lake kinneret (israel) and lake biwa (japan)

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ACOUSTIC SIGNATURES OF GASSY SEDIMENTS IN TWO SUBTROPICAL LAKES – LAKE KINNERET (ISRAEL) AND LAKE BIWA (JAPAN) J Tegowski I Ostrovsky M Kumagai M Zamaryka K Ishikawa

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Institute of Oceanography, University of Gdansk, Poland Israel Oceanographic & Limnological Research, Kinneret Limnological Laboratory Lake Biwa Environmental Research Institute, Otsu, Japan Institute of Oceanography, University of Gdansk, Poland Lake Biwa Environmental Research Institute, Otsu, Japan

INTRODUCTION

Methane and carbon dioxide are the most important greenhouse gases. They are produced in organic-rich marine and freshwater sediments. However, the fate of these gases in sediments depends on ambient conditions, their production, dissolution and consumption rate, formation of bubbles, their growth and migration. The main biogeochemical source of methane in sediments is methanogenesis associated with anaerobic bacterial decomposition of the deposited organic matter. Other sources of sedimentary gases are submarine geothermal processes, and infiltration of gases (e.g. nitrogen, argon, helium) dissolved in the near-bottom water [1]. Methane is usually the dominant gas in bottom sediments. Because of low dissolution rate of methane comparatively to carbon dioxide, escape of this gas via ebullition is the most efficient mechanism of methane transport from the shallow sediments to the atmosphere. Quantification and characterization of free gases in surface sediments is an important ecological issue. High spatial heterogeneity of methane distribution does not allow using conventional sampling methods for representative quantification of this sedimentary gas over large areas, such that development of remote-sensing techniques is required to investigate and map gassy sediment distribution. New gas monitoring techniques are also requited for detection and quantification of carbon dioxide escaping from storage caverns, which were artificially created under the sea floor for sequestration of this gas [2]. The presence of gas in sediments causes the changes of their elastic properties, which can be studied by changes of sound attenuation, acoustic wave velocity, and reflective features of the upper sediment layer [1].

Fig.1. Bathymetric maps of Lake Biwa (left) and Lake Kinneret (right). The black lines identify locations of acoustic transects.

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In this paper we study the sound scattering in soft gassy sediments in two deep large lakes - Lake Biwa (Japan) and Lake Kinneret (Israel) (Fig. 1) in order to detect specific reflectance properties that can help mapping the presence of gas below the bottom surface.

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MEASUREMETS ON LAKE BIWA AND LAKE KINNERET

Lake Biwa (Fig. 1) is the largest freshwater lake in Japan located in west-FHQWUDO+RQVKnj,sland. Its 2 surface area is 672 km , maximal depth is 104 m. Lake Kinneret (Sea of Galilee) is the largest 2 freshwater lake in Israel. Lake Kinneret surface area is ~165 km , its maximal depth is varied from 39 to 44 m depending on water level. It provides about 50% of the country's water demand for drinking water and agricultural needs. Sandy sediments dominate the littoral, while soft mud prevails in deeper area [6]. Large fluctuations in Lake Kinneret water level affect the amount of methane bubbles released from bottom sediments to the overlying water. The most intensive emission of methane from the sediments was recorded at the lowest water level and was associated with decreased hydrostatic pressure at the bottom [4]. Methane in Lake Biwa and Lake Kinneret is predominantly biogenic [3,4]. Acoustic samplings of Lake Biwa were carried out using Kaijo KFC-3000 single beam echosounders (Kaijo Corp., Japan) working at 70 kHz (3 dB beam width – 19.8°, pulse width W=0.48 ms). In Lake Kinneret acoustic sampling was done with the Biosonics DE5000 echo sounder operated at 120 kHz (beam width - 6.5°, W=0.2 ms). In both lakes measurements were conducted along standard transects (Fig.1). To determine typical acoustic features of gassy sediments we carried out an echo envelope parameterization using different spectral, wavelet, fractal, statistical and energy parameters [6]. Examples of 70-kHz (Lake Biwa) and 120-kHz (Lake Kinneret) echograms displaying gas outflow from the gas-saturated sediments are shown in Fig. 2.

Fig.2. Echograms displaying gas emission in (a) Lake Biwa (18/12/2010) and (b) Lake Kinneret (15/11/2007). Inclined lines represent the tracks of raising individual gas bubbles. The gas seepages are seen as columns of tracks. Long horizontal noisy trails in the interior part of the water column (~30-m depth in Lake Biwa and ~20-m depths in Lake Kinneret) are acoustic scattering layers associated with the presence of suspended particles, plankton or gas bubbles in the thermocline. The Lake Biwa echogram shows acoustical traces of fishes below 60-65 m depth.

