Seiche

Abstract: Five strong paleoseismic events were recorded in the past 15 k.y. in a series of slump deposits in the subsurface of Lake Lucerne, central Switzerland, revealing for the first time the paleoseismic history of one of the most seismically active areas in central Europe. Although many slump deposits in marine and lacustrine environments were previously attributed to historic earthquakes, the lack of detailed three-dimensional stratigraphic correlation in combination with accurate dating hampered the use of multiple slump deposits as paleoseismic indicators. This study investigated the fingerprint of the well-described A.D. 1601 earthquake (I = VII–VIII, Mw ∼ 6.2) in the sediments of Lake Lucerne. The earthquake triggered numerous synchronous slumps and megaturbidites within different subbasins of the lake, producing a characteristic pattern that can be used to assign a seismic triggering mechanism to prehistoric slump events. For each seismic event horizon, the slump synchronicity was established by seismic-stratigraphic correlation between individual slump deposits through a quasi-three-dimensional high-resolution seismic survey grid. Four prehistoric events, dated by accelerator mass spectrometry, 14C measurements, and tephrochronology on a series of long gravity cores, occurred at 2420, 9770, 13,910, and 14,560 calendar yr ago. These recurrence times are essential factors for assessing seismic hazard in the area. The seismic hazard for lakeshore communities is additionally amplified by slump-induced tsunami and seiche waves. Numerical modeling of such tsunami waves revealed wave heights to 3 m, indicating tsunami risk in lacustrine environments.

Abstract: [1] A numerical model was developed for the prediction of the density stratification of lakes and reservoirs. It combines a buoyancy-extended k-� model with a seiche excitation and damping model to predict the diffusivity below the surface mixed layer. The model was applied to predict the seasonal development of temperature stratification and turbulent diffusivity in two medium-sized lakes over time periods ranging from 3 weeks to 2 years. Depending on the type of boundary condition for temperature, two or three model parameters were optimized to calibrate the model. The agreement between the simulated and the observed temperature distributions is excellent, in particular, if lake surface temperatures were prescribed as surface boundary condition instead of temperature gradients derived from heat fluxes. Comparison of different model variants revealed that inclusion of horizontal pressure gradients and/or stability functions is not required to provide good agreement between model results and data. With the aid of uncertainty analysis it is shown that the depth of the mixed surface layer during the stratified period could be predicted accurately within ±1 m. The sensitivity of the model to several parameters is discussed. INDEX TERMS: 4211 Oceanography: General: Benthic boundary layers; 4255 Oceanography: General: Numerical modeling; 4568 Oceanography: Physical: Turbulence, diffusion, and mixing processes; KEYWORDS: lake, turbulence model, seiche, stratification, simulation, turbulence kinetic energy

Abstract: The influence of spatial and temporal variations in wind forcing on the circulation in lakes is investigated using field data and the three-dimensional Estuary and Lake Computer Model (ELCOM) applied to Lake Kinneret. Lake Kinneret field data from six thermistor chains and eight wind anemometers deployed during July 2001 are presented. Internal wave motions are well reproduced by the numerical model when forced with a spatially uniform wind taken from a station near the lake center; however, simulated seiche amplitudes are too large (especially vertical mode 2) and lead observations by 3‐10 h (for a 24-h period wave) at different locations around the lake. Consideration of the spatial variation of the wind field improves simulated wave amplitude, and phase error at all stations is reduced to less than 1.5 h. This improvement is attributable to a better representation of the horizontally averaged wind stress and can be reproduced with a spatially uniform wind that has the same horizontally averaged wind stress as the spatially varying wind field. However, a spatially varying wind field is essential for simulating mean surface circulation, which is shown to be predominantly directly forced by the surface-layer‐averaged wind stress moment.