Exchange between littoral and pelagic waters in a stratified lake due to wind-induced motions: Lake Kinneret, Israel

Marti, Clelia; Imberger, Jörg

doi:10.1007/s10750-007-9243-6

Cited by 35 publications

(47 citation statements)

References 50 publications

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“…Furthermore, the long duration of wind-wave events may result in an exhaustion of the methane stored in the sediments such that toward the end of the wind event only little methane is available for mobilization by the wind waves. Lakes that are characterized by periodic day-night winds (e.g., Lake Kinneret [Marti and Imberger 2008] or Lake Erie [Bolsenga and Herdendorf 1999]), and thus by a periodically occurring wave field, may have a similar pattern of methane emissions from the sediments, compared with shore regions with a ship-wave-dominated wave field. However, lake shorelines that are exposed to surface waves can be expected to be hot spots for high dissolved methane concentrations, especially if these sites are characterized by sediments that are fine grained and rich in organic material (e.g., river estuaries, embayments, or bays).…”

Section: Discussionmentioning

confidence: 99%

Wave‐induced release of methane: Littoral zones as source of methane in lakes

Hofmann

Federwisch

Peeters

2010

Limnology & Oceanography

104

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This study investigates the role of surface waves and the associated disturbance of littoral sediments for the release and later distribution of dissolved methane in lakes. Surface wave field, wave-induced currents, acoustic backscatter strength, and the concentration and distribution of dissolved methane were measured simultaneously in Lake Constance, Germany. The data indicate that surface waves enhance the release of dissolved methane in the shallow littoral zone via burst-like releases of methane during the passage of wave groups. The amount of released methane depends on the surface wave field and the water temperature that controls the methane production in the sediments. The dissolved methane concentrations in the shallow littoral zone were always higher than concentrations in the deep water and open water, while methane concentrations in the epilimnion were typically higher than methane concentrations in the metalimnion and upper hypolimnion. The relatively high epilimnetic methane concentrations in the pelagial can be explained by lateral transport of methane from the littoral zone to the pelagic zone. Littoral zones can thus be an important source of methane in lakes. Methane released by surface waves from littoral sediments may cause elevated near-surface methane concentrations in large areas that enhance the flux of methane at the air-water interface and, thus, the overall methane emissions from lakes to the atmosphere.

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Section: Discussionmentioning

confidence: 99%

Wave‐induced release of methane: Littoral zones as source of methane in lakes

Hofmann

Federwisch

Peeters

2010

Limnology & Oceanography

104

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“…In contrast, horizontal velocities are highest in the middle of the metalimnion for a vertical mode-2 (V2) wave. Evidence for transport by V2 waves was presented by Marti and Imberger (2008), who associated changes in a well-defined turbid layer with changes in the bottom boundary layer as seiches passed over a slope. They concluded that the turbid layer was advected offshore by residual currents.…”

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confidence: 97%

Internal wave‐driven transport of fluid away from the boundary of a lake

Wain

Kohn

Scanlon

et al. 2013

Limnology & Oceanography

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A field experiment was conducted to study transport of fluid from the boundary to the interior of a lake. Tracking of a tracer injected into the metalimnion was combined with measurements of meteorological forcing, internal waves, and temperature microstructure. Seiches of vertical mode 2 and horizontal modes 1 and 2 were initiated after a wind event, and the tracer moved 950 m into the interior after 29.2 h. Four potential mechanisms for spreading of the tracer from the boundary to the interior were considered: intrusions from boundary mixing, horizontal dispersion, advection by seiches, and advection and dispersion driven by internal waves. Some evidence of boundary mixing was observed 0.5 h before the dye injection, when the speed of seiche-driven currents was large, but a model of an intrusion driven by steady input overpredicted the propagation distance by a factor of about two. A one-dimensional model with only dispersion yielded a dispersion coefficient of 0.8 m 2 s 21 , and a one-dimensional model with only advection caused by internal waves predicted the position of the peak concentration and a change in longitudinal variance that was 60% of the measured change. Estimates of dispersion caused by the interaction of vertical diffusion with velocity gradients in the internal wave field are large enough to explain the rest of the spreading and suggest that the transport can be modeled as wave-driven advection and dispersion.

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“…MODIS-derived Kd(490) was slightly higher than GOCI-derived Kd(490) on 8 June 2013, especially in the low value range (see Figure 9). It is clear that most of the pixels of Kd (490) The strength and duration of wind govern the sediment resuspension and the formation of algal blooms [29][30][31][32]. Floating algae will appear on the water surface when the wind speed is low, which would suspend on the water if the wind speed increases [23,[33][34][35].…”

Section: Comparison Of Modis-derived and Goci-derived K D (490)mentioning

confidence: 99%

Semi-Analytical Retrieval of the Diffuse Attenuation Coefficient in Large and Shallow Lakes from GOCI, a High Temporal-Resolution Satellite

Huang

Yao

2017

Remote Sensing

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Abstract:Monitoring the dynamic characteristics of the diffuse attenuation coefficient (K d (490)) on the basis of the high temporal-resolution satellite data is critical for regulating the ecological environment of lake. By measuring the in-situ K d (490) and the remote-sensing reflectance, a semi-analytical algorithm for K d (490) was developed to determine the short-term variation of K d (490). From 2006 to 2014, the data about 412 samples (among which 60 were used as match-up points, 282 for calibrating dataset and the remaining 70 for validating dataset) were gathered from nine expeditions to calibrate and validate the aforesaid semi-analytical algorithm. The root mean square percentage error (RMSP) and the mean absolute relative error (MAPE) of validation datasets were respectively 27.44% and 22.60 ± 15.57%, while that of the match-up datasets were respectively 34.29% and 27.57 ± 20.56%. These percentages indicate that the semi-analytical algorithm and Geostationary Ocean Color Imager (GOCI) data are applicable to obtain the short-term variation of K d (490) in the turbid shallow inland waters. The short-term GOCI-observed K d (490) shows a significant seasonal and spatial variation and a similar distribution to the matching Moderate Resolution Imaging Spectroradiometer (MODIS) which derived K d (490). A comparative analysis on wind (observed by buoys) and GOCI-derived K d (490) suggests that wind is a primary driving factor of K d (490) variation, but the lacustrine morphometry affects the wind force that is contributing to K d (490) variation.

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Exchange between littoral and pelagic waters in a stratified lake due to wind-induced motions: Lake Kinneret, Israel

Cited by 35 publications

References 50 publications

Wave‐induced release of methane: Littoral zones as source of methane in lakes

Wave‐induced release of methane: Littoral zones as source of methane in lakes

Internal wave‐driven transport of fluid away from the boundary of a lake

Semi-Analytical Retrieval of the Diffuse Attenuation Coefficient in Large and Shallow Lakes from GOCI, a High Temporal-Resolution Satellite

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