Phosphorus Loadings to the World's Largest Lakes

18 Pages·2017·3.18 MB·English

Global Biogeochemical Cycles
’
RESEARCH ARTICLE Phosphorus Loadings to the World s Largest Lakes:
10.1002/2017GB005858 Sources and Trends
KeyPoints: GabrielFink1,2 ,JosephAlcamo1,3 ,MartinaFlörke1 ,andKlaraReder1
(cid:129) Phosphorusloadingstolakesarea
majorcauseoflakeeutrophication, 1CenterforEnvironmentalSystemsResearch,UniversityofKassel,Kassel,Germany,2NowatLandesanstaltfürUmwelt
yettherearefewestimatesofthe
Baden-WürttembergLUBW,Karlsruhe,Germany,3SussexSustainabilityResearchProgramme,UniversityofSussex,
extentoftheseloadings,includingfor
theworld’slargestlakes Brighton,UK
(cid:129) TPloadingstolargelakesin
developingcountriesareonthe
averagemuchlargerthantolakesin AbstractEutrophicationisamajorwaterqualityissueinlakesworldwideandisprincipallycausedbythe
developedcountries loadingsofphosphorusfromcatchmentareas.Itfollowsthattodevelopstrategiestomitigate
(cid:129) ThemostimportantsourceofTP
eutrophication,wemusthaveagoodunderstandingoftheamount,sources,andtrendsofphosphorus
loadingsisinorganicfertilizer;the
secondmostimportantare pollution.Thispaperprovidesthefirstconsistentandharmoniousestimatesofcurrentphosphorusloadings
“background”loadingsfrom totheworld’slargest100lakes,alongwiththesourcesoftheseloadingsandtheirtrends.Theseestimates
atmosphericdepositionand
provideaperspectiveontheextentoflakeeutrophicationworldwide,aswellaspotentialinputtothe
catchmentweatheringofP
evaluationandmanagementofeutrophicationintheselakes.Wetakeamodelingapproachandapplythe
WorldQualmodelfortheseestimates.Theadvantageofthisapproachisthatitallowsustofillinlargegapsin
SupportingInformation:
(cid:129) SupportingInformationS1 observationaldata.Fromtheanalysis,wefindthatabout66ofthe100lakesarelocatedindeveloping
countriesandtheircatchmentshaveamuchlargeraveragephosphorusyieldthanthelakecatchmentsin
Correspondenceto: developedcountries(11.1versus0.7kgTPkm(cid:1)2year(cid:1)1).Second,themainsourceofphosphorustothe
G.Fink, examinedlakesisinorganicfertilizer(47%oftotal).Third,between2005–2010and1990–1994,phosphorus
gabriel.fi[email protected]
pollutionincreasedat50outof100lakes.Sixtypercentoflakeswithincreasingpollutionareindeveloping
countries.PpollutionchangedprimarilyduetochangingPfertilizeruse.Inconclusion,weshowthatthe
Citation:
riskofP-stimulatedeutrophicationishigherindevelopingcountries.
Fink,G.,Alcamo,J.,Flörke,M.,&Reder,K.,
(2018).Phosphorusloadingstothe
world’slargestlakes:Sourcesand 1. Introduction
trends.GlobalBiogeochemicalCycles,32,
617–634.https://doi.org/10.1002/ Eutrophicationisconsideredasoneofthemostimportantformsoflakepollutionbecauseoftheextentofits
2017GB005858
occurrenceandtheintensityofitsimpactonlakewaterquality(MillenniumEcosystemAssessment,2005).
Eutrophicationisanoversupplyofnutrientstoanaquaticsystem,usuallycausingundesirablechangesin
Received6DEC2017
Accepted18MAR2018 aquaticecosystemssuchastoxicalgalblooms,decreaseinwatertransparency,oxygendepletionoranoxia
Acceptedarticleonline23MAR2018 duetodecompositionoforganicmatter,changesinspeciescomposition,increasedincidenceoffishkills,
Publishedonline19APR2018
reduced species diversity, and a reduction in harvestable fish (Correll, 1998; Smith & Schindler, 2009).
Corrected21MAY2018
Eutrophicationthreatensfreshwaterecosystemservicesimportanttohumanwell-beingsuchastheprovi-
Thisarticlewascorrectedon21MAY sion of drinking water, the harvesting of fish, and the recreational use of lakes (Aylward et al., 2005). For
2018.Seetheendofthefulltextfor
instance,inLakeTaihu,China,eutrophicationintheformofmassivealgalbloomshasendangeredthedrink-
details.
ingwatersupplyofmillionsofpeopleinShanghaiandothercities(Qinetal.,2007).Anotherwell-known
exampleisLakeErie(CanadaandUnitedStates)wherethedischargeofagricultural,industrial,anddomestic
wastewaterstimulatedalgalbloomsandfishkillsuntilthemid-1980s(Allinger&Reavie,2013).Ittakesupto
decadesforlakestorecoverfromeutrophication(Jeppesenetal.,2005).Solvingeutrophicationproblems
was given new attention in 2015, when UN Member States agreed “By 2020, [to] protect and restore
water-related ecosystems, including … lakes” as part of Target 6.6 of the UN Sustainable Development
Goals(UnitedNations,2015).
