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Climate change and recent water level variability in Patagonian proglaciallakes, Argentina

Andrea I. Pasquini ⁎, Karina L. Lecomte, Pedro J. DepetrisCentro de Investigaciones en Ciencias de la Tierra (CICTERRA/CIGeS) CONICET/Universidad Nacional de Córdoba. Av. Vélez Sarsfield 1611, X5016CGA, Córdoba, Argentina

a b s t r a c ta r t i c l e i n f o

Article history:Received 13 August 2007Accepted 13 July 2008Available online 19 July 2008

Keywords:ENSOAAOglacial retreatspectral analysistrend analysisPatagonia

A long series of lakes (~150) borders the Patagonian Andes (south of ~38°S), most of which are ageomorphologic relict of Pleistocene glaciations. Employing instrumental records, we inspected lake waterlevel departures from seasonal variations in seven proglacial lakes: Lacar, Mascardi, Steffen, Escondido, Puelo,Vinter, and Argentino. Lakes north of ~42°S showmaximum gage (water) level during austral winter months;lakes between ~42° and ~45°S appear transitional; the one lake south of ~50°S (Argentino) shows maximumwater level in early autumn. Most lakes show moderate level fluctuation throughout yearly records and, ingeneral, show heteroscedacity. Furthermore, Hurst exponents reveal persistent behavior (i.e., long-termmemory effect) in all water level series. In most lakes there are no trends in deseasonalized mean andmaximumwater levels (Seasonal Kendall test). Lake Mascardi–Manso River system (mostly fed by melt waterfrom the retreating Manso Glacier) is a contrasting example that shows a decreasing trend during summermonths that we ascribe to the also declining ice volume. Harmonic analysis (Fourier and wavelet transform)of deseasonalized mean and maximum water level time series shows interannual and decadal periodicitiesthat we link to the occurrence of El Niño and/or the Antarctic Oscillation. The associated phase spectrumindicates that there is a ~13-month lag between ENSO occurrences and its effect on anomalous lake waterlevels. Increased snow accumulation during austral winters usually follows summertime El Niño events,which normally result in increased melt water volume that occurs with about one-year delay during thefollowing (austral) spring/summer.

© 2008 Elsevier B.V. All rights reserved.

1. Introduction

Water levels in Andean Patagonian proglacial lakes can showsignificant variability in response to changes in melt water supplyfrom glaciers or snow accumulation, from rainfall or due to cyclicalmodifications in the evapotranspiration regime. Such variabilityresults from the customary seasonal oscillation and from the super-imposed effect of several non-seasonal forcing factors. Furthermore,unusual level fluctuations are often discernible despite the time thatwater resides in the lake, which usually imposes a significantmodulation on the hydrological regime. At any rate, the resultinghigh and/or low frequency oscillations may turn water level fluctua-tions into indicators of changing climate scenarios in the lake's recenthistory. There are a number of examples in the literature that haveused lake water level dynamics to infer ongoing changes in climate(e.g., Kotwicki and Allan, 1998; Arpe et al., 2000; Jöhnk et al., 2004;Kebede et al., 2006). Basic data are obtained from instrumental

records or from satellite (e.g., Topex/Poseidon) altimetry readings(e.g., Mercier et al., 2002; Crétaux and Birkett, 2006).

In Argentina, there are more than 400 lakes with surface areaslarger than 5 km2. A significant proportion – about 150 – is located inPatagonia andmost have a proglacial origin (Quirós,1997). A relativelysmall number are still fed by glaciers, most of which are retreating inapparent accordance with the ongoing global warm spell. In thispaper, we are inspecting trends and harmonic behavior in water leveltime series recorded through gaging registers in seven proglacial lakeslocated in Andean Patagonia. Our main objective is to unveil climaticfluctuations through the significance of forcing factors that determinenon-seasonal fluctuations in the water level of Patagonian lakes.

