed agriculture).

The terms water conservation and water saving are generallyassociatedwith the managementof water resourcesunderscarcity.However, these terms are often used with different meaningswithin specic scientic and technical disciplines or in the wateruser sector considered. Often, both terms are used synonymously.

The term water conservation is used herein to refer to everypolicy, managerial measure, or user practice that aims to conserveor preserve the water resource, as well as to combat the degra-dation of the water resource, including its quality. Differently, theterm water saving describes the avoidance of loss of water by lim-iting or controlling water demand and use for any specic purpose(cf. diversion and depletion savings proposed by Haie and Keller,2008 ), including the avoidance of wastes and the misuse of water.In practice these terms or perspectives are complementary andinter-related. Water conservationplaysa major role in rainfed agri-culture and when irrigation is supplemental of rainfall ( Unger andHowell, 1999; Oweis and Hachum, 2003, 2006; Rockstrm et al.,2010 ) but it isessentialin all water use systems, often asa means toachieve water saving ( Pereira et al., 2009 ). Water conservation canplay a major role in agricultural and landscape irrigation consid-ering that predictions for climate change indicate a concentrationof rainfall and an increase of its intensity. A coupling of soil andwater conservation is then essential to increase water inltrationand storage in the soil prole as well as to control soil evapo-ration. Water conservation increases the amount of consumptiveuse by crops and natural vegetation, sometimes called the green

water fraction, andassists in preserving thequalityof ows that areoften calledthe blue water,the general good quality environmentalwater ( Falkenmark and Lannerstad, 2005 ). Water savings usuallyrefer to the blue water fraction. Despite it often not being easyto distinguish between conservation and saving, these termsshould not be used synonymously. For example questions rela-tive to preservation and upgrading of water quality are essentialin water conservation but are rarely relevant to the usual ideasof water saving. A comprehensive analysis on water conservationand saving for a variety of agricultural and non-agricultural uses ispresented by Pereira et al. (2009) .

It is arguablya moderntragedy that considerablevolumes of thescarceresourcecanandarebeinglostorwastedduetolackofclarityof termsused andmiscommunication betweenthoseinvolved. This

is analysed in most papers in this issue, with the various authors

adopting a variety of approaches. Yet communication must alsoapply to specic elds or scales: our main focus in this paper iswater use at the farm scale, or a group of users served by the samesystem,not basin planning orwater allocation. Thereforethe aimof thispaperis twofold: (1) to demonstratethe confusionof the termsused both between and within disciplines and groups of users, andthe resulting potential for poor use of water, and (2) to suggestalternative terms that could gain wide acceptance and commonusage. Some case study applications are used to illustrate the useof these terms and ideas.

2. Water use, consumptive use, water losses, andperformance

2.1. Water systems, efciency, and water use performance

The performance of water supply systems and water use activi-ties areoften expressed with terms relative to efciency. However,there are no widely accepted denitions, and the efciency termsare used with different meanings, mainly relative to the variouswater use sectors. In certain cases, both water conservation andwater saving are used as synonymous with water use efciency

(e.g., Gardu no and Arregun-Corts,1994 ). Fora better understand-ing of terminology utilized in relation to water use performance, amore consistent conceptual approach is required.

Theterm efciency is often used in thecase of irrigation systemsand it is commonly applied to each irrigation sub-system: storage,conveyance,off- and on-farm distribution, and on-farm applicationsub-systems ( Bos and Nugteren, 1982; Wolters, 1992 ). It can bedened by an output to input ratio, between the water depth ben-ecially used by the sub-system under consideration and the totalwater depth supplied to that sub-system, usually being expressedin percentage terms. In case of on-farm application efciency, thenumerator is replaced by the amount of water added to the rootzone storage and thedenominator is thetotal waterapplied to thateld. However, we argue that an efciency indicator refers to asingle event and should not be applied to a full irrigation seasonwithout adopting an appropriate up-scaling approach. These indi-cators relate to individual processes and their use as a bulk termdoes not provide sufcient information on the processes involved.A schematic of processes involved in irrigation water use is givenin Fig. 1. For non-irrigation water systems, the term efciency is

Croptranspiration

Soilevaporation

Seepage +runoff

Conveyance +distribution

Application tocropped field

Deep percolation+ runoff

Direct evaporation+ non-crop ET

YIELD

Reuse

Classical transport &distribution efficiency

Classical applicationefficiency

Water diversion

Agriculture

Effective rain

Reuse

Fig. 1. Processes inuencing irrigation efciency off- and on-farm: grey boxes arethe processes leading to the crop yield; white boxes are those leading to water

wastes and losses.


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NON-CONSUMEDFRACTION

-

DegradedQuality

PreservedQuality

BeneficialBeneficial

WATER DIVERTEDFOR ANY USE

CONSUMEDFRACTION

-NON-REUSABLE

-

BeneficialBeneficial

REUSABLE

Beneficial

Non-beneficial

Beneficial

Non-beneficial

Non-consumptiveprocess use

Non-beneficial, waste(available for reuse)

Non-beneficial(non-reusable)

LOSSES

Fig. 2. Water use, consumptive and non-consumptive use, benecial and non-benecial uses, water wastes and losses.

adopted WP with physiological meanings such as photosyntheticandbiomass WP, which arefar from water uses in irrigation, indus-try or elsewhere. Hence, WP should be used with more precisionwith identication of the scalesto which it refers, as discussed laterin this paper relative to irrigation and non-irrigation water use.

2.2. Water use, consumption, wastes and losses

New concepts to clearly distinguish between consumptive andnon-consumptive uses, and benecial and non-benecial uses arebeing developed. Similarly the differences between reusable andnon-reusable fractions of the non-consumed water diverted intoan irrigation system or subsystem are being claried ( Willardsonet al.,1994;Allen et al.,1997;Pereiraet al.,2002; Perry et al.,2009 ).Along this line, aimed at promoting sustainable groundwater usein irrigation, Foster and Perry (2010) also proposed a set of wateruse fractions. These descriptors consist of alternative performanceindicators that are much more relevant than irrigation efciencywhen adopted in regional water management for the formulationof water conservation and water saving policies and measures. Anexpected advantage of these indicators is that irrigating farmersunderstandthembetterthan efciencies.Moreover,these conceptsand indicators areapplicable to irrigation and non-irrigation wateruses.

When water is diverted for any use only a fraction is consump-tive use. The non-consumed fraction is returned after use with itsquality preserved or degraded. Quality is preserved when the pri-mary use does not degrade its quality to a level that does not allowreuse, or when water is treated after that primary use, or whenwater is not added to poor quality, saline water bodies. Otherwise,water quality is considered degraded and water is not reusable

(Fig. 2). Alternatively, the terms recoverable and non-recoverableare adopted by Perry et al. (2009) .

Both consumed and non-consumed fractions concern benecialand non-benecial water uses. These are benecial when they arefully oriented to achieve the desirable yield, product, or service.Alternatively, when that use is inappropriate or unnecessary, it iscalled non-benecial. Reusable water fractions arenot lost becausethey return to thewater cycle and may be reused laterby the sameor by other users. They are not losses, but are wastes since theycorrespond to water unnecessarily mobilized. Contrarily, the non-benecial water consumed (perhaps evaporated) or returned topoor quality, salinewaterbodies, or that contributes to degradationof any water body, is effectively a water loss ( Fig. 2).

Although a water use attempts to be purposeful, it is impor-

tant to recognize, from the water economy perspective, both the

WATER USE INAGRICULTURE AND

LANDSCAPE

Reservoir

System

Field

YIELD

Crop ET

Leaching

BWU

Seepage +runoff

Non-crop ET

Evaporation

Percolation +runoff

N-BWU

Fig. 3. Benecial and non-benecial water use (respectively BWU and N-BWU) incrop and landscape irrigation.

benecial and non-benecial water uses ( Fig. 3). This has also been

attempted by Solomon and Burt (1999) when they proposed thetermirrigation sagacity. In crop and landscape irrigation, the bene-cial uses are those directly contributing to an agriculturalproductor anagreeablegarden, lawn or golf coursewherethe desired prod-uct may be maintenance of certain characteristics in the biomass.Non-benecial uses are those that result from excess irrigation,poor management of the supply system, or from misuse of thewater.

