The analysis of large-scale watershed processes and development of an efficient and integrated modelling platform is the focus of this research. The research focused on developing a series of modelling tools that can be used in the simulation of the overall response of a watershed based on a localized or distributed hydrologic event. This is achieved through the introduction of a hybrid modelling concept using a combination of empirically based lumped hydrologic processes and a physics-based distributed model representation. The watershed simulation model (GFLOOD) was developed to account for the complexity of the watershed including the variations in climate, soils, topography, and landuse conditions across the watershed. GFLOOD stands for Guelph Flood Forecasting Model, a river basin or watershed scale flow prediction model. Two major modelling components of the GFLOOD model are the time parameters (time of concentration (Tc) and recession constant (K)) and the channel routing component. Each of these modelling components is evaluated separately. The equations developed in this study for estimating the time parameters can be used as an initial estimate for Tc and K for ungauged basins, and through calibration and/or sensitivity analysis the values of Tc and K can be finalized. The Saint Venant equations for flood routing are solved by transforming the momentum equation into a partial differential equation which has six parameters related to cross-sectional area and discharge of the channel, left floodplain and right floodplain. The simplified dynamic model was further modified to account for transmission losses, evaporation losses and bank storage within the channel. The model was compared with the solutions of the general dynamic wave model, diffusion wave model and the more complex dynamic wave model. The comparison shows that there is good agreement between the results of the simplified dynamic model and the other models however, the simplified dynamic model is easier to formulate and compute than the other models. The complete GFLOOD model was applied to the Welland River Watershed within Southern Ontario. The model was evaluated for its ability to predict streamflow and water levels along the main branch of the Welland River.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19976号 / 工博第4220号 / 新制||工||1653(附属図書館) / 33072 / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 立川 康人, 教授 堀 智晴, 准教授 KIM SUNMIN / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

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The two-dimensional depth-averaged shallow water equations have attracted considerable attentions as a practical way to solve flows with free surface. Compared to three-dimensional Navier-Stokes equations, the shallow water equations give essentially the same results at much lower cost. Solving the shallow water equations by the Godunov-type finite volume method is a newly emerging area. The Godunov-type finite volume method is good at capturing the discontinuous fronts in numerical solutions. This makes the method suitable for solving the system of shallow water equations. In this dissertation, both the shallow water equations and the Godunov-type finite volume method are described in detail. A new surface flow routing method is proposed in the dissertation. The method does not limit the shallow water equations to open channels but extends the shallow water equations to the whole domain. Results show that the new routing method is a promising method for prediction of watershed runoff. The method is also applied to turbulence modeling of free surface flow. The κ - ε turbulence model is incorporated into the system of shallow water equations. The outcomes prove that the turbulence modeling is necessary for calculation of free surface flow. At last part of the dissertation, a total load sediment transport model is described and the model is tested against 1D and 2D laboratory experiments. In summary, the proposed numerical method shows good potential in solving free surface flow problems. And future development will be focusing on river meandering simulation, non-equilibrium sediment transport and surface flow - subsurface flow interaction.