2. Data and methods

Argentina's Secretaría de Recursos Hídricos supplied the relativelake water level records (http://www.obraspublicas.gov.ar/hidricos),as well as the upper and lower Manso River discharge time series,which were studied by means of statistical techniques such as trendand harmonic analysis. Original daily gage-height readings were usedas basic data, which we have converted to monthly means prior to theanalysis. Therefore, seiches were not detected. We also used time

Global and Planetary Change 63 (2008) 290–298

⁎ Corresponding author. Tel.: +54 351 434 4983x20; fax: +54 351 433 4139.E-mail addresses: apasquini@com.uncor.edu (A.I. Pasquini),

klecomte@com.uncor.edu (K.L. Lecomte), pdepetris@com.uncor.edu (P.J. Depetris).

0921-8181/$ – see front matter © 2008 Elsevier B.V. All rights reserved.doi:10.1016/j.gloplacha.2008.07.001

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series constructedwithmaximum andminimummonthly readings. Inorder to investigate periodicities in mean lake water levels or riverdischarges, we have used deseasonalized monthly mean seriesobtained by subtracting the monthly historical means from monthlydata series.

Fractals are frequently employed to assess order within random-ness in hydrologic systems (e.g., Tavares Lima et al., 2003; Li andZhang, 2007). We initially explored the fractal dimension of thestudied time series through the calculation of the Hurst exponent,which was computed by means of the growth in cumulative rangealgorithm.

To assess the significance of water level trends, we have employedthe seasonal Kendall test (Hirsch et al., 1982) to examine monthlytrends. This is a non-parametric tool that detects monotone trends intime series (e.g., Burn and Hag Elnur, 2002; Yue et al., 2002). This testhas been identified as one of the most robust techniques available touncover and estimate linear trends in environmental data (Hess et al.,2001).

To investigate periodicities in lake water level data, we have usedmonthly arithmetic means, plus maximum and minimum series (i.e.,daily maximum or minimum level for each month). Two harmonictools were applied to these data series; classical Fourier analysis andcontinuous wavelet transform (CWT).

The Fourier transform uses sine and cosine base functions thathave infinite span, is globally uniform in time, and only reveals thepresence of spectral components (Lau and Weng, 1995). For theFourier harmonic analysis, we used the conventional power of 2 FastFourier Transform (FFT) procedure. Both, the amplitude and thefrequency location of the spectral peaks – in the correspondingperiodograms – are detected by means of a cubic spline interpolation.Statistical significance of the largest peaks in the spectra was

determined, after using a Fourier filtering, with peak-based criticallimits method, based on the null hypothesis that postulates a whitenoise signal or Gaussian distribution.

To determine with statistical significance the connection betweenhydrological variables (i.e., lake water level and river discharge) andclimatic indexes (e.g., Southern Oscillation Index or SOI, and theAntarctic Oscillation or AAO), we run a cross-spectrum analysis. Itconsisted in the calculation of the squared coherency and the phaseshift between two time series. The squared coherence, which can beinterpreted as a squared correlation coefficient, is computed bysquaring the cross-amplitude values and dividing by the product ofthe spectrum density estimates for each series. The phase shift iscomputed as tan−1 of the ratio of the quad density estimates over thecross-density estimate, and are measures of the extent to which eachfrequency component of one series leads the other (Shumway andStoffer, 2006).

The CWT examines a time series using mother wavelets that arestretched and translated with a resolution in both frequency and time.This tool offers advantages in comparison with traditional Fourieranalysis because it provides a time-scale localization of a signal. Weuse in our analysis the Morlet CWT that is the most commonlyemployed wavelet based on a Gaussian-windowed complex sinusoid.

The literature offers numerous reviews on the theoretical aspectsof CWT and Fourier analysis (e.g., Lau and Weng, 1995; Torrence andCompo, 1998; Labat, 2005).

3. Regional setting

The hemisphere-scale climate variations that affect erosional andtectonic regimes are the major factors that control morphologicalfeatures in the Andes (Montgomery et al., 2001). In the Patagonian

Fig. 1.Map of Patagonia showing the location of studied proglacial lakes. A north–south profile of the Andes modified fromMontgomery et al. (2001) is included. Frames showwaterlevel annual variability of the lakes, where y-axes are gage lake levels in meters. Note that y-axes scales are variable. Error bars are coefficients of variation.