Toassesstheriskofeutrophicationinlargelakes,itisimportanttounderstandtheloadingsofphosphorus(P)
totheselakesfromtheircatchment.Therearetworeasonsforthis.First,Piscommonlythemainlimiting
nutrient for phytoplankton growth in freshwater systems (Brönmark & Hansson, 2005; Dodson, 2005;
Sterner,2008);hence,acertainlevelofPinlakesabovenormallypristinelevelsisacommontriggerofeutro-
phication (Correll, 1998; Schindler, 1977; Yan et al., 2016). Second, P loadings into a lake also affect the
balanceofothernutrients,suchasnitrogen,thatplayaroleinphytoplanktonproduction(e.g.,Finlayetal.,
2013).BecauseoftheimportanceofP,manyinvestigatorshavemeasuredPloadingstolakes.Avarietyof
methodshavebeenusedincludingpollutionsourceassessments(e.g.,Scherenetal.,2000)andmeasure-
©2018.AmericanGeophysicalUnion.
AllRightsReserved. mentsofinflows(e.g.,Zimmer&Bendoricchio,2001).EstimatesofPloadingstovariouslakesaroundthe
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worldhavebeencompiledintheWorldLakeDatabase(ILEC,2015)andforEuropeinEuropeanEnvironment
Agency (2005). Specifically for large lakes, estimates of P loadings have been published for Lake Victoria
(Scherenetal.,2000),LakeMichigan(Johengenetal.,1994),LakeBaikal(Callender&Granina,1997),Lake
Malawi (Pasche et al., 2012), Lake Erie (Dolan & McGunagle, 2005), Lake Winnipeg (LWSB, 2006), Lake
Ladoga (Holopainen & Letanskaya, 1999), and Lake Onega (Bilaletdin et al., 2011). Some of these studies,
forexample,Scherenetal.(2000),provideinformationonPsourcesaswell.Hence,therearealreadyesti-
matesofcurrentPloadingstoseverallargelakes.
However,inthispaperwepresentforthefirsttimeaconsistentestimateoftotalphosphorus(TP)loadingsto
theworld’s100largestlakes.AsatoolweusetheWorldQualmodelfromtheglobalmodelingframework
Water—Global Assessment and Prognosis (WaterGAP3; Alcamo et al., 2003; aus der Beek et al., 2010;
Flörkeetal.,2013;Verzano,2009;Voßetal.,2012).Thesenewtop-down,model-basedcalculationsprovide
addedvaluetocurrentPloadingestimatesinthefollowingways:First,theycovermanymorelargelakes
andinamoreconsistentwaythanpreviousresearch;Second,usingthesamemodeltoestimatePloadings
toseverallakesenablesconsistentcomparisonsbetweenlakesbecauseauniformmethodisusedforcalcu-
lations;Itisdifficulttocompareliteraturevaluesfordifferentlakesbecausetheyhaveuseddifferentmethods
(notedabove)anddifferentdatainputs.Third,usingadeterministicmassbalancemodeldrivenbyvarious
sourcesofPallowsthelinkagebetweensourcesandresultingloadings.Thisprovidesimportantinformation
topolicymakersandlakemanagersbecauseitmakesitpossibletoidentifywhichsourcesmustbereducedto
substantiallyreduceloadings.Fourth,themodelcanbeusedtoestimatechangesinthesourcesofPwithina
lakebasinandhencebeusedtogenerateatimeseriesofhistoricloadings.Fifth,themodelcanbeusedto
makeprojectionsofchangesinPloadingsandhenceprovideinputtoassessmentsofchangesintheintensity
ofproblemsasafunctionofsocioeconomicdriversandclimatechange.Likewise,itcanbeusedtocompute
scenariosofprogresstowardachievingtargets,suchasthoseundertheSustainableDevelopmentGoals.
Inthispaper,weaimtoanswerthreemainquestions:
A WhatarethemagnitudesofPloadingstolargelakesworldwide,andhowdotheyvarybetweenlakes?
B WhatarethemainsourcesofPloadingtolargelakesandhowdopatternsvaryworldwide?
C Whatarethe20yeartrendsofPloadingstolargelakes?
2. The Investigated Lakes
Inthisstudywefocusontheworld’smajorlakes,whichwedefineasthe100largestlakesandreservoirsin
termsoflakesurfacearea,asidentifiedintheGlobalLakeandWetlandDatabase(Lehner&Döll,2004).We
excludetheCaspianSea(technicallimitationforitssize)andtheAralSeaandLakeChad(rapidlychanging
morphology).Hereafter,forthesakeofsimplicityweusetheterm“lake”forreservoirs.
Although most lakes are small, the few with large volumes and/or surface areas are especially significant
becauseoftheiruniqueecosystemsandlargefisheries.Insomecasestheyarealsoamajorsupplierofwater
forirrigation,industry,andthedomesticsectors.The100largestlakescoverawiderangeofenvironmental
conditionsandlevelsofwaterquality.Somelakesinthenortharecoveredwithiceformorethanhalfthe
year,whilethetropicallakesofSouthAmericaneverfreeze.Anthropogenicloadsofnutrientsarehigherin
intensivelyfarmed,industrial,andsemiruralorurbanareas(e.g.,LakeTaihu;Wangetal.,2014)andmuch
lowerinremotecatchments(e.g.,GreatSlaveLake,Canada).
Thelargelakesinvestigatedhereconsistsof11lakesinEurope,17inAfrica,28inAsia,1inOceania,33in
NorthandCentralAmerica,and10inSouthAmerica.Thelake’smappingtoeachcontinentisdefinedby
thelandmaskusedintheWaterGAP3modelingframework(Figure1).Foradetailedlistofthestudiedlakes,
seesupportinginformation.
