Hydrochemistry (Major and Trace Elements) of Lake Malawi (Nyasa), Tanzanian Northern Basin: Local Versus Global Considerations P

Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , Sciences 2,* Discussions Earth System Hydrology and , M. Delalande 4 ´ eochimie de Strasbourg, 1 rue , D. Cardinal 3 ´ een de l’Arbois, BP 80, 13545 Aix En Provence ´ e Paris-Sud, 91405 Orsay Cedex, France 4372 4371 ˆ at. 701, Centre CEA de Saclay, 91191 Gif sur 6 ´ editerran ˆ ole M , J.-P. Ambrosi 2 ´ edex, France ´ e Paris 7, Case postale 7052, 75205 Paris Cedex 13, France ˆ at. 504, Universit , and M. Benedetti 5 ´ egional de l’Ouest Parisien, 12 rue Teisserenc de Bort, 78190 Trappes, France , L. Bergonzini 1 ´ edex, France This discussion paper is/has beenSystem under Sciences review for (HESS). the Please journal refer to Hydrology the and corresponding Earth final paper in HESS if available. Royal Museum for Central Africa,LSCE Dept. – of UMR Geology 1572, and Orme Mineralogy, 3080 des Tervuren, Merisiers Belgium B UMR 7154 – IPGP, Universit CEREGE – UMR 6635 – Europ UMR-CNRS 8148 IDES, B Laboratoire R Received: 8 June 2010 – Accepted: 14Correspondence June to: 2010 P. – Branchu Published: ([email protected]) 7 July 2010 Blessig – 67084 Strasbourg C *present address: UMR7517 Laboratoire d’Hydrologie et de G cedex 04, France 4 5 Yvette C 6 3 Hydrol. Earth Syst. Sci.www.hydrol-earth-syst-sci-discuss.net/7/4371/2010/ Discuss., 7, 4371–4409, 2010 doi:10.5194/hessd-7-4371-2010 © Author(s) 2010. CC Attribution 3.0 License. 2 E. Pons-Branchu 1 Hydrochemistry (major and trace elements) of Lake Malawi (Nyasa), Tanzanian Northern Basin: local versus global considerations P. Branchu Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ect ff 4374 4373 , Alkalinity and Si, along three profiles in the lake northern extremity, in 4 preserved besides a water warming during last century (Branchu et al., 2005a; Vollmer hen et al., 1996).reservoirs Consequences constitute an of important such provideron human of anthropogenic activities freshwater could disturbances and be fish inpossible protein. drastic, East eutrophication as Researches African that these Great issedimentary Lakes a inputs focus regional particularly to scale lakes onstudies problem (Hecky the were (UNEP/IETC, et focused 2000) al., onin and 2003; sediments organic-pollutants on Machiwa, and in 2003). mercury water1999, food and 2003). On web sediments, Lake According contamination trace Malawi, toof (Karlson East these elements et African characterisations al., Great and Lakes 2000; (Cohen other Kidd et reports al., et on 1996), al., the Lake Malawi pollution appears to be relatively expressed through fishing pressure,and land new use species changes, introduction. urbanisation, Indeed,annual industry, in growth mining the East of African population Greatreau, (about Lakes 2009) region, 2.5% is the according high responsiblelead to for large to the watershed Population contamination pressure Reference and/or and Bu- overexploitation for water of stress both that water can and fish resources (Co- For example, Tanganyika’s falling productivity overlinked the to past century increased has2003; water been O’Reilly temperature recently et and al., 2003).the then The early higher unprecedented 1960’s rates stratification of ininvolves (Verburg sedimentation a the et increase combination since Lake al., of Tanganyikadeforestation; climatic basin Cohen and suggests et anthropogenic strong al., causesmetals-metalloids 2005). disturbances, (e.g. contamination Lake which heavy Victoria of rainfall eutrophicationKishe and its (Machiwa, and waters 2003) Machiwa, and and 2003; sediments Ramlal (Ikingura et et al., al., 2003) 2006; have been linked to human threats Tropical lakes are ofsity fundamental conservation, importance but theytheir for experience productivity, regional ecology, large economies physico-chemistry limnologicalof and and changes human biodiver- their that life. water greatly The level a at mechanisms the behind time these fluctuations scale are not fully understood. 1 Introduction tivity. Evaporation is onesuperimposes of on the the controlling watershedlake, factors control. controls of the lake Hydrothermal chemistry elementson activity, of concentration not between one that Northern evidenced of rivers in thegeological and main the specificity other northern of tributaries tributary. studied characterises northernical Chemical the budget compari- watershed. geographical shows and Moreover that the northernlake, lake illustrating watershed annual the generates chem- dual the importanceto main the of elemental lake. this input area to in the terms of water and ionic recharge luting elements with World Health OrganisationEast Guidelines African and those lakes reported shows forhuman other that stress. this Major reservoir element ismodel behaviour uncontaminated is Cl assessed despite and through an K aby increasing are 3 diatom boxes conservative productivity model. elements and In whereas sedimentation. this Si Ca, is Na, removed from Mg the and solution alkalinity show low reac- Na, K, Cl, SO five tributaries and two on-landmental hydrothermal distributions springs. and Water concentrations profilesstratification. that show are Stratification, similar influenced assessed ele- by usingfiles, lake temperature, is physical-chemical conductivity, characterised Si by and(150–190 two m). Mn boundaries: pro- Elemental the wateranalyse. concentrations thermocline Epilimnetic are (70–90 concentrations m) discussed and and distribution using aredeposition the simple also and influenced oxicline covariance river by atmospheric diving. Comparison of dissolved concentrations for potentially pol- This paper presents the firstMn, inventory Ba, of dissolved Cd, minor Cr,largest and African Cu, trace lake. element Pb, Sampling (F, Al, Mo, waspart Fe, carried Bi, of out Sr, during the Zn) 1993 lake. dry concentrations season in Trace in metal Lake the concentrations Malawi, northern were the measured, second together with Ca, Mg, Abstract 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , K, Ca, Na, 4 bottle. On land, five ® , since 1967 (Calder et al., ff E), 700 m of maximum depth vessel. Three lake water pro- ◦ ected by a tropical climate and is ). Non-acidified samples were de- ff S; 34 3 0 Nyanja 40 ◦ ) is a 2 –14 0 C until processing. Water samples were then 4376 4375 ◦ 30 ◦ 4 < (Vollmer et al., 2002), is the second largest surface wa- 3 , 47 mm type) through 0.45 µm cellulose nitrate membranes ® 1 (with Suprapur 65% HNO ∼ type). Two PP flasks were filled with this filtered sample, only one (200 mL) and stored at temperature ® erent types of waters from the north basin (Tanzanian part of Livingstone ff ® ) MilliQ water and rinsed with MilliQ water. All the reagents are analytical grade. 