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Andes (~71°Wand south of ~38°S), glacial dynamics are predominantand the abundant fjords and lakes that characterize this region are ageomorphologic relict of Pleistocene glaciations. Both, glacial and“pluvial” palaeolakes formed along the eastern slope of the southernAndes. A number of proglacial palaeolakes in this region were limitedeastward by moraines deposited by retreating glaciers during the LatePleistocene and Early Holocene time (Tatur et al., 2002). Most modernPatagonian proglacial lakes drain through rivers to the Atlantic Ocean,although there are some systems than drain to the Pacific (e.g., thelower Manso River). A detailed description of the evolution ofdrainage in Patagonia since the Late Pleistocene was presented byTatur et al. (2002).

Limnological and chemical characteristics of a large number ofPatagonian lakes and artificial reservoirs were studied by Quirós(1997) and recently revisited by Diaz et al. (2007). In summary, theyare undisturbed lakes, chemically diluted, silica-dominated, and witha trophic state that ranges from oligotrophic to ultra-oligotrophic.They are classified as warm monomictic, bearing a period of summerstratification (Quirós and Drago, 1985). The total Patagonian lakesurface area is approximately 15,300 km2. Andean Patagonian waterbodies are the largest and deepest glacial lakes in South America.

Patagonia lies between the semi permanent subtropical highpressure and subpolar low pressure zones. Surface air moving towardsthe poles from the subtropical high zone results in westerly windswhich, in the south, shift poleward in summer and equatoward inwinter. A north–south altitudinal cross section of the Andes showsthat, between 39°S and 45°S, the maximum elevation of the Cordillerais relatively constant at ~3300 m a.s.l. After peaking at ~47°S(~4000 m a.s.l.) a pronounced southward descending trend (downto about 2200 m a.s.l.) allows intrusion of Pacific moisture to thesouthern extra Andean Patagonia (Fig. 1). The drainage basins of theeastward-flowing Colorado and Negro rivers (38°–39°S) define thelimit between the subtropical summer rain regime (in the north) andthe mid-latitude winter rain regime that dominates in Patagonia(Mancini et al., 2005). Themain characteristics of Holocene climate forthis region were described by Mancini (1998, 2002).

Finally, we must mention here that the noticeable recession of mostPatagonian glaciers during the 20th century has generally beenassociatedwith the jointeffect of increasing temperature anddecreasingprecipitation (Masiokas et al., 2008, and references therein).

4. Hydrological framework

We have inspected the variability in instrumental records of waterlevel time series in seven proglacial lakes located in AndeanPatagonia: Lacar, Mascardi, Steffen, Escondido, Puelo, Vinter, andArgentino (Fig. 1). They are situated between ~40°S and ~50°S andbetween ~71°W and ~73°W, along the Andes. The Mascardi andArgentino lakes are directly fed by glacial melt water. Table 1 showsthe location, themain characteristics, and the lake level record periodsof the lakes studied.

Lakes to the north of ~42°S (Lacar, Mascardi, Steffen, andEscondido) show maximum gage (water) level during (southern)

winter months, lakes between ~42°S and ~45°S (Puelo and Vinter)appear transitional, whereas the one lake south of ~50°S (Argentino)shows maximum gage level in early (southern) fall (Fig. 1). Most lakesshow moderate level fluctuations throughout the available yearlyrecords and, in general, the records violate homoscedacity (i.e., theyshow unequal variance over time, Fig. 1).

The first group (i.e., those north of 42°S) has the high-water seasonin winter and spring. They appear to be mostly fed by wintertimeprecipitation and spring snowmelt. The transitional group (i.e., lakesPuelo and Vinter) similarly reach minimum levels in late summer andearly autumn but the annual variance is much reduced compared withtheir northern counterparts (Fig. 1). Lake Argentino, in contrast,exhibits remarkable water level uniformity from year to year andhydrological dynamics which are significantly different to itsneighbors to the north: atmospheric precipitation alone determinesmaximum levels in autumn and low water levels in spring.