3. Methods
3.1. ModelingFrameworkWaterGAP3
ThemaintoolusedinthisstudyistheWorldQualmodeloftheWaterGAP3modelingframework.WaterGAP3
isagrid-based,integrativeassessmenttooloperatingona5-arcminglobalgrid(about9by9kmattheequa-
tor)(Alcamoetal.,2003;ausderBeeketal.,2010;Flörkeetal.,2013;Verzano,2009;Voßetal.,2012)whichhas
been applied in numerous studies (e.g., Reder et al., 2013; Ward et al., 2014; Williams et al., 2012). The
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Figure 1.Assignment of countries to continents used in this paper. Lighter orange = Central and North America; darker orange = South America; lighter
blue=Europe;darkerblue=Africa;lightergreen=Asia;darkergreen=Oceania.Thepointsindicatethepositionsoftheinvestigatedlakes.
modeling framework (Figure 2a) includes three modules: (i) The distributed global hydrological model
(Alcamo et al., 2003; Döll et al., 2003; Eisner, 2016) simulates hydrological storage compartments with a
dailytemporalresolution. Thehydrologicalmodel is drivenbya meteorologicaldataset(WATCHForcing
DatamethodologyappliedtoERA-Interimdata,Weedonetal.,2014)andcalibratedandvalidatedagainst
measured river discharge from 2,446 stations of the Global Runoff Data Center data repository (Eisner,
2016).(ii)Thewaterusemoduleincludesfivesectoralwaterusemodels(ausderBeeketal.,2010;Flörke
etal.,2013).(iii)ThewaterqualitymodelWorldQual(Voßetal.,2012)simulatesmonthlyloadingsandin-
stream concentrations from point sources and diffuse sources (Figure 2b) of TP, fecal coliform bacteria,
total dissolved solids, and biochemical oxygen demand (Punzet et al., 2012; Reder et al., 2015; Voß et al.,
2012;Williamsetal.,2012).
Usingseverallargeglobaldatasets(Table1),theWorldQualmodelcalculatesTPloadingsintolakesintwo
majorsteps.First,theTPloadingsineachgridcelljinthelakecatchmentarecalculatedandsummed(TP
loadingisthetotalmassflowintoalake,andTPyieldistheareallynormalizedPtransport).Thisincludes
Figure2.(a)OverviewoftheWater—GlobalAssessmentandPrognosis(WaterGAP3)modelingframework(Verzano,2009;modified),and(b)waterpollutantloading
sectorsinWorldQualcategorizedaseitherpointsourcesordiffusesources.
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Table1
CompilationofGlobalDataSourcesUsedinTPLoadingCalculations
Data Application Datasourceorrelatedpublication Originalspatialresolution
Proteinconsumptiondata Domesticseweredandnonsewered FAO(2014) Countries
Population Domesticseweredandnonsewered KleinGoldewijk(2005)andKlein 5arcmin
Goldewijketal.(2010)
Treatmentlevel Domesticsewered,manufacturing Williamsetal.(2012) Countries
wastewater,urbansurfacerunoff
Sanitationpractice Domesticnonsewered WHO/UNICEF(2013) Countries
(scatteredsettlements)
Fertilizerapplicationbycrop Inorganicfertilizer FAO(2003) Countries
Totalfertilizerapplication Inorganicfertilizer IFA(2014) Countries
Soilloss Alldiffusesources Nachtergaeleetal.(2011) 5arcmin
Animaltypeanddensity Livestockwastes FAO(2014) Countries
Phosphorusinmanure Livestockwastes ASAE(2003) Countries
Livestockunits Livestockwastes FAO(2003) FAOregions
Chemicalweathering Backgroundloads Hartmannetal.(2014) 0.008°
Atmosphericdeposition Backgroundloads Mahowaldetal.(2008) 0.5°
InputfromtheWaterGAP3hydrologymodel
Urbansurfacerunoff Urbansurfacerunoff WaterGAP3calculationspublishedin 5arcmin
Schellekensetal.(2017)
Built-upfraction Urbansurfacerunoffretentioncalculation WaterGAP3standardinput 5arcmin
(Alcamoetal.,2003)
Watersurfacearea Retentioncalculation WaterGAP3standardinput 5arcmin
(Alcamoetal.,2003)
Surfacerunoff Alldiffusesources WaterGAP3calculationspublishedin 5arcmin
Schellekensetal.(2017)
Note.TP=totalphosphorus;FAO=FoodandAgricultureOrganization;WHO/UNICEF=WorldHealthOrganization/UnitedNationsChildren’sFund;ASAE=
AmericanSocietyofAgriculturalEngineers;WaterGAP3=Water—GlobalAssessmentandPrognosis.FAOSTAT=FAOStatisticalDatabases;IFA=International
FertilizerAssociation.
loadingsfromdomesticseweredwastewater(Ld ),domesticnonseweredwastewater(Ld ),manu-
dsTP,j dnsTP,j
facturing wastewater (Ld ), urban surface runoff (Ld ), inorganic fertilizer (Ld ), and livestock
mfTP,j usrTP,j ifTP,j
wastes(Ld ).Themethodspresentedinsections3.1.1–3.1.7areusedforthesecalculations.Thesumof
orgTP,j
allcellloadingsinalakecatchmentis
Xn
LsumTP½tTP=month(cid:3)¼ LddsTP;jþLddnsTP;jþLdmfTP;jþLdusrTP;jþLdifTP;jþLdorgTP;j (1)
j¼1
L represents the sum of all anthropogenic TP generated in the catchment. In the second step, the
sumTP
amount of these loadings retained in rivers, smaller lakes, and wetlands in the catchment is calculated
(section3.1.8).Theremainderoftheloadingisassumedtodrainintothemainlakeofthecatchment.