These concepts may also be applied to the use ofwater in indus-try, urban regions, energy production and other activities. Thenbenecial uses include all the activities and processes leading toachievement of some production or service which results in somegood or benet, such as drinking, cooking, washing, heating, cool-ing, or generating energy. The uses are not benecial when wateris used in non-necessary processes, is misused or is used in excessof the requirements for productivity ( Fig. 4).

It is important to recognize that the approach referred toabove, which is based upon the water use fractions proposed byWillardson et al. (1994) and Allen et al. (1997) , as well as thewater accounting developed by Molden (1997) , essentially aims atassessingthepathwaysforimprovingwater usesin agricultural and

WATER DIVERSIONFOR ANY USE

Reservoir

Conveyance+ delivery

system

Processapplication

PRODUCT

Processwater use

BWU

Seepage +runoff

Evaporation

Non-processwater use

N-BWUReuse andrecycling

Fig. 4. Benecial and non-benecial water use (respectively BWU and N-BWU) inagriculture, industry, urban processes, energy production and landscape develop-

ment, with referenceto reuse or recycling.


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L.S. Pereira et al./ Agricultural Water Management 108 (2012) 3951 43

non-agricultural processes.Theyapply to singleusers or to groupedusers practicing a common activity that leads to the same type of product or service, e.g., a farm, a group of farmers within an irri-gation sector, an industry or a urban sector. This papers approachdiffers from the water accounting approach developed by IWMI(Molden, 1997; Molden et al., 2003 ) where the water balance ismainly focused on the (basin) water allocation and its assessment.

Assuming theconcepts above,it is thereforeimportant to recog-nize what ismeantby efcientwateruse.To support this concept,a few important ideas are developed in Fig. 5. First, it is necessaryto identify the water pathways in any water use, then to distin-guish what is consumptive and non-consumptive water use, whatis a benecial or a non-benecial water use, and which fractionsare really losses or wastes; the latter can be recovered later bysome means and used for other uses. This requires that productiveand non-productive processes, i.e., those oriented to achieve thewater use goal, be recognized. Then, a water use is more efcientwhen benecial water uses are maximized, water productivity isincreased, and water losses and wastes are minimized. However, itdoes notmean that less water is consumed when makingwater usemore efcient becausemaximizing benecial water uses andwaterand land productivities through the use of improved technologiesmay give the opportunity for higher crop evapotranspiration withreduced water wastesand losses(e.g., Ahmad et al., 2007 ). Thetermefcient water use may therefore be thought of as a synonymouswith sustainable or rational water use.

3. Water use performance indicators

3.1. Consumptive use and benecial use

Assuming the concepts above, it is possible to dene water useindicators adapted to any process or system involving water, forirrigation or non-irrigation uses, and to ensure measures are putin place to make more efcient use of the water, i.e., aimed atimproving performances from the perspective of water resourcesconservation. These indicators may be useful for water resourcesplanning and management under scarcity. They may be combinedwith process indicators, including those which relate to the qual-ity of service of water systems. It needs to be emphasized thatit is necessary to actually measure water ows at various pointsin the system so that real values can be attributed to the perfor-mance and productivity of each part of the system. For example,mosturbanwater delivery systems suffer largeleakagelosses (fromburied pipes) which remain undetected for years because insuf-cient measurements are routinely made to allow the location of major leaks to be determined.

The indicators refer to the three water use fractions ( Fig. 2) andto the respective benecial and non-benecial water use compo-nents. These indicators can be characterized in equations such asthose show below:

(a) The consumptive use fraction (CF), consistingof the fraction of diverted water which is evaporated, transpired or incorporated inthe product, or consumed in drinking and food, which is no longeravailable after the end use:

CF =E + ETprocess + ETweeds + INfood + INproduct

TWU (1)

where the numerator refers to process evaporation ( E ) and evap-otranspiration (ET) and incorporation in products (IN), and thedenominator is the total water use (TWU) or total water appliedor input. Subscripts identify the main sinks of water consumption.

The CF benecial and non-benecial components are:

BCF=E process + ETprocess + INfood + INproduct

TWU (2)

and

N-BCF =E non-process + ETweeds

TWU (3)

(b) The reusable fraction (RF), consisting of the fraction of diverted water which is not consumed when used for a given pro-duction process or service butthat returnswith appropriate qualityto non-degraded surface waters or ground-water and, therefore,can be used again.

RF =(Seep + Perc + Run) non-degraded + (Ret ow + Ef)treated

TWU (4)

where the numerator consists of non-consumptive use processes seepage (Seep), deeppercolation (Perc) and runoff (Run) that didnotdegrade thewaterquality, thus allowing furtheruses,includingwhen the return ows (Ret ow) and efuents (Ef) are treated toavoid degradation of water bodies where efuents are disposed.The RF components are the benecial and non-benecial reusablefractions. The benecial reusable fraction (BRF) is:

BRF=(LF+ Runoff process )non-degraded + Eftreated

TWU (5)

which includeswater used forsalt leaching (LF), runoffnecessarytotheprocesses such as tail end runoff in open furrowand border irri-gation, or channel lling (though developments in pipe networksand sprinkler and micro irrigation methods can reduce the needfor this water use), and controlled efuents (Ef) required by non-agricultural uses, as for many domestic uses. The non-benecialreusable fraction (N-BRF) is then

N-BRF =(Seep + Perc + Exc Runoff) non-degraded + Exc Eftreated

TWU (6)

and refers to excess (Exc) water use in the processes involved suchas seepage and leaks from canals and conduits, spills from canals,excess percolation in irrigation uses or excess runoff that is non-degraded, and efuents produced by water wastage when they are

captured and treated.(c) The non-reusable fraction (NRF), consisting of the fractionof diverted water which is not consumed in a given productionprocess or service but which returns with poor quality or returnsto degraded surface waters or saline ground-water and, therefore,cannot be used again.

NRF =(Seep + Perc + Run) degraded + (Ret ow + Eff l)non-treated

TWU (7)

which refers to thesame process as theRF but where thewater haslost quality and is not treatedor is added to water bodies which arenot usable for normal processes. The NRF shall also be divided intoa benecial (BNRF) and a non-benecial component (N-BNRF):

BNRF=(LF+ Runoff process )degraded + Efnon-treated

TWU (8)

and

N-BNRF =(Seep + Perc + ExcRunoff) degraded + ExcEff non-treated

TWU (9)

In addition to the indicatorsdened above, it is also worthwhiledening the benecial and the non-benecial water use fractions(BWUF andN-BWUF), which areobtained from the various compo-nents dened above, respectively through Eqs. (2), (5) and (8) f ortherst, and (3), (6) and (9) f or the second. Examples of applicationof indicators dened above are described in Section 4.

Illustrations of the main processes of water use for the fractionsdescribed above arepresented in Tables 1 and 2 for agricultural andnon-agricultural uses, respectively.


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Beneficial

Non-beneficial

REUSABLE

Degraded

Quality

Preserved

Quality

Beneficial

Non-beneficial

Beneficial

Non-beneficial

WATER DIVERTEDFOR ANY USE

CONSUMEDFRACTION

NON-CONSUMEDFRACTION

NON-REUSABLE

-

Wastage,non-beneficial

LOSSES

Beneficial

Non-beneficial

Beneficial

Non-beneficial

Beneficial

Non-beneficial

--


LOSSES

Identify the pathways of water use

Maximize beneficial uses

Minimize non-beneficial uses

Control, avoid water losses

Maximize water productivity

Beneficial

Non-beneficial

Beneficial

Non-beneficial

Beneficial

Non-beneficial

-


LOSSES

Beneficial

Non-beneficial

Beneficial

Non-beneficial

Beneficial

Non-beneficial

--


LOSSES

Fig. 5. Pathwaysof water use identifying main locationsor processesinuencing theefcientuse of water.