3 Lake Malawi (Fig. 1), 570 km long (9 HNO The filtration unit was rinsed before each operation with MilliQ water and then sam- Parafilm processed in a closedfiltration place unit on a (Sartorius clean(Sartorius surface: 240 mL werebeing filtered acidified using at a pH frontal voted to anion analysesFor and alkalinity acidified determination, ones oneter. to PP cation, All flask Si PP (60 and mL) flasks trace was and element fully filters analysis. filled were by previously non-filtered washed wa- using acidified (Suprapur 65% basin) were sampled on land andfiles on-board (P1, of P2 the and P3,(105–220 Fig. m) 1), waters, corresponding were to sampledrivers epilimnetic using and (0–105 a m) two 5 hydrothermal and L springs metalimnetic PVC(PP) were Hydro-Bios flasks also were sampled flushed (Fig. and 1). filled 500 with mL sampled polypropylene water, flask cap was then sealed using 2 Material and methods 2.1 Sample collection and processing During the frameworkMechanisms of in the Rifts) CASIMIR Belgian1993, project, (Comparative di and Analysis especially of during Sedimentary the fieldwork Infill of October with tectonic, seismic, volcanicthe and catchment hydrothermal activities and compared a2005a). with It relatively is the high based rest on heatMg, of major, Si, minor flows and Al, at trace Fe, element the Cr,water (Alkalinity, Mn, Cl, column lake’s F, Co, and SO bottom Ni, tributaries. Cu, (Branchu Zn, et Sr, al., Mo, Cd, Ba and Pb) analyses performed on northern part of the lake and its watershed (Fig. 1) that expresses singular features, Rungwe volcanic rocks (Hecky and Bugenyi, 1992). The present study focuses on the dominant, leading to anoxia2002). between 170 This and hydrodynamictions 300 scheme m occur is (Halfman, due somewhat to 1993; simpleAccording internal Vollmer to since waves et classification and spatio-temporal al., based upwelling varia- onered (Eccles, as nutrient 1974; oligotrophic budget Hamblin but concentration due et itas to al., would mesotrophic its 2003). (Bootsma be high et plankton consid- al., productionEast 2003). rates African it Its is water waters composition rather (Kilham belongs considered dominance and to Hecky, (Kilham, the 1973), “common” 1990; resulting Gibbs, fromcambrian 1970), a granitic mostly water-rock and interaction controlled metamorphic by rocks the of weathering of its Pre- watershed with little influence of the Rivers (Fig. 1).ingstone This mountains, northern volcanic basin rocks is andto has characterised the the by rest highest the of specificmanent Poroto-Rungwe water the thermo-haline and flow catchment stratification Liv- compared (Bergonzini, (Halfman,penetration 1993), 1998). at which depths The limits where lake mixing biological is and degradation meromictic oxygen of with settling a organic per- matter is pre- and a volume ofter 7790 reservoir km on thefree African freshwaters. continent and(Fig. The represents 1). lake about Overall, 6% presentsmainly its of at located catchment the on its the (126 world 500 western km southDwanga, surface coast drained Bua a by and surface the Songwe, Linthipethe outlet, North Rivers Ruhuhu and the (Fig. South River Rukuru, Shire 1). and River the The northern eastern one shore by is the mainly Kiwira, drained by Mbaka, Lufirio and Lumbila 1995) changing the lake waterchanges in balance; water Furthermore compositions it of theLake has tributaries been Malawi could shown water induce that important quality potential characterise changes (Branchu in the et the inorganic al., waterdetermine 2005b). geochemistry its of origin The northern 3) goals to part of discuss of this the specificity Lake study of Malawi, are the 2) 1) northern to to watershed. et al., 2005) and increase of deforestation, along with runo 5 5 25 20 15 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | at 1 − ). Calibrations ® C and sealed using ◦ 4 0.003‰ is calculated; < C) with a main gradient ± ◦ ) and cations (K, Ca, Na and 4 at the Royal Museum for Cen- + ). Calibrations ranged from 2 to 40 ppb ® ´ een de Recherche et d’Enseignement en C) to 240 m (22.8 ◦ 4378 4377 Plasma Quad PQ2 ® values are highly variable without clear depth-related 4 at 240 m with three main gradients at about 50–60 m, 70– 1 − ) are presented, dissolevd oxygen concentration was unfortunately not C at the CEREGE (Centre Europ 25 ◦ . Non-refrigerated transport was restricted to a few days, water samples were ® CTD casts were performed in the north basin prior to sampling with a Sea-Bird SBE Thermodynamic computations discussed below were performed using MINTEQA2 ´ eosciences de l’Environnement, Aix-en-Provence) prior to analysis. missing as the imbalance(Table 2). percentage is From these in data the an range average of weight analytical salinity of standard 0.203 deviation Temperature decreases from surface (25.4 between 70 and 90 mthe (Fig. surface 2a), to whereas 263.5 conductivity µS cm increases90 m from and 256.7 190–210 µS m cm (Fig. 2b).are similar Cl, Ca, for Na, the K, threeing Mg profiles and to alkalinity and concentrations standard display (Table 2) deviations notrend. significant SO Si changes with concentrations depth exhibitsharply the accord- below same 70 behaviour m in (Table the 2, three Fig. profiles 2c). and Ionic increase budget indicates that no significant ion is mainly focussed on organic(Karlson pollutants et al., in 2000; water Kidd and et al., on 1999, metals 2003). 3.1 in fish Lake and water sediments column data 3 Results and interpretations Water column and on landbles (rivers 2 and hydrothermal and springs) 3 datageneral for are physical-chemical major presented features and in are trace Ta- presentedical elements, with characterisations. respectively. reference to Lake To previous Malawi ourelements limnolog- major data knowledge set ions this relative and to work Lake Malawi provides whereas the previous contaminants first studies minor were and trace 25 logger. Only temperatureductivity, and K electrical conductivity (expressedmeasured as due reference to con- probe problems. equilibration speciation model and data set presented in Tables 2 and 3. centrations. (ICP-MS) on a Fisons Instrument tral Africa (Tervuren, Belgium). Ananalysis internal to standard correct (In) for was sensitivitycalculated added detection drift. to limits samples Analytical and before reproducibility standardare (in deviations the and, reported lower for part in ICP-MS, of Tableand the 1. calibration field range) processing, Hydrobios To bottle considerformed blank at potential analysis laboratory (Table using metal 1). MilliQ However, contaminationreveal hydrobios water bottle potential during has blank contamination been trace sampling in per- element analyses Zn and Pb but in a lower range than measured con- for Al and 1 tocal 40 Emission ppb Spectrometer for (ICP-OES: Fe. JYanalyses Si 38 were was type measured performed III) with in at Inductively(60), the CEREGE. Coupled 1–10 Cu Concentrations ppm Plasma (65), range. of Opti- Zn All Crsured these (66), (mass: in Sr 52), (88), the Mn Mo 0.05–20 (55), ppb (95), Ni Cd range (111), by Ba Inductively (138) Coupled and Plasma-Mass Pb (208) Spectrometry were mea- Dissolved concentrations of major anionsMg) (Cl, were F measured and SO usingranged capillary from electrophoresis 0.1 (CIA to fromChromate-OFM, 20 Waters pH ppm 8, for for anions anionsmined and and by UV 0.2 potentiometric Cat2, HCl to pH titration 20method. 