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Hydrological modeling is essential for a variety of water management challenges, from natural stream restoration to urban flood control. The widespread availability of high-frequency and/or high-resolution remotely sensed data provides an opportunity to improve hydrological modeling. While incorporating large amounts of data is computationally intensive, tools that distill information from remote sensing into useful empirical relationships, simple tools, or summary parameters allow for greater uptake in situations when resources are limited or practitioners prefer a simpler or quicker method.This dissertation approaches surface water modeling using simple process-based analytical and empirical models and remotely sensed data. High-resolution imagery is used to examine empirical relationships between in-channel wood length and channel width and characterize the differences in the role of large wood in spring-fed and runoff-fed streams. A model of overland flow on convergent/divergent surfaces is presented and verified via numerical and laboratory techniques. This method is then applied to examine the limits of applicability of the Rational Method, one of the most widely-recommended tools for predicting peak flows, in terms of the fundamental mathematical assumptions. This work identifies landscape properties that cause the Rational Method to perform poorly under idealized conditions and presents a framework for applying the Rational Method as an optimization.

Over the past decade, there has been appreciable progress towards modeling the water, energy, and carbon cycles at field scales (10–100 m) over continental to global extents in Earth system models (ESMs). One such approach, named HydroBlocks, accomplishes this task while maintaining computational efficiency via Hydrologic Response Units (HRUs), more commonly known as “tiles” in ESMs. In HydroBlocks, these HRUs are learned via a hierarchical clustering approach from available global high-resolution environmental data. However, until now there has yet to be a river routing approach that is able to leverage HydroBlocks' approach to modeling field-scale heterogeneity; bridging this gap will make it possible to more formally include riparian zone dynamics, irrigation from surface water, and interactive floodplains in the model. This paper introduces a novel dynamic river routing scheme in HydroBlocks that is intertwined with the modeled field-scale land surface heterogeneity. Each macroscale polygon (a generalization of the concept of macroscale grid cell) is assigned its own fine-scale river network that is derived from very high resolution (∼ 30 m) digital elevation models (DEMs); the inlet–outlet reaches of a domain's macroscale polygons are then linked to assemble a full domain's river network. The river dynamics are solved at the reach-level via the kinematic wave assumption of the Saint-Venant equations. Finally, a two-way coupling between each HRU and its corresponding fine-scale river reaches is established. To implement and test the novel approach, a 1.0∘ bounding box surrounding the Atmospheric Radiation and Measurement (ARM) Southern Great Plains (SGP) site in northern Oklahoma (United States) is used. The results show (1) the implementation of the two-way coupling between the land surface and the river network leads to appreciable differences in the simulated spatial heterogeneity of the surface energy balance, (2) a limited number of HRUs (∼ 300 per 0.25∘ cell) are required to approximate the fully distributed simulation adequately, and (3) the surface energy balance partitioning is sensitive to the river routing model parameters. The resulting routing scheme provides an effective and efficient path forward to enable a two-way coupling between the high-resolution river networks and state-of-the-art tiling schemes in ESMs.

Existing dynamical systems for day-to-day departure time choice are either unstable, or stable but assuming drivers to possess complete information and make decisions on both arrival and departure times. In this paper, we present a new dynamical system with local shifting of departure times, such that a driver only defers or advances his/her departure time to a time interval later or earlier with lower costs. We establish the asymmetrical upper bounds of the deferral and advance coefficients for the discrete model to be well-defined. We then derive the continuous version as a kinematic wave model and present some examples of symmetrical deferral and advance coefficients. We demonstrate that the stationary state of the dynamical system is the same as the user equilibrium, and the user equilibrium is proved with Lyapunov's second method to be stable for the symmetrical deferral and advance coefficients. With numerical examples, we verify the analytical results and examine the model's sensitivity to different factors with different combinations of heuristic asymmetrical coefficients and theoretically stable symmetrical coefficients. Both analytical and numerical results confirm that the new dynamical system is asymptotically stable in a stability region. This study provides some guidelines on how to derive new day-to-day dynamical system models of departure time user equilibrium. Such a dynamical system can potentially be applied to solve the general dynamic traffic assignment problem in the future.

