73 research outputs found
Hydrodynamic modelling of the tide propagation in a tropical delta: overcoming the challenges of data scarcity
Hydrodynamic
Modelling fine-grained sediment transport in the Mahakam land–sea continuum, Indonesia
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
Biotic and abiotic factors control the geomorphic characteristics of channel networks in salt marshes
Toward a generic method for studying water renewal, with application to the epilimnion of Lake Tanganyika
We present a method, based on the concept of age and residence time, to study the water renewal in a semi-enclosed domain. We split the water of this domain into different water types. The initial water is the water initially present in the semi-enclosed domain. The renewing water is defined as the water entering the domain of interest. Several renewing water types may be considered depending on their origin. We present the equations for computing the age and the residence time of a certain water type. These timescales are of use to understand the rate at which the water renewal takes place. Computing these timescales can be achieved at an acceptable extra computer cost.
The above-mentioned method is applied to study the renewal of epilimnion (i.e. the surface layer) water in Lake Tanganyika. We have built a finite element reduced-gravity model modified to take into account the water exchange between the epilimnion and the hypolimnion (i.e. the bottom layer), the water supply from precipitation and incoming rivers, and the water loss from evaporation and the only outgoing river. With our water renewal diagnoses, we show that the only significant process in the renewal of epilimnion water in Lake Tanganyika is the water exchange between the epilimnion and the hypolimnion, other phenomena being negligible. (C) 2007 Elsevier Ltd. All rights reserved
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