Ascomparedtootherlarge-scalemodels,WorldQualandtheWaterGAP3frameworkhaveglobalcoverage
andcomputesnutrientsourcetermsonaglobal5-arcmingrid;itthereforecandepictthespatialvariability
ofpollutionsources.Othermodelscomputenutrientexportatthemouthofrivers(e.g.,thelumpedmodels
NEWS2,Mayorgaetal.,2010;NANI/NAPI,Hongetal.,2012),oronlyforselectedlarge-scalebasins(e.g.,the
semidistributedanddistributedmodelsRiNUX,Loosetal.,2009;HBV-NP,Anderssonetal.,2005).Inthispaper
we use WorldQual to compute the P loading on a grid cell basis and then sum up to a lake basin total,
whereaswecomputePretentionasabasinaverage.ThemethodologyforcalculatingTPloadingsforvarious
sectorsisdescribedinthefollowingsections.
3.1.1. DomesticSeweredWastewater
The TP loading from domestic sewered wastewater is the phosphorus in domestic wastewater that is
collectedinsewersbutnotremovedbywastewatertreatment.Thisloadingiscalculatedas
Ld ½tTP=month(cid:3)¼Pc=12(cid:4)N=Pc(cid:4)Ex(cid:4)P=N(cid:4)Pop(cid:4)Cr(cid:4)ð1(cid:1)TrÞ (2)
dsTP
wherePc(tcap(cid:1)1year(cid:1)1)isthecountry-specificproteinconsumptionpercapitaandyear.DataforPcwere
obtainedfromtheFoodandAgricultureOrganization(FAO,2014).ForcountrieswithnoPcinformationcon-
tinentalaveragesweretaken.N/PcistheaveragefractionofNitrogen(N)inconsumedprotein(16%).Existhe
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ratioofexcreted/consumedprotein(36.5%onaverage,VanDrechtetal.,2009),P/NistheratioofPandNin
human feces (17% on average, Van Drecht et al., 2009). Pop is the population in each grid cell (History
DatabaseoftheGlobalEnvironment,HYDE,KleinGoldewijketal.,2010).Cr[0–1]isthefractionofpeople
livingin the gridcell that are connectedto thesewage system. Tr is thecountry-average treatmentlevel
forTPremovalinsewagetreatmentplants.Thisfactoraccountsforremovalinprimary,secondary,andter-
tiarytreatmentandalsoaccountsforthedeficienciesinachievingthedesignremovalrate.DataforCrand
TrarefromReder(2017).
3.1.2. DomesticNonseweredWastewater(ScatteredSettlements)
“Domesticnonseweredwastewaterfromscatteredsettlements”consistsofwasteorwastewaterthatiscol-
lectedatonsitedisposalfacilities(forexample,inseptictanksorhanginglatrines)andthenaftertreatment,
ornot,isfinallyintroducedtosurfacewatersaspointsources.Italsoconsistsofwastesfromopendefecation
and pit latrines that are washed off land surfaces by precipitation and enter lakes as a diffuse source. In
WorldQualTPloadingsfromscatteredsettlements(Ld )areestimatedsimilarlytoequation(2)butalso
dnsTP
takeintoaccountthefractionofurbanandruralpopulationthatisnotconnectedtothesewagesystem.
Todistinguishbetweendiffuseandpointsourcesfromscatteredsettlements,dataonsanitationpractices
are derived from the Joint Monitoring Programme for water supply and sanitation (WHO/UNICEF, 2013),
nationaldatabases,andtheliterature.
3.1.3. WastewaterFromtheManufacturingSector
Wastewaterfrommanufacturingfacilitiesisassumedtobecollectedinasewagesystemandtransportedto
wastewater treatment facilities where part of its phosphorus content is removed. The remainder is dis-
chargedtothelocalsurfacewatersystem.TPloadingsoriginatingfrommanufacturingwastewaterarecalcu-
latedfrom
LdmfTP½tTP=month(cid:3)¼CTP;mf(cid:4)10(cid:1)9(cid:4)Rflmf=12(cid:4)ð1(cid:1)TrÞ (3)
whereC (mgTP/L)istheaverageTPconcentrationinmanufacturingwastewater.WorldQualusesavalue
TP,mf
of3mgTP/Lasanaveragevalueoverliteraturevaluesfordifferentmanufacturingsectors.Rfl (L/year)isthe
mf
return flow from the manufacturing industry in each grid cell and month as calculated by the Water Use
modelofWaterGAP3(ausderBeeketal.,2010;Flörkeetal.,2013).Similartothedomesticsector,manufac-
turingloadsarereducedbythecountry-averagetreatmentremovalrate,Tr(0–1).
3.1.4. UrbanSurfaceRunoff
Somephosphorus accumulates onurbansurfaces and is washedoffto surfacewaters byprecipitation to
sewage canals or other drainage routes. Sewage treatment plants are assumed to remove P from urban
surface runoff at the same rate as they remove P from domestic sewered wastewater (see section 3.1.1).