This paper studies a stochastic model that describes the evolution of vehicle densities in a road network. It is consistent with the class of (deterministic) kinematic wave models, which describe traffic flows based on conservation laws that incorporate the macroscopic fundamental diagram (a functional relationship between vehicle density and flow). Our setup is capable of handling multiple types of vehicle densities, with general macroscopic fundamental diagrams, on a network with arbitrary topology. Interpreting our system as a spatial population process, we derive, under natural scaling, fluid, and diffusion limits. More specifically, the vehicle density process can be approximated with a suitable Gaussian process, which yield accurate normal approximations to the joint (in the spatial and temporal sense) vehicle density process. The corresponding means and variances can be computed efficiently. Along the same lines, we develop an approximation to the vehicles’ travel time distribution between any given origin and destination pair. Finally, we present a series of numerical experiments that demonstrate the accuracy of the approximations and illustrate the usefulness of the results.

The storage function model (SFM) is a rainfall–runoff model widely used in Korea for flood forecasting and warning systems. The traditional equations for parameter estimation are based on observed ...

The characteristics of overland flow resulting from a uniform rainfall intensity on an impervious sloping plane are investigated. The characteristic solution of the one dimensional unsteady nonuniform flow equations with the kinematic wave approximation applied to the momentum equation is used. The influence of the different overland flow parameters on the synthesized hydrograph, the peak runoff discharge, and the time taken to reach equilibrium is studied for the case of turbulent flow. The overland flow parameters include the slope and the length of the plane, the surface resistance, and the uniform rainfall intensity. A dimensionless peak runoff hydrograph is determined and compared with both Izzard's experimental dimensionless hydrograph and the dimensionless hydrograph determined by the finite difference solution of the full dynamic form of the momentum equation.

The kinematic-wave theory of particle settling in tube centrifuges has become a subject of scientific discussion. Specifically, the common assumption was made that the flow in a rotating tube of large length/diameter ratio can be treated in one-dimensional approximation. The respective results have been found in agreement with measurements. However, an analysis of the two-dimensional settling process performed in the limit of vanishing particle concentration led to some results that are not in accordance with the one-dimensional flow approximation, irrespective of the length/diameter ratio. It is the aim of the present investigation to gain a better understanding of the process. According to the analysis presented here, quasi-one-dimensional kinematic waves are embedded in a two-dimensional bulk flow that is governed by the continuity equation for the mixture plus the boundary conditions at the walls of the tube. The results based on simplification assumptions are compared with those of the one-dimensional flow approximation. Limiting cases, based on an elaborate analysis of three distinct settling models, are investigated analytically, and the plausibility of some of the respective results is evaluated also in the context of the one-dimensional approximation. Experimental observations, reported in the time span 2001 through 2008, are compared with analytical results obtained and presented. Further experimental work beyond this time span is also analyzed.

The recent influx of remote sensing data provides new opportunities for quantifying spatiotemporal variations in glacier surface velocity and elevation fields. Here, we introduce a flexible time series reconstruction and decomposition technique for forming continuous, time-dependent surface velocity and elevation fields from discontinuous data and partitioning these time series into short- and long-term variations. The time series reconstruction consists of a sparsity-regularized least squares regression for modeling time series as a linear combination of generic basis functions of multiple temporal scales, allowing us to capture complex variations in the data using simple functions. We apply this method to the multitemporal evolution of Sermeq Kujalleq (Jakobshavn Isbrae), Greenland. Using 555 ice velocity maps generated by the Greenland Ice Mapping Project and covering the period 2009–2019, we show that the amplification in seasonal velocity variations in 2012–2016 was coincident with a longer-term speedup initiating in 2012. Similarly, the reduction in post-2017 seasonal velocity variations was coincident with a longer-term slowdown initiating around 2017. To understand how these perturbations propagate through the glacier, we introduce an approach for quantifying the spatially varying and frequency-dependent phase velocities and attenuation length scales of the resulting traveling waves. We hypothesize that these traveling waves are predominantly kinematic waves based on their long periods, coincident changes in surface velocity and elevation, and connection with variations in the terminus position. This ability to quantify wave propagation enables an entirely new framework for studying glacier dynamics using remote sensing data.