Table 1Benecial and non-benecial water use and its relation to consumptive and non-consumptive uses in irrigation.

Consumptive Non-consumptive but reusable Non-consumptive and non-reusable

Benecial uses ET from irrigated crops Leaching water added to reusable water Leaching added to saline water Evaporationfor climate control Water incorporated in product

Non-benecial uses Excess soil water evaporation Deep percolation added to good quality aquifers Deep percolation added to saline groundwater ET from weeds and phreatophytes Reusable runoff Drainage wateradded to saline waterbodies Sprinkler evaporation Reusable canal seepage and spills Canal and reservoir evaporation

Consumed fraction Reusable fraction Non-reusable fraction

Table 2Benecial and non-benecial water use and its relation to consumptive and non-consumptive uses in non-irrigation user sectors.

Consumptive Non-consumptive but reusable Non-consumptive andnon-reusable

Benecial uses Human and animal drinkingwater

Treated efuents fromhouseholds and urban uses

Degraded efuents fromhouseholds and urban uses

Water in food andprocess drinks Treated efuents from industry Degraded efuents from industry Water incorporated in industrialproducts

Return ows from powergenerators

Degraded efuents from washingand process waters

Evaporation for temperaturecontrol

Return ows from temperaturecontrol

Every non-degraded efuentadded to salineand lowqualitywater bodies

ET from vegetation inrecreational and leisure areas

Non-degraded efuents fromwashing and industrial processes

Evaporation from recreationallakes

Non-benecial uses ET fromnon-benecial vegetation Non-degraded deep percolationfrom recreational and urban areasadded to good quality aquifers

Deep percolation fromrecreational and urban areas addedto saline aquifers

Evaporation from water wastes Leakage of non-degraded waterfrom urban, industrial anddomestic systems added to goodquality waters

Leakage from urban, industrialand domestic systems added tolowquality waters andsalinewater bodies

Evaporation from reservoirs

Consumed fraction Reusable fraction Non-reusable fraction


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Waterdiversion

Agricultureand landscape

Effective rain

CropTranspiration

SoilEvaporation

Seepage +runoff

Conveyance +distribution

Application tocropped field

Percolation +runoff

Non-crop ET

YIELD

reuseTotal WP

Irrig WP

WUE

Farm WP

Fig. 6. Water productivity in agriculture at various scales: (a) the plant, throughthe water use efciency WUE; (b) the irrigated crop at farm scale (Farm WP); (c)the irrigated crop, at system level (Irrig WP); and the crop including rainfall andirrigation water (Total WP).

3.2. Water productivity: irrigation water uses

Nowadays, there is a trend to call for increasing water pro-ductivity (WP) as an important issue in irrigation ( Molden et al.,2003, 2010; Oweis and Hachum, 2003; Clemmens and Molden,2007 ). The attention formerly given to irrigation efciency is nowtransferred to water productivity. However, this term is used withdifferent meanings in relation to various scales ( Fig. 6) as discussedby Molden et al. (2003, 2010) and, relative to biomass WP, bySteduto et al. (2007) . The analysis herein is oriented only to theWP of irrigated crops. WUE was discussed in Section 2.1 .

Water productivity in agriculture and landscape irrigation maybe generically dened as the ratio between the actual crop yieldachieved ( Y a ) and the water use, expressed in kg/m 3 . For agiven landscape, a convenient denition of Y a has to be selectedby observers/users of a particular landscape because irrigatinggardens, lawns or golf courses produces qualitative yields. Thedenominator may refer to the total water use (TWU), includingrainfall, or just to the irrigation water use (IWU). This results intwo different indicators:

WP =Y a

TWU (10)

and

WP Irrig =Y a

IWU (11)

The meaning of these indicators is necessarily different. The

same amount of grain yield depends not only on the amount of irrigation water used but also on the amount of rainfall water thatthe crop could use, which depends on the rainfall distribution dur-ing the crop season. Moreover, we believe pathways to improvecrop yields are often not so much related to water management asto agronomicpracticesandthe adaptation of the crop variety to thecropping environment. However, a crop varietywith a higherWUEthan another varietyhas the potential for using less water than thesecond when achieving the same yield. Therefore, discussing howimproving WP could lead to water saving in irrigation requires theconsideration of various different factors: (a) the contribution of rainfall to satisfy crop water requirements, (b) the managementand technologies of irrigation, (c) the agronomic practices, (d) theadaptability of the crop variety to the environment, and (e) the

water use efciency of the crop and variety under consideration.

Eq. (10) may take a different form:

WP =Y a

P + CR + SW + I (12)

where Y a is theactualharvestableyield (kg), P is the seasonamountof rainfall, CR is the amount of water obtained from capillaryrise, SW is the difference in soil water storage between plant-ing andharvesting, and I is the season total amount of irrigation, allexpressed in m 3 . When appropriate soil water conservation prac-tices are adopted, the proportion of total P that is available to thecrop is increased and soil water storage at planting may also beincreased. When irrigation practices are oriented for water con-servation, crop roots may be better developed and the amount of water from CR and SW may become higher. The result may thenbe a lower demand for irrigation water.

The same Eq. (10) may be written in another form:

WP =Y a

ETa + LF+ N-BWU (13)

where Y a is the actual harvestable yield (kg), ET a is the actual sea-son evapotranspiration, LF is the leaching fraction, the water usedfor leaching when control of soil salinity is required, and N-BWU isthenon-benecial water use, i.e., thewater in excess to the bene-cial ETa andLF water needs.N-BWUconsists of percolation throughthe bottom of the root zone, runoff out of the irrigated elds, andlosses by evaporation, and wind drift in sprinkling, as shown inFig. 3. WP may be increased by minimizing the N-BWU compo-nents. The relationship between WP and the potential seasonalirrigation efciency referring to these N-BWU components is dis-cussed by Rodrigues and Pereira (2009) . For sprinkler systems itis also of interest to analyse the energy performance of the irriga-tion system and crop production (e.g., energy output to input ratio,i.e., crop energy produced per unit of energy used in production, orcrop energy produced per unit water used, MJm 3 ) in addition toirrigation performance ( Rodrigues et al., 2010a ).

A higher WP could also be attained through higher yields.Achieving this may require an increase in ET a to its optimum level,ETc. It could be that attaining the maximal value for WP in irriga-tion requires that yields are maximized, ET and LF are optimizedand N-BWU is minimized:

max(WP) =Y max

ETc + LF+ min(N-BWU) (14)

A high WP may also be obtained when a crop is water stressed,but then the yield is reduced. It is the case for decit irrigation,where crops are deliberately allowed to sustain some degree of water decit in such a way that crop production is economicallyviable. It is also observed that the resulting increases in WP areoften small (e.g., Zairi et al., 2003 ). Under these conditions the eco-nomic results of production may not be good, particularlyfor smallfarms where perfect management may not be possible or econom-

ically feasible. This implies that in addition to WP

economic waterproductivity should also be considered as shown in the analysis byRodrigues and Pereira (2009) on the economic water productivityof various scenarios of decit irrigation as inuenced by the waterprice. An interesting review on water value issues was recentlypresented by Hussain et al. (2007) .

3.3. Economic water productivity: irrigation water use

The productivity of water needs to be considered not only inphysical terms but also in economic terms. The economic value of water is of great importance but so is the economic return thatresults for the farmer when using water in irrigation. A good dis-cussion on the need to consider the social or public value of water

was presented by Perry et al. (1997) .

An appropriate consideration


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0,0

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810720630540450360270180900

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400

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360300240180120600

E W P ( U S D m

- 3 )

L E P

( U S D h a - 1 )

E W P ( U S D m

- 3 )

L E P

( U S D h a - 1 )

Season irrigation (mm)

b

Fig. 7. EWP () and LEP ( ) curves relative to various water stress irrigation strategies for maize (a) and wheat (b) under center-pivot irrigation and the average (*) andvery high climatic demand ( ) in southern Portugal.Source : Rodrigues et al. (2003) .

ofthe problem ispossiblewhenWP is observed under an economicperspective ( Barker et al., 2003; Rodrigues and Pereira, 2009 ).

