• Rural Digital Europe
• Other research productsclose
• Open Access close
• NEANIAS Underwater Research Community close
• Rural Digital Europe close

The accuracy of flood forecasting models depends crucially on understanding wave runup. I use theory, insitu and remote observations, numerical modeling, computer vision, and deep learning to (1) investigate numerically the runup dependence on bathymetry and incident wave conditions, (2) improve video-based bathymetry estimates, and (3) characterize infragravity waves in 10m depth, for use in boundary conditions of runup models. Implementation into operational runup observing systems and models is ongoing. A numerical modeling (SWASH) study used 138 hindcast historical storm waves, two offshore boundary conditions, and 24 representative eroded beach bathymetries from a Southern California beach. The runup 2% exceedance level varied by more than 30% in response to changes in bathymetry or infragravity wave boundary conditions. An empirical parameterization trained on this dataset includes both a foreshore beach slope beta_f and an effective mid-surfzone slope beta_eff (Chapter 2, Lange et al. 2022). Subaqueous bathymetry is usually unknown because of the large expense of insitu jetski surveys, but beta_f and beta_eff can be estimated approximately and cost-effectively from images. The new 2-slope runup models have smaller errors than 1-slope models, but lack generality and have fundamentally limited accuracy. I show that useful bathymetry can be extracted from video collected during a single 17-minute quadcopter hover. The existing cBathy algorithm is extended with a crest-tracking algorithm that significantly reduces large cBathy errors near the breakpoint. The crest-tracking algorithm uses a deep-learning neural network to annotate timestacks for celerity estimates, and the depth inversion includes a nonlinear correction. This approach reduces RMSE surfzone depth errors to 0.17m, from ~0.81m with cBathy (Chapter 3, Lange et al. 2023, revision submitted to Coastal Engineering). The infragravity offshore (~10m depth) boundary condition is another potential error source in the runup model estimates. Several years of observations show that free infragravity waves are often much larger (up to x10) than the bound waves often used as a boundary condition. A parameterization of the incident-free IG wave field is combined with the predicted boundwave energy into a sea surface elevation timeseries of the incident IG energy suitable for use in numerical models (Chapter 4).

Airborne lidar systems (ALS) provide 3D point clouds of the topography by direct time measurement of a short laser pulse after reflection on the Earth surface. For the last decade, this technique has proved to be the ideal remote sensing tool for delivering very accurate digital terrain model (DTM) of the Earth surface, and then for answering main environmental issues such as natural hazard prevention and natural ressource management. Moreover, such active systems, also called multiple echo lidar, allow to detect several return signals for a single laser shot. It is particularly relevant in case of vegetation areas since a single lidar survey allows to acquire not only the canopy top (the only visible layer from passive sensors), but also points inside the vegetation layer and on the ground underneath. Thus, among the different remote sensing techniques, airborne laser scanning has also proved to be the most efficient technique to characterize both forest structure and ground topography. For a few years, new airborne laser scanning systems called full-waveform lidar systems have emerged, providing not only 3D point clouds as classical ALS systems, but entire altimeter profiles of reflected energy from the Earth surface. These profiles represent the laser backscattered energy as a function of time. They give to the end-user more control and flexibility on the signal processing steps and enable to extract more information than classical multi-echo lidar data. A detailed state-of-the-art of such systems can be found in [1]. However, managing these data with spacial and time dependency is much more complex than images or 3D point clouds : raw full-waveform lidar data are sets of range profiles of various lengths that are stored in the sensor geometry following both the scan angle of the lidar system and the chronological order along the flight track. Moreover, the data volume is drastically larger than 3D point clouds: it takes about 140 GB for an acquisition time of 1.6 h with a pulse repetition frequency (PRF) of 50kHz. Furthermore, there is neither commercial nor opensource toolkit to handle full-waveform lidar data, but some constructor solutions, that are black boxes, can only extract 3D point clouds from raw data and are designed to their own sensors. Finally, there is not standard file format for full-waveform data (such as the LAS format for multi-echo data). Managing full-waveform lidar data is therefore a challenging task, and we adress this issue by developping a specific research tool: FullAnalyze.