This research concerns about the development and application of Variable Parameter Kinematic Wave Numerical model (VPKWM) based on 1-D Saint-Venant equation, to study the behaviour of the propagation of a flood wave in Non-prismatic natural waterways in an ungauged basin. The channel slope and wetted perimeter are considered as variable because of the irregularity of the boundary of the channel and the change in magnitude of discharge. The scarcity of reliable inflow data at upstream is a serious problem for the flood routing process in an ungauged basin. In this study the inflow hydrograph and lateral inflow hydrographs are obtained using SCS-CN method as rainfall runoff model. The performance of the model assessed considering four parameters such as root mean square error (RMSE), peak discharge, peak time and total volume. The results indicated that the VPKWM for non-prismatic channel provided reasonable output compared with the observed data.

Predicting the behavior of overland flow with analytical solutions to the kinematic wave equation is appealing due to its relative ease of implementation. Such simple solutions, however, have largely been constrained to applications on simple planar hillslopes. This study presents analytical solutions to the kinematic wave equation for hillslopes with modest topographic curvature that causes divergence or convergence of runoff flowpaths. The solution averages flow depths along changing hillslope contours whose lengths vary according hillslope width function, and results in a one‐dimensional approximation to the two‐dimensional flow field. The solutions are tested against both two‐dimensional numerical solutions to the kinematic wave equation (in ParFlow) and against experiments that use rainfall simulation on machined hillslopes with defined curvature properties. Excellent agreement between numerical, experimental and analytical solutions is found for hillslopes with mild to moderate curvature. The solutions show that curvature drives large changes in maximum flow rate q peak and time of concentration t c , predictions frequently used in engineering hydrologic design and analysis.

An increase in developmental activities such as afforestation, paved surfaces and construction of buildings and other structures leads to an increase in surface runoff and peak discharge from the watershed. These all cause a decrease in detention storage and surface depression and thus diminish the concentration time that flow will take and distributes flow to the adjoining stream quickly rather than that would have taken before development or urbanization. Despite the importance of time of concentration, planners and engineers are often puzzled by different profiles of the channels and their equation available in the literature without knowing the accuracy of each formula. In this paper, kinematic wave theory integrated with the Manning’s equation has been applied for the comparative assessment of the performance of the various cross-sectional channels. The result of different channel profiles toward travel time of flow has been matched for nine channel profiles. Of the nine channel profiles, it was found that the deep rectangular cross-sectional channel possesses the highest time of travel. Therefore, the use of deep rectangular channel yields lesser watershed runoff. The parabolic channel with more depth yields the lesser time of travel; therefore, the use of parabolic channel profile yields larger watershed runoff.

Surface flow and subsurface flow constitute a naturally linked hydrologic continuum that has not traditionally been simulated in an integrated fashion. Recognizing the interactions between these systems has encouraged the development of integrated hydrologic models (IHMs) capable of treating surface and subsurface systems as a single integrated resource. IHMs are dynamically evolving with improvements in technology, and the extent of their current capabilities are often only known to the developers and not general users. This article provides an overview of the core functionality, capability, applications, and ongoing development of one open-source IHM, ParFlow. ParFlow is a parallel, integrated, hydrologic model that simulates surface and subsurface flows. ParFlow solves the Richards equation for three-dimensional variably saturated groundwater flow and the two-dimensional kinematic wave approximation of the shallow water equations for overland flow. The model employs a conservative centered finite-difference scheme and a conservative finite-volume method for subsurface flow and transport, respectively. ParFlow uses multigrid-preconditioned Krylov and Newton–Krylov methods to solve the linear and nonlinear systems within each time step of the flow simulations. The code has demonstrated very efficient parallel solution capabilities. ParFlow has been coupled to geochemical reaction, land surface (e.g., the Common Land Model), and atmospheric models to study the interactions among the subsurface, land surface, and atmosphere systems across different spatial scales. This overview focuses on the current capabilities of the code, the core simulation engine, and the primary couplings of the subsurface model to other codes, taking a high-level perspective.