Replacing the numerator of the equations above by the mon-etary value ( D ) of the achieved yield Y a , the economic waterproductivity (EWP) is expressed as D /m 3 and can be dened by:

EWP =Value( Y a )

TWU (15)

However, the economics of production are less visible in thisform. An alternative when focusing at farm level is to use in thenumeratorthe grossmargin corresponding to the achievedyield Y a ;thenEWP describes thefarmer grossreturn,particularly whencon-sidering decit irrigation ( Rodrigues et al., 2003; Zairi et al., 2003 ).It is interesting to note the difference in behaviour of both EWP andland economic productivity (LEP) as a function of the consumptive

use of the crops, also depending upon the climatic evapotranspira-tion demand. EWP and LEP curves for maize and wheat relative tovarious water decit irrigation strategies are compared in Fig. 7for the average and very high climatic demand (drought). BothEWP and LEP were obtained from the gross margins of both crops(Rodrigues et al., 2003 ).

Because maize yields strongly depend upon irrigation waterin climates having a dry spring-summer period, both EWP andLEP decrease when the seasons irrigation dosage also decreases(Fig. 7a); that decrease is greater when the climatic demand forwater is higher under drought conditions. Alternatively for a win-ter cereal such as wheat ( Fig. 7b), where irrigation is supplementalof rainfall, LEP decreases when the season irrigation applicationdose is lesser but EWP increases when less water is applied. Thesedifferences between a full irrigated and a supplemental irrigatedcrop explain why it is relatively easy to adopt decit irrigation forwinter wheat in contrast with maize.

To understand the economics of water productivity, it may bebetter to express both the numerator and the denominator in mon-etary ( D ) terms,respectivelythe yield value andthe TWU cost, thusyielding the economic water productivity ratio (EWPR):

EWPR =Value( Y a )

Cost(TWU) (16)

which shows to be very useful to analyse impacts of water priceson theeconomic return of irrigation ( Rodrigues and Pereira, 2009 ).Alternatively, considering Eq. (12) , we have:

EWPR =Value( Y a )

Cost(soil water conservation) + Cost( I ) (17)

Eq. (17) shows the costs for capturing more rainfall in the soiland encouraging capillary rise, and the costs of irrigation. Improv-ing this ratio implies nding a balance between production andyield costs, as well as appropriate soil and water conservation andirrigation practices. This is not easy to achieve and explains whyfarmers may retain low irrigation performance and poor conser-vation practices if related costs for improvement are beyond theireconomic capacity.

Alternatively, considering Eq. (13) , the following ratio isobtained:

EWPR =Value( Y a )

Costs(ETa + LF+ N-BWU) (18)

This suggests that the costs for reducing the N-BWU may bethe bottleneck in improving water productivity. To reduce N-BWU

implies investment in improving the irrigation system and thismay be beyond the farmers capacity, particularly for small farm-ers. Attention can then be directed to the need for support andincentives for farmers when a society requires they decrease thedemand forwater and increase thewater productivity.In collectiveandcooperativeirrigation systems partof thedifcultyresults frompoor system managementand inadequate delivery services, whichare often outside the control of the farmers, as mentioned earlier(Section 2.1) for the warabandi water sharing system ( Zardari andCordery, 2009 ).

Maximizing EWPR, when all costs other than for water use arekept constant,meansnding thelimitto theratiobetweenthe yieldvalue and the water use costs, which corresponds to maximizingcrop revenue in the form:

max(EWPR) = max Value( Y opt )Water Costs for Y opt

max(Income) (19)

This maximal EWPR generally relates to the maximal farmincome. The optimal yield, Y opt , is often different from the maxi-mum yield, depending upon the structure of the production costs.

An alternative to EWPR (Eq. (16) ) is to compute the ratio yieldvalue to full productioncosts (EWPR full-cost ). It allows assessing thefeasibility of a different irrigation strategy, e.g., a decit irrigationstrategy. An application is given in Section 4.

3.4. Water productivity for any water use sector

The concept of water productivity is also applied in other water

user sectors. It must be adapted to the specicities of each sector


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Total Water Use

Agriculture, Industry,Urban, Landscape, Energy

Conveyance &distribution

Processapplication

End productor service

Total WP

Process WPBeneficial andnon-beneficial

water use

Non-processwater use

Fig. 8. Water productivity in any user sector considering the full water use (TotalWP) anda singleprocess.

and activity. The term water productivity probably needs to beused or dened separately for each production or service process

(Fig. 8). Similar to WP being expressed in kg of grain per m 3 of waterusedin the case of irrigation, it is also possible to express WPinmetersof fabricper m 3 of water in the textile industry; kWh pro-duced per m 3 of water in energy generation; m 2 of lawns irrigatedper m 3 of waterin recreational areas; or m 2 of area washed per m 3of water in commercial areas, or even as value of sales per m 3 .

Extending the water productivity concepts used in agricultureto other user sectors yields:

WP =End Product or Service

TWU (20)

where the numerator is expressed in units appropriate to the activ-ity under consideration, and the denominator consists of the totalwater used to yield that product or service.

Eq. (20) may

take a different form to distinguish the benecialand non-benecial water uses contributing to yield of product orservice

WP =End Product or Service

BWU + N-BWU (21)

This equation shows that WP may be increased through improvedproduction processes that may require less BWU or when N-BWU (non-process water uses) is minimized. In the industrial

applications, BWU is commonly reduced by recycling and reusefor less stringent processes and applications. In urban and domes-tic uses, BWU may also be decreased when treated wastewater isused for processes not requiring the highest water quality.

Replacing the numerator of equations above by the monetaryvalue ( D ) of theachieved product or service produces theeconomicwater productivity (EWP) expressed as D /m 3

EWP =Value(Product or Service)

TWU (22)and the economic water productivity ratio

EWPR =Value(Product or Service)

Cost(TWU) (23)

Eq. (23) shows that when this ratio is very large, which is com-mon to most non-agricultural water uses there is no incentive toreduce TWU unless water policies relative to the quality of efu-ents and respective treatment induce a reduction of the amountsto be treated and, therefore, used. Water scarcity may be a signif-icant reason for reducing TWU, mainly when competition amongusers is high or the available supply is very limited. Simple mone-tary cost may not be a possible disincentive since high water costmay cause elimination of processes or services considered essen-tial for example irrigation water to provide food but also localemployment.

Maximizing EWPR is a question of minimizing thecosts of waterused to yield the desired product or service:

max(EWPR) = max Value(Product or Service)

Water Costs (24)

Differently from agriculture, where water use and related costs(including equipment, labour, and energy) may constitute a largepercentage of production costs, water costs in other user sectorsare often thoughtto be a small fraction of the production costs, butoften include wastewater treatment and water recycling. There-fore, the rationale behind water productivity for most sectors andactivities is very different from that in agriculture. In urban sup-ply systems consumption data are usually available in terms of litres/person/day;consideringwater savingobjectives, there needstobe anoperationalaimtohave thesequantities continuallyfalling.In allthe abovecases,for farms,factories anddomestic supplyoper-ations there need to be policies and incentives aimed at bringingwater consumption to the lowest possible level for each unit of production or activity, i.e., increasing the water productivity in alluses.

Table 3Assessing decit irrigationstrategiesfor sprinkler irrigatedpotatoand tomato andrespective alternatives in terms of surface allocatedto eachcrop under droughtconditions.