Drastic growth and chaotic deployment of Wireless Local Area Networks (WLANs) in dense urban areas are some of the common issues of many Internet Service Providers (ISPs) and Wi-Fi users. These issues result in a substantial reduction of the throughput and impede the balanced distribution of bandwidth among the users. Most of these networks are using unmanaged consumer-grade Access Points (APs) and there is no cooperation among them. Moreover, the conventional association mechanism that selects APs with the strongest Received Signal Strength Indicator (RSSI) aggravates this situation. In spite of all these challenges, there is a great opportunity to build cooperative overlay networks among the APs that are owned by different ISPs, companies or individuals in dense urban areas. In fact, ISPs can distribute the resources among their customers in a cooperative fashion using a shared overlay platform which is constructed on top of the existing infrastructures. This approach helps the ISPs with efficient utilization of their resources and promoting the Quality of their Services (QoS). For instance, cooperative association control among the APs of different ISPs enables them to alleviate the drastic impact of interference in populated areas and improves the network throughput. Indeed, all Wi-Fi customers can associate to the APs from different ISPs and it leads to the construction of a large unified WLAN that expands the network coverage, significantly. Moreover, it results in a notable reduction of deployment costs and enhancement of customer satisfaction. Hence, as one of the key contributions of this dissertation, a cooperative framework for fine-grained AP association in dense WLANs is presented. On top of this framework, a thorough formulation and a heuristic solution to solve the aforementioned problems are introduced. The key enabler of the proposed solution is Software Defined Networking (SDN) which not only gives us an exceptional level of granularity but also empowers us to utilize high-performance computing resources and more sophisticated algorithms. Also, over the past few years, some of the largest cellular operators restricted their unlimited data plans and proposed tiered charging plans enforced by either strict throttling or large overage fees. While cellular operators are trying to guarantee the QoS of their services in a cost-effective and profitable manner, WLANs and Wi-Fi Mesh Networks (WMNs) as viable complements can be used to form a multihop backhaul connection between the access and the core networks. Indeed, the utilization of WMNs provides an opportunity to achieve a high network capacity and wide coverage by the employment of inexpensive commercial off-the-shelf products. Moreover, by bridging the WMNs and cellular networks, and the fine-grained traffic engineering of network flows, it is possible to provide a cost-effective Internet access solution for people who cannot afford the high cost of data plans. However, there are certain requirements in terms of QoS for different services over multi-hop backhaul networks. In addition, the process of service provisioning in WMNs incorporates tightly correlated steps, including AP association, gateway selection, and backhaul routing. In most of the prior studies, these steps were investigated as independent NP-hard problems and no unified formulation that considers all these steps (at different tiers of WMNs) has been presented. Hence, as another contribution of this dissertation, a structured and thorough scheme to address the demands of end-users over SDN-aware WMNs is introduced. In contrast to most of the former work, this scheme takes the key characteristics of wireless networks into account, especially for Multi-Channel Multi-Radio WMNs. The proposed solution can be applied to the large-scale scenarios and finds a near-optimal solution in polynomial time. Furthermore, since the presented solution may split the packets of a single flow among multiple paths for routing and there are non-trivial drawbacks for its implementation, a randomized single-path flow routing for SDN-aware WMNs is introduced. The randomized nature of the introduced solution avoids the complexities of implementing a multi-path flow routing and it presents a viable routing scheme that guarantees certain performance bounds. The functionality and performance of all the presented solutions have been assessed through extensive numerical results and real testbed experimentations as a proof of concept. It is important to note that the solutions presented in this dissertation can be utilized to provide a large variety of services for Wi-Fi users, while they guarantee different QoS metrics. / Graduate