Sequential segmentation of the body axis is fundamental to vertebrate embryonic patterning. This relies on the segmentation clock, a multi-cellular oscillating genetic-network, which mainifests as tissue-level kinematic waves of gene expression that arrest at the position of each new segment. How this hallmark wave pattern is generated is an open question. We compare cellular-resolution oscillatory patterns in the embryo to those generated cell-autonomously in culture without extrinsic signals. We find striking similarity, albeit with greater variability in the timing of clock arrest in culture. Our simple physical description of a clock controlled by a noisy cell-intrinsic timer captures these dynamics. We propose the segmentation clock integrates an intrinsic, timer-driven oscillatory program, which underlies the waves and arrest, with extrinsic cues regulating the intrinsic timer’s duration and precision.One-sentence SummarySegmentation clock and wavefront activities underlying tissue-level wave patterns are cell-autonomous properties in the PSM.

DQM has found increasing use in recent years in Hydraulic Engineering, because it is an alternative approach to the standard methods such as Finite Difference Method, Finite Element Method and Finite Volume Method. From the previous applications of DQM in different engineering fields, it is seen that the results of DQM are converged rapidly and closer to analytical solutions than other numerical solutions. A similar consequence is observed in an application of Hydraulic Engineering (Kaya et al., 2010). The St. Venant equations that are written for an unsteady open channel flow under some acceptance can be translated to linear form, and then can be solved by numerical solution methods. In this study, DQM were employed for one-dimensional, gradually varied, unsteady open-channel flows. The DQM results were compared with the results using the FDMs and FVMs. It is obvious from the examples given above that the DQM results are closer to the measurements than the other numerical methods. In calculations making use of 1978 Murumbidgee River flood data, the DQM’s RMS error values are less than nonlinear solution results in Sivapalan et al. (1997); On the contrary, in calculations of 1983 flood, that is bigger. Yet, for a linear solution performed in this study, the DQM’s RMS error values are less than other numerical methods. In contrast to the FDM and FVM, in the DQM, a small number of grid points are sufficient for a stable solution. The results of FDMs and FVMs are converged from 2000 at t direction, but this value is 25 in DQM. Determining the weight coefficients is the most crucial step in the use of DQM. In wave propagation problems in open channels, by making use of Legendre polynomials for weight coefficients and Chebyshev-Gauss-Lobatto points for the numerical discretization, the results can be obtained closer to an analytical solution (Kaya, 2010).

The kinematic wave theory is widely used to simulate traffic flows on road segments. Link transmission models are methods to find a solution to the kinematic wave model, however, their computational efficiency heavily relies on the shape of the fundamental diagram that is used as input. Despite the limitations and drawbacks of triangular and piecewise linear fundamental diagrams, they remain popular because they result in highly efficient algorithms. Using smooth nonlinear branches is often preferred in terms of realism and other desirable properties, but this comes at a significantly higher computational cost and requires time discretization to find an approximate solution. In this paper we consider a nonlinear fundamental diagram as input and propose on-the-fly multi-step linearization techniques to simplify expansion fans. This leads to two simplified link transmission models that can be solved exactly in continuous time under the assumption of piecewise stationary travel demand. One of the models simplifies to shockwave theory in case of a single step. We show that embedding shockwave theory in the link transmission model allows for finding an exact solution in continuous time and we discuss the potential for the design of efficient event-based algorithms for general networks.

In this paper a novel solution algorithm is proposed for solving general first order dynamic network loading (DNL) problems in general transport networks. This solution algorithm supports any smooth non-linear two regime concave fundamental diagram and adopts a simplified fanning scheme. It is termed eGLTM (event-based General Link Transmission Model) and is based on a continuous-time formulation of the kinematic wave model that adapts shockwave theory to simplify expansion fans. As the name suggests eGLTM is a generalisation of eLTM, which is a special case that solves the simplified first order model assuming a triangular fundamental diagram. We analyse the impact of modelling delay in the hypocritical branch of the fundamental diagram to assess the differences between the two models. In addition, we propose an additional stream of mixture events to propagate multi-commodity flow in event based macroscopic models, which makes both eLTM and eGLTM suitable for dynamic traffic assignment (DTA) applications. The proposed solution scheme can yield exact solutions as well as approximate solutions at a significantly lesser cost. The efficiency of the model is demonstrated in a number of case studies. Furthermore, different settings for our simplified fanning scheme are investigated as well as an extensive analysis on the effect of including route choice on the algorithms computational cost. Finally, a large scale case study is conducted to investigate the suitability of our newly proposed model in a practical context and assess its efficiency. In this study comparisons between eLTM and eGLTM are included to demonstrate the impact of aforementioned generalisation as well as the multi-commodity extension that is proposed.