Water decit irrigationstrategies

Season net irrigationwater available (mm)

Land economicproductivity, LEP(USDha 1 )

Economic waterproductivity, EWP(USDm 3 )

Percent surface allocated to givenirrigation strategy as alternative to amore severe water decit

PotatoSC 320 3209 0.802 100% SCLDI 280 3032 0.866 100% LDIDI 240 2537 0.845 85% LDILID 200 2159 0.863 71% LDIVLID 160 1612 0.806 57% LDIEID 120 976 0.650 42% LDITomatoSC 840 4206 0.400 100% SCLDI 680 3600 0.423 100% LDIDI 560 2700 0.385 82% LDILID 560 2700 0.385 82% LDIVLID 480 2207 0.367 71% LDIEID 400 1734 0.346 59% LDI

Source : Zairi et al. (2003).Note : SC: satisfaction of crop need; LDI: low decit irrigation; DI: (moderate) decit irrigation; LID large irrigation decit; VLDI: very large irrigation decit; EID: extreme

irrigation decit.


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Fig. 10. EWP for various levelsof farm andsystem improvements forwater savingin the Huinong system, Yellow River basin, China.Source : Goncalves et al. (2007) .

system modernization was analysed through a decision supportsystem (DSS) applied to the Huinong canal system in the upperreaches of the Yellow River, China ( Gonc alves et al., 2007 ). Resultsof this application were analysed using the EWP corresponding toeach step of the improvement ( Fig. 10).

Fig. 10 shows that improvements in drainage and the deliverysystem bring the largest improvements overall. Results comparingEWP computed at the farm and system scales show that followingthose improvements leading to higherwater productivity,the EWPincreasesmoreatthesystemscalethanatthefarmscale,suggestingthere aredifculties in involving farmers in a large and long lastingprocess of modernization when they do not perceive a reasonableand continuous gain at their level.

Fig.11. Comparing water productivity(WP), water consumedfractions (WCF), ben-ecial water use fractions(BWUF) andrelativeyields ( Y a /Y max ) forfurrow irrigatedcottonat Fergana, Uzbekistan, for various farm systems. Farm systemsymbols are:EC irrigation in every furrowwithcontinuousow; ES irrigation in every furrowwith surge ow; AC irrigation in alternatefurrows with continuous ow; and AS irrigation in alternate furrows with surge ow.

Source :

Horst et al.(2007) .

4.4. Relating yields and the benecial water use fraction for various farm furrow irrigation improvements

Water saving in cotton irrigation in the Aral Basin, Central Asia,is generally considered a must. However it is necessary to assessthe economic feasibility of adopting improvements in presentlyused furrow irrigation systems. Experimental results obtained forFergana, Uzbekistan, from comparing various techniques contin-uous and surge ow, and irrigation in every furrow or in alternatefurrows are summarized in Fig. 11 (Horst et al., 2007 ).

Results show the potential for water saving when adoptingalternate furrow irrigation and surge owsince these systems pro-duce the highest WP, consumed fraction and benecial water usefraction (BWUF). However, the actual yield is less than the max-imum because these practices are difcult to apply by the localfarmers, thus causing a decrease inyields. Since thefarmers incomedirectly relates to the actual yield and not to WP, the farmers arereluctant to adopt water saving. These results were conrmed ina study on furrow irrigation design applied to the same area usingmulticriteria analysis. Environmental and economic criteria wereshown tobe contradictory:when water savingcriteriaprevailmoreadvanced solutions are selected, but when economic criteria areprevalentthen thewater savingtechniques arerejected ( Gonc alveset al., 2011 ). It is likely that when economic factors change and allfarmer subsidies are removed the adopted managerial and tech-nical options may change and real water conservation and savingmay occur.

Examples above may be extended to analyse water use andproductivity for non-irrigation uses. Similarly, the extension of economic water productivity concepts to industry may show thatpaying the real value for releasing efuents (which is not exactlythe same as the principle that the polluter pays) can have a hugeimpacton water savingand conservation butfew agencies orgov-ernments appear willing to confront this issue, presumablybecausethey fear it may have unexpected effects in the wider economy.

5. Conclusion

There are some difculties in discussing water productivity andefciency because there are many terms which are used ratherloosely and even synonymously. Opportunities for increases inwater productivity and efcient application of water are being

missed or hidden by the use of a number of similar, but actually


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THE IMPORTANCE OF SAP FLOW MEASUREMENTS TO ESTIMATE ACTUAL WAUSE OF MESKI OLIVE TREES UNDER DIFFERENT IRRIGATION REGIMES IN TUN

MAURITS W. VANDEGEHUCHTE1 *, MOHAMED BRAHAM2 , RAOUL LEMEUR1 AND KATHY STEPPE11 Laboratory of Plant Ecology, Department of Applied Ecology and Environmental Biology, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium

2 Institute of the Olive Tree Station of Sousse, Sousse, Tunisia

ABSTRACTImprovement in irrigation techniques has led to an expansion of the irrigated olive area in Tunisia and consequentlyagricultural water consumption. Here, the actual water use of Olea europaea L. Meski as estimated by thermal dissipationprobe measurements was compared for different irrigation regimes: three plots with irrigation doses based on Penman Monteithcrop evapotranspiration (ETc), 0.33ETc and the local grower s experience (about 0.6ETc), respectively. The scaling up of sap ux densities proved to be dif cult given the azimuthal and radial sap ux density variability and the conductive surface areaasymmetry. Moreover, natural thermal gradients may lead to inaccurate use of standard sap ow formulas. Depending on themanner of upscaling, differences in water use of more than 50 l day-1 per tree were obtained (up to 0.7ETc irrigation dose).Despite these dif culties, sap ow calculations seem crucial to accurately determine the water needs of the orchard uinvestigation, as they corresponded closely to the lowest irrigation dose which was considered suf ciently high as no signicant differences in drought stress variables were detected between the plots. Therefore, irrigation based solely on ETc wasting of water; hence, careful application of both meteorological and sap ow methods is desirable in irrigation scheduling.Copyright 2012 John Wiley & Sons, Ltd.key words: irrigation; Penman Monteith; thermal dissipation probe (TDP); sap ow; radial prole; Olea europaea L. (olive) tree

Received 22 July 2011; Revised 12 April 2012; Accepted 12 April 2012

RSUML amlioration des techniques d irrigation conduit l expansion de la super cie irrigue pour la culture d oliviers en Tunisie,et par consquent l augmentation de la consommation d eau par l agriculture. Dans cette tude, la consommation d eau rellede Olea europaea L. Meski telle qu elle est estime par des mesures de dissipation thermique a t compare diffrrgimes d irrigation: trois parcelles avec des doses d irrigation sur la base de l vapotranspiration des cultures de PenmanMonteith (ETC), 33% de cette ETC et l exprience du producteur local (environ 60% de l ETC), respectivement. L intensi cationdes densits de ux de sve s est avre dif cile en raison de la variabilit azimutale et radiale de la densit de ux de sve et de l asymtrie de la surface conductrice. En outre, les gradients thermiques naturels peuvent conduire une utiinexacte des formules standard de ux de sve. En fonction de changer d chelle, des diffrences de consommation d eauarbre de plus de 50 l arbre-1 j-1 ont t obtenues (jusqu 70% de la dose d irrigation ETC 100%). Malgr ces dif cults,les calculs de ux de sve semblent d une importance cruciale pour dterminer avec prcision les besoins en eau du vetudi car les calculs obtenus de ux de sve correspondaient troitement la dose la plus faible d irrigation qui a t juge

suf samment leve pour ne pas gnrer de diffrences signicatives dans les variables indicatrices de stress hydrique intparcellaire. Par consquent, l irrigation base uniquement sur ETC mne au gaspillage d eau, et une application rigoureusedes deux mthodologies bases respectivement sur des donnes mtorologique et les mthodes de ux de sve est doncsouhaitable pour laborer le calendrier d irrigation. Copyright 2012 John Wiley & Sons, Ltd.mots cls: irrigation; Penman Monteith; sonde de dissipation thermique (TDP); ux de sve; prol radial; Olea europaea L. (olivier)

* Correspondence to: Maurits W. Vandegehuchte. Laboratory of Plant Ecology, Department of Applied Ecology and Environmental Biology, FaBioscience Engineering, Ghent University, Coupure links 653, B-9000 Ghent, Belgium, Phone +32 9 264 61 12, Fax +32 9 224 44 10.E-mail: [email protected] L importance des mesures de ux de sve pour estimer la consommation d eau relle d oliviers Meski sous diffrents rgimes d irrigation en Tunisie.