5. Analysis of lake level time series

We started our study of Patagonian lake water level time series byinspecting their persistence, anti-persistence, or randomness. Hurst(1951) developed an appropriate measurement procedure, known as“re-scaled range analysis” or R/S analysis. This is accomplished bycalculating the persistence measure H (Mandelbrot, 1982). Persistentor super diffusive processes are characterized by HN0.5, Gaussianprocesses have H=0.5, and anti-persistent ones have Hb0.5. H=1would indicate a deterministic behavior.

Hurst exponents determined for all deseasonalized monthly meanwater level series range between 0.69 and 0.91. This means thatanomalous water levels in all lakes have a memory effect, i.e., each islikely to have a positive correlation with preceding unusual values.The same procedure applied to maximum water level time seriesshowed lower values for H, implying that, in such cases, a randomcomponent becomes more important.

To examine monotonic trends in monthly mean lake water levelswe have employed the seasonal Kendall test (Hirsch et al., 1982). Withthe only exception of Lake Mascardi, which is discussed in detailbelow, all lakes fail to show either a significant positive or negativetrend in their historical mean water level time series. We have toemphasize here that this test computes the trend for eachmonth, thusremoving the seasonal component (Hirsch et al., 1982).

Monthly maximum lake water levels examined in all lakes bymeans of this test produced results which are similar to thoseobtained for the mean level series: positive or negative departuresfrom the mean water level do not exhibit a significant trend. Theexception is again Lake Mascardi where the time series of maximumwater levels shows a significant decreasing trend over the period from1970 to 2005. The significance of this trend is discussed in Section 6.

It is interesting to point out that similar trend less behavior isdiscernible in most Patagonian rivers, which show non-significantannual discharge trends by means of Mann–Kendall tests (Pasquiniand Depetris, 2007). The exception in this case is the Negro Riverwhich shows a significant negative trend.

Table 1Name, location, and record period for the employed water level gage stations. The numbers in the second column correspond to stations in Fig. 1. Zmean and Zmax are mean andmaximum lake depth, respectively

Lake Key in Fig. 1 Gage station Latitude(S)

Longitude(W)

Altitude(m a.s.l.)

Area(km2)

Volume(km3)

Zmean

(m)Zmax

(m)Record period

Lacar 1 San Martín 40° 14′ 71° 30′ 625 49 8.1 166 277 1969–2005Mascardi 2 Central Frey 41° 20′ 71° 34′ 790 39.2 4.4 111 218 1970–2005Steffen 3 Muelle 41° 30′ 71° 32′ 525 13 0.3 47 77 1976–2005Escondido 4 El Foyel 41° 41′ 71° 37′ 440 – – – – 1977–2005Puelo 5 Lago Puelo 42° 10′ 71° 40′ 150 44 4.9 111 180 1961–2005Vinter 6 Vinter 43° 58′ 71° 33′ 936 57 – – 300 1993–2005Argentino 7 Calafate 50° 19′ 72° 15′ 187 1466 220 150 500 1992–2005

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We have studied deseasonalized monthly mean and maximumwater level records by means of Fourier spectral analysis and theresults are listed in Table 2. The mean water level time series in theLacar, Steffen, Escondido, Puelo, and Vinter lakes mostly show a near-decadal periodicity (between 7 and 12 yr). Only Lake Lacar exhibits aninterannual oscillation in its deseasonalized mean water level record.Fourier analysis of maximumwater level time series for all lakes showan interannual oscillation in addition to the near-decadal one. Sincethe maximum water level time series were not deseasonalized, thecorresponding Fourier analyses show a strong annual component thatwe have omitted from the results (Table 2). Furthermore, theperiodicities determined from the maximum water level seriesreach a higher level of significance than do mean water levels(Table 2). Interannual or ENSO-like frequencies have also beenobserved for the varved record from proglacial Lake Frías, near LakeMascardi (Aristegui et al., 2007).