This study develops and analyses the centralised and decentralised solution procedures for urban network traffic management through an optimal control framework. The optimal control is formulated based upon the Hamilton-Jacobi formulation of kinematic wave model. Following the problem decomposition under the decentralised scheme, we introduce the use of semi-analytical performance derivatives when developing the decentralised solution algorithm. The proposed control strategies are applied to a set of test scenarios constructed from a real road network in Central London in the UK. Specific interests in the investigation include comparison of the performance gain and computational effort of the two strategies under different circumstances. We also investigate effect of network decomposition strategies on the performance of the solution algorithm. This study generates insight on urban traffic management with use of traffic flow theory, decentralised optimisation, and network decomposition techniques.

This study is an attempt to establish a suitable speed–density functional relationship for heterogeneous traffic on urban arterials. The model must reproduce the traffic behaviour on traffic stream and satisfy all static and dynamic properties of speed–flow–density relationships. As a first attempt for Indian traffic condition, two behavioural parameters, namely the kinematic wave speed at jam (C j) and a proposed saturation flow (λ), are estimated using empirical observations. The parameter C j is estimated by developing a relationship between driver reaction time and vehicle position in the queue at the signalised intersection. Functional parameters are estimated using Levenberg–Marquardt algorithm implemented in the R statistical software. Numerical measures such as root mean squared error, average relative error and cumulative residual plots are used for assessing models fitness. We set out several static and dynamic properties of the flow–speed–density relationships to evaluate the models, and these properties equally hold good for both homogenous and heterogeneous traffic states. From the numerical analysis, it is found that very few models replicate empirical speed–density data traffic behaviour. However, none of the existing functional forms satisfy all the properties. To overcome the shortcomings, we proposed two new speed–density functional forms. The uniqueness of these models is that they satisfy both numerical accuracy and the properties of fundamental diagram. These new forms would certainly improve the modelling accuracy, especially in dynamic traffic studies when coupling with dynamic speed equations.

Sediment mass conservation is a key factor that constrains river morphodynamic processes. In most models of river morphodynamics, sediment mass conservation is described by the Exner equation, which may take various forms depending on the problem in question. One of the most widely used forms of the Exner equation is the flux-based formulation, in which the conservation of bed material is related to the stream-wise gradient of the sediment transport rate. An alternative form of the Exner equation, however, is the entrainment-based formulation, in which the conservation of bed material is related to the difference between the entrainment rate of bed sediment into suspension and the deposition rate of suspended sediment onto the bed. Here we represent the flux form in terms of the local capacity sediment transport rate and the entrainment form in terms of the local capacity entrainment rate. In the flux form, sediment transport is a function of local hydraulic conditions. However, the entrainment form does not require this constraint: only the rate of entrainment into suspension is in local equilibrium with hydraulic conditions, and the sediment transport rate itself may lag in space and time behind the changing flow conditions. In modeling the fine-grained lower Yellow River, it is usual to treat sediment conservation in terms of an entrainment (nonequilibrium) form rather than a flux (equilibrium) form, in consideration of the condition that fine-grained sediment may be entrained at one place but deposited only at some distant location downstream. However, the differences in prediction between the two formulations have not been comprehensively studied to date. Here we study this problem by comparing the results predicted by both the flux form and the entrainment form of the Exner equation under conditions simplified from the lower Yellow River (i.e., a significant reduction of sediment supply after the closure of the Xiaolangdi Dam). We use a one-dimensional morphodynamic model and sediment transport equations specifically adapted for the lower Yellow River. We find that in a treatment of a 200 km reach using a single characteristic bed sediment size, there is little difference between the two forms since the corresponding adaptation length is relatively small. However, a consideration of sediment mixtures shows that the two forms give very different patterns of grain sorting: clear kinematic waves occur in the flux form but are diffused out in the entrainment form. Both numerical simulation and mathematical analysis show that the morphodynamic processes predicted by the entrainment form are sensitive to sediment fall velocity. We suggest that the entrainment form of the Exner equation might be required when the sorting process of fine-grained sediment is studied, especially when considering relatively short timescales.