Monthly TP loadings in urban surface runoff are calculated by multiplying an event mean concentration
(EMC [mg/L])timesthemonthlyurbansurfacerunoffR (mm/month):
TP us
Ld ½tTP=month(cid:3)¼R (cid:4)EMC (cid:4)A (cid:4)10(cid:1)3(cid:4)F (cid:4)ð1(cid:1)TrÞ (4)
usrTP us TP cell built
A (km2)andF (0–1)arethecellareaandbuilt-upfraction,respectively.Inthisstudy,R isfromthe
cell built us
WaterGAP3calculationspresentedinSchellekensetal.,(2017).ForEMC weusearepresentativevalueof
TP
0.2mg/LbasedonGöbeletal.(2007).Becausethisvalueisformotorways,itislikelyaconservativenumber
forallbuilt-upfractions.
3.1.5. InorganicFertilizerintheAgriculturalSector
OurcalculationsalsotakeintoaccountthefractionofPcontainedininorganicfertilizerwhichisnottakenup
byplantsbutiswashedinsteadintothesurfacewatersystem(inthispaperweuse“inorganicfertilizer”to
mean manufactured fertilizer). We estimate this loading by multiplying the applied inorganic fertilizer
F (tTP/year)timesthetermsinbracketsthataccountforthelossofPbyleachinganderosion.
inorg,TP
!
L R
LdifTP½tTP=month(cid:3)¼Finorg;TP(cid:4) 1þðRmacatx=aÞ(cid:1)bþSl(cid:4)c(cid:4)Rmaecatn (cid:4)1=12 (5)
L (0,1)isthemaximalleachablefractionofTPinappliedinorganicfertilizerTP(dissolvedfraction).R /
max act
R representsacorrectionfactorthatincludestheannualvariationofsurfacerunoff(R [mm/year]is
mean act
thesurfacerunoffinayear;R [mm/year]isthemeanannualsurfacerunoff1980–2000).R andR
mean act mean
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arecalculatedbytheWaterGAP3hydrologymodelandcorrespondtotheWaterGAP3estimatesinaglobal
waterresourcesreanalysis(Schellekensetal.,2017).a(mm)andb(–)definetheshapeoftheresponseof
dissolved TP loadings on runoff changes. Their values as well as the value for L were taken from
max
Harrisonetal.(2005)(a=850mm,b=2,L =0.04).Slisthegriddedsoilloss(tha(cid:1)1year(cid:1)1)thatwaspre-
max
dictedbytheFAOprojectLADA(Landdegradationassessment)(Nachtergaeleetal.,2011)withtheUniversal
SoilLossequation(Wischmeier&Smith,1978).c(hayear/t)isanempiricalcoefficientthatdefinestherela-
tionshipbetweentheamountofTPininorganicfertilizer,TPthatisfixedtosoilparticles,andtheamount
oferodedsoil(cwascalibratedtoc=3·10(cid:1)6hayear/t).
WaterGAP3calculatesTPloadingsfromfertilizerapplicationfortheunsealedareaingridcellswithcropland
asdominantlandusetype.Hereby,itusescountry-specificF for21differentcroptypesaccordingto
inorg,TP
FAO data (FAO, 2003). These FAO data approximately represent the time period 1995 to 1999. However,
between 1990 and 2010, the global application of phosphate in inorganic fertilizer increased by about
13%(IFA,2014). Hence, dataoftheInternationalFertilizer Association(IFA)wereusedto derivecountry-
specificcorrectionfactorsforthecrop-specificfertilizerapplicationrelativetotheperiod1995–1999.These
relativechangesareaveragesfor5-yearintervals,thatis,1990–1994,1995–1999,2000–2004,and2005–2010.
3.1.6. Agriculture—LivestockWastes
Phosphorus in livestock wastes is partly used as an organic fertilizer and is partly unused and remains in
pastures.Eitherwayitispartlyabsorbedbyplantsandwhatisnotabsorbedislargelywashedoffintosurface
waters.WorldQualcalculateslivestockTPproductionineachcell(F )astheproductofananimal-specific
org,TP
TPexcretionrateex andthenumberofanimalsls:
i,TP i
X12
Forg;TP½tTP=year(cid:3)¼ lsiexi;TP (6)
i¼1
The index i represents 12 animal types: dairy cattle, nondairy cattle, pigs, sheep, goats, buffaloes, camels,
horses, chicken, turkey, ducks, and geese. Animal type and density data were taken from the Water Use
model of the WaterGAP3 modeling framework. The excretion rate for each specific animal type ex
i
(thead(cid:1)1year(cid:1)1)iscomputedusingtheapproachofPotteretal.(2010):
(cid:2) (cid:3)
exi thead(cid:1)1year(cid:1)1 ¼mTP;ilci (7)
inwhichm (thead(cid:1)1year(cid:1)1)istheamountofTPinthemanureofaparticulartypeofanimal(takenfrom
TP,i
ASAE,2003,andthereforeOrganisationforEconomicCo-operationandDevelopmentdata).Theparameter
lc (0–1)isanimalspecificandaccountsforregionaldifferencesinanimalnutrition.Theseregionaldifferences
i
are taken into account by taking the ratio of regional and Organisation for Economic Co-operation and
Developmentequivalentlivestockunits.ValuesoflcarederivedfromFAO(2003)data.
SimilartoLd (equation(5)),WorldQualassumesthatthefractionF ofwastesiswashedouttothe
ifTP org,TP
surfacewatersystemasafunctionofrunoff:
!