To analyze the time-scale localization of the periodical signals inthe lake level series we used continuous wavelet transform (CWT)analysis. Fig. 2 shows the real part of the continuous Morlet waveletspectra for the two longest deseasonalized mean water level timeseries: lakes Lacar and Puelo. It can be seen in Fig. 2a that significantinterannual and near-decadal periodic oscillations are present at LakeLacar. The first is persistent throughout the entire record period,whereas the near-decadal signal is stronger since the beginning of the1980s. The Lake Puelo wavelet spectrum (Fig. 2b) shows a near-decadal signal, which is stronger in the second half of the recordperiod, again since the early 1980s. A faint interannual oscillation(~30 months) appears in the record around 1980 and becomes moreprominent during the last 10 recorded years.

To investigate the connection between water level periodicities,the SOI and the Antarctic Oscillation (AAO) we performed a squaredcoherency test. In general, significant results (pb0.05) are present inmost lake records at both interannual and near-decadal frequency(Table 2). Furthermore, squared coherency is higher than 0.78 in alllakes. The examination of the associated phase spectrum for SOI andmaximum water levels at Lake Puelo revealed a phase lag of about13 months: the occurrence of El Niño events precedes maximumwater levels at the Puelo. To illustrate this assertion, Fig. 3 shows the

nine-point moving average smoothing of Lake Puelo maximumwaterlevel series, plotted with a 13-month lag, and the SOI. In Fig. 3, over65% of El Niño occurrences (negative SOI values) correspondwith highlake water levels.

6. Two special cases: Mascardi and Argentino lakes

In as much as both drainage basins host Pleistocene glaciers, meltwater is a significant water source for Mascardi and Argentino lakes.This appears as the main factor that places them into a specialcategory amongst the Patagonian proglacial lakes considered here.They exhibit, as well, other special features that we are now analyzing.

6.1. Lake Mascardi

LakeMascardi (e.g., Markert et al., 1997; Román-Ross et al., 2002) isa conspicuous feature of the Manso River drainage basin (Fig. 4). Theupper Manso River discharges (mean flow ~11 m3 s−1) into LakeMascardi (~790m a.s.l.) and has its headwaters in theManso glacier orVentisquero Negro (at Mount Tronador, 3554 m a.s.l.), which is areceding regenerated glacier (Fig. 4). The lake has an area of 39.2 km2

(23 km long, by about 4 km wide) and its maximum depth is 218 m.The outfall at Los Moscos bears the name lower Manso River. It passesinto Lake Hess and then flows towards the southeast receiving anumber of tributaries before reaching Lake Steffen (Fig. 4). MansoRiver mean discharge increases significantly after leaving Lake Steffen(~67 m3 s−1). Thereafter it flows westward, and crosses the Andes toreach a Pacific outfall.

Table 2Fourier spectral analysis for deseasonalized monthly mean and maximum lake waterlevels

Key inFig. 1

Lake N(months)

Fourier significantperiodicities(period in years)

Squared coherence*(period in years)

Deseasonalizedmonthly meanwater level

Maximummonthlywaterlevel

Maximummonthlywater levelvs. SOI

Maximummonthlywater levelvs. AAO

1 Lacar 435 2.5* 10*** 2.1 102.5

10.6* 3.410

3 Steffen 341 10.7** 2.5** 2.7 153.8***5.9*** 1010.6***

4 Escondido 340 7.1** 2.2*3.2** 2 26*** 4.2 5.310*** 14 14

5 Puelo 533 12.7*** 2.4*4.7* 27.7*** 2.4 2.412.2*** 12 3.817.1***

6 Vinter 154 7.1** 3.5**

*pb0.05, **pb0.01, ***pb0.001.

Fig. 2. Real part of the continuous Morlet wavelet spectra for water levels in Lacar(a) and Puelo (b) lakes. Light colors in the wavelet spectra correspond to high power.(For interpretation of the references to color in this figure legend, the reader is referredto the web version of this article.)

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Climate in the region is cold and humid, with a mean annualtemperature of ~7 °C in the lake area. Abundant rainfall, snowfall(between May and July) and glacier melt water feed the system. Thereis a marked west to east decreasing precipitation gradient betweenMount Tronador (~27 cm yr−1) and Lake Mascardi (~14 cm yr−1).