Remote sensing has been used to map river bathymetry for several decades. Non-contact methods are necessary in several cases: inaccessible rivers, large-scale depth mapping, very shallow rivers. The remote sensing techniques used for river bathymetry are reviewed. Frequently, these techniques have been developed for marine environment and have then been transposed to riverine environments. These techniques can be divided into two types: active remote sensing, such as ground penetrating radar and bathymetric lidar; or passive remote sensing, such as through-water photogrammetry and radiometric models. This last technique which consists of finding a logarithmic relationship between river depth and image values appears to be the most used. Fewer references exist for the other techniques, but lidar is an emerging technique. For each depth measurement method, we detail the physical principles and then a review of the results obtained in the field. This review shows a lack of data for very shallow rivers, where a very high spatial resolution is needed. Moreover, the cost related to aerial image acquisition is often huge. Hence we propose an application of two techniques, radiometric models and through-water photogrammetry, with very high-resolution passive optical imagery, light platforms, and off-the-shelf cameras. We show that, in the case of the radiometric models, measurement is possible with a spatial filtering of about 1 m and a homogeneous river bottom. In contrast, with through-water photogrammetry, fine ground resolution and bottom textures are necessary.

The East Demerara Water Conservancy (EDWC) and east coast drainage and irrigation systems provide water storage and flood control mechanisms for Guyana's most populous region, including the capital city of Georgetown. In 2005, extreme rainfall caused devastang flooding along these coastal lowlands, with many areas remaining inundated for up to three weeks. The flood highlighted the vulnerability of the EDWC dam to overtopping and potential breaching. The Conservancy Adaptation Project (CAP) was conceived in the wake of the 2005 flood to help the Government of Guyana adapt to the threats posed by future climate change. The aim was to reduce the likelihood of catastrophic flooding along Guyana's low-lying coastal areas, also threatened by sea level rise. The project identified key investments totaling over US$ 123 million. These are being used by the Government to update the national master-plan strategy for drainage and irrigation and to plan future investment programs for reducing flood risk.

Estimating river discharge from in situ and/or remote sensing data is a key issue for evaluation of water balance at local and global scales and for water management. Variational data assimilation (DA) is a powerful approach used in operational weather and ocean forecasting, which can also be used in this context. A distinctive feature of the river discharge estimation problem is the likely presence of significant uncertainty in principal parameters of a hydraulic model, such as bathymetry and friction, which have to be included into the control vector alongside the discharge. However, the conventional variational DA method being used for solving such extended problems often fails. This happens because the control vector iterates (i.e., approximations arising in the course of minimization) result into hydraulic states not supported by the model. In this paper, we suggest a novel version of the variational DA method specially designed for solving estimation-under-uncertainty problems, which is based on the ideas of iterative regularization. The method is implemented with SIC2, which is a full Saint-Venant based 1D-network model. The SIC2 software is widely used by research, consultant and industrial communities for modeling river, irrigation canal, and drainage network behavior. The adjoint model required for variational DA is obtained by means of automatic differentiation. This is likely to be the first stable consistent adjoint of the 1D-network model of a commercial status in existence. The DA problems considered in this paper are offtake/tributary estimation under uncertainty in the cross-device parameters and inflow discharge estimation under uncertainty in the bathymetry defining parameters and the friction coefficient. Numerical tests have been designed to understand identifiability of discharge given uncertainty in bathymetry and friction. The developed methodology, and software seems useful in the context of the future Surface Water and Ocean Topography satellite mission.

This report is the primary output from the climate change impact and adaptation study for the Bangkok Metropolitan Region (BMR) produced for the Bangkok Metropolitan Administration (BMA) with financial support provided by the World Bank. The report concerns climate change, and provides an analysis of climate change impacts and adaptation options for the BMR. In addition to the more general matters on the physical setting and socioeconomics of BMR, the report considers a number of issues related to climate change in detail. These are: changes in the inundation pattern, and impact on the population and socioeconomics, and coping mechanisms to deal with the changed situation.

During the past few years there was an increasing demands of needs for mapping the bottom of water, either because it was needed for Navigation Safety, Nautical charts, or for Pollution controlling, mineral and fish industries. Over the years the methods of bathymetry and mapping showed a huge improvement especially in the last 40 years where a rapid growth occurs in this part of science. Particular growth occurs in the bathymetry area using satellite data which continuously presented and exported new models in order to create maps in a shorter time period and with fewer expenses. Additionally there is an increasing improvement in the accuracy of the results of the maps over time and it is accomplished with smaller errors. For export of maps and finding data followed a fairly complicated process which needs to take into account many parameters are either located in the constituents of water, either the nature of the water bottom, or in the atmosphere and beyond. The method of remote sensing is divided into two main categories imagine methods and the Non imagine methods. Both are widely known, in conclusion, the methodology of remote sensing comparatively with the eco-sounding method is more efficient in a matter of time, financial budget, data accuracy than any other method exists, and usually is recommended for use. Πάντα υπήρχε η ανάγκη της χαρτογράφησης του πυθμένα του νερού, είτε ο λόγος αυτός αφορούσε την ασφαλή ναυσιπλοία είτε αφορούσε τον έλεγχο της στάθμης του νερού ή αφορούσε περιβαλλοντικούς λόγους. Κατά την πάροδο των χρόνων οι μέθοδοι της βυθομέτρησης και της χαρτογράφησης εξελίσονταν και βελτιώνονταν, ειδικά τα τελευταία 40 χρόνια όπου παρουσιάζεται μία ραγδαία ανάπτυξη στον τομέα αυτό. Ιδιαίτερη ανάπτυξη παρουσιάζεται στον τομέα της βυθομετρίας με την χρήση δορυφορικών δεδομένων όπου συνεχώς παρουσιάζονται νέοι τρόποι εξαγωγής χαρτών σε συντομότερο χρόνο και με λιγότερες δαπάνες. Επιπρόσθετα διακρίνεται μία συνεχής βελτίωση στην ακρίβεια των αποτελεσμάτων καθώς με τον καιρό επιτυγχάνεται η εξαγωγή αποτελεσμάτων με μεγαλύτερες ακρίβειες συνεπώς με μικρότερα σφάλματα. Για την εξαγωγή των χαρτών και την εύρεση των δεδομένων ακολουθείται μία αρκετά περίπλοκη διαδικασία όπου χρειάζεται να λαμβάνονται υπόψη πολλοί παραμέτροι είτε αυτοί βρίσκονται στα συστατικά του νερού, είτε στο είδος του πυθμένα του νερού, είτε στην ατμόσφαιρα και όχι μόνο. Η μέθοδος της τηλεπισκόπησης διακρίνεται σε δύο βασικές κατηγορίες η μέθοδος απικόνησης και η μέθοδος μη απικόνησης. Είναι και οι δύο ευρέως γνωστές. Εν κατακλείδι, η μέθοδολογία της τηλεπισκόπησης είναι πιο αποδοτική σε θέμα χρόνου, οικονομικού προυπολογισμού, ακρίβεια δεδομένων σε σχέση με οποιαδήποτε άλλη μέθοδο υπάρχει, και συνήθως είναι αυτή που συστήνεται για χρήση. Completed

Possessing accurate, spatial and current data on the water levels and the depths are necessary for anticipation and better management of coastal and continental waters. Among the remote sensing techniques to monitor the water bathymetry and altimetry, the LIDAR appears as an adapted and promising technique, already proven on airborne platforms, because of its potential accuracy, spatial resolution and repeatability of measurements. The objective of this thesis is to evaluate the potential of the transfer technology on satellite LiDAR to estimate the water altimetry and bathymetry of continental and coastal areas. An experimental approach based on actual LiDAR data and a theoretical approach based on simulated LiDAR waveforms were used to explore the performance of satellite LiDAR sensors. In the first part, the altimetry data quality from the satellite LiDAR sensor GLAS / ICESat was evaluated in order to monitor the altimetry of water bodies. The evaluation method developed is based on the consideration of the autocorrelation phenomena of successive measurements when comparing the elevation GLAS / ICESat with water levels measured at gauging stations. Accuracies are estimated in the order of 12 cm. In the second part, a simulation model of LiDAR waveform has been developed. The confrontation between simulations from the model compared to observed waveform provided by satellite and aircraft sensors was performed. In the last section, the performance of two space borne LiDAR emitting in the UV (355 nm) or the green (532 nm) were evaluated using a methodology based on waveform simulation following aggregate distributions of various water parameters assumed to be representative on a global scale and for four different types of water. A sensitivity analysis was performed to identify and order the environmental parameters that influence the most the LiDAR bottom echo of the water signal in determining the feasibility of measuring bathymetry. Then, the probability of measuring water depth and the accuracy of estimating the bathymetry were calculated according to an experimental design that meets the global distributions of water parameters. This thesis proposes a global methodology, a starting point to explore the overall performance and the limiting factors for future satellite LiDAR sensors totally or partially dedicated to altimetry and bathymetry of coastal and inland waters. / Disposer de données précises, spatialisées et actualisées sur les niveaux et les profondeurs des eaux côtières ou continentales est nécessaire pour assurer et anticiper une meilleure gestion des eaux littorales et continentales. Parmi les techniques de télédétection de suivi de la bathymétrie et d'altimétrie des eaux, le LIDAR apparaît, de par son potentiel de précision, de résolution et de répétitivité spatiale des mesures, comme une technique adaptée et prometteuse, déjà éprouvée sur des plateformes aéroportées. L'objectif de cette thèse est d'évaluer le potentiel du transfert de la technologie LiDAR sur satellite pour estimer l'altimétrie et la bathymétrie des eaux de surfaces continentales et côtières. Une approche expérimentale basée sur des données LiDAR réelles, puis une approche théorique basée sur des formes d'onde LiDAR simulées ont été utilisées pour explorer les performances de capteurs LiDAR satellitaires. Dans une première partie, la qualité des données altimétriques du capteur LiDAR satellitaire GLAS/ICESat fut évaluée pour le suivi de l'altimétrie de plans d'eau. La méthode d'évaluation développée repose sur la prise en compte des phénomènes d'autocorrélation des mesures successives lors des comparaisons de l'élévation GLAS/ICESat avec les niveaux d'eau mesurés aux stations hydrométriques. Les précisions estimées sont de l'ordre de 12 cm. Dans une seconde partie, un modèle de simulation des trains d'ondes LiDAR a été développé. La confrontation des simulations issues du modèle par comparaison à des trains d'ondes observés par des capteurs satellitaires et aéroportés a été effectuée. Dans une dernière partie, les performances de deux configurations de potentiels capteurs LiDAR spatiaux émettant dans l'UV (355 nm) ou dans le vert (532 nm) ont été évaluées à partir des formes d'ondes simulées suivant des distributions globales des différents paramètres de l'eau assumées comme représentatives à l'échelle mondiale et pour quatre types d'eaux différents. Une analyse de sensibilité a été effectuée pour identifier et ordonner les paramètres environnementaux qui influent le plus sur l'écho LiDAR du fond de l'eau, signal déterminant dans la faisabilité de la mesure bathymétrique. Ensuite, les probabilités de mesure de la bathymétrie ainsi la précision sur l'estimation de la bathymétrie ont été calculées suivant un plan d'expérience qui respecte les distributions globales des paramètres d'eau. Cette thèse propose une méthodologie globale, point de départ pour explorer les performances globales et les facteurs limitant de futurs capteurs LiDAR satellitaires dédiés totalement ou partiellement à l'altimétrie et la bathymétrie des eaux côtières et continentales.

/ Au cours de ce stage, j'ai développé de nouvelles méthodes d'estimation (d'inversion) de la bathymétrie et de la hauteur d'arbres à partir de formes d'onde LiDAR. Ces nouvelles méthodes statistiques, utilisant un apprentissage, tombent dans le domaine dit de l'analyse fonctionnelle. Ces méthodes réduisant le signal en un nombre réduit de paramètres qui décrivent ce signal et une régression statistique (modèle d'inversion) est ensuite effectuée entre ces paramètres et la variable d'intérêt (bathymétrie ou hauteur de canopée). Quatre méthodes de réduction de la dimension ont été testée : l'Analyse en Composantes Principales, la décomposition en ondelettes, l'approximation par splines cubique et l'approximation par BSplines. Trois méthodes de régression ont été testées : la régression multiple, CART et la méthode de forêt aléatoire (random forest). Les résultats de ces méthodes montrent que, pour des formes d'onde simulées, parfaitement contrôlées, on peut estimer la bathymétrie avec des précisions allant jusqu'à 3 cm pour des gammes de profondeur comprises entre 0 et 3 mètres. Les résultats de ces méthodes sur des formes d'onde simulées pour une eau claire et turbide sont équivalents. Les résultats des modèles d'inversion des formes d'onde bathymétriques réelles pour le Golfe du Morbihan avec deux types de capteurs (APD et PMT) sont également très proches. L'écart de précision entre les formes d'onde réelles et simulées s'explique par le fait que les paramètres du milieu sont fixés pour le cas des formes d'onde LiDAR simulées. En ce qui concerne l'estimation des hauteurs d'arbres, les résultats des modèles d'inversion des formes d'onde LiDAR atlimétriques (réelles) obtenues donnent une précision allant jusqu'à 2.35 mètres. Les modèles d'inversion utilisant les forêts aléatoires donne de meilleurs résultats que pour la régression linéaire. CART reste le modèle statistique le moins précis. Si on compare les différentes méthodes, on voit que les B-Splines donnent les meilleurs résultats. L'Analyse en Composantes Principales et l'analyse en ondelettes restent également un bon choix pour l'inversion des formes d'onde LiDAR. L'avantage de ces méthodes est qu'elles proposent des modèles statistiques avec peu de variables explicatives.

Tsunamis can be devastating. The 2004 Indian Ocean and 2011 Tohoku disasters provide frightening examples of the power of tsunamis. The Pacific has long been recognized as a place where tsunamis occur - the 'Pacific Ring of Fire' (PRF) contains regions of volcanoes and large earthquakes associated with tectonic plate motions that are ideal breeding grounds for tsunamis. The Pacific Ocean covers an area of 30 million km. Some 22 Pacific Island Countries and Territories (PICTs) are dotted throughout the Pacific and are vulnerable to varying degrees, to the effects of tsunamis generated locally, regionally and distantly tsunamis in the Pacific have claimed numerous lives, caused widespread damage to coastal infrastructure and heavily impacted natural ecosystems.