The use of video imagery to analyse groundwater and shoreline dynamics on a dissipative beach

Groundwater seepage is known to influence beach erosion and accretion processes. However, field measurements of the variation of the groundwater seepage line (GWSL) and the vertical elevation difference between the GWSL and the shoreline are limited. We developed a methodology to extract the temporal variability of the shoreline and the wet-dry boundary using video imagery, with the overarching aim to examine elevation differences between the wet-dry boundary and the shoreline position in relation to rainfall and wave characteristics, during a tidal cycle. The wet-dry boundary was detected from 10-minute time-averaged images collected at Ngaranui Beach, Raglan, New Zealand. An algorithm discriminated between the dry and wet cells using a threshold related to the maximum of the red, green and blue intensities in Hue-Saturation-Value. Field measurements showed this corresponded to the location where the watertable was within 2 cm of the beachface surface. Timestacks, time series of pixels extracted from cross-shore transects in the video imagery, were used to determine the location of the shoreline by manually digitizing the maximum run-up and minimum run-down location for each swash cycle, and averaging the result. In our test data set of 14 days covering a range of wave and rainfall conditions, we found 6 days when the elevation difference between the wet-dry boundary and the shoreline remained approximately constant during the tidal cycle. For these days, the wet-dry boundary corresponded to the upper limit of the swash zone. On the other 8 days, the wet-dry boundary and the shoreline decoupled with falling tide, leading to elevation differences of up to 2.5 m at low tide. Elevation differences between the GWSL and the shoreline at low-tide were particularly large when the cumulative rainfall in the preceding month was greater than 200 mm. This research shows that the wet-dry boundary (such as often used in video shoreline-finding algorithms) is related to groundwater seepage on low-sloped, medium to fine sand beaches such as Ngaranui Beach (mean grain size~0.27 mm, beach slope ~1:70) and may not be a good indicator of the position of the shoreline

Modelling long-term morphodynamic evolution of mega-nourishments

Peer ReviewedPostprint (published version

Multivariate analysis of nonlinearity in sandbar behavior

International audienceAlongshore sandbars are often present in the nearshore zones of storm-dominated micro- to mesotidal coasts. Sandbar migration is the result of a large number of small-scale physical processes that are generated by the incoming waves and the interaction between the wave-generated processes and the morphology. The presence of nonlinearity in a sandbar system is an important factor determining its predictability. However, not all nonlinearities in the underlying system are equally expressed in the time-series of sandbar observations. Detecting the presence of nonlinearity in sandbar data is complicated by the dependence of sandbar migration on the external wave forcings. Here, a method for detecting nonlinearity in multivariate time-series data is introduced that can reveal the nonlinear nature of the dependencies between system state and forcing variables. First, this method is applied to four synthetic datasets to demonstrate its ability to qualify nonlinearity for all possible combinations of linear and nonlinear relations between two variables. Next, the method is applied to three sandbar datasets consisting of daily-observed cross-shore sandbar positions and hydrodynamic forcings, spanning between 5 and 9 years. Our analysis reveals the presence of nonlinearity in the time-series of sandbar and wave data, and the relative importance of nonlinearity for each variable. The relation between the results of each sandbar case and patterns in bar behavior are discussed, together with the effects of noise. The small effect of nonlinearity implies that long-term prediction of sandbar positions based on wave forcings might not require sophisticated nonlinear models

The potential risk induced by climate change in the context of mega-nourishments

Peer ReviewedPostprint (published version

Long-term and large-scale modeling of mega-nourishments

The Sand Engine, ZM (Zandmotor), is a hook-shaped mega-nourishment (21.5 millions m³) located on the Dutch coast with an alongshore length of 2.4 km and an offshore extension of 1 km. The mega-nourishment project was initiated as a coastal protection measure on decadal time scales to maintain the coastline under predicted sea level rise. It follows the philosophy of working in harmony with the forces of nature by taking advantage of the longshore transport as the main distributor of sand along the adjacent coast (Stive et al., 2013). In the present contribution we use the Q2Dmorfo model (van den Berg, et al., 2012) to predict the long-term dynamics of the ZM.Peer ReviewedPostprint (published version

Инновационный фактор совершенствования внешнеэкономической деятельности предприятий Украины: теоретический аспект

Infragravity waves (0.005–0.05 Hz) have recently been observed to dissipate a large part of their energy in the short-wave (0.05–1 Hz) surf zone, however, the underlying mechanism is not well understood. Here, we analyse two new field data sets of near-bed pressure and velocity at up to 13 cross-shore locations in View the MathML source depth on a ≈1:80 and a ≈1:30 sloping beach to quantify infragravity-wave dissipation close to the shoreline and to identify the underlying dissipation mechanism. A frequency-domain Complex Eigenfunction analysis demonstrated that infragravity-wave dissipation was frequency dependent. Infragravity waves with a frequency larger than View the MathML source were predominantly onshore progressive, indicative of strong dissipation of the incoming infragravity waves. Instead, waves with a lower frequency showed the classic picture of cross-shore standing waves with minimal dissipation. Bulk infragravity reflection coefficients at the shallowest position (water depth View the MathML source) were well below 1 (≈0.20), implying that considerable dissipation took place close to the shoreline. We hypothesise that for our data sets infragravity-wave breaking is the dominant dissipation mechanism close to the shoreline, because the reflection coefficient depends on a normalised bed slope, with the higher infragravity frequencies in the mild-sloping regime where breaking is known to dominate dissipation. Additional numerical modelling indicates that, close to the shoreline of a 1:80 beach, bottom friction contributes to infragravity-wave dissipation to a limited extent, but that non-linear transfer of infragravity energy back to sea–swell frequencies is unimportant