We have inspected the historical trend and periodicity in MansoRiver discharge series, as well as in lakes Mascardi and Steffen waterlevels (Fig. 4). Monthly mean discharge series of Manso River wereanalyzed in three gaging stations: the upper Manso in Mascardi(1969–1991 record period), and lower Manso River in Los Moscos(1946–2004 record period) and in Los Alerces (1951–2004 recordperiod). Fig. 5a and c shows the upper and lower Manso River

discharge series as well as the water level series in Lake Mascardi(Fig. 5b). The covariance shown by upper (Fig. 5a) and lower Manso(Fig. 5c) hydrographic records indicates that the passage through LakeMascardi (Fig. 5b) does not alter significantly the Manso River regime.

Lake Mascardi appears to be the only Patagonian proglacial lakethat shows a significant decreasing trend in water level time series.Seasonal Kendall trend analysis (Table 3, Kendall τ coefficients), showsa significant negative trend for the upper Manso River, Lake Mascardiwater levels, and the lower Manso River for the end of the australspring and summer (November through February–March). The lowerManso River maintains its significant negative trend until May (at LosMoscos discharge-measuring station). It is interesting to underline

Fig. 3. SOI values and maximum water level series of Lake Puelo plotted with a 13-month lag. Time series correspond to monthly averages smoothed using a nine-point movingaverage. Arrows indicate the occurrence of El Niño events that match with high-water levels (13 months delayed).

Fig. 4. Schematic map of Mascardi–Manso hydrological system. Gage stations of lake water level and river discharge are indicated (framed).

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here that the significant decrease in Manso River discharge volumeand Lake Mascardi water level is occurring in austral summer,precisely when the Ventisquero Negro melt water is the main water

source in the drainage system and there is a limited rainfallcontribution to the budget. We must add that significant hydro-climatic changes have occurred in northwestern Patagonia during the

Fig. 5. Time series of hydrological variables in the Mascardi–Manso system: a) monthly mean discharge of upper Manso River (at Mascardi gaging station); b) Lake Mascardi waterlevel; c) monthly mean discharge of lower Manso River (at Los Moscos gaging station). Insets in the figure are the annual mean variations of the corresponding variable.

Table 3Seasonal Kendall test results for Mascardi and Steffen lake water level series, and upper and lower Manso River discharge. Numbers in bold are statistically significant. Positive valuesindicate increasing trend, negative ones indicate decreasing trend

River /lake Station N(months)

τ coefficients Allcombined

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Upper Manso R. Mascardi 261 −3.05** −2.71** −0.71 0.61 −1.06 −0.39 −1.72* −1.41 −0.65 −1.24 −2.40** −2.63** −3.49***Lake Mascardi Central Frey 420 −3.69*** −4.30*** −3.15*** −1.09 −1.72 −1.04 −0.49 −1.26 −0.66 −1.00 −1.82* −2.51** −3.03**Lower Manso R. Los Moscos 695 −3.2*** −2.99** −1.87* −1.29* −2.43** 0.35 0.47 −0.86 0.25 0.32 −2.25* −1.95* −1.81*Lower Manso R. Los Alerces 636 −2.59** −2.27* −1.01 −0.57 −1.75* 0.32 −0.77 −1.01 0.5 0.31 −1.55 −1.56 −2.53**Lake Steffen Muelle 341 0.30 0.39 2.14* 1.27 −0.10 −0.25 0.93 −0.23 0.39 0.63 −0.51 −0.15 0.21

*pb0.05, **pb0.01, ***pb0.001.

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20th century (Masiokas et al., 2008). Linear trends in regionallyaveraged annual and seasonal temperature and precipitation recordsindicate that mean temperature has increased significantly, whereasautumn–winter rainfall and snowfall decreased over the 1912–2002time interval resulting in a continuous decrease of the glacier volumeand, hence, a decreasing river runoff.

It is also significant that this negative trend seems to fade awayas thesystem leaves Lake Hess and receives other tributaries, reinforcing thenotion that the process is restricted to the effect of reduced melt water.Table 3 shows theprogressive lossof statistical significancedownstream,terminating in the disappearance of the negative trend in Lake Steffen.