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PARAMETRIC ANALYSIS OF ECHOES FROM SINGLE BEAM ECHOSOUNDER

Parametrical analysis of echo signals has been developed in numerous bottom classification systems [5]. The currently available seabed classification methods either use small set of known echo envelope parameters (eg. VBT, RoxAnn [5]) or large number of unrevealed envelope descriptors (e.g. QTC [5]). In all systems the parameters are used as input sets to supervised or unsupervised classification algorithms (e.g. principal component analysis, fuzzy logic, k-means and neural networks) in order to deliver classified maps of sediments or morphological types of the bottom. In this work we test a set of echo parameters that can be characteristic for sediments containing large amount of gas bubbles. Before parameter computation, the procedures of signals correction were applied. The consecutive envelopes were divided for sets of 20 pulses, where only echoes of energy greater than 75% of maximum pulse energy in the set were analysed. The other procedure compensated dependency of echo shape on the bottom depth following the Caughey and Kirlin algorithm [6] t ' t ˜ H 0 R , where t’ is rescaled time, H0 – reference depth (in our case 10-m), R – distance from transducer to the bottom. The TVG function was established for 30log10R. The computations of parameters were conducted for echo envelopes expressed in logarithmic form of Sv (volume backscattering strength) and in its recalculated linear form. The first group of echo features describes the part of energy coming from the surface scattering – Satt and energy scattered at the sediment volume (echo tail) Sdec. The set of statistical parameters contained envelope autocorrelation length, statistical moments and moment of inertia. Parameters very sensitive for detection of gas bubbles in the bottom were derived from products of Fourier transform, as spectral moments – mr (r = 0-12) and theirs 2 2 combinations - spectral widths H , Q , skewness Jand central frequencyZ: f

³ Z S Z dZ , r

mr

(1)

0

Q2

~ m 3 , Z0 32 ~ m2

m0 m 2 , J m12

m1 , m0

(2)

where S( Z) is power spectral density of echo envelope. The slope E of spectrum was utilized for estimation of fractal dimension in form of D = (5-E)/2 [6]. The normalized spectrum of echo signal Cf was the base of classification parameters defined as relationships of integrals of parts power spectral densities to integral of total spectral density: f Ny

S f1

³C 0

f

df , S f m

1 S f1

1 f Ny m

³C

f

df

(3)

0

were m=2, 4, 8, 16 and fNy is the Nyquist’s frequency. The last large groups of echo envelope parameters are products of wavelet transformation, which was calculated for Coiflet, Daubechies j and Meyer wavelets. Sum of transformation coefficients for chosen dyadic scales a=2 (where j=112) were the base for computation of the wavelet energies Ewav. Other parameter received from wavelet transform was the Hausdorff exponent H and fractal dimension Dwav = 2-H calculated for different wavelets [6]. The listed above echo envelope features were tested for sensitivity to gas in top layer of lake sediments.

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RESULTS AND DISCUSSION

The presence of large amount of gas bubbles in the top layer of bottom sediments can be the main reason of echo shape fluctuations in otherwise homogenous muddy sediments. Gas bubbles trapped in sediments radically change its properties, reflective features [6] and thus affect the echo envelope parameters. Fig. 4 displays a small section of acoustic transect with two bubble seeps and concomitant variations of selected echo envelope parameters computed from signal backscattered from the bottom. Rapid changes in parameter values (see the areas confined by dashed lines on Fig.4, were detected on parts of transect from where the gas bubbles were emitted. Such changes

Fig.4. Lake Biwa echogram displaying the presence of two gas seepages emitted from 90-m depth (upper panel) and respective variations of selected echo envelope parameters (four lower panels). 9 E9.Coif3 is a wavelet energy computed for Coiflet wavelet of order 3 and scale a=2 ; St,16 is the ratio of integrals of parts power spectral densities to integral of total spectral density ratio (Eqn. 3); J is spectral skewness; Sdec is energy scattered at the sediment volume. Data were collected on 17/12/2010. are apparently associated with locations of high abundance of bubbles in soft sediments. Similar changes in parameter values in other sections of transect probably pinpoint the areas of the enlarged abundance of bubbles in sediments without their visible emission to the water column. Similarly, Fig.5 shows good matching of peaks of echo envelope parameters to the location of methane seepage along transect in Lake Kinneret. Fig. 6 presents dependence of (a) spectral width and (b) spectral moment of 7-th order of echo envelopes on depth of bottom and water level in Lake Kinneret. Both parameters achieved their maxima in the deepest part of the lake at the lowest water level, when intensity of gas emission was the largest [4, 6]. This is in good agreement with data presented on Figs. 4 and 5. The obtained results suggest strong relationship between the reflectance properties of sediments and water level (hydrostatic pressure), which controls abundance of gas bubbles in Lake Kinneret soft sediments.