Проблеми структурної модернізації регіонального ринку трудових ресурсів АПК в експертній оцінці працівників органів регіонального управління

Barriers and sandbars are ubiquitous natural coastal features, whose variability often determines nearshore morphological evolution. Wave-dominated beach profile evolution results from the interaction between wave non-linearities, wave-breaking induced turbulence, undertow, infragravity motions and swash processes. To explore each of these contributions to the sediment transport, the full-scale Barrier Dynamics Experiment (BARDEX II), performed in the Delta Flume in June 2012, provides a new dataset for the rigorous testing of the performance of beach profile evolution models in the case of steep beaches. This new experiment will improve our knowledge on (1) swash zone processes, including infiltration and exfiltration of water into the sand and subsequent groundwater table response, (2) bore-generated turbulence inducing suspend sediment transport, (3) surfzone sandbar dynamics and (4) overtopping/overwash impact on barrier dynamics. This study aims at testing the ability of the process-based beach profile model 1DBeach in the case of a steep beachface and a predominance of plunging breakers. In this context, we tested the model with a morphological sequence characterised by onshore and subsequent rapid offshore sandbar migration for time-invariant wave forcing and falling tide. A simulated annealing algorithm is used to calibrate the model. In this paper, we discuss the model configuration and associated results, as well as the need of intensive high-frequency full-scale data to further develop and improve process-based models

Observations of velocities, sand concentrations, and fluxes under velocity-asymmetric oscillatory flows

Peer reviewedPublisher PD

Observations on decadal sandbar behaviour along a large-scale curved shoreline

Nearshore sandbars are characteristic features of sandy surf zones and have been observed with a variety of geometries in cross-shore (e.g. location) and longshore direction (e.g. planform). Although the behaviour of sandbars has been studied extensively on spatial scales up to kilometres and timescales up to years, it remains challenging to observe and explain their behaviour on larger spatial and temporal scales, especially in locations where coastline curvature can be prominent. In this paper, we study a data set with 38 years of coastal profiles, collected with alongshore intervals of 50 m, along the 34 km-long curved sandy shoreline of Sylt island, Germany. Sylt's shoreline has an orientation difference of ~20° between the northern and southern half of the island. We found that the decadal coastal profiles on the southern half show features of a low-tide terrace and a sandbar located further from the shoreline (~441 m). On the nothern half, the sandbar was located closer to the shoreline (~267 m) and was less pronounced, while the profiles show transverse bar and rip features. The alongshore planform also differed systematically and significantly along the two island sides. The sandbar on the southern island half, with alongshore periodicity on a larger length scale (~2240 m), was coupled out-of-phase to the shoreline, while no phase coupling was observed for the sandbar with periodicity on a shorter length scale (~670 m) on the northern half. We related the observed geometric differences of the sandbars to the difference in the local wave climate along Sylt, imposed by the shoreline shape. Our observations imply that small alongshore variations in wave climate, due to the increasing shoreline curvature on larger spatial scales, can lead to significant alongshore differences in the decadal evolution of coastal profiles, sandbars and shorelines. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Lt

Non-linear complex principal component analysis of nearshore bathymetry

International audienceComplex principal component analysis (CPCA) is a useful linear method for dimensionality reduction of data sets characterized by propagating patterns, where the CPCA modes are linear functions of the complex principal component (CPC), consisting of an amplitude and a phase. The use of non-linear methods, such as the neural-network based circular non-linear principal component analysis (NLPCA.cir) and the recently developed non-linear complex principal component analysis (NLCPCA), may provide a more accurate description of data in case the lower-dimensional structure is non-linear. NLPCA.cir extracts non-linear phase information without amplitude variability, while NLCPCA is capable of extracting both. NLCPCA can thus be viewed as a non-linear generalization of CPCA. In this article, NLCPCA is applied to bathymetry data from the sandy barred beaches at Egmond aan Zee (Netherlands), the Hasaki coast (Japan) and Duck (North Carolina, USA) to examine how effective this new method is in comparison to CPCA and NLPCA.cir in representing propagating phenomena. At Duck, the underlying low-dimensional data structure is found to have linear phase and amplitude variability only and, accordingly, CPCA performs as well as NLCPCA. At Egmond, the reduced data structure contains non-linear spatial patterns (asymmetric bar/trough shapes) without much temporal amplitude variability and, consequently, is about equally well modelled by NLCPCA and NLPCA.cir. Finally, at Hasaki, the data structure displays not only non-linear spatial variability but also considerably temporal amplitude variability, and NLCPCA outperforms both CPCA and NLPCA.cir. Because it is difficult to know the structure of data in advance as to which one of the three models should be used, the generalized NLCPCA model can be used in each situation