Geophysical granular flows, such as snow avalanches, pyroclastic density currents, mudslides and debris flows, can be extremely hazardous to local populations, and understanding their complex behaviour remains an important challenge. This project aims to provide insight into these events by exploring different aspects in isolation, using a combination of mathematical theory, numerical simulations and small-scale experiments. Firstly, the effect of lateral confinement is examined by studying granular material moving in an inclined chute. This can have applications to natural releases flowing down confined valleys or conduits, and the relative simplicity of the geometry also provides a useful test case for new theoretical models. One such model is the recent depth-averaged μ(I)-rheology, which, because of the viscous terms introduced into the depth-averaged momentum balance, may be described as an intermediate approach between full constitutive laws and classical shallow-water-type equations for dense granular flows. Here, a generalisation of the new system to two spatial dimensions is described, and the resulting viscous equations are able to capture the cross-slope curvature of the downslope velocity profiles in steady uniform chute flows. This may be regarded as major progress compared to traditional hyperbolic models, which only admit constant velocity solutions. Particle size-segregation in geophysical granular flows is then investigated, which can cause important feedback on the overall bulk properties as it can lead to the development of regions with different frictional properties. A particularly striking example is segregation-induced 'finger' formation, where large particles are segregated to the flow surface and sheared to form a resistive coarse-rich front, which is unstable and spontaneously breaks down into a series of lobate structures. These travel both faster and further than one might anticipate. To model such segregation-mobility feedback effects, the depth-averaged μ(I)-rheology is extended to bidisperse flows by coupling with a depth-integrated model for size-segregation. The system of equations remains mathematically well-posed and is able to qualitatively capture finger formation, with the newly-introduced viscous terms controlling the characteristics of the leveed channels that develop. A more subtle segregation effect is studied in bidisperse roll waves, which form as small irregularities merge and coarsen as they move downslope, eventually growing into destructive large amplitude pulses. Experimental measurements show lateral, as well as vertical, segregation profiles, with the coarser grains accumulating at the fastest moving wave crests. The disturbances that form in mixtures with higher proportions of large particles grow more slowly, leading to smaller amplitude waves that travel at slower speeds, and the new coupled model predicts qualitatively similar behaviour. Finally, the influence of complex topography is investigated. A smooth two-dimensional bump is placed across the width of a chute, which, depending on the initial conditions, can lead to the formation of an airborne jet or granular shock at steady state. A simple depth-averaged model in a curvilinear coordinate system following the topography accurately captures both regimes, and represents a significant improvement on using an aligned Cartesian approach.

Bed topography identification in open channel and glacier flows is of paramount importance for the study of the respective flows. In the former, the knowledge of the channel bed topography is required for modelling the hydrodynamics of open channel flows, fluvial hydraulics, flood propagation, and river flow monitoring. Indeed, flow models based on the Shallow Water Approximation require prior information on the channel bed topography to accurately capture the flow features. While in the latter, usable bedrock topographic information is very important for glacier flow modellers to accurately predict the flow characteristics. Experimental techniques to infer the bed topography are usually used but are mostly time consuming, costly, and sometimes not possible due to geographical restrictions. However, the measurement of free surface elevation is relatively easy. Alternative to experimental techniques, it is therefore important to develop fast, easy-to-implement, and cost-effective numerical methods. The inverse of the classical hydrodynamic problem corresponds to the determination of hydraulic parameters from measurable quantities. The forward problem uses model parameters to determine measurable quantities. New one-shot and direct pseudo-analytical and numerical approaches for reconstructing the channel bed topography from known free surface elevation data is developed for one-dimensional shallow water flows. It is shown in this work that instead of treating this inverse problem in the traditional partial differential equation (PDE)-constrained optimization framework, the governing equations of the direct problem can be conveniently rearranged to obtain an explicit PDE for the inverse problem. This leads to a direct solution of the inverse problem which is successfully tested on a range of benchmark problems and experimental data for noisy and noiseless free surface data. It was found that this solution approach creates very little amplification of noise. A numerical technique which uses the measured free surface velocity to infer the channel bed topography is also developed. The one-dimensional shallow water equations along with an empirical relationship between the free surface and the depth averaged velocities are used for the inverse problem analysis. It is shown that after a series of algebraic manipulation and integration, the equation governing the inverse problem simplifies to a simple integral equation. The proposed method is tested on a range of analytical and experimental benchmark test cases and the results confirm that, it is possible to reconstruct the channel bed topography from a known free surface velocity distribution of one-dimensional open channel flows. Following the analysis of the case of one-dimensional shallow water flows, a numerical technique for reconstructing the channel bed topography from known free surface elevation data for steep open channel flows is developed using a modified set of equations for which the zero-inertia shallow water approximation holds. In this context, the shallow water equations are modified by neglecting inertia terms while retaining the effects of the bed slope and friction terms. The governing equations are recast into a single first-order partial differential equation which describes the inverse problem. Interestingly, the analysis shows that the inverse problem does not require the knowledge of the bed roughness. The forward problem is solved using MacCormack’s explicit numerical scheme by considering unsteady modified shallow water equations. However, the inverse problem is solved using the method of characteristics. The results of the inverse and the forward problem are successfully tested against each other. In the framework of full two-dimensional shallow water equations, an easy-to-implement and fast to solve direct numerical technique is developed to solve the inverse problem of shallow open channel flows. The main underlying idea is analogous to the idea implemented for the case of one-dimensional reconstruction. The technique described is a “one-shot technique” in the sense that the solution of the partial differential equation provides the solution to the inverse problem directly. The idea is tested on a set of artificial data obtained by first solving the forward problem. Glaciers are very important as an indicator of future climate change or to trace past climate. They respond quickly compared to the Antarctica and Greenland ice sheets which make them ideal to predict climate changes. Glacier bedrock topography is an important parameter in glacier flow modelling to accurately capture its flow dynamics. Thus, a mathematical technique to infer this parameter from measured free surface data is invaluable. Analogous to the approaches implemented for open channel flows, easy-to-implement direct numerical and analytical algorithms are developed to infer the bedrock topography from the knowledge of the free surface elevation in one space dimension. The numerical and analytical methods are both based on the Shallow Ice Approximation and require the time series of the ablation/accumulation rate distribution. Moreover, the analytical method requires the knowledge of a non-zero glacier thickness at an arbitrary location. Numerical benchmark test cases are used to verify the suitability and applicability of the algorithms.

京都大学 / 0048 / 新制・論文博士 / 博士(農学) / 乙第13021号 / 論農博第2831号 / 新制||農||1042(附属図書館) / 学位論文||H28||N4967(農学部図書室) / 32949 / 京都大学大学院農学研究科地域環境科学専攻 / (主査)教授 藤原 正幸, 教授 村上 章, 准教授 宇波 耕一 / 学位規則第4条第2項該当 / Doctor of Agricultural Science / Kyoto University / DFAM