The heterogeneity and complexity of modern communication networks demands coupling network nodes with intelligence to perceive and adapt to different network conditions autonomously. Cognitive Networking is an emerging networking research area that aims to achieve this goal by applying distributed reasoning and learning across the protocol stack and throughout the network. Various cognitive node and cognitive network architectures with different levels of maturity have been proposed in the literature. All of them adopt the idea of coupling network devices with sensors to sense network conditions, artificial intelligence algorithms to solve problems, and a reconfigurable platform to apply solutions. However, little further research has investigated suitable reasoning and learning algorithms. In this dissertation, we take cognitive network research a step further by investigating the reasoning component of cognitive networks. In a deviation from previous suggestions, we suggest the use of a single flexible distributed reasoning algorithm for cognitive networks. We first propose an architecture for a cognitive node in a cognitive network that is general enough to apply to future networking challenges. We then introduce and justify our choice of the island genetic algorithm (iGA) as the distributed reasoning algorithm. Having introduced our cognitive node architecture, we then focus on the applicability of the island genetic algorithm as a single reasoning algorithm for cognitive networks. Our approach is to apply the island genetic algorithm to different single and cross layer communication and networking problems and to evaluate its performance through simulation. A proof of concept cognitive network is implemented to understand the implementation challenges and assess the island genetic algorithm performance in a real network environment. We apply the island genetic algorithm to three problems: channel allocation, joint power and channel allocation, and flow routing. The channel allocation problem is a major challenge for dynamic spectrum access which, in turn, has been the focal application for cognitive radios and cognitive networks. The other problems are examples of hard cross layer problems. We first apply the standard island genetic algorithm to a channel allocation problem formulated for the dynamic spectrum cognitive network environment. We also describe the details for implementing a cognitive network prototype using the universal software radio peripheral integrated with our extended implementation of the GNU radio software package and our island genetic algorithm implementation for the dynamic spectrum channel allocation problem. We then develop a localized variation of the island genetic algorithm, denoted LiGA, that allows the standard island genetic algorithm to scale and apply it to the joint power and channel allocation problem. In this context, we also investigate the importance of power control for cognitive networks and study the effect of non-cooperative behavior on the performance of the LiGA. The localized variation of the island genetic algorithm, LiGA, is powerful in solving node-centric problems and problems that requires only limited knowledge about network status. However, not every communication and networking problems can be solved efficiently in localized fashion. Thus, we propose a generalized version of the LiGA, namely the K-hop island genetic algorithm, as our final distributed reasoning algorithm proposal for cognitive networks. The K-hop island genetic algorithm is a promising algorithm to solve a large class of communication and networking problems with controllable cooperation and migration scope that allows for a tradeoff between performance and cost. We apply it to a flow routing problem that includes both power control and channel allocation. For all problems simulation results are provided to quantify the performance of the island genetic algorithm variation. In most cases, simulation and experimental results reveal promising performance for the island genetic algorithm. We conclude our work with a discussion of the shortcomings of island genetic algorithms without guidance from a learning mechanism and propose the incorporation of two learning processes into the cognitive node architecture to solve slow convergence and manual configuration problems. We suggest the cultural algorithm framework and reinforcement learning techniques as candidate leaning techniques for implementing the learning processes. However, further investigation and implementation is left as future work. / Ph. D.

A distributed approach can improve functionality of H/WQ (Hydrology and Water Quality) modeling by facilitating a way to explicitly incorporate spatial characteristics of a watershed into the model. The time-area approach, with its intuitive and inherently distributed concept, provides a simple method to simulate runoff mechanisms. This study developed a distributed model based on the time-area approach with the goal of improved utility and efficiency in H/WQ modeling. Uncertainty is always introduced into watershed modeling because of imperfect knowledge and scale dependant spatial heterogeneity and temporal variability. Uncertainty analysis can provide a modeler, policy maker, and stakeholder with reliability information, better understanding, and better communication about the modeling results. This study quantified uncertainty of the model parameter and output through uncertainty analysis in order to assess risk in watershed management. The main goal of this study was to develop a hydrology and sediment transport model capable of routing overland flow using a time-area concept and providing reliability of