IRRIGATION AND DRAINAGE Irrig. and Drain. 61 : 645 656 (2012)

Published online 15 July 2012 in Wiley Online Library (wileyonlinelibrary.com) DOI : 10.1002/ird.1670

Copyright 2012 John Wiley & Sons, Ltd.


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INTRODUCTIONGiven the adaptations of olive trees (Olea europaea L.) tolong-term drought, their cultivation is widely spread insemi-arid areas with a Mediterranean climate such as Tunisia(Gimenez et al ., 1997). While rain-fed orchards are still oftenexploited, irrigated orchards are gaining ground thanks tolarger fruit yield andgrowth. Given thehighereconomicvalueand to meet the growing demand for olive products, manytraditional orchardshave thereforebeen modernized by meansof several irrigation procedures (Fernandez and Moreno,1999), inevitably raising the consumption of water. Becauseof this augmented water use, researchers are stressing thenecessity of more accurate and precise irrigation methodolo-gies (Fereres and Evans, 2006).

Irrigation is often based on direct measurements of thesoil-water status either in terms of water content (gravimet-ric method) or water potential (tensiometer, psychrometer).

These methods have the disadvantage that multiple sensorsare needed when dealing with a heterogeneous soil. Analternative approach is to determine the atmospheric water demand based on the combination of an energy and water balance such as the Penman Monteith method (Allenet al ., 1998). A major shortcoming of soil- and atmospheric-based methods is that they do not take specic plant water interactions into account such as changes in internal water storage. Therefore, Jones (2004) suggests that when develop-ing new irrigation strategies, stress indicators which aremeasured on the plant itself are taken into account. Possiblestress indicators are leaf water potential, stomatal resistance,

sap

ux density or stem diameter variations (Nadezhdina,1999; Moriana and Fereres, 2002; Jones, 2004; Saveynetal ., 2007; De Pauwetal ., 2008; Sevantoetal ., 2008;Steppeet al ., 2008; De Swaef et al ., 2009; Villez et al ., 2009). Irriga-tion methods based on direct measurements of leaf water potential and stomatal resistance have, however, the disadvan-tage that theyare hard to automate. Moreover, theydonot leadto accurate results when dealing with isohydric speciesbecause of the partial separation of the linkage between theseindicators and sap ux density (Buckley, 2005; Fisher et al .,2006; Frankset al ., 2007).Because of these limitations, irriga-tion methods based on direct sap ux density measurementsare gaining in importance (Fernandez and Moreno, 1999;Do and Rocheteau, 2002; Nadezhdina et al ., 2002; Lu et al .,2004; Steppe et al ., 2008).

This study had the objective of assessing the applicabilityand benets of thermal dissipation probe (TDP) measure-ments to determine whole-tree water use of olive (Oleaeuropaea L. Meski ) growing in a commercial orchard at En dha, Tunisia, in comparison with classically appliedPenman Monteith based crop evapotranspiration for irriga-tion scheduling. To this end, water use of Meski olive trees(Olea europaea L. Meski ) irrigated based on the local

grower s experience was compared with water use of treeirrigated according to the Penman Monteith crop evapo-transpiration (ETc), both for 100% ETc and 33% ETc. Nexto TDP sap ux density estimates, ecophysiological mea-surements of leaf and stem water potential and azimutha

and radial sap

ux densities were conducted.

MATERIALS AND METHODSPlant material and experimental set-up

Measurements were carried out on 15-year-old Meski olivtrees (Olea europaea L. Meski ), an important table olivecultivar. These trees were part of an orchard located aEn dha, central Tunisia (10220 E, 36380 N), which belongsto l Of ce de Terres Domaniales de l En dha (OTD). Thisregion is characterized by a semi-arid climate with dry, hsummers and humid, mild winters, resulting in an averagannual rainfall of 300 mm and temperature of 18 25 C.The loamy-sand soil has an average to low organic carbocontent and nitrogen content. The trees are located in gridof 7 7 m and are pruned once a year after harvesting. In thorchard, three plots of 10 trees were selected for the experments. In each plot, three trees were selected with a stemdiameter of 18 3.4 cm at breast height and a similar height(3.5 0.4 m), crown shape and leaf area index (1.70.2).Still, differences in stem and branch shape were detectablThese irregular forms are typical of olive trees.

Each plot was irrigated by a localized irrigation systemwith, for each tree, four drip nozzles located at a distanc

of 1.0 m to the north, east, south and west of the trunkrespectively. All plots were irrigated based on the experence of the local grower, irrigating 8 ha day1 with adischarge rate of approximately 1.4 l h-1 per nozzle (approx-imately 45 l day1 per tree) before the experiment wasstarted. From April onwards, the three plots were irrigatedifferently. For plot one, a water irrigation amount equivalent to 100% of crop evapotranspiration (ETc) wasprovided, calculated using the Penman Monteith FAOmethod (Allen et al ., 1998). To obtain crop evapotranspira-tion from reference evapotranspiration, a single estimatecrop coef cient (K c = 0.45) and a coverage coef cient (K r =0.67) were applied, as it has recently been shownthat the K c values provided by the FAO lead to overestima-tions of crop evapotranspiration (d Andria et al ., 2004;Er-Raki et al ., 2008). For plot two, one-third of this irriga-tion dose was applied, while for plot three, the dose as detemined by the local grower remained applicable.

Evapotranspiration

For evapotranspiration measurements an on-site weathestation was used to measure the relative humidity (RH

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Copyright 2012 John Wiley & Sons, Ltd. Irrig. and Drain. 61 : 645 656 (2012)


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and the air temperature (T ) using an integrated relativehumidity sensor (RHT2nl combined sensor, Delta-TDevices Ltd, Cambridge, UK). Shortwave radiation wasmeasured with a photodiode 5 m above the ground surface(ES2 Si, Delta-T Devices Ltd, Cambridge, UK) and soil heat

ux with a Heat ux plate (HFP01SC, Hukseux, Delft,Netherlands). Wind speed was measured with an anemometer (AN1, Delta-T Devices Ltd, Cambridge, UK), installed 5 mabove the orchard oor.

Evapotranspiration calculations were carried out manu-ally based on the FAO Penman Monteith method developedby Allen et al . (1998). To determine the net radiation ( Rn inJ m-2 day-1 ), the following formula was used:

Rn 1 a Rs Rl;in es T4surf (1)

where a is the albedo (for olive orchards with sand-loamysoils equal to 0.2 (Moreno et al ., 1996), s the Stefan-Boltzmann constant (J K-4 m-2 day-1 ), e the emissivityconstant (equal to 0.98 according to Sepulcre-Canto et al .,2006), T surf the surface temperature (K), Rs the incomingshortwave radiation (J m-2 day-1 ) and Rl,in the incominglongwave radiation (J m-2 day-1 ).

To determine Rl,in several empirical formulas, using air temperature (T in K) and vapour pressure (ea in hPa), wereevaluated. Most commonly used formulas are those of Swinbank (1963) (Equation 2), Idso (1981) (Equation 3)and Brunt (1932) (Equation 4):

Rl;in 0:92 10 5T 2 s T 4 (2)

Rl;in 0:70 5:95 105ea exp 1500=T s T

4(3)

Rl;in 0:51 0:066 ea1=2 s T 4 (4)These formulas are adequate for use with clear skies,

which was the case in this study where they were comparedwith the standard FAO method.