6, with ppm for Al calculation for cations. and of cations. Fe equivalent Alkalinity concentrations volume wassorption Electrolyte were by deter- measured Spectrometry the was using Gran (GFAAS: Z8200 Graphite Hitachi Furnace Atomic Ab- Parafilm stored at 4 G 2.2 Analytical methods ple’s aliquot is flushed. All samples were stored at temperature 5 5 25 20 15 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 3 ; ma- C and 4 ◦ C) than other ◦ , F, Mo and Cd concentrations in 4 (James, 1959). Their contribution to 1 − s 3 4380 4379 hot springs (Table 2) could be associated to the presence 3 30) and also than epilimnetic waters. Rivers are diluted compared to 30%, largely above the analytical variability) for all major components, < > C ◦ 0.92) suggesting their control by a same phase. Cu, Cr and = r 1 and 0.75, between Cr and Cu and Cr and Ni, respectively) and their = r nity with Mn and mainly Fe oxi-hydroxides a possible scavenging by these freshly From this covariance analyse some phase associations are proposed but trace metal Several elements show correlation but without depth related gradient. Sr and Ba ffi per mines (Bugenyi, 1982).values exceeding Lead the in guidelines (Table Lake 6). Malawi Kiwira is river the fluoride concentration only is exception higher with extreme Finally, our data (lake andwater rivers) (Cr, allow, Ni, for elements Cu,parison of Mo, with health Cd, World significance Health Pb, in Organisationother F drinking guidelines East and (WHO, African Mn) 2004) lake and a1996; comparison data water Challe, with (Kilham quality and 2002; evaluationtions Hecky, based Table 1973; are 6). on Bugenyi, below com- 1982; WHO Globally,as Cohen guidelines Lake contaminated et and Malawi (Cohen al., the and etsame ones range al., northern measured than 1996). river in those measured regional concentra- However, in lakes Cu Lakes classified Edward concentrations and are George contaminated high, by in cop- the sitions, which is probably responsible ofbetween the and lake surface along enrichment. the The threeprocesses homogeneity profiles that occur indicates in comparable North e Lake Malawi. 3.7 Water quality assessment other lakes, to atmospherictling deposition particles (Stumm and and then Morgan,depositions to 1996). are the In denuded tropical elemental regions soils scavenging potentiallakes and sources by Malawi biomass of set- and such burning Tanganyika from watersheds,dry local biomass season or burning long-range and mainly area. has(Bootsma occurs been In et during al., proposed the 1996; to LangenbergCa, partly et Mg al., explain 2003). rain N, However contents Slikely soil that and (Bootsma and biomass wind P et burning influence rain al., and also concentrations wind 1996). over eroded In soils should addition also to influence this dry depo- rainy influence, it is and Scholz, 1993).enrichment Lake (Mn, surface waters Fe, (0–10 Al,concetrations m) are Ni, are lower also Pb, for characterised these Cd,contribute elements significantly by Ba than to a this and surface metal level lake Sr) exceptminerals water by and at one’s, interaction they other with all cannot their particles). stations. particulate load Such (clay As enrichment tributaries can water be associated, as for oceanic or son in the southern part of Livingstone Basin near the Ruhuhu River mouth (Halfman temperature) of Lumbila River enablesmocline it (Branchu to et sink al., in 2005b). the water A column similar down layer to was the identified ther- during 1992 rainy sea- attention should be paidcolumn sampling to followed by suspensed sample matter processing in characterization anoxic and conditions. 3.6 to deeper Local water processes Local processes are superimposedconductivity over this show general pattern. indeed(0–20 gradients At m) P3, within is temperature surface and warmer(Fig. water and 2a,b). (0–70 with m): Relative higher to the conductivity the upper than surface layer water the the thermocline higher bound density layer (lower conductivity and suggesting a direct watersheda control. Duereactive to surfaces (Sigg redox et This al., 1987; implies Trivedi for and Axe, metals 2001). behaviour having is not assessed through the present data set. In future works a particular hydroxides should be associated asFe coatings under reducing with conditions these corresponds clay toassociation minerals. an with increase The Fe of release oxi-hydroxides Pb of as andet Ni previously al., suggesting observed 1994; their Balistrieri in et aquatic al., systems 1994). (Benoit are well correlated ( Ni covary ( averaged relative ratio is the same in the water column (0–200 m) and in the tributaries, Lumbila (Branchu, 2001) seemsphase. to Consistent be with controlled akaolinite, Al/Fe by illite a and particulate vermiculite typescapacity (or (Drever, (Branchu colloidal) 1988). et Al-Fe al., Submicron size 2005a)even after clay that filtration minerals have and can are high natural be adsorption carrier found of in trace water elements (Allard samples et al., 2002). Fe oxi- same than suspended matter (SM) Al/Fe measured in river Kiwira, Songwe, Mbaka and 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | erently ma- ff erent climatic ff ects di cient of variation of ff for mean lake water- ffi 1 − 75%). For all elements, cient of variation of 19% > ffi 4386 4385 and about 35% of the whole catchment) includ- ff cient of variation) of water column (0–250 m) composition ffi in the northern area compared to 1350 mm y 1 − For all elements the main input to the lake is from rivers ( Seasonal and inter annual variations of river chemistry have also been considered Hydrochemical budget is