the modeling results in a probabilistic manner through uncertainty analysis. The HYSTAR (HYdrology and Sediment transport simulation using Time-ARea method) model incorporates a modified Curve Number (CN) method and the newly devised time-area routing method to estimate runoff. HYSTAR is capable of simulating direct runoff, base flow, soil moisture, and sediment load in a distributed manner and in an hourly time step. In the model, the modified CN and a continuity equation are used to calculate infiltration of the routed runoff as well as rainfall on every overland cell. The effective direct runoff volume is distributed over downstream areas using the newly developed routing method. A direct runoff hydrograph is constructed directly through the discrete convolution of the time-area histogram and the effective direct runoff volume map without employing a unit hydrograph. In addition, sediment transport is simulated using the routing method and the sediment transport capacity approach without using a delivery ratio. The sensitivity analysis found that the CN and root zone depth were the most critical parameters for runoff simulation with HYSTAR. The model provided acceptable performance in predicting runoff and sediment load of a subwatershed of the Owl Run Watershed (ORD) with the Nash-Sutcliffe efficiency coefficient and coefficient of determination greater than 0.5. However, it failed to reproduce runoff for a subwatershed of Polecat Creek Watershed (PCA), where data show that runoff is not immediately responsive to rainfall. Uncertainty analysis revealed that the confidence intervals of the simulated monthly runoff and sediment load corresponded to 9.7 % and 10.2 % of their averages, respectively, at a significance level of 0.05. In addition, the average ranges of variation created by the Digital Elevation Model (DEM) and National Land Cover Data (NLCD) errors in the simulated monthly runoff and sediment load were equivalent to 7.5 % and 15.9 % of the average of their calibrated values, respectively. Based on the uncertainty analysis results, the Margin of Safety (MOS) of Total Maximum Daily Load (TMDL) were explicitly quantified as corresponding to 7.0 % and 21.3 % of the average of the simulated runoff and sediment load for ORD at significance level of 0.05. In conclusion, the HYSTAR model provided a new way to explicitly simulate runoff and sediment load of a watershed in a distributed manner. The approach developed here retains the simplicity of a unit hydrograph approach without employing numerical methods. Uncertainty analysis found that parameter uncertainty had greater impact on the model output than did expected Geographic Information System (GIS) data errors. In addition, the impact of the topographic data error on the model output was greater than was that of the land cover data error. Finally, this study provided a proof that a 5 to 10 % MOS that many TMDL studies consider underestimates modeling uncertainty. / Ph. D.

The Florida Keys National Marine Sanctuary (FKNMS) encompasses North America's only living coral barrier reef and the third longest barrier reef in the world, making it a unique national treasure of international notoriety (FKNMS, 2005). Recent evidence of environmental decline within the sanctuary has created a sense of urgency to understand and protect the valuable resources within. This thesis contributed to the understanding of habitat connectivity to aid managers and decision makers in the creation of additional Marine Protected Areas (MPAs) in the FKNMS to help prevent further environmental decline. This research specifically focused on modeling larval transport and larval connectivity among Acropora palmata (Lamarck, 1816) populations, coral habitats and MPAs in the upper and middle FKNMS. The transport of larvae in relation to ocean currents is a very limited area of research, and the analytic modeling results may serve as powerful guides to decisions about the relative importance of individual coral habitats and MPAs in the study area.Larval transport was modeled with ArcGIS and TauDEM using SoFLA-HYCOM simulated ocean currents during the A. palmata spawning season. This model allowed for the assessment of coral habitat and A. palmata population larval connectivity. The dependence of three distant A. palmata test populations on other upstream coral habitats and A. palmata populations significantly differed (Kruskal-Wallis test, P less than 0.0001). The clonally diverse Sand Island Reef A. palmata population's larval connectivity was significantly higher compared to other distant monoclonal populations (Mann-Whitney test, P less than 0.0001). Compared to the clonal structure of each test population determined by Baums, Miller, and Hellberg (2006), results indicated simulated larval connectivity may be a determinant of A. palmata population clonal diversity.By modeling MPA and coral habitat connectivity, this study also identified unprotected and distant coral habitat areas with the greatest downstream influence on MPAs; these may serve as potential coral larvae sources. It is recommended that establishing these areas as no-take MPAs would improve overall coral habitat and MPA network connectivity.

