Development of a modelling methodology for simulation of long-term morphological evolution of the southern Baltic coast

Abstract

The Darss-Zingst peninsula at the southern Baltic Sea is a typical wave-dominated barrier island system which includes an outer barrier island and an inner lagoon. The formation of the Darss-Zingst peninsula dates back to the Littorina Transgression onset about 8,000 cal BP. It originated from several discrete islands, has been reshaped by littoral currents, wind-induced waves during the last 8,000 years and evolved into a complex barrier island system as today; thus, it may serve as an example to study the coastal evolution under long-term climate change. A methodology for developing a long-term (decadal-tocentennial) process-based morphodynamic model for the southern Baltic coastal environment is presented here. The methodology consists of two main components: (1) a preliminary analysis of the key processes driving the morphological evolution of the study area based on statistical analysis of meteorological data and sensitivity studies; (2) a multi-scale high-resolution process-based model. The process-based model is structured into eight main modules. The two-dimensional vertically integrated circulation module, the wave module, the bottom boundary layer module, the sediment transport module, the cliff erosion module and the nearshore storm module are realtime calculation modules which aim at solving the shortterm processes. A bathymetry update module and a long-term control function set, in which the 'reduction' concepts and technique for morphological update acceleration are implemented, are integrated to up-scale the effects of short-term processes to a decadal-to-centennial scale. A series of multi-scale modelling strategies are implemented in the application of the model to the research area. Successful hindcast of the coastline change of the DarssZingst peninsula for the last 300 years validates the modelling methodology. Model results indicate that the coastline change of the Darss-Zingst peninsula is dominated by mechanisms acting on different time scales. The coastlines of Darss and the island of Hiddensee are mainly reshaped by long-term effects of waves and longshore currents, while the coastline change of the Zingst peninsula is due to a combination of long-term effects of waves and short-term effects caused by wind storms.

A multi-scale hybrid long-term morphodynamic model for wave-dominated coasts

“…Without a parallel computational structure process-based long-term modeling of coastal morphology is extremely time-consuming even on modern high-performance computers, and thus not realistic to serve as a tool for research. In an application on the Darss-Zingst Peninsula (Zhang et al, 2010) with a computational grid of 242× 162 and a maximum spatial resolution of 100 m × 100 m, the total time needed in a serial coupling model for a simulation of 300 years is about 106 h (on a computer platform with Intel(R) Xeon(R) CPU E5530@2.40 GHz and a memory of 32 GB). The calculation efficiency will be hardly acceptable if such a serial coupling model is applied to a millennial-scale simulation, in which a large number of sensitivity runs are needed.…”

“…(1) a 2DH (two-dimensional vertically integrated) circulation module based on shallow-water equations, (2) a wind-induced wave module based on momentum conservation equations, (3) a bottom boundary layer (BBL) module based on the Grant-Madsen formulation (Grant and Madsen, 1979), (4) a sub-aqueous sediment transport module based on a processbased formulation of suspended transport of cohesive and noncohesive sediment and a behavior-oriented formulation of bed-load sediment transport, (5) a cliff erosion module based on a behavior-oriented formulation (Zhang et al, 2010), (6) a nearshore storm module based on the XBeach model (Roelvink et al, 2009), (7) a bathymetry update module based on the technique of morphological update acceleration (Roelvink, 2006) and approaches for maintaining the computational stability, and (8) a control function set for up-scaling of the short-term effects.…”

“…(5) are solved with finite differences using a first order upwind scheme with the bed elevations at the old time step and the corresponding wind shear velocities at the new time step. Because morphological update acceleration is applied (Zhang et al, 2010), a variable morphological factor f is used in the morphology update. Eq.…”

“…Promising results were obtained in the model application to a hindcast of 300 years' morphological evolution of the Darss-Zingst peninsula in the southern Baltic Sea. Long-term residual effects of waves as well as short-term effects of storms are revealed as the dominant factors driving the morphological evolution of the research area during the last several centuries (Zhang et al, 2010). Although good agreement between simulation results and measured data is shown for the major part of the coast, some key areas such as the spit and the newlyformed barrier are not satisfactorily reproduced.…”

“…Recently Zhang et al (2010Zhang et al ( , 2011a presented a modeling methodology for long-term morphological evolution of wavedominated coasts based on a multi-scale morphodynamic model. The model consists of 8 modules which calculate the processes of interest at different scales.…”