L R
Ldorg;TP½tTP=month(cid:3)¼Forg;TP(cid:4) 1þðRmacatx=aÞ(cid:1)bþSl(cid:4)c(cid:4)Rmaecatn (cid:4)1=12 (8)
Again,thefirstandsecondtermswithinbracketsrepresentleachinganderosionofTP,respectively.
3.1.7. BackgroundLoadings
WorldQualconsiderstwobackgroundsourcesofTP.ThefirstisatmosphericPdepositionF (tTP/year),
atm,TP
whichwasderivedfromtheglobaldistributionofdepositionfluxesforTPinMahowaldetal.(2008).This
depositionoriginatesfrombothnaturalsourcessuchasPcontainedinsoilstransportedbywindandanthro-
pogenicsourcessuchasPcontainedinairpollutionemissions.Basedonthesedata,WorldQualestimatesthe
fractionofatmosphericdepositionthatiswashedouttothesurfacewaterasanempiricalfunctionofrunoff:
!
L R
Ldatm;TP½tTP=month(cid:3)¼Fatm;TP(cid:4) 1þðRmacatx=aÞ(cid:1)bþSl(cid:4)c(cid:4)Rmaecatn (cid:4)1=12 (9)
TheparametersL ,a,b,andcarethesameasforequations(5)and(8).
max
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Table2 ThesecondbackgroundsourceischemicalweatheringofTP(Ld
cw,TP,
ListofReferencesUsedforModelTesting
[tTP/year]).ThisinvolvesthetransportofPfromsoilsandrock
annual
Numberof in the catchment via runoff. Data for this source were taken from
Reference Riverandlakebasins datapoints
Hartmannetal.(2014)andadjustedtomonthlyloadingsusing
TPloadingdata R
MeybeckandRagu(1995) Largeriverdischarges 15 LdcwTP½tTP=month(cid:3)¼Ldcw;TP;annualR ac(cid:4)t12 (10)
intotheocean mean
OECD(2015) KymijokiRiver 1 whereR (mm/year)istheannualrunoff,andR (mm/year)the
act mean
PedrozoandBonetto(1989) ParanaRiver 1 meanannualrunoffoftheperiod1980–2000.Runoffvaluesaretaken
SkogenandSoiland(2001) RiversintotheNorthSea 3
fromthehydrologicalmodeloftheWaterGAP3modelingframework.
LurryandDunn(1997) MississippiRiverbasin 1
3.1.8. TPRetentionintheSurfaceWaterSystem
Stalnackeetal.(1999) RiversintotheBalticSea 3
deWit(2000) ElbeandRhinebasins 3 Retention in surface water systems that are within the watersheds
LfW(2002) MoselRiver 1 drainingtofocallakesisdefinedbyHejzlaretal.(2009)as“thefraction
TeodoruandWehrli(2005) Danubeatinflow 3 of external N or P loading that is retained within the water bodies,
toBlackSeaandIron eitherinabsolutevaluesorrelativetotheinput.”InWorldQual,reten-
GateReservoir
tionofTPiscalculatedonthecatchmentscalebasedontheapproach
SaundersandLewis(1988) ApureRiver 1
ChineseAcademyof YangtzeRiver 1 ofBehrendtandOpitz(1999):
Science,Instituteof
L 1
Oceanology(2011) rTP ¼ (11)
Skoulikidisetal.(1998) Greecerivers 6 LsumTP 1þaHLb
Ludwigetal.(2009) Riversintothe 19
HereL istheTPloadingatacatchment’soutflowpoint,whichin
Mediterraneanand rTP
BlackSeas thisstudyisequivalenttoitslakeinflowlocation.HL(m/year)isthe
Holopainenand LakeLadoga 1 hydraulicload,definedastheratioofannualrunoffinthecatchment
Letanskaya(1999) (m3/year)toitswatersurfacearea(m2)(Hejzlaretal.,2009).Annual
Bilaletdinetal.(2011) LakeOnega 1
runoffistakenfromthehydrologymodelofWaterGAP3andsurface
ILEC(2015) Lakesoftheworld 11
area from Alcamo et al. (2003). The values for the empirical para-
Scherenetal.(2000) LakeVictoria 1
ZimmerandBendoricchio LagunadeBay 1 metersa=13.2andb=(cid:1)0.93aretakenfromHejzlaretal.(2009).
(2001)
Johengenetal.(1994) LakesMichiganandOntario 2
3.2. ReliabilityoftheLoadingEstimates
DolanandMcGunagle(2005) LakeErie 1
LWSB(2006) LakeWinnipeg 1 Thereliability oftheTPmodel canbetestedbycomparingcalcula-
IGKB(2000) LakeConstance 1 tionstomeasurementsin92lakeandrivercatchments(notequiva-
Pascheetal.(2012) LakesKivuandMalawi 2
lent to the 100 largest lakes), as well as the percentage share of
Matzingeretal.(2007) LakeOhrid 1
eachTPsource(Table2andFigure3a).Forstudieswithmultiyeartime
Wangetal.(2014) LakeTaihu 1
deAndaetal.(2001) LakeChapala 1 seriesdata(e.g.,1990–2000forLakeVictoriaasreportedinScheren
SalasandMartino(1991) SouthAmericanlakes 3 etal.,2000)weonlyusethelong-termannualaverageofthesedata,
EuropeanEnvironment LargeEuropeanlakes 3 ratherthanseparatemeasurementsfromindividualyears.Therefer-
Agency(2005)
encesinTable2covertheavailableliteratureonTPloadingsinthe
BUWAL(1994) Swisslakes 3
basinsoflargelakesandriversaccordingtotheauthors’knowledge.