computed using this water budget and chemical data from 250 m by Gonfiantini et al. (1976). Global River inflow to the Lake is computed us- conditions (Gonfiantini et al., 1979). The whole lake higher residence time of alkalinity 2001 and March 200522% (Delalande, is 2008). computed. For A Si meantrations (in are temporal its stable soluble coe throughout reactive the phase)was year, it a computed has mean (Bootsma been temporal et shown coe al., that 2003). concen- except Si and Cl, thethan lake residence for time water, (average ca. illustratesdeep 520 waters. years) the about The relatively 5 long times Cl slownetic higher residence vertical Cl time content (ca. excanges of 1000 years) between deep is waters surface linked that to and was the associated high hypolim- to record of past di present data characterise the endflow of variability the has been dry demonstrated season.jor in The elements such (Vandelannoote importance environments et but of al., a chemical 1999;For and Hecky major et elements al., (Ca, 2003; Na, Langenbergsessed Mg, et for K, al., Mbaka 2003). Cl) and the Kiwira seasonal rivers to by interannual comparing variability data was from as- October 1993, November steep area. An averagethen composition, been computed attributed from tois similar this required characterised remaining to area, catchment. compute has required. Chemical this steady From budget state Table and 5, assumption ability constant we (expressed chemical can as composition estimate coe a oflower temporal waters than (seasonal 10% are with and higest interannual) variability vari- for potassium and magnesium. as Hecky and Bugenyi data correspond to the end of the rainy season whereas the ing present chemical data set(additional completed 15% with Hecky of and lake Bugenyiing global (1992) rivers river runo data Linthipie, set Bua,The Dwangwa, 65% Luweya, remaining N. riverare Rukuru, not inflow, characterised corresponding N. from to a Rumphi physico-chemical about and consideration are 35% S. globally Rukuru. of associated to the catchment, that > Bootsma et al. (1996, 2003) for rain and our water column data set completed for depth ment area and drains the Rungwehigh volcanoes relief, that responsible culminate of at the aboutthan highest 3000 2000 m precipitation mm a.s.l.. y rates The ofshed), the whole generates catchment about (more 20%state of conditions, total inputs river to inflow.and the river lake In inputs are this whereas equally budget, outputsresidence distributed computed are time between for dominated, is direct steady at 99 precipitation 83%, yearsthe by for relative direct the isolation evaporation. whole of Water lake deep and waters. 5 years for the epilimnion illustrating have however been understimatedwater in budget this for budget. Lake Malawitributary Recently based and we on outlet monthly flows, published evaporation data an andlevel (recorded precipitation original records over over water several (Branchu surface years) et and of Kiwira, on al., lake- Mbaka, 2010; Lumbila Table 7). and Lufirio This watersheds, northern covers area, about including 9% Songwe, of the total catch- polluting human activities areprocess present with in visible impact Malawi evidenceddue watershed. from to biomass this The burning study sole and is anthropogenic to the soil atmospheric erosion. inputs partly 4 Lake Malawi water and chemicalLake budgets Malawi chemicalNorthern budget tributaries was that firstly have published specific by features Hecky (geological, and hydrological, Bugenyi relief, (1992). . . . ) watershed (Branchu et al.,system 2005a). (lake and Presented northern data(Martin rivers) characterise and but an Windom, enriched uncontaminated compared 1991).metals to in In the aquatic accordance food World web with Averageuncontaminated and River previously system sediments published (Kidd from et data dissolved al., on trace 1999, metal heavy 2003), consideration Lake whereas Malawi is potentially an than the WHO guideline resulting from the influence of hydrothermal springs in its 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , i (2) (3) (1) and ], indi- em ): from R 1 Q − erences are ff erences between ff and CAT can be used R , from individual tributaries , water fluxes (L y i Q ) i ] P [ × P − i [Ep] × 4388 4387 ): from tributaries 1 ex ) in: global catchment average tributary [CAT] − ) in: global catchment average tributary [ 1 Q 1 and CAT is presented for major elements (Fig. 4). and precipitations [P] − − i + R , exchanged between epi- and metalimnion ) i P [Met] − i ) i ] j ([Ep] (Eq. 1) is 123 times higher than CAT (Eq. 2). Di ], water fluxes (L y · R j concentrations are presented for Ca, Na, Mg, Cl, Alk, K and Si in [ R · i R em ] j concentration (mol L , metalimnion [Met] Q concentration (mol L R Q i ( i ( i . × , from precipitations . ). [ 0 j X and [CAT]. Evaporative process that concentrates ions in the surface is also Q · ex /Q = Q Q 1 t Q P /Q d = 1 / = i i and CAT values plotted in a Gibb’s diagram (Gibbs, 1970; Kilham, 1990) fall in Q = ( i ] R Data used (in Eq. 2) are from i) Lake water budget and Lake vertical water fluxes The second approach for assessing global tributray concentration is based on an j R both computations are explained by the biological cycle. Si is largely removed from tion whereas for alkalinity itto overestimates variability it slightly in (21%). databeen This (flow previously variability involved and in is diagenetic chemistry, likely processes see due remove (Hecky and above). then Bugenyi, from 1992) However that the Ca, could modynamic lake Na computation and suggests and store occurrence Mg of them a(cf. have in Ca, above). the Mg carbonate Occurrence sedimentary controlling of pool. phase modern such sediments phase Moreover of in a the lake the ther- whereif water authigenic and they column biological have is calcites a also are low present consistentSi contribution even is with to particular the the as total particle fluxes (Pilskaln, 2004). As expected, the central part ofweathering. the Comparison boomerang between shape (notFor shown) Cl illustrating and their K,the control similitude steady by between state rock assumption computed and concentrationsvalidity. demonstrate (Eqs. For the 1 Ca, boxes model and Na accuracy 2) and and reinforces Mg data CAT set slightly underestimates (about 19%) the concentra- particulate phases (incomputation. the water Groundwater fluxes column are andthrough not identified in in sediments) this areintegrated equation but also in are included this expressed in computation.to this illustrate Then elemental comparison behavioursiking between (reactive of or river water conservative) fromthen in interprated steep eplimnetic in catchments terms water. is of not reactivity Only taken of into a account. disolevd element Di in epilimnetic waters. to outlet (Table 7, from Bergonzini, 1998; Vollmer1996, et al., 2003) 2002), ii) and rain chemistrydissolved iii) (Bootsma fluxes present et al., but water dissolved column element chemistry. fluxes This induced equation by only precipitation/dissolution considers of tributaries with: element epilimnion [Ep] This allows computing the dissolvedtary chemistry (CAT), of following the Eq. global (3) Catchmentare and Average assuming equal Tribu- that to for Lake each chemicalflow element concentration. outputs Lake and chemical that inputs epilimnetic concentration[CAT] is equal to out- 5 Lake Malawi mean tributary concentration In order to determine the meanthe tributary first concentration one, two this approaches concentration areical is followed. budget, directly In using computed following from Eq. data (1) used in[ the dydrochem- epilimnetic hydrochemical budget in steady state conditionsd[Ep] (Eq. 2). tion in deep waters.1979) Moreover, is the partly hypolimnetic due alkalinityof to increase organic nutrient matter. (Gonfiantini remineralisation Other et associated contributionriver with al., for waters anaerobic example (Bootsma degradation for et Si al., can 2003) be associated to sinking of with: element vidual tributaries [ Q Table 8. (Table 8) can be related to photosynthesic activity in epilimnetic waters and degrada- 5 5 25 15 20 10 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | to the lake and (Fig. 4) allow to ff R . Specificity of the Kiwira R and CAT) which can be explained mainly by 4390 4389 R . General accordance between major element CAT and i R Both approaches (Eqs. 1 and 2) are consistent and allow to characterise the global Northern tributary composition (Table 2) is compared to Computation of a trace metal annual budget is unrealistic as inputs are only partly Major element (Si excepted) epilimnetic residence time is similar to the water one on-land spring is noticeablethropogenic through contamination the except Kiwira some River. dry atmospheric We deposition, found probably no linked evidence of an- 7 Summary and conclusions This is the firstMalawi published report and on one minorogy, of and weathering the trace processes, element rare evaporation, watertivity dealing chemistry biological mainly with in processes control Lake major and Lakethis context, Malawi element hydrothermal the major, Rungwe ac- chemistry. volcanic minor rocksWhereas and are Regional sub-lacustrine an trace important geol- hydrothermal element source input of concentrations. element has to the not In lake. been observed, the influence of trachyte-phonolite series accounting forthe the enrichment high in K Cu, concentrations Cr,trolled and and by Ni. the the The basalts high chemistry for weathering offor rates the the of northern Kiwira rocks River tributaries of the is the hydrothermal then Rungwe signal con- volcanic superimposes center; on in this addition bedrock signature. factor is thefeatures peculiarity (high of relief, the highmineral precipitation northern charge rates) watershed of of (Branchu thisments northern northern et of rivers, area, al., local including characterise 2005b).metamorphic rocks a high rocks) higher relative is weathering All to assessed rates. the Harkin, by the 1960) comparing “average” to The their the watershed major enrich- upperfor element (Precambrian continental trace composition granitic crust (e.g., elements composition and a (UCC;UCC. Weathering Wedepohl, basaltic of 1995) composition basic and rocks (Drever, could 1988) explain the has relatively been high alkalinity: compared rocks to of the the Trace elements, except Al andaverage 2 Fe more that concentrated are in the about average 10 northern times river more thanriver in concentrated, concentration CAT. are that in isCr globally and Ni, lower, than particularly in for the K, northern alkalinity, rivers. Al, The Fe, most Cu, likely Pb, explanation for this enrichment be confident on CAT computations to assess trace element tributary input to the Lake. pled rivers, average concentration ofa northern factor river, 2 Kiwira River excluded, exceeds by 6 Lake chemistry control: the northernThe area northern specificity area is responsibleat of least 57% of of 48% the forillustrating total Cl, the Na importance 35% input of for by this alkalinity runo zone. and from 28 toRiver 31% presented for above other major isand elements illustrated Mg contents. here with For major high elements, Cl except and Cl Na that contents is in and low low concentration Ca in sam- important (see above). Mnbetween is the epi- only and trace meta-limnion. elementsinking showing particulate a Input Mn concentration is of gradient dissolvedcentration dissolved trough computed Mn reduction, for from can the average explain the tributary the metalimnion, (Eq. negative 2). Mn where con- evaporation that concentrates inputs. Siresidence is time a and an nutrient input with concentrationone. a 5.7 high times more recycling concentrated rate, than a eplimnetic short known for the northernstate computation tributaries (Eq. 2) and of therefore theabout CAT remain gives 3 for times poorly all elements higher constrained.the (except than Mn) uncharacterised a the Steady atmospheric concentration input epilimnetic even measured if one. for some The elements computation such neglects fluxes may be by sedimentation, whereas dissolution occurset in al., the 2003; meta- Pilskaln, and 2004). hypo-limnion (Bootsma (about 4 years).more Ca, concentrated than Na, average Mg, input ( Cl, K and alkalinity epilimnetic waters are about 3.0 the euphotic zone in the epilimnion during diatom productivity and then from the lake 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ` a la pol- ´ e 4392 4391 ect of spatial and temporal variability on the geo- ff ´ eologiques. Publ. no. 103. Mus. Roy. Afr. Centr., Tervuren, Bel- ´ ements majeurs et traces dans les grands lacs de rift tropicaux (Lacs ´ el ´ erie), 161–180, 2005a. ´ etallique de deux grands lacs africains (Tanganyika et Malawi), Revue des Sciences ´ eologiques, Publ. no. 106, Mus. Roy. Afr. Centr., Tervuren, Belgique, 374 pp., 2001. Tanganyika et Malawi),g Processus et enregistrements biogochimiques, Annales-sciences lution m de l’Eau, 18 (Hors-s internal cycling of silica2003. in a large, tropical lake, J. Great Lakes Res., 29 (sup. 2), 121–138, and its significance toand Palaeoclimatology the of nutrient the East budget AfricanGordon Lakes, of and edited Lake by: Breach Malawi, Johnson, Publ., T. Amsterdam, C. in: and The Odada, Netherland, The E. 241–250, O., Limnology, 1996. Climatology gique, 183 pp., 1998. perspective, Conserv. Biol., 7, 644–656, 1993. and Santschi, P. H.:particles, Partitioning colloids, of and solution Cu, in Pb, six Ag, Texas estuaries, Zn, Mar. Chem., Fe,Africain, 45, Al, Annales-sciences 307–336, g and 1994. Mn between filter-retained properties of suspended solids in the Amazon Basin, B.genic Soc. meromictic Geol. lake, Fr., Geochim. 