Water potential and stomatal resistance

Differences in drought stress between the three different irrigation plotswere assessedbased on different physiologicalmeasurements during July and August 2008 as thesemonths were considered to cause the highest level of drought stress. Leaf and stem water potential were measured with aScholander pressure chamber (Scholander pressure chamber,PMS Instrument Company, Oregon, USA) for nine trees(three trees per irrigation plot). As the trees were of similar height, crown structure and shape, stem diameter at breast height and leaf area index, comparison of measurements waspossible. For each measurement day, one tree from eachirrigation plot was measured in four azimuthal directions fromsunset till approximately 7 pm. This was repeated for the same

trees on three comparable clear sky days. As the meteorological conditions during the measurement period remaineapproximately constant, comparison of the three measuremenrepetitions per tree was possible. Hence, nine measuremendays in total were conducted: three repetitions with for ever

repetition one tree per irrigation plot. For a single measurment, the average of three leaves was taken.For each tree, leaf and stem water potential and stomata

resistance (AP4 dynamic porometer, Delta-T Devices LtdCambridge, UK) were measured in the four azimuthadirections. To determine stem water potentials, selecteleaves were enclosed, still attached to the tree, in plastibags covered with aluminium foil 2 h prior to the measurement (Fulton et al ., 2001). Both for the stem and leaf water potentials as for the stomatal resistance, the average of threleaves was taken for each measurement point. Attention wapaid to choose leaves at similar height and of similar age anexposure to sunlight.

For each measurement day, six to seven measuremenpoints per azimuthal direction for both stem and leaf watepotential and stomatal resistance were obtained betweesunset and 7 pm.

Sap ux density

Sap ux density was continuously monitored approximately30 cm above soil level in four azimuthal directions usinthermal dissipation probes (TDP30, Dynamax Inc., HoustonTX, USA) on the same trees on which stomatal resistancand water potentials were measured. As natural temperaturgradients were considered a risk, a cyclical heating schemas suggested by Do and Rocheteau was applied (2002). Ththermocouple of the thermal dissipation probes was locate15mm fromthe tip of the needle. The heaterand measuremenneedle were located 4 cm distant. The heater element wadiscontinuously heated (10 min heating, 20 min cooling) iorder to use less energy. Using the equations of Do andRocheteau (2002), sap ux density was calculated as

SFD 0:00274 K a = 1 K a 0:707 (5)

with SFD the sapuxdensity (m m-2 s-1 ) (Steppeetal ., 2010)and K a calculated as

K a T a0 T au = T au (6)

with T a0 the maximum alternating signal ( T on T off with T on the temperature difference between the needles atthe end of the heating and T off the temperature differencebetween the needles at the end of the cooling period) an T au the measured alternating signal.

To determine whole-tree water use, sap ux density wasmultiplied by the total conductive surface area. Thisurface area is commonly calculated as a fraction of the tot

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cross- sectional area of the stem (considered as a perfect disc) (Allen and Grime, 1995)

To gain more insight in the radial sap ux pro le inolive, the sensor needles were displaced at different depths(5, 8, 15 and 20 mm) every second day with 24 h measure-

ments for each depth. Hence, on the measurement days onwhich sap ux was determined at 5, 8 and 15 mm depth,water potential and stomatal resistance were also measuredon the same trees.

For each new depth, the insertion hole was drilled a bit deeper, taking care not to extend the diameter of the drillhole. To be able to compare these measurements, meteoro-logical conditions between the days should not differ toomuch. To this end, average values and correlation coef -cients of air temperature, relative humidity, shortwaveradiation, soil heat ux and wind speed for the different dayswere calculated. For air temperature, shortwave radiationand soil heat ux, correlation coef cients varied between0.92 and 0.99 for the four depths considered. The correla-tions for relative humidity and wind speed were lesspronounced (Table I). Table II gives the lower and upper bounds of the signicant differences for the meteorologicalvariables for the different depths. Because the environ-mental variables were statistically comparable, it waspossible to approximate the radial sap ux pro le in olive(determined by averaging the sap ow measurements of the four azimuthal directions). This statistical analysisalso justies the comparison of the water potential andstomatal resistance measurements for the consecutive mea-surement days.

In addition, the actual surface area of the conductivetissue was determined by colouring the xylem tissue.Therefore, a waterproof receptacle was constructed aroundthe stem of one of the olive trees. This receptacle was lledwith an acid fuchsine solution (0.5% w/v). Several holeswere drilled underwater to prevent air bubbles from enteringthe trunk. The coloured solution penetrated the conductivetissue and was taken up by the sap stream. When colouringof the leaves was visible, the tree was cut down. A surfacescanner (Li 3050A, Li-Cor, Lincoln, Nebraska, USA)was used to determine the actual conductive surface areaof the trunk.

Statistical analysis

For statistical analysis, the software package S + (TIBCSoftware Inc.) was used. Normality and homoscedasticit

of the data were tested with Kolmogorov Smirnov anmodi ed Levene tests, respectively. Averages were thencompared based on a Tukey test (95% signicance level).

RESULTSPenman Monteith crop evapotranspirationThe use of different empirical formulas to determine Rl,in ledto differences in Rn (Figure 1a) and, subsequently, to smalldeviations in reference evapotranspiration (Figure 1bStatistical analysis showed that only the reference evapotranspiration calculated according to Idso (1981) was signiicantly higher than the other methods.

The irrigation dose based on the reference evapotranspiration, which was on average about 5.5 mm day-1 during JulyandAugust2008,corresponded to approximately75 l per treeFor the second irrigation plot, one-third of this dose waapplied ( 25 l per tree) while, based on the experience othe local grower, plot three was irrigated with45 l per tree.

Water potential and stomatal resistance

The average meteorological conditions for the measuremedays are presented in Figure 2. In the three differen

Table I. Correlation coef cients for relative humidity and wind speed for thermal dissipation probe measurements at 5, 8, 15 and 20 m

Relative humidity Wind speed

Depth 5 mm 8 mm 15 mm 20 mm 5 mm 8 mm 15 mm 20 m

5 mm 1 0.559 0.810 0.753 1 0.775 0.632 0.7068 mm 0.559 1 0.841 0.770 0.775 1 0.722 0.82815 mm 0.810 0.841 1 0.821 0.632 0.722 1 0.84020 mm 0.753 0.770 0.821 1 0.706 0.828 0.840 1

Table II. Lower and upper bound for the signicant differencesbetween the four depths (5, 8, 15 and 20 mm) for thmeteorological variables (Tukey, 95% signicance)

Lower bound

Upper bound

Temperature 8 mm 5 mm (C) 0.694 5.75Temperature 8 mm 20 mm (C) 0.598 5.65Relative humidity 15 mm 20 mm (%) 31.2 14.2Relative humidity 8 mm 20 mm (%) 33.5 16.5Relative humidity 5 mm 20 mm (%) 29.1 12.1Wind speed 15 mm 5 mm (m s-1 ) 1.22 0.238Wind speed 8 mm 5 mm (m s-1 ) 1.08 0.099




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Figure 1. Net radiation calculated according to the standard FAO method and the Idso, Brunt and Swinbank equations (a). Corresponding reference evpiration using the net radiation calculated according to the standard FAO method and the Idso, Brunt and Swinbank equations (b)

Figure 2. Average net radiation (a) and vapour pressure decit (b) for the measurement days

Figure 3. Leaf water potentials for the different azimuthal orientations on DOY (day of the year) 225 for irrigation dose of 100% ETc (a), 33% ETc (b)experience of the grower (c)




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irrigation plots, a typical water potential pattern was found,with values declining during the morning to reach aminimum around midday and riseing again in the afternoon(Figure 3). Standard deviations were relatively small(average 0.32 MPa for leaf water potential and0.18MPa for stem water potential). This resulted from smallerrors in the actual measurements. Besides spatial differ-ences between the four orientations, temporal differencesoccurred where relative ratios of water potentials for the four orientations changed with time (data not shown).

Despite the use of different irrigation doses, average leaand stem water potential (average of four azimuthal directioand three trees per plot) showed no signicant differencesduring the measurement period (Figure 4). To conrm this,the pre-dawn leaf water potential and leaf water potential

13 h were statistically compared for the different irrigatioplots. This test did not yield signicant differences betweenthe plots ( p > 0.05). For the pre-dawn leaf water potential,an overall average value of 0.5 0.11 MPa was obtained.