Total 92
Dataonsectoralcontributiona Aninitialfindingofthiscomparisonwithliteraturevaluesisthatthe
EuropeanEnvironment Europeanriversandlakes 10
rangeofmodelandliteraturevaluesissimilar(Figure3a).Forindivi-
Agency(2005)
dual basins, the nearest agreement is for the Danube basin (calcu-
WhiteandHammond(2011) Thames 1
LfW(2002) MoselRiver 1 lated versus measured, 30 versus 31 kg km(cid:1)2 year(cid:1)1, respectively)
ILEC(2015) Lakesoftheworld 9 and the farthest for Lake Taihu basin (calculated versus measured,
Scherenetal.(2000) LakeVictoria 1 384versus65kgkm(cid:1)2year(cid:1)1,respectively).TheR2ofmodelversus
LWSB(2006) LakeWinnipeg 1
measurementsis0.53,whichistypicalofothermodelsinthelitera-
IGKB(2000) LakeConstance 1
Total 24 ture(e.g.,theNEWS(GlobalNutrientExportfromWatersheds)model:
R2=0.55;Harrisonetal.,2005).Themeanabsolutedeviationofmodel
Note.TP=totalphosphorus;OECD=OrganisationforEconomicCo-operation
and Development; ILEC = International Lake Environment Committee versus measurements is 39%. On average, model estimates are
Foundation;LWSB=LakeWinnipegStewardshipBoard;LfW=Landesamtfür 5kgkm(cid:1)2year(cid:1)1higherthanmeasurements.
Wasserwirtschaft; IGKB = Internationale Gewässerschutzkommission für den
Bodensee;BUWAL= BundesamtfürUmwelt. Asafurthertestofthemodel,weexaminetheconsistencybetween
aThereferencesdonotprovidethefractionofcontributionofeachsectorforall WorldQual and other model estimates by comparing our TP source
lakesandrivers.Thus,eachsubplotinFigures3b–3ddoesnotcontain24data
apportionment calculations with those of other models (Table 2).
pointsintotal.
For this comparison we harmonize data from the different models
FINKETAL. 623
Global Biogeochemical Cycles 10.1002/2017GB005858
Figure3.TestingoftotalWorldQualtotalphosphorus(TP)calculations.Theloadingsin(a)aregivenperunitcatchmentarea.Diagrams(b)to(d)showmodeled
sectoralcontributionsversusdataofothersourceapportionmentstudies.
intothreecategories:domestic+industrysector,agriculturesector,andbackgroundloadings(Figures3b–3d).
Wefindthatthereisagoodagreementbetweentheaveragevaluesofthemodelversusliteraturevalues
(Table3),suggestingthatWorldQualgivescentralestimatesofPloadingswithrespecttotheensembleof
available studies. There is a lower level of agreement when
WorldQual is compared one-on-one with individual studies
Table3 (Figures 3b–3d). The model agrees with literature estimates
ComparisonofEstimates(WaterGAP3andOtherStudies)forAveragePercentage
moderately well for the domestic + industry sector and less so for
ShareofTPSources
the agriculture sector and background loadings, because
Averagepercentageshare Averagepercentageshare
background loadings are controlled by complex factors that are
Source calculatedinthispaper(%) ofotherstudies(%)
difficulttocapturewithinaglobalmodels.Theagreementbetween
Domestic + 33.2 37.5
models for the domestic + industry sector suggests a similarity in
industry
methodologyorinputdataforthedifferentmodels.
Agriculture 38.7 35.6
Background 23.0 19.4 DiscrepanciesbetweenWorldQualandmeasurementsorothermodel
Note. WaterGAP3 = Water—Global Assessment and Prognosis; TP = total estimatesmaybeduetovariousreasons.First,theobservationaland
phosphorus. inputdatacontainerrorsanduncertainties.Second,simplifiedmodel
FINKETAL. 624
Global Biogeochemical Cycles 10.1002/2017GB005858
assumptionsareatypicalsourceoferrorinallmodels.Ingeneral,webelievethatthesimplifiedrepresenta-
tionofPprocessesinWorldQualisappropriateforglobalanalysis,wherethetemporalandspatialresolution
iscoarseandwherethekeyobjectiveistoobtainaconsistentglobaloverviewofmanydifferentlakes.Itis
lessappropriateforsimulatinglocal,specificconditions,forexample,theimpactofparticularaquaculture
facilitiesonoverallPloadingtolargelakes.
4. Results
Toaddresstheresearchquestionspresentedatthebeginningofthispaper,wenowanalyzeandcompare
theTPinputtoinvestigated100largelakes(section4.1),aswellastheirmainsources(section4.2),andtrends
(section4.3).WepresentresultsforbothTPyieldspercatchmentareaandloadingsperlakearea.Themetric
“yield”illustratestheintensityofPproducedinthecatchmentandisthereforeusefulforinvestigatingstra-
tegiestoreducetheseloadings.Themetric“loadingperlakearea”canbeusedasinputtosimplifiedassess-
ments of eutrophication potential of lakes, for example, along the lines of Vollenweider (1976). Here we
presentmeanannualyieldsofthecatchmentsandtheloadingsperlakeareafortwoperiods,1990–1994
and 2005–2010,that arebased onthesequentially modeled monthlyloadings fortheperiod1990–2010.
The 5-year averaging period takes into account the temporal irregularity of inorganic fertilizer data (IFA,
2014).SinceagricultureisamajorsourceofTPloading,thesedataplayacrucialroleinmodelcalculations.