Neste trabalho é apresentada uma ferramenta de otimização para análise de problemas de alocação de água em bacias hidrográficas utilizando técnicas de programação linear e linear por partes, integradas a um modelo de amortecimentos de ondas em canais. A otimização é feita de forma global, com uso de softwares de programação linear baseados nos métodos de pontos interiores. A metodologia de uso do sistema consiste em se obter uma solução ?ótima? para situações de disponibilidade de água insuficiente a todos os usos conflitantes na bacia. A ferramenta está sendo acoplada e incorporada ao AcquaNet, um Sistema de Suporte a Decisões (SSD) para análise de sistemas de recursos hídricos, que utiliza um algoritmo de rede de fluxo afim de otimizar a alocação de água. A formulação utilizando programação linear permite a análise global do sistema e por isso, espera-se melhor aproveitamento da água disponível, seja no menor déficit de atendimento às demandas ou maior armazenamento nos reservatórios. A programação linear com utilização de métodos de pontos interiores é atualmente uma técnica bastante conhecida e bem desenvolvida. Existem vários pacotes computacionais gratuitos com implementações eficientes dos métodos de pontos interiores que motivaram sua utilização neste trabalho. / This work presents an optimization tool for analyzing the problems of water allocation in watersheds by utilizing techniques of linear and piecewise linear programming integrated to a pattern of stream flow routing. The optimization is done in a global way with the usage of linear programming packages based upon the Internal Point Methods. The methodology of the usage consists in the acquirement of an optimal solution for situation of insufficient water availability for all conflicting consumptions from the watershed. The tool is being attached and incorporated to AcquaNet, which is a decision support system (DSS) for analysis of water resources systems that utilizes a network flow algorithm, with the purpose of optimizing the water allocation. The formulation that uses the linear programming leads to the analysis of the system as a whole and for this reason it is expected a better usage of the available water with a lower deficit in the supply or a greater storage in the reservoirs. Linear Programming with Internal Point Methods is nowadays a well known and very well developed technique. There are several computational packages with efficient implementations of the Internal Points Methods freely available, and that, has brought great motivation in its usage in the present work.

Neste trabalho é apresentada uma ferramenta de otimização para análise de problemas de alocação de água em bacias hidrográficas utilizando técnicas de programação linear e linear por partes, integradas a um modelo de amortecimentos de ondas em canais. A otimização é feita de forma global, com uso de softwares de programação linear baseados nos métodos de pontos interiores. A metodologia de uso do sistema consiste em se obter uma solução ?ótima? para situações de disponibilidade de água insuficiente a todos os usos conflitantes na bacia. A ferramenta está sendo acoplada e incorporada ao AcquaNet, um Sistema de Suporte a Decisões (SSD) para análise de sistemas de recursos hídricos, que utiliza um algoritmo de rede de fluxo afim de otimizar a alocação de água. A formulação utilizando programação linear permite a análise global do sistema e por isso, espera-se melhor aproveitamento da água disponível, seja no menor déficit de atendimento às demandas ou maior armazenamento nos reservatórios. A programação linear com utilização de métodos de pontos interiores é atualmente uma técnica bastante conhecida e bem desenvolvida. Existem vários pacotes computacionais gratuitos com implementações eficientes dos métodos de pontos interiores que motivaram sua utilização neste trabalho. / This work presents an optimization tool for analyzing the problems of water allocation in watersheds by utilizing techniques of linear and piecewise linear programming integrated to a pattern of stream flow routing. The optimization is done in a global way with the usage of linear programming packages based upon the Internal Point Methods. The methodology of the usage consists in the acquirement of an optimal solution for situation of insufficient water availability for all conflicting consumptions from the watershed. The tool is being attached and incorporated to AcquaNet, which is a decision support system (DSS) for analysis of water resources systems that utilizes a network flow algorithm, with the purpose of optimizing the water allocation. The formulation that uses the linear programming leads to the analysis of the system as a whole and for this reason it is expected a better usage of the available water with a lower deficit in the supply or a greater storage in the reservoirs. Linear Programming with Internal Point Methods is nowadays a well known and very well developed technique. There are several computational packages with efficient implementations of the Internal Points Methods freely available, and that, has brought great motivation in its usage in the present work.