Larger variations were found for stomatal resistance, buno signi cant difference in average values existed betweenthe three irrigation plots for the measured times ( p > 0.05)(Figure 5). Stomatal resistance declined strongly durinthe morning to reach a minimum between 9.30 h and 10 hthen rose to a maximum between 12 h and 14 h, subsequently declining again towards a second minimum in thafternoon and nally rising again slowly in the evening.

Sap ux density and radial pro le

Figure 6 shows a typical sap ux density pattern obtained byapplying the Do and Rocheteau (2002) equation. From thtemperature measurements at the end of the cooling periothe natural thermal gradient in the wood was assessed (cosidering a distance of 4 cm between heater and measuremeneedle) (Figure 7). This gradient was largely positive witonly short negative periods around midday.

Figure 8(a) shows sap ux density measurements for thefour azimuthal orientations for a measurement tree of th33% ETc plot. When compared to Figures 8(b) and (c

Figure 4. Daily pattern of average leaf water potentials (thin lines) and stemwater potentials (thick lines) for the three irrigation doses for the different measurement days. 100% ETc: solid lines, 33% ETc: dashed lines, local

experience grower: dotted lines

Figure 5. Daily pattern of average stomatal resistances for the different measurement days for irrigation dose of 100% ETc (a), 33% ETc (b) experience of the grower (c)




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showing the leaf water potential and stomatal resistance,respectively, it is clear that no conclusive pattern for theazimuthal variation can be detected. For the other trees,different ratios for the sap ux densities of the azimuthaldirections were obtained. There was no statistical correlationbetween differences in azimuthal sap ux density andmeteorological conditions, ecophysiological variables or the irrigation plots.

The radial sap ux pro le is summarized in Figure 9. Asimilar temporal and spatial pattern was observed for theother trees, namely a clear daily pattern of rising sap owfrom sunset till midday, falling again towards the evening,and a radial pattern rising from the bark to the centre of the tree till about 12 14 mm depth and then falling further towards the centre. To gain better insight into the azimuthalin uence on the obtained radial prole, box plots were madeusing the sap ux density data of the different directions and

depths (Figure 10). In the south, measurements at 20 mmdepth were relatively higher compared to the other azimuthdirections for this measured tree. This was, however, noalways the case for the other trees measured. In general, foall trees, it was clear that the radial sap ux density patterns

differed between azimuthal directions.

Water use based on sap ux density

Based on the sap ux density measurements at 15 mm depth,the water use of the three irrigation plots was calculated (as average of the azimuthal directions and the three repetitionper irrigation plot) and compared with the Penman Monteithcrop evapotranspiration obtained (Figure 11a). There seemto be good correspondence between the calculated cropevapotranspiration and the water use based on TDP measurements. Moreover, Figure 11(a) conrms the hypothesis that no signi cant drought stress differences occurred betweenthe three irrigation plots as there was no signicant differencein water use. However, when the radial prole is taken intoaccount, the calculated cropevapotranspirationclearly overestimates the actual water use (Figure 11b).

DISCUSSION More water, less stress?

Given the large differences in irrigation doses, a differencin water potential, as a direct drought stress indicator, waexpected. When comparing leaf and stem water potentia

for the three irrigation plots (Figure 3), no signicant differences in drought stress could be detected. Moreoverthe pre-dawn leaf water potential, which is considered good approximation of soil water potential, showed nosigni cant difference between the plots and had an overalaverage value of 0.5 0.11 MPa which is considered theupper limit for good soil water status (Michelakis et al .,1994; Fernandez and Moreno, 1999; Tognetti et al ., 2004;Diaz-Espejo et al ., 2007). This indicates that no large differ-ences in drought stress at soil level occurred. Moreover, nsigni cant difference in stomatal resistance was notedbetween the irrigation plots (Figure 4). Although no signi-cant differences in water potentials were observed betweethe irrigation plots, stomatal resistance showed a maximushortly after midday for all plots (so-called midday closur(Figure 4). This can be explained by the high vapoupressure decit during this period of the day (up to 4 kPa)which has also been noted by Trilo et al . (2007) whomention 45% loss in hydraulic conductivity at an appliepressure of 3.5 MPa for twigs of Olea europaea Leccino .

From these data, it seems the lowest irrigation dos(25 l day-1 per tree) was suf cient for irrigation purposes,while the irrigation dose of 75 l day-1 per tree based on

Figure 6. Typical sap ux density pattern as obtained by the Do andRocheteau equation (2002)

Figure 7. Natural thermal gradient measured at the end of the cooling periodof the discontinuous heating cycle (southern sensor) from DOY 228 to 234for one of the measured trees. Similar results were obtained for the other

trees although the gradient varied slightly between azimuthal directions




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Penman Monteith evapotranspiration calculations led towater overspill.

Sap ux density

In uence of thermal gradient: pitfall for cyclic heat-ing. The use of crop coef cients to determine crop evapo-transpiration from reference evapotranspiration is susceptibletoerrors, because the actual physiologyof the plant is not fullytaken into account (Fernandez et al ., 1997; Tognetti et al .,2004). Factors such as midday stomatal closure, pruning,cropheight, tree- to-tree distance, etc. can inuence the cropcoef cient, making it dif cult to apply when no validationmeasurements (for instance based on eddy covariance) havebeen conducted (Teixeira et al ., 2008). In order to includethe actual plant water relations of the studied species and to

take the individual variability of trees into account, increasiattention is currently being paid to irrigation methods that uspeci c plant-based variables, including sap ow, detectingdrought stress directly at the plant level (Jones, 2004However, when using sap ow as a variable, attention shouldbe paid to natural thermal gradients. In this study, the naturthermal gradient was mainly positive (Figure 7). This is contrast with the original study of Do and Rocheteau (2002When analysing the temperature differences between thsensor needles at the end of the cooling period, Do anRocheteau (2002) found mainly positive natural gradient(up to 1.5 C) during the night, while negative natural gradi-ents occurred during the day (down to 2 C). This led toan overestimation of the reference temperature differenc(for zero ow conditions) and, hence, an overestimation oftheactual sapux density when applying the Granier formula,

Figure 8. Sap ux density (a), water potential (b) and stomatal resistance (c) for the different azimuthal directions for the irrigation dose of 33%

Figure 9. Radial sap ux density prole for a tree for the irrigation dose of 33% ETc. This gure is available in colour online at wileyonlinelibrary.com/journal/ird


http://wileyonlinelibrary.com/journal/irdhttp://wileyonlinelibrary.com/journal/ird


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because during the day the reference needle was inuencedbythe negative natural gradient. In this study, application of theGranier method would have led to underestimation of thesap ux density, probably due to the heat capacity of the soil.

Although the formula developed by Do and Rocheteau(2002) has proven to be very useful when taking naturalgradients into account, it should be applied with caution.Indeed, when the K a value in Equation (5) is larger than 1,imaginary results are obtained. A K a value larger than 1might occur when T a0 > 2. T au . This is possible for high T a0 or low T au values. Since T a0 values are based onzero sap ow conditions, this value always reaches a

maximum dependent on the thermal conductivity of thtissue in which the sensor is installed and on the naturathermal gradients that occur. For a tree, this value is moror less constant. The reason why K a values can be larger than 1 is thus mainly due to low T au values with

T au T on;u T off ;u (7)

with T on,u and T off,u the temperature difference betweenthe needles at the end of the heating period and at the end othe cooling period, respectively. Low values are thus causeby either a high sap ux density (which results in a low

Figure 10. Sap ux density at the different measurement depths and for the different azimuthal orientations for one tree: (a) north, (b) east, (c) south,

Figure 11. Water use of the different irrigation plots compared to the calculated Penman Monteith crop evapotranspiration: (a) based on the TDP measurementat 15 mm, (b) based on the radial prole. For both (a) and (b) an outer annulus of 36 mm was considered as

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