Estimatesoffertilizerusearebasedoncountry-specificfertilizerbalances(production,consumption,produc-
tion,export,andimport)whichdonotnecessarilyreflecttheactualuseoffertilizerinaparticularyear.The
problemisthatcountriesfrequentlyimportfertilizerandstorelargequantitiesofitfromyeartoyear.Inorder
tosmoothoutthiseffect,weuse5-yearaverageddata.Anotherreasonforusing5-yearaveragingperiodsis
tosmoothouttheeffectofyear-to-yearhydrologicvariations.
4.1. GlobalDistributionofTPLoadings
Fortheworld’s100largestlakes,asdefinedinthispaper,themedianlakecatchmentTPyield(Figure4a)was
5 kg TP km(cid:1)2 year(cid:1)1 during the period 2005–2010, which represents current conditions. The frequency
distribution of TP yields has a positive skewness of 4.1, indicating a bias toward smaller loadings.
Catchment yields are most frequently in the pollution class ranging from 0 to 1 kg TP km(cid:1)2 year(cid:1)1.
Qinghai Lake catchment in China has the largest TP yield (516 kg TP km(cid:1)2 year(cid:1)1), and the Canadian
LakesDubawnt,Martre,andNueltininCanadahavethelowestTPyield(<0.01kgTPkm(cid:1)2year(cid:1)1.Other
largelakesinthesecountriesalsotendtobeeitherveryhighorverylow,respectively,inaccordancewith
thedensity of population and economicactivity and level of environmental protection. Despite thelarge
loadings to Chinese lakes, the Asian average is not as high as Latin America because of the numerous
Siberianlakeswithsmallloadings. ThemedianofLatinAmericavalueis abovetheglobalaverage(70kg
TP km(cid:1)2 year(cid:1)1). In particular, the Lake Titicaca catchment stands out with yields of about 115 kg TP
km(cid:1)2year(cid:1)1.Africanlakecatchments(4kgTPkm(cid:1)2year(cid:1)1)arebelowthemedian,andEuropeanlakecatch-
ments(median:5kgTPkm(cid:1)2year(cid:1)1)areclosetothemedianofalllakecatchmentsexamined.
ThedistributionofTPloadingsperlakeareaissimilartothatofcatchmentTPyields.Althoughspatialpat-
ternsaresimilar(Figures4aand4b),loadingsperlakeareatendtobe2ormoreordersofmagnitudelarger
becauselakeareaismuchsmallerthanlakecatchmentarea.AnomaliesareEuropeandNorthAmericawhere
loadingsperlakeareaareonlyafactorof5and9,respectively,largerthanloadingspercatchmentarea.This
isbecauseEuropeanandNorthAmericanlakeshaveasmalleraverageratioofcatchmenttolakesurface.
Becauseofthis,TPloadingsperlakeareatoAfricanlakesaremorethan4timeshigherthantoEuropean
lakes,althoughtheyhaveapproximatelythesamecatchmentTPyields(Table4).
IntheNorthernHemisphere,TPloadingstolakestendtodecreasewithlatitude,roughlyinaccordancewith
populationdensity(Figure5a).Nevertheless,lakeswithhighloadingscanbeobservedatalllatitudes.Below
30°NthereisnoapparentcorrelationbetweenTPloadingsandlatitudeorpopulationdensity(Figure5a).
Apartfromalatitudinalvariation,TPloadingsalsovarygreatlybetweendevelopinganddevelopedcountries
(fordefinitionof“developing”and“developed”seeUNEP,2017).Outofthe100largelakesexaminedinthis
paper,66arelocatedindevelopingcountries,andtheircatchmentshaveanaverageTPyieldofabout11.1kg
TPkm(cid:1)2year(cid:1)1.TheremaininglakesareindevelopedcountriesandhaveacatchmentTPyieldofabout
0.7kgTPkm(cid:1)2year(cid:1)1.
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Global Biogeochemical Cycles 10.1002/2017GB005858
Figure4.Totalphosphorusloadingstothe100largestlakesintheworldwithrespecttocatchmentsize,fortheperiod2005–2010:(a)loadingsperunitcatchment
areaand(b)loadingsperunitlakesurfacearea.
4.2. TheSourcesofPLoading
The sources of TP loadings to thelarge lakes investigated, in order of importance, are inorganic fertilizer,
background loadings (weathering and atmospheric deposition), domestic sewered wastewater, livestock
wastes,andothersources(wastewaterfrommanufacturing,domesticunseweredfromscatteredsettlements
[septic tanks, pit latrines, and others], and open defecation). However, the relative importance of these
sourcesvariesbetweenlakesandcontinentsasnotedinthefollowingparagraphs.
Inorganicfertilizeraccountsforabout47%ofthetotalTPloadingstoalllargelakessurveyedandmorethan
50%in44outof100largelakes.Itaccountsfor88%ofTPloadingstolargelakesinAsia(Figure6c),ranging
from<0.1%calculatedfortheremoteSiberianlakesTaymyrandVilyuyskoyetomorethan99%forthelakes
HulunandNa-Mu(China)andHovsGolLake(Mongolia).Inorganicfertilizerisalsothemostimportantsource
in Latin America (76%) with the exception of the Brokopondo Reservoir in Surinam, where only a small
amountofinorganicfertilizerisapplied.Inorganicfertilizeraccountsfor45%ofTPloadingsinAfricanlake
FINKETAL. 626