173, Cosmochim. 67–75, Ac., 2002. 58, 3993–4008, 1994. Future work should include the e A detailed investigation of the water column around thermocline will permit to precise Branchu, P.,Bergonzini, L., Delvaux, De Batist, D. M., Golubev, V., Benedetti, M., and Klerkx, J.: Branchu, P., Bergonzini, L., Benedetti, M. F., Ambrosi, J. P., and Klerkx, J.: Sensibilit Branchu, P.: Cycle des Bootsma, H. A., Hecky, R. E., Johnson, T. C., Kling, H. J., and Mwita, A. J.: Inputs, outputs and Bootsma, H. A., Bootsma, M. J., and Hecky, R. E.: The chemical composition of precipitation Bootsma, H. A. and Hecky, R. E.: Conservation of the African Great Lakes: a limnological Bergonzini, L.: Bilans hydriques de lacs (Kivu, Tanganyika, Rukwa and Nyassa) du Rift Est- Benoit, G., Oktay-Marshall, S. D., Cantu, A., Hood, E. M., Coleman, C. H., Corapcioglu, M. O., Balistrieri, L. S., Murray, J. W., and Paul, B.: The geochemical cycling of trace metals in a bio- Allard, T., Ponthieu, M., Weber, T., Filizola, N., Guyot, J.-L., and Benedetti, M. F.: Nature and euthrophication. References itored parameters should be relevant with metallic and organic pollutants and also watershed monitoring program should then be organised in the near future. Mon- (rivers, wet and dryphases. depositions), While a Lake characterisationwater Malawi of body, in the this regard dissolved statushydrochemical to and is system, analysed particulate relative elements, the as isimply it present-day a a was non-contamination non systematic recently of contaminated shownet non-pollution lake al., that of 2005a). waters due tributaries Computations does to ofmodel, (Bootsma chronic not inertia and contamination indicate of response, Hecky, that using the 1993;depending simple once 3-boxes on Branchu pollution the is elementassociated detected, reactivity. to it This biological reactivity will and linked be physico-chemical to persistent processes liquid-solid for reactions described a is here. long time A global spatial extension of sinking riveroxicline layer; would in allow the to precise same i) way oxidantii) a sequence nature detailed linked of to investigation the organic around “turbid matter degradation, layer” occurring at or just abovechemical the parameters, depth an of exhaustive DO characterisation disappearance. of the inputs into the lake system are also influenced byvariance river between inputs. elements could be Behaviour indicative ofindeed of phase control trace association. Ca metal Carbonates and is could Mgassociated not to concentrations. discussed Fe Some and but Mn trace hydroxides co- elements whereaswith most (Zn, depth. of Pb, This them Ni) study do could not isand show a be large particular new reservoir trend contribution of to freshwater theand and knowledge modelling food. of of Nevertheless this such the unique aquatic complete ecosystem system comprehension require more data. for several trace metals (Mn, Fe,chemistry Al, presents Ni, the Zn, usual Pb, features Cd, reportedincrease Ba, for below Sr). stratified the lakes: The thermocline a water and Si columnological a and physico- scheme conductivity Mn of enrichment in organic the matterdominate suboxic-anoxic production-degradation these waters. and features. 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Bottle Blank 1 (%) − 3 15.7 – 17.8 – 355.3 14.5 544.7 2.9 296.2 5.4 297.6 2.7 ∗ ∗ < < < < < < 50.541.3 1780 1520 – – a a n.a. 18.1 51.6 – n.a. 16.5 87.9 – n.a. 20.8n.a. 18.2 17.0n.a. 50.2 16.7 – 66.9 – n.a. n.a. – n.a. 19.5 19.6 18.5 18.9 – – 815.1 Alkali- F Si Ionic 1267.9 1751.4 2120.0 limit (ICP-MS) 4 5.3 2395.9 19.2 45.0 – < < < < < < < < < 146 1.6 12.5 78.8 – < > 2 < < < < < < Tributaries Hydrothermal springs 4398 4397 , except alkalinity in µeq L 1 − P1 station (water depth: ca. 215 m) P2 station (water depth: ca. 200 m) P3 station (water depth: ca. 245 m) 1 calculated with 15 blank determinations σ standard (ICP-MS) % erence of meq cations minus meq anions ff deviation (%) 0 450 861 294 151 1255 4.7 2333.9 508 22.0 923 14.6 314 0.2 166 104 50 458 860 295 154 105 1.1 n.a. 22.2 12.8 – 10 455 922 322102030 15150 452 152 458 880 470 5.7 885 451 880 295 n.a. 880 305 313 140 294 152 12810 161 136 156 2.7 140 11.1 95 494 38.3 2368.2 n.a. 2397.8 18.9 910 19.9 21.4 19.6 18.9 18.9 315 0.2 – 0.2 167 85 75 459 887 2982550 16575 153 492 484 3.8 902 482 906 n.a. 895 305 20.0 304 301 176 19.2 182 106 173 – 79 133 7.0 11.4 n.a. n.a. 15.6 16.5 17.1 17.4 – – 100 483 902 312 162 106 150190 486 490 902 948 306 312 160 190 119 97 1.6 n.a. 20.0 67.6 – Sample/ Ca Na Mg K Cl SO 100125150197 446 463 859 464 886 453 888 292 854 300 292 153 260100 166150 161 55 104200 164240 75 483 7.8 114 501Average 916 2461.3 499SD 7.0 (%) 940 17.0 496 474 897 2400.7 314 58.7 4.1 906 14.3 895Songwe 313 103.2 317 171 317.4 0.6 2.7 309 303 182 504.1 2.1 171 170 141 164 164 206.9 4.2 6.8 142 146.1 5.4 115 99 7.0 n.a. 2.9 n.a. 2407.3 1.6 21.9 24.1 20.2 22.5 2402.3 49.1 104.3 21.8 78.7 133.89 – 5.8 – 6.5 depth mity balance KiwiraMbaka 179.7 237.5 2659.8 867.9 203.7 177.7 346.6 1037.2 184.1 72.2 24.1 2294.4 79.6 4247.1 3 Lumbila 221.6 209.6 99.5 56.6 Lufirio 490.7 683.1 232.4 108.1 AverageSD (%) 289.4 984.9 42.5 184.0 98.2 168.3 27.8859 65.5 – – – 1649.8 – – 37.0 1148.2 – – 151.1 – Mapulo 950 53 210 910 1750 7120 3120 50 Kasimulo 1130Average 58 230 1040 930 55 720 1890 920 6270 1820 3890 6695 45 3505 47.5 45.9 1650 – 1 − 1 1 − − blank value. σ 3 = tmmol L Elements Relative ReproductibilityClSO4 DetectionKNa Hydrobios CaMg 1 µmol L F 5 Al 1 Si 2 Sr 2 5 5 2 2 1 0.0008 Banmol L FeCuZnCr 1MnNiMo 2 Cd 3Pb 2 4 4 4 3 3 6 8 2 3 0.0014 9 9 6 12 3.2 18 7.6 18 1 1.3 1.7 1.2 0.4 25.8 0.2 0.4 Major ion concentrations (µmol L Analytical characteristics for water analysis. : Below calibration limit, in this case average is computed using the first calibration point DL: concentration lower than detection limit Values calculated from the di Mean value computed using all analysesComputed performed using 3 two times analyses in performedDetection in repeatability limit reproducibility conditions conditions in the lower concentration range Not considered for average and SD computations (see text) n.a.: Not analysed < a ∗ Table 2. < 1 2 3 Table 1. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ∗ 2377.5 ∗ 161.9 ∗ 1845 242 30 229 54.8 ∗ 0.9 ∗ < ∗ 12.1 781 36 83.3 38.0 ∗ 198.2 37.2 154.6 34.9 258.1 35.4 940.8 23.4 6 162.5 36.5 ∗ ). . 0 1 < < < < < P1 station P2 station P3 station Tributaries Tributaries 1.9 < − ∗ ∗ 4400 4399 Hydrothermal springs Hydrothermal springs 82.9 ∗ P2 station (water depth: ca. 200 m) P3 station (water depth: ca. 245 m) P1 Station (water depth: ca. 215 m) 8.8 14.3 31.8 252.0 32.8 1854.9 236.0 1736.4 ∗ 0 8.6 2.4 531.0 51.1 5 10.2 3.1 561.1 86.9 50 7.5 0.8 411.7 41.5 10 12.5 10203050 8.175 9.7 0.6 8.3 1.0 8.7 470.1 0.7 8.6 513.4 32.9 0.9 473.6 34.5 0.3 505.9 32.6 474.6 36.5 10 33.2 255075 10.3 11.2 1.4 10.0 1.0 502.2 9.8 1.0 484.5 39.2 1.1 490.3 40.7 37.7 504.2 46.6 100150190 8.5 8.4 1.0 8.3 2.7 500.9 0.7 511.4 39.3 494.5 38.1 34.2 Sample/Depth Mo Cd Ba Pb 100125150197 8.6 8.2 0.4 9.7 11.3 1.0 511.2 5.3 478.8 1.8 30.3 515.7 34.3 510.8 34.2 79.4 100150200240 8.9Average 9.4SD (%) 1.7 8.6 9.1 0.8 8.5 478.1 11.1 1.0 1.4 524.8 38.4 0.9 81.1 513.0 45.6 499.0 515.7 36.8 42.6 5.7 55.4 33.4 Songwe 9.4 LufirioSD (%) 6.6 136.1Mapulo – 98 42.1 3.5 KiwiraMbakaLumbila 92.6 26.0 3.0 2.2Average 118.4 27.5 36.9 Kasimulo n.a. n.a. n.a. n.a. < 92.8 150.1 4.9 79.0 13.8 3.4 8.9 46.7 2780.9 57.1 31.0 200.0 27.4 1806.7 236.1 971.3 > < 0 521.1 2036.6 14.9 32.7 187.0 35.9 1909.35 541.7 1571.5 698.7 3129.7 24.1 39.9 77.0 87.5 2204.6 979.2 1620.8 10203050 714.875 221.9 1114.5 211.8 872.8 265.0 10.3 800.2 198.0 28.2 1005.9 7.3 7.5 743.8 118.6 10.1 34.3 23.2 30.8 35.2 7.5 20.1 1774.910 16.0 20.5 31.0 248.7 26.325 26.850 27.8 1979.4 1500.5 13.775 1864.2 1984.7 399.8 279.9 28.0 258.6 239.6 281.7 1585.3 1595.8 1922.7 194.6 1509.9 1577.1 1213.7 282.2 250.5 11.1 1269.9 8.3 1526.8 35.5 1298.0 9.4 42.7 22.9 9.8 38.7 36.3 34.6 44.4 19.1 1989.6 41.2 19.6 312.5 39.0 2426.2 39.4 1552.8 2279.5 307.5 2437.2 307.7 1532.0 333.8 1554.9 1594.1 50 334.1 1223.1 10.1 40.2 25.9 37.2 2311.9 335.9 1354.6 10 n.a. 770.0 100125150197 188.7 296.0 659.3 222.6 844.7 428.7 1078.9 7.5 1691.3 9.2 9.0 29.3 11.8 29.0 33.4 13.7 79.3100 14.1 25.9 21.6 1076.8150 26.1200 1778.9 82.7 30.2240 1798.6 246.6 3847.5 n.a. 1950.3Average 224.9 291.8 567.2 1578.3 270.3SD (%) 208.6 1483.4 321.9 1510.7 1567.4 713.6 1605.0 417.2 1955.4 1265.6 7.8 47.3 1151.9 9.3 9.3 10.6 38.1 9.4 39.2 44.0 37.8 38.5 24.5 41.7 17.4 204.6 859.0 36.1 39.6 1873.3 38.1 40.9Average 32.3 26.9 2126.2 43.4 2155.2 2266.9 2179.1 1041.7 326.5 221.7 2338.5 372.8 305.1 302.4 1520.0 370.0 42.8 1556.1 1643.4 1573.7 1573.5 19.6 50.4 3.6 100150190 277.5 286.1 1179.0 230.8 1323.9 16.9 723.8 14.7 36.7 38.8 9.5 30.8 71.3 31.3 37.4 46.3 122.6 2105.9 2179.1 360.4 29.7 831.4 1571.8 1914.4 1589.1 283.9 1577.0 SongweKiwira 637.1MbakaLumbila 1487.2 1186.5Lufirio 366.0 3856.1 1213.2 20.9 6674.1 210.2 2113.5SD 32.2 1505.1 (%) 30.1 16.7 23.3 192.5 435.3 49.5 28.8 32.2 25.2 28.6 1816.0 24.6 95.4 1729.5 227.2 22.8 27.8 263.5 925.6 1759.0 1874.1 601.9 207.2 246.7 932.4 660.5 MapuloKasimulo 1414 n.a. 482 n.a. 105 n.a. 23 n.a. 268 n.a. n.a. n.a. n.a. n.a. Sample/depth Fe Al Ti Cr Mn Ni Cu Zn Sr Continued. Trace element concentrations (nmol L : Below detection limit. In this case average is computed using detection limit. : Below detection limit or calibration limit for Al. In this case average is computed using the first calibration point or Not considered for average and SD computations (see text) Not considered for average and SD computations (see text) n.a.: Not analysed < ∗ Table 3. n.a.: Not analysed < the detection limit. ∗ Table 3. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (%) balance 1 − µeq L ) 1 − 3.110.0 Bootsma et al. (2003) ± ± ) (µmol L 1 − 1 − µmol L 4402 4401 C) (µS cm ◦ ( Ca Mg Na K Cl Alk. Ionic 470 311 894 164 140 2379 0.6 (3.0) (27.7)(3.0) (3.4) (7.6) (1.9) (6.3) (1.8) (1.6) (4.2) 1 2 80–200 23.07 258.2 et al. (1979) cient 3.3 9.5 5 9.9 1.3 0.5 ffi Major element mean epilimnetic concentrations (and standard deviation in %): com- Comparison with previous temperature, conductivity and dissolved silicon data. Sep 98North. Basin:Sep 1997 105–220 0–80 80–200 24.48 23.16 (K25) 255.5 257.3 Vollmer 76.7 et al. (2002) Ref./dateCentral Basin: Jun 1976 0–80Central and south.Basins Depth Jan range 1992 Temperature 25.61North. Basin: ConductivityOct 1993 Si 0–80Whole 80–200 lake: Sep 248.5 1996– 26.15 23.21 Ref 0–105 0–80 257.6 80–200 (K25) 261.2 24.86 23.19 Gonfiantini (K25) 256.1 17.5 259.1 Halfman (1993) This study 71.8 20.7 Gonfiantini et al. (1979) 0–250 m –Jun 1976Hecky (unpublished)–Nov 1980 0–250 m (3.7) (1.3) (1.7) 451 (3.2) 258 960 136 (1.7) 140 May 1981This work(Oct 1993)Variability (coe of variation in %) 0–240 m 474 442 303 278 895 873 (4.1) 164 160 (4.2) (2.7) 115 137 (7.0) 2396 (24.1) (1.6) 1.8 Data are available for one 640Data m are deep available water for column. one 600 m deep water column. 1 2 Table 5. parison with previous studies. Table 4. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ∗ C P P 3 ect the ff WHO (2004) volume/input 3 = 5–6 George 3 9–11 1.1 6 10 Edward 2 a 2–8 7–94 Victoria c b 1 ) 4404 4403 1 b ) − a 1 ) y − 3 3 y 3 1 25–125 5000 6 5–57.6 15–130 90–110 2000 0.007–0.12 10 < < < LakeEpilimnionMetalimnionHypolimnion 2760 2310 7790 2720 RiversRainTotal 40.2 38.5 78.7 OutflowEvaporationTotal 65.2 13.5 78.7 Epi-metalimneticMeta-hypolimnecticLake 18 4 Epilimnion 5 99 Input (km Output (km Volume (km Vertical exchange time (y) Residence time (y) 6.3–18.0 0.1–0.6 < Comparison between ranges of concentrations (µg/L) for Cr, Ni, Cu, Zn, Mo, Cd, Pb, ects is limited. Annual water budget in Lake Malawi (Branchu et al., 2010.) ff Concentration MalawiCrNi Tanganyika CuMoCd 1.5–4.1 112.8–244.5 1.3–5.1 0.7–1.1 50 20 70 Zn 15.7–64.0 (µg/L) Pb MnF 0.8–102.9 271.7–427.5 10 1060 50–3280 400 1500 Concentrations of the substance at or below the health-based guideline value may a Constituents for which there is some evidence of a hazard but the available information on From Vollmer et al. (2002) Adapted from Bergonzini (1998) Challe (2002) except F (KilhamCompilation and from Hecky, 1973) Cohen et al.From (1996) Bugenyi (1982) Residence time computation assumes steady state conditions. Residence time From WHO guidelines, 2nd edn. (1998) a b c Table 7. appearance, taste or odour of(Grey the filled water. cases correspond to excess values relative to WHO guidelines) 1 2 3 P health e ∗ C Table 6. F and Mn, i) analysedCohen in et Lake al., Malawi, ii) 1996; published Challe, for 2002) other and East iii) African from lakes the (Bugenyi, WHO 1982; guidelines (2004).

