Modeling storm surges in the Belgian coastal area: preliminary work

Water Qualit

Modelling tides and storm surges on the European continental shelf

Water Qualit

Hydrodynamic modelling of the tide propagation in a tropical delta: overcoming the challenges of data scarcity

Hydrodynamic

On the relative role of abiotic and biotic controls in channel network development: insights from scaled tidal flume experiments

Tidal marshes provide highly valued ecosystem services, which depend on variations in the geometric properties of the tidal channel networks dissecting marsh landscapes. The development and evolution of channel network properties are controlled by both abiotic (dynamic flow–landform feedbacks) and biotic processes (e.g. vegetation–flow–landform feedbacks). However, the relative role of biotic and abiotic processes, and under which condition one or the other is more dominant, remains poorly understood. In this study, we investigated the impact of spatio-temporal plant colonization patterns on tidal channel network development through flume experiments. Four scaled experiments mimicking tidal landscape development were conducted in a tidal flume facility: two control experiments without vegetation, a third experiment with hydrochorous vegetation colonization (i.e. seed dispersal via the tidal flow), and a fourth with patchy colonization (i.e. by direct seeding on the sediment bed). Our results show that more dense and efficient channel networks are found in the vegetation experiments, especially in the hydrochorous seeding experiment with slower vegetation colonization. Further, an interdependency between abiotic and biotic controls on channel development can be deduced. Whether biotic factors affect channel network development seems to depend on the force of the hydrodynamic energy and the stage of the system development. Vegetation–flow–landform feedbacks are only dominant in contributing to channel development in places where intermediate hydrodynamic energy levels occur and mainly have an impact during the transition phase from a bare to a vegetated landscape state. Overall, our findings suggest a zonal domination of abiotic processes at the seaward side of intertidal basins, while biotic processes have an additional effect on system development more towards the landward side

Vegetation controls on channel network complexity in coastal wetlands

Channel networks are key to coastal wetland functioning and resilience under climate change. Vegetation affects sediment and hydrodynamics in many different ways, which calls for a coherent framework to explain how vegetation shapes channel network geometry and functioning. Here, we introduce an idealized model that shows how coastal wetland vegetation creates more complexly branching networks by increasing the ratio of channel incision versus topographic diffusion rates, thereby amplifying the channelization feedback that recursively incises finer-scale side-channels. This complexification trend qualitatively agrees with and provides an explanation for field data presented here as well as in earlier studies. Moreover, our model demonstrates that a stronger biogeomorphic feedback leads to higher and more densely vegetated marsh platforms and more extensive drainage networks. These findings may inspire future field research by raising the hypothesis that vegetation-induced self-organization enhances the storm surge buffering capacity of coastal wetlands and their resilience under sea-level rise.</p

Finite element modeling of sediment dynamics in the Scheldt

A densely populated watershed and numerous industrial activities, are responsible for the Scheldt Estuary and River to be highly polluted. Water and sediment circulation are major processes contributing to the global dynamics of the various pollutions. The objective of this thesis is to develop a numerical tool in order to make possible simulations of those environmental issues. The finite element technique enables the use of unstructured meshes, so that the spatial resolution can vary widely over the domain. In our implementation, we combine 1D equations for rivers and 2D equations for estuaries and seas. Nevertheless, the tidal river network, the estuary and the adjacent coastal zone are simulated in the same framework. The Scheldt Estuary features large shallow areas that are periodically emerging at low tide. This phenomenon is a numerical challenge in estuarine modeling. A flux-limiting method has been developed, which modifies the discrete form of the governing equations, in order to prevent the water surface to go down where it is already very low. The last contribution is the development of the sediment transport module. Its calibration pointed out the influence of suspended sediment concentration, salinity and biology on flocculation, as the influence of the biology on the erodibility of bottom sediments. Our 1D-2D model, with a very competitive computer cost, appears to provide results as accurate as those from more complex, three-dimensional tools, traditionally deemed indispensable in sediment transport modeling. Our approach appears therefore to be very promising for long-term environmental simulations of the Scheldt.(FSA 3) -- UCL, 201

A Morphological Algorithm for the Detection of Linear Contrails

International audienceThe climate impact of aviation can be separated into CO2 and non-CO2 effects, with the latter being potentially larger than the former. In thiscontext we are more specifically interested in condensation trails (hereafter contrails) and induced cirrus. Monitoring contrail formation and evolution isnecessary to understand their radiative effects and help the aviation industry to transition towards a more sustainable activity. Current research aimed atdetecting contrails is mostly based on geostationary satellite images because they allow to follow the contrail over a long period of time. However a majorshortcoming is that the formation phase of the contrails cannot be detected and larger, but older, contrails cannot always be attributed to the flightsthat produced them. To circumvent the problem that satellite images do not have a sufficient resolution to observe the contrail formation phase, weuse a ground-based hemispheric camera with a two-minute sampling rate as a complementary source of information. As a first step, we have developeda traditional morphological algorithm that will help preparing a sufficiently large labelled database as required to train a deep-learning algorithm. Ouralgorithm aims to detect whether each aircraft that passes in the field of view of the camera (as monitored from an ADSB radar) produces a contrail or not. We are thus able to relate contrail formation and evolution with aircrafttype, flight altitude and weather conditions. We start by focusing on the young linear contrails that appears just behind the aircraft. We also considerall weather conditions except completely cloudy conditions that prevents contrails to be observed. The algorithm combines various morphologicaltreatments to binarise the image and a linear Hough transform to identify straight lines in a direction close to the aircraft’s trajectory. Its performance is evaluated against a database that was manually annotated consisting of 400 images with 407 contrails. We find that our algorithm has a specificityof 97%, i.e. there are few false detections, but its sensitivity is about 55%, i.e. it is missing a significant fraction of contrail appearances. Looking inmore details, the sensitivity is 60% in clear-sky contidions but only 40% in conditions of a thin high cloud cover with superimposed contrails. Ananalysis of several years of contrail detection will be presented to determine precisely the fraction of contrail-producing flights and the associated weatherconditions with non-persistent and persistent contrails

Investigating sediment supply impact on centennial saltmarsh biogeomorphic development with Demeter

Abstract: This repository contains a series of simulations to investigate the impact of (changing)\ua0sediment supply on the long-term biogeomorphic development (200 years) of saltmarshes (4 km2). The model used is Demeter (https://doi.org/10.5281/zenodo.7101535)