We have used the time series of minimum annual discharges at theupper Manso River gaging station to further examine the statisticaldistribution of such data. Fig. 6 shows that this data fit fairly well to anormaldistribution, althoughsomedepartures fromthe ideal distributionare discernible at the tails. This is particularly evident at the lowdischargeend, which appears to be significantly lower than the distributionpredicts. Furthermore, extreme value theory (Haan et al., 1994) showedthat the return period of a low flow regime (equivalent to the meandischarge minus two standard deviations or ~3.6 m3 s−1) is ~55 yr.

We examined the Fourier frequency spectra of mean, maximum,and minimum water level time series at Lake Mascardi and Manso

River (Table 4). Significant frequency peaks reach a high level ofconfidence in the analysis of maximumwater level time series. Meanand minimum water levels, however, are less revealing. Inspection ofTable 4 shows that: a) there are outstanding significant frequencies atinterannual (between ~2 and 6 yr) and decadal ranges in themaximum level time series; b) mean water level time series onlyshow significant oscillations at the interannual frequencies; c)minimum water level time series are similar to mean water levels.The upper Manso River deseasonalized discharge series is short – incomparison with the other Manso River series – and, hence, we didnot consider it here. The lower Manso River Fourier analysis has asignificant peak at ~7 yr in both stations.

The maximum water level time series produced a significantsquared coherency with SOI at interannual frequencies: it showssignificant (pb0.05) peaks at ~2.5, and ~7 yr. Results from the squaredcoherence analysis performed with AAO were not conclusive.

6.2. Lake Argentino

Lake Argentino (Fig. 7) is another Patagonian example of aproglacial lake, which is the geomorphologic result of the 26glacial–interglacial cycles that occurred during the Quaternary. It isdirectly fed by rivers, streams, and melt water supplied by severalglaciers (e.g., Perito Moreno, Viedma, Uppsala, Ameghino, Onelli). Thelake is located at ~50°S, 73°W, at an altitude of ~190 m a.s.l., has asurface area of ~1500 km2 and a volume of ~220 km3 (Table 1). Themain climatic characteristics of the area were described elsewhere(Depetris and Pasquini, 2000, and references therein).

The Perito Moreno glacier snout dams the southernmost branch(Brazo Rico) of Lake Argentino with periodic recurrence. This causeswater level to rise at Brazo Rico, to the east of the ice dam. This barrierusually lasts for about 2 yr and then collapses catastrophically. Theexcess water stored at Brazo Rico floods Lake Argentino's main waterbody and the Santa Cruz River (Depetris and Pasquini, 2000). Suchextraordinary natural phenomenon made Lake Argentino a world-renowned geographical feature and a tourist attraction.

The Argentino, with headwaters in the Southern Andean IceFieldor SAI (~50°S), is more exposed to the influence of Pacific climate thanits northern neighbors because the Andean Cordillera looses heighttowards the south (e.g., Montgomery et al., 2001) allowing circulationof Pacific moisture. Within the context of the recent evolution ofvolume changes observed in the Pio XI glacier (located on the Pacificseaboard of the SAI), Rivera and Casassa (1999) commented on the

Fig. 6. Cumulative probability distribution of minimum annual flow for the Manso Riverat Los Moscos gage station.

Table 4Fourier analysis for Lake Mascardi water level and Manso River discharge series. Mean lake levels and river discharges have been deseasonalized

Lake/river N(months)

Fourier significant periodicities Squared coherence*

Period in years Period in years

Monthly water level/mean discharge

Monthly water level Maximum waterlevel/meandischarge vs. SOI

Maximum Minimum

L. Mascardi 420 2.5** 2.2* 2.2** 26** 3.2** 3.3*** 2.614* 4.7*** 4.75*** 7

6*** 6***10.6***

Lower Manso R. (in Los Moscos) 695 7.1* – – 2.12.56.612

Lower Manso R. (in Los Alerces) 636 7** – – 2.54.77.212

*pb0.05, **pb0.01, ***pb0.001.

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contrasting behavior of the Perito Moreno and Uppsala glaciers. Theformer have not retreated in the recent past (i.e., since the beginningof the 20th century) whereas the latter shows a retreat of tens ofkilometres during the same time span.

In view of the short length of thewater level data series (12 yr), andconsidering the effect of the glacier-triggered closure-rupturesequence, we did not examine the trend in the lake water level dataseries. We have, however, examined the harmonic behavior of theSanta Cruz River in earlier contributions (Depetris and Pasquini, 2000;Pasquini and Depetris, 2007).

7. Concluding comments

Inspection of the mean annual water level variability in the set ofstudied lakes shows a latitudinal variation associated with predominantclimatic factors. Lake Lacar for example, thenorthernmost lake in the set,shows minimum water height at the end of the austral summer andbeginning of autumn, because of reduced rainfall. Increased winterprecipitation and spring/early summer snowmelt clearly raises lake levelto a maximum at this time. The instrumental record shows significantwater level variability for each individual month. This characteristic isquite noticeable in other lakes (e.g., lakes Escondido andVinter), where itis probably more dependent on local forcing factors.

In contrast, the southernmost lake in the set, the Argentino, showsmaximum water level in late summer/early autumn as a jointconsequence of increased precipitation and melt water. Because of apronounced modulation, monthly water level variability is restrictedto a narrow band around the mean yearly limnograph (Fig. 1). Clearly,the extensive lake surface area and a very large volume of storedwatercontrol a long-lasting residence time for the lake water and define theobserved modulation.

Moreover, monthly water level variability shows a surprisinguniformity that appears to be a direct effect of westerly-driven Pacificmoisture. We also feel that this factor determines that, after icedamming of the lake, the collapsing of the Perito Moreno snout oftenoccurs in March.

Most lakes in the set studied (i.e., Lacar, Steffen, Escondido, Puelo,and Vinter) do not exhibit a significant trend in either deseasonalizedmonthly mean or maximumwater level time series. The lakes that do

show identifiable trends are those for which a direct influence ofglaciers can be demonstrated: lakes Mascardi and Argentino. SeasonalKendall tests show that Lake Mascardi has a clear summertimenegative trend that we have interpreted as an indication that meltwater is decreasing because the ice volume of theManso glacier is alsomarkedly diminishing.

These lakes, however, show a clear interannual or near-decadalsignature, which appears to be significantly coherent with the SOI.Recent studies have revealed a growing body of evidence that relatesthe role played by the tropical ENSO with the high southern latitudetropospheric circulation (Fogt and Bromwich, 2006). Furthermore, ithas been argued that the AAO could also affect hydrological variablesin Patagonia. However, the individual forcing effect of these variableson water level fluctuations of Patagonia's lakes could not berecognized because – as was recently established by Bertler et al.,2006 – they appear to be correlated and this turns indistinguishablethe significance of each mechanism. At any rate, the effect of theENSO/AAO is discernible in Patagonian lakes although it does notseem to induce a trend in their respective water levels. Following ouranalysis, water level gage height in Patagonia's proglacial lakes showsthat strong decadal and interannual oscillations appear to beteleconnected with the ENSO. This is supported by coherenceanalysis, which shows a ~13-month time lag between ENSOoccurrences and lake water level positive anomalies. It follows thatENSO phenomena (December–January) determine increased snowaccumulation the following months, mostly along the uppermostAndes. The resulting excess snow then supplies the added watervolume that determines increasedwater levels in the lakes during thefollowing spring–summer (October–February). Such a delayedmechanism was previously observed in the Perito Moreno glacier(Depetris and Pasquini, 2000).

Acknowledgements

We acknowledge the financial support of Argentina's ConsejoNacional de Investigaciones Científicas y Técnicas (CONICET) andFONCYT (PICT 7-25594). We are also grateful to the UniversidadNacional de Córdoba for sustained assistance. A.I.P., K.L.L and P.J.D. aremembers of CONICET's CICyT.

Fig. 7. Map of Lake Argentino showing the location of Perito Moreno and other glaciers located in the drainage basin.

297A.I. Pasquini et al. / Global and Planetary Change 63 (2008) 290–298

Author's personal copy

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