h u

mass/input

i h

0 0

L 0 0 0

0 0

5 0 1

5 3 2 0

o 4

0 0 i 0

r 3 0 0

i 2 0

u u

r r

u u

k k

33°E 34° 35°

u u

r a

R R

w B

t g r

u n

o a

o o

N w

S S

D 10° 11° 12° 13° 14° 9°S p of p Malawiof andLake locations of d its catchment. Inset box d its catchment. Inset shows location 9°45' S 9°45' 9°25' S 9°25' 9°35' S 9°35' ) 34°10' E 34°10' Riv. (245 m (245 4406 4405 Lumbila ) P3 P3 ) 34°05' 215 m 215 Water depth theat sampling station 200 m P1 ( P1 P2 P2 ( CTD cast 50m Lake Malawi Lake Basin Livingstone 250 m by Gonﬁantini et al., 1976). Lufirio Riv. > Ca Na Mg Cl Alk K Si 33°55' ) 94.7 193.3 58.4 21.1 324.4 29.0 100.1 a 1 − ) 6.2 10.6 3.6 2.0 29.0 2.3 0.3 1 Kiwira Riv. Mbaka Riv. ) 7.5 15.2 4.6 1.7 25.5 2.3 7.9 − 1 − Songwe Riv. (µmol L HS2 HS1 i Lake water sampling River sampling station ] Hydrothermal spring R Chemical budget of Lake Malawi. 33°45' 1: Schematic bathymetricFigure hydrographic and ma water sampling stations basin water in the anLivingstone Malawi in Africa.of Lake

Schematic bathymetric and hydrographic map of Lake Malawi and locations of water LakeEpilimnion 4 508 459 4 540 4 966 3 733 580 4 98 4 0.7 LakeEpilimnion 1292 3786 2456 6893 905 2486 386 1610 18 707 6431 1324 469 772 46 Residence time (y) Output (Gmol y Riverine Input (%)Input [ 96 96 98 88 75 93 84 Input (Gmol y Mass (Gmol) Residence time computation assumes steady state conditions. Residence time Fig. 1. sampling stations in the LivingstoneMalawi Basin in and Africa. its catchment. Inset box shows location of Lake a Computed from hydrological1996, data 2003), river of (thisstudy, study Table completed completed for 7, by depth Hecky and and Bugenyi, chemical 1992) data and water of column (this rain (Bootsma et al., Table 8. 33 32 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Si (c)

es es of the water column ) P1 station P2 station P3 station -1 P3 station elative. Mn (nmol L Conductivity (µS/cm)

d) d) deviation. eported for P3eported station to clarity due nductivity and dissolved and nductivity µm(0.01 filtrates) Dissolved manganese 0 500 1000 1500 2000 250 255 260 265 270 275 280 0 0 Mn 50 50 100 150 200 250 100 150 200 250

Depth (m) Depth Depth (m) Depth 0

50 100 150 200 250

4408 4407 conductivity and dissolved (0.01 µm ﬁltrates) T (b) = 0 2 O

P3 station P3 . P1 station P2station P3station ) Temperature

-1 Thermocline Sal y temperature,

Si Si (µmol L Dissolved silicon (a) Temperature (°C) Temperature

Si c) c) a) a) b) Oxicline Conductivit 22 22.5 23 23.5 24 24.5 25 25.5 26 0 20 40 60 80 100 120 140 0

0 50

100 150 200 250

) m (

h t p e D

Depth (m) Depth Depth (m) Depth Physical-chemical and hydrodynamic features of the water column Concentration/ Mn. Error bars (only reported for P3 station due to clarity considerations) correspond Depth proﬁles of

2: Depth temperature, Figure profiles (b) (a) of co (c) Si and (d) Mn Si (d) and (c) concentration. bars (only r Error correspondconsiderations), to 2 x 1 standard table Table 1 standard deviation. (d) ×

Figure 3: Physical-chemical Concentration/Temperature/Conductivity scales r are and hydrodynamic featur

Fig. 3. Temperature/Conductivity scales are relative. to 2 and Fig. 2. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 34 TAC alinity) comparison between Ralinity) CAT. and 4409 R (EqnR 1) µmol L-1 Na Ca Mg K Cl Si 0 100 200 300 400 500 600 700 800 0

800 700 600 500 400 300 200 100 CAT (Eqn 2) µmol L-1 µmol 2) (Eqn CAT Major elements (Na, Ca, Mg, K, Si and alkalinity) comparison between R and CAT.

4: Major Figure Mg,Ca, elements Si K, alk and (Na,

Fig. 4.