Spectral quantification of nonlinear behaviour of the nearshore seabed and correlations with potential forcings at Duck, N.C., U.S.A

Local bathymetric quasi-periodic patterns of oscillation are identified from monthly profile surveys taken at two shore-perpendicular transects at the USACE field research facility in Duck, North Carolina, USA, spanning 24.5 years and covering the swash and surf zones. The chosen transects are the two furthest (north and south) from the pier located at the study site. Research at Duck has traditionally focused on one or more of these transects as the effects of the pier are least at these locations. The patterns are identified using singular spectrum analysis (SSA). Possible correlations with potential forcing mechanisms are discussed by 1) doing an SSA with same parameter settings to independently identify the quasi-periodic cycles embedded within three potentially linked sequences: monthly wave heights (MWH), monthly mean water levels (MWL) and the large scale atmospheric index known as the North Atlantic Oscillation (NAO) and 2) comparing the patterns within MWH, MWL and NAO to the local bathymetric patterns. The results agree well with previous patterns identified using wavelets and confirm the highly nonstationary behaviour of beach levels at Duck; the discussion of potential correlations with hydrodynamic and atmospheric phenomena is a new contribution. The study is then extended to all measured bathymetric profiles, covering an area of 1100m (alongshore) by 440m (cross-shore), to 1) analyse linear correlations between the bathymetry and the potential forcings using multivariate empirical orthogonal functions (MEOF) and linear correlation analysis and 2) identify which collective quasi-periodic bathymetric patterns are correlated with those within MWH, MWL or NAO, based on a (nonlinear) multichannel singular spectrum analysis (MSSA). (...continued in submitted paper)Comment: 50 pages, 3 tables, 8 figure

Time constraints do not limit group size in arboreal guenons but do explain community size and distribution patterns

To understand how species will respond to environmental changes, it is important to know how those changes will affect the ecological stress that animals experience. Time constraints can be used as indicators of ecological stress. Here we test whether time constraints can help us understand group sizes, distribution patterns and community sizes of forest guenons (Cercopithecus/Allochrocebus). Forest guenons typically live in small to medium sized one-male multi-female groups and often live in communities with multiple forest guenon species. We developed a time-budget model using published data on time budgets, diets, body sizes, climate, and group sizes to predict maximum ecologically tolerable group and community sizes of forest guenons across 202 sub-Saharan African locations. The model correctly predicted presence/absence at 83% of these locations. Feeding-foraging time (an indicator of competition) limited group sizes, while resting and moving time constraints shaped guenon biogeography. Predicted group sizes were greater than observed group sizes but comparable to community sizes, suggesting community sizes are set by competition among guenon individuals irrespective of species. We conclude that time constraints and intra-specific competition are unlikely to be the main determinants of relatively small group sizes in forest guenons. Body mass was negatively correlated with moving time, which may give larger bodied species an advantage over smaller bodied species under future conditions when greater fragmentation of forests is likely to lead to increased moving time. Resting time heavily depended on leaf consumption and is likely to increase under future climatic conditions when leaf quality is expected to decrease

A predictive data-driven approach based on reduced order models for the morphodynamic study of a coastal water intake

For many environmental applications, field measurement techniques are increasingly evolving, resulting in more complex and complete datasets. The statistical analysis of these datasets is challenging, and requires the use of relevant mathematical tools. Furthermore, the access to a richer collection of data offers a new optimistic perspective on data-driven modeling, to complement, or even replace, process-based modeling. The presented work is within the context of a power plant water intake monitoring. The intake channel is subject to massive sediment arrivals, which represents a clogging risk. One of the challenges is therefore to better understand the sediment dynamics observed in the channel, and to characterize their correlation to environmental forcing. The final goal is to proceed to the forecasting of the dynamics using the knowledge of forcing parameters. Luckily, due to monitoring needs, bathymetric measurements of the channel are realized on a regular basis, along with meteorological and hydrodynamic survey. A statistical study is hereby proposed on the basis of this data. Firstly, a Proper Orthogonal Decomposition (POD) is applied to the two-dimensional bathymetric data set, in order to reduce it to a low-dimensional set of time dependent scalar coefficients. The latter are linked to the physical forcings via an adapted statistical model. In this study, a Polynomial Chaos Expansion (PCE) is used for this purpose. Consequently, a data-driven model is proposed, on the basis of a POD-PCE coupling. The proposed step-by-step methodology could also be transposed to other applications

Modelling of coastal evolution on yearly to decadal time scales

There is still no universal model for analysing and predicting coastal evolution and its governing processes on yearly to decadal time scales. Instead, depending on the nature of the problem and project objectives, there is a wide range of models available, each focusing on the problem complex from a specific standpoint. The present paper gives an overview of available numerical model types. A differentiation is made between equilibrium and non-equilibrium model types as well as between longshore uniform and non-longshore uniform model types. These models are discussed in terms of their general assumptions, approaches, and applicability. Most of the model descriptions are supplemented by an illustrative example. In addition, generic issues, such as level of knowledge on different scales, selection of model type on the basis of the nature of the application, the concept of equilibrium, model validation and utilisation are discussed