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Fig.5. Lake Kinneret echogram displaying the presence of gas seepage emitted from 30-m depth (upper panel) and respective peaks of echo envelope parameters (five lower panels). E12.Coif3 is a 12 2 wavelet energy computed for Coiflet wavelet of order 3 and scale a=2 ; Q is spectral width; Dfft is fractal dimension; Satt is energy coming from the surface scattering; Min is moment of inertia. Data were collected on 03/04/2006. Thus, the presence and abundance of gas bubbles in sediments is one of the key factors affecting its acoustic features. In case of low water level, the presence of gas bubbles in deeper muddy sediments causes the backscattered signals to be shorter and smoother than the backscattered signals scattered at the bottom sediments that contain small amount of gas bubbles. The small dispersion of the both parameters at the low water level supports the findings mentioned above. The opposite situation was characteristics at the high water level, where signals scattered from the lake floor have long and corrugated tails, as a result of volume scattering. This is a reason of large dispersion of both parameters. The presence of gas in sediments causes large diversity of backscattered signal shapes and respective large dispersion of parameters value. For small abundance of gas bubbles in sediments (i.e. at high water level) the dispersion of this variable is also smaller. For more accurate understanding of the impact of water level fluctuation on acoustic characteristics of bottom sediments further data analyses is needed, because preceding degassing history of bottom sediments may influence the amount and size composition of sedimentary bubbles and thus affect the location-specific acoustic features of sediments.

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Fig.6. Dependences of (a) echo envelope spectral width, Q and (b) spectral moment of 7-th order, m7 on depth of sediment location and water level in Lake Kinneret. The echo envelop variables were computed for backscattered signals recorded along 14 acoustic transects (Fig.1) in 2002 2007 (totally 80 measurements). The averaged data were binned into a 0.5-m depth interval, and each point represents the mean of 10–100 measurements. Thus, comparison of the results obtained on two lakes allowed detecting several parameters, which appear to be sensitive to the presence of free gases in sediments. Our analysis of Lake Kinneret data revealed the effect of bottom location (depth) and water level on acoustic properties of the top layer of sediments and also suggest the importance of long-term acoustic and sedimentological monitoring for better understanding the factors influencing sediment properties under altering ambient conditions (e.g. water level fluctuation, climate change).The obtained information is essential for characterization, mapping and modeling of gassy sediments in various aquatic ecosystems.

ACKNOWLEDGEMENTS This work was supported by grants from the EU FP7 project (Sub-seabed CO2 Storage: Impact on Marine Ecosystems, ECO2, No 265847), the Israel Science Foundation (211/02, 1011/05), the German-Israeli Foundation for Research and Development (No. I-711-83.8/2001), the Israel Water Commissioner (2009, project “Methane ebullition under lower water levels”).

REFERENCES 1. 2. 3. 4. 5. 6.

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A. L. Anderson, L. D. Hampton, Acoustics of gas-bearing sediments, I. Background, J. Acoust. Soc. Am., Vol. 67 (6), 1865-1889, (1980). The EU FP7 project : Sub-seabed CO2 Storage: Impact on Marine Ecosystems (ECO2), EU FP7 project no. 265847, http://www.eco2-project.eu/. J. Dan, T. Kumai, A. Sugimoto, J. Murase, Biotic and abiotic methane releases from Lake Biwa sediment slurry, Limnology 5, 149–154, (2004). I. Ostrovsky, Methane bubbles in Lake Kinneret: quantification and temporal and spatial heterogeneity. Limnol Oceanogr, 48, 1030–1036, (2003). J.T. Anderson, D.V. Holliday, R. Kloser, D.G. Reid, Y. Simard, Acoustic seabed classification of marine physical and biological landscapes. ICES Coop Res Rep 286, 1– 183, (2007). I. Ostrovsky and J. Tegowski, Hydroacoustic analysis of spatial and temporal variability of bottom sediment characteristics in Lake Kinneret in relation to water level fluctuation, GeoMar Letters, 30, 261–269, (2010).