In the literature, many kinematic wave models have been proposed for multi-class vehicles on multi-lane roads; however, there lacks an explicit model of unifiable multi-commodity traffic, in which different commodity flows can have different speeds and violate the first-in-first-out (FIFO) principle, but there exists a speed-density relation for the total traffic. In this study, we attempt to fill the gap by constructing and solving a unifiable multi-commodity kinematic wave model. We first construct commodity speed-density relations based on generic generating functions. Then for two commodities we discuss the properties of the unifiable kinematic wave model and analytically solve the Riemann problem with a combination of total and commodity kinematic waves. We propose a unifiable multi-commodity Cell Transmission Model (CTM) with a general junction model for numerical simulations of network traffic flows, which are unifiable but may violate the FIFO principle. We prove that the CTM is well-defined under an extended CFL (Courant et al., 1928) condition. With examples we verify the consistency between the analytical and numerical solutions and demonstrate the convergence of the CTM. We conclude with several follow-up research directions for unifiable multi-commodity kinematic wave models.

Submitted by Aline Batista (alinehb.ufpel@gmail.com) on 2021-05-07T11:14:24Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_Marcelle_Martins_Vargas.pdf: 8628354 bytes, checksum: 29b30b20f685d35e584424cff6478fb3 (MD5) Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2021-05-08T13:49:58Z (GMT) No. of bitstreams: 2 Dissertacao_Marcelle_Martins_Vargas.pdf: 8628354 bytes, checksum: 29b30b20f685d35e584424cff6478fb3 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Made available in DSpace on 2021-05-08T13:49:58Z (GMT). No. of bitstreams: 2 Dissertacao_Marcelle_Martins_Vargas.pdf: 8628354 bytes, checksum: 29b30b20f685d35e584424cff6478fb3 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2021-02-25 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES Diante da situação atual de uso e gestão dos recursos hídricos, a importância de estudos em bacias hidrográficas é imprescindível para subsidiar projetos e, quando for o caso, também comitês e planos de bacias hidrográficas. Para tal, modelos hidrológicos são fortemente recomendados e, dentre os modelos, o Lavras Simulation of Hydrology (LASH) tem sido utilizado com sucesso em bacias hidrográficas brasileiras. A principal contribuição deste estudo foi implementar o modelo LASH em linguagem MATrix LABoratory (MATLAB®), aprimorar seus módulos de propagação de cheias em rios e de calibração, e testá-lo como estudo de caso na bacia hidrográfica do rio Camaquã (BHRC), a qual possui um comitê e um plano de bacias hidrográficas associado. No capítulo 1, foram exploradas a concepção do LASH em MATLAB®, a implementação do módulo de propagação de vazões em rios de acordo com o método da Onda Cinemática e a inserção de um algoritmo de calibração multiobjetivo, o A Multi-Algorithm Genetically Adaptive Multiobjective (AMALGAM). Ao contrário do capítulo 1, em que foi realizada uma abordagem mais técnica e computacional, o capítulo 2 foi pautado na aplicação do LASH estruturado em MATLAB®, tendo como estudo de caso a BHRC. E ainda, dois cenários de calibração foram avaliados: i) cenário 1: parâmetros calibráveis do LASH concentrados e; ii) cenário 2: espacialização dos parâmetros lambda (λ) e tempo de resposta do reservatório superficial (CS) por sub-bacia. Os resultados do capítulo 1 permitiram constatar os ganhos da estruturação do modelo em linguagem MATLAB®, principalmente no que concerne: i) ao módulo de propagação da onda de cheias baseado na Onda Cinemática; ii) à facilidade do acoplamento do algoritmo de calibração multiobjetivo AMALGAM; iii) aos artifícios computacionais implementados para otimizar o tempo de processamento do modelo; e iv) à facilidade de alteração, atualização e ampliação do script, sendo o grande gargalo da implementação do LASH em MATLAB®. No tocante aos resultados do capítulo 2, estes foram satisfatórios e foi possível inferir que: i) a formulação do LASH em MATLAB® trouxe uma melhoria do módulo de propagação de vazões em rios, adicionando uma estrutura com viés mais hidráulico ao modelo, e viabilizou a implementação do cenário 2; ii) o cenário 2 permitiu realizