Glacial-dominated areas pose unique challenges to downstream communities in adapting to recent and continuing global climate change, including increased threats of glacial lake outburst floods (GLOFs) that have substantial impacts on regional social, environmental and economic systems increasing risk due to flooding of downstream communities. In this dissertation, two lakes with potential to generate GLOFs were studied, Imja Lake in Nepal and Palcacocha Lake in Peru. At Imja Lake, basic data was generated that allowed the creation of a conceptual model of the lake. Ground penetrating radar and bathymetric surveys were performed. Also, an inundation model was developed in order to evaluate the effectiveness of a project that seeks to reduce flooding risk by lowering the lake at least 3 meters. In Peru, a GLOF inundation model was created. Also, the vulnerability of the people living downstream in the City of Huaraz was calculated, and the impacts of an early warning system were evaluated. The results at Imja indicated that the lake deepened from 98 m in 2002 to 116 m in 2012. Likewise, the lake volume increased from 35.8 to 61.6±1.8 million m3 over the past decade. The GPR survey at Imja and Lhotse-Shar glaciers shows that the glacier is over 200 m thick in the center of the glacier. The modeling work at Imja shows that the proposed project will not have major impacts downstream since the area inundated does not reduce considerably unless the lake is lowered by about 20 m. In Huaraz, the results indicate that approximately 40646 people live in the potentially inundated area. Using the flow simulation and the Peru Census 2007, a map of vulnerability was generated indicating that the most vulnerable areas are near the river. Finally, the potential number of fatalities in a worst case GLOF scenario from Lake Palcacocha was calculated to be 19773 with a standard deviation of 1191 if there is no early warning system and 7344 with a standard deviation of 1446 people if an early warning system is installed. Finally, if evacuation measures are improved the number reduces to 2865 with a standard deviation of 462. / text

Space-borne remote sensing datasets have the potential to allow us to progress towards global scale flood prediction systems. However, these datasets are limited in terms of space-time resolution and accuracy, and the best use of such data requires understanding how uncertainties propagate through hydrological models. An unbiased investigation of different datasets for hydrological modeling requires a parsimonious calibration-free model, since calibration masks uncertainties in the data and model structure. This study, which addresses these issues, consists of two parts: 1) the development and validation of a multi-scale distributed hydrological model whose parameters can be directly linked to physical properties of the watershed, thereby avoiding the need of calibration, and 2) application of the model to demonstrate how data uncertainties propagate through the model and affect flood simulation across scales. I based the model development on an interactive approach for model building. I systematically added processes and evaluated their effects on flood prediction across multiple scales. To avoid the need for parameter calibration, the level of complexity in representing physical processes was limited by data availability. I applied the model to simulate flows for the Cedar River, Iowa River and Turkey River basins, located in Iowa. I chose this region because it is rich in high quality hydrological information that can be used to validate the model. Moreover, the area is frequently flooded and was the center of an extreme flood event during the summer of 2008. I demonstrated the model's skills by simulating medium to high-flow conditions; however the model's performance is relatively poor for dry (low flow) conditions. Poor model performance during low flows is attributed to highly nonlinear dynamics of soil and evapotranspiration not incorporated in the model. I applied the hydrological model to investigate the predictability skills of satellite-based datasets and to investigate the model's sensibility to certain hydro-meteorological variables such as initial soil moisture and bias in evapotranspiration. River network structure and rainfall are the main components shaping floods, and both variables are monitored from space. I evaluated different DEM sources and resolution DEMs as well as the effect of pruning small order channels to systematically decreasing drainage density. Results showed that pruning the network has a greater effect on simulated peak flow than the DEM resolution or source, which reveals the importance of correctly representing the river network. Errors on flood prediction depend on basin scale and rainfall intensity and decrease as the basin scale and rainfall intensity increases. In the case of precipitation, I showed that simulated peak flow uncertainties caused by random errors, correlated or not in space, and by coarse space-time data resolution are scale-dependent and that errors in hydrographs decrease as basin scale increases. This feature is significant because it reveals that there is a scale for which less accurate information can still be used to predict floods. However, the analyses of the real datasets reveal the existence of other types of error, such as major overall bias in total volumes and the failure to detect significant rainfall events that are critical for flood prediction.

Flood inundation is a major natural hazard that can have very severe socio-economic consequences. This thesis presents an enhanced numerical model for flood simulation. After setting the context by examining recent large-scale flood events, a literature review is provided on shallow flow numerical models. A new version of the hyperbolic horizontal variable density shallow water equations with source terms in balanced form is used, designed for flows over complicated terrains, suitable for wetting and drying fronts and erodible bed problems. Bed morphodynamics are included in the model by solving a conservation of bed mass equation in conjunction with the variable density shallow water equations. The resulting numerical scheme is based on a Godunov-type finite volume HLLC approximate Riemann solver combined with MUSCL-Hancock time integration and a non-linear slope limiter and is shock-capturing. The model can simulate trans-critical, steep-fronted flows, connecting bodies of water at different elevations. The model is validated for constant density shallow flows using idealised benchmark tests, such as unidirectional and circular dam breaks, damped sloshing in a parabolic tank, dam break flow over a triangular obstacle, and dam break flow over three islands. The simulation results are in excellent agreement with available analytical solutions, alternative numerical predictions, and experimental data. The model is also validated for variable density shallow flows, and a parameter study is undertaken to examine the effects of different density ratios of two adjacent liquids and different hydraulic thrust ratios of species and liquid in mixed flows. The results confirm the ability of the model to simulate shallow water-sediment flows that are of horizontally variable density, while being intensely mixed in the vertical direction. Further validation is undertaken for certain erodible bed cases, including deposition and entrainment of dilute suspended sediment in a flat-bottomed tank with intense mixing, and the results compared against semi-analytical solutions derived by the author. To demonstrate the effectiveness of the model in simulating a complicated variable density shallow flow, the validated numerical model is used to simulate a partial dam-breach flow in an erodible channel. The calibrated model predictions are very similar to experimental data from tests carried out at Tsinghua University. It is believed that the present numerical solver could be useful at describing local horizontal density gradients in sediment laden and debris flows that characterise certain extreme flood events, where sediment deposition is important.

3D environment reconstruction has received great interest in recent years in areas such as city planning, virtual tourism and flood hazard warning. With the rapid development of computer technologies, it has become possible and necessary to develop new methodologies and techniques for real time simulation for virtual environments applications. This thesis proposes a novel dynamic simulation scheme for flood hazard warning. The work consists of three main parts: digital terrain modelling; 3D environmental reconstruction and system development; flood simulation models. The digital terrain model is constructed using real world measurement data of GIS, in terms of digital elevation data and satellite image data. An NTSP algorithm is proposed for very large data assessing, terrain modelling and visualisation. A pyramidal data arrangement structure is used for dealing with the requirements of terrain details with different resolutions. The 3D environmental reconstruction system is made up of environmental image segmentation for object identification, a new shape match method and an intelligent reconstruction system. The active contours-based multi-resolution vector-valued framework and the multi-seed region growing method are both used for extracting necessary objects from images. The shape match method is used with a template in the spatial domain for a 3D detailed small scale urban environment reconstruction. The intelligent reconstruction system is designed to recreate the whole model based on specific features of objects for large scale environment reconstruction. This study then proposes a new flood simulation scheme which is an important application of the 3D environmental reconstruction system. Two new flooding models have been developed. The first one is flood spreading model which is useful for large scale flood simulation. It consists of flooding image spatial segmentation, a water level calculation process, a standard gradient descent method for energy minimization, a flood region search and a merge process. The finite volume hydrodynamic model is built from shallow water equations which is useful for urban area flood simulation. The proposed 3D urban environment reconstruction system was tested on our simulation platform. The experiment results indicate that this method is capable of dealing with complicated and high resolution region reconstruction which is useful for many applications. When testing the 3D flood simulation system, the simulation results are very close to the real flood situation, and this method has faster speed and greater accuracy of simulating the inundation area in comparison to the conventional flood simulation models

Cette thèse aide à approfondir les connaissances sur les différentes sources d’incertitude dans l’évaluation économique du risque inondation. Elle explore plusieurs disciplines afin d’analyser l’impact des stratégies utilisées pour modéliser l’aléa inondation et la vulnérabilité d’un territoire, sur l’évaluation des dommages potentiels. On a mesuré la variabilité des estimations en fonction des bases de données, modèles, méthodes et échelles considérés pour : analyser la probabilité des inondations (hydrologie) ; modéliser et cartographier l’aléa inondation (hydraulique) ; caractériser la vulnérabilité des enjeux et leur susceptibilité à subir des dommages (génie civil, géographie et économie de l’environnement). Les analyses et méthodes développées devront appuyer la prise en compte d’incertitudes, la détermination de priorités et l’optimisation de la distribution des ressources entre les différents modules de l’évaluation. Afin d’explorer un degré de complexité supplémentaire d’analyse de risque, nous avons développé une méthode d’analyse de la vulnérabilité systémique des réseaux d’infrastructure en lien avec leur résilience. / This thesis aims at exploring different sources of uncertainty related to the economic analysis of the flood risk. It embraces several fields of knowledge in order to determine how the selection of strategies used to model flood hazard and assess the vulnerability of a territory may affect damage potential estimations. We measured the variability of damage estimations as a function of the datasets, methods, models and scales considered to: analyse the probability of floods (hydrology); model and map flood hazard (hydraulics); assess the vulnerability and susceptibility of properties to floods (civil engineering, geography and environmental economics). The methods and analyses developed here should bring support for practitioners in the investigation of uncertainties, determination of evaluation priorities and optimisation of the distribution of resources between the different modules of the evaluation process. In order to explore a second level of complexity of flood risk evaluations, we developed a method for analysing the systemic vulnerability of infrastructure networks, in relation with their resilience.

3D environment reconstruction has received great interest in recent years in areas such as city planning, virtual tourism and flood hazard warning. With the rapid development of computer technologies, it has become possible and necessary to develop new methodologies and techniques for real time simulation for virtual environments applications. This thesis proposes a novel dynamic simulation scheme for flood hazard warning. The work consists of three main parts: digital terrain modelling; 3D environmental reconstruction and system development; flood simulation models. The digital terrain model is constructed using real world measurement data of GIS, in terms of digital elevation data and satellite image data. An NTSP algorithm is proposed for very large data assessing, terrain modelling and visualisation. A pyramidal data arrangement structure is used for dealing with the requirements of terrain details with different resolutions. The 3D environmental reconstruction system is made up of environmental image segmentation for object identification, a new shape match method and an intelligent reconstruction system. The active contours-based multi-resolution vector-valued framework and the multi-seed region growing method are both used for extracting necessary objects from images. The shape match method is used with a template in the spatial domain for a 3D detailed small scale urban environment reconstruction. The intelligent reconstruction system is designed to recreate the whole model based on specific features of objects for large scale environment reconstruction. This study then proposes a new flood simulation scheme which is an important application of the 3D environmental reconstruction system. Two new flooding models have been developed. The first one is flood spreading model which is useful for large scale flood simulation. It consists of flooding image spatial segmentation, a water level calculation process, a standard gradient descent method for energy minimization, a flood region search and a merge process. The finite volume hydrodynamic model is built from shallow water equations which is useful for urban area flood simulation. The proposed 3D urban environment reconstruction system was tested on our simulation platform. The experiment results indicate that this method is capable of dealing with complicated and high resolution region reconstruction which is useful for many applications. When testing the 3D flood simulation system, the simulation results are very close to the real flood situation, and this method has faster speed and greater accuracy of simulating the inundation area in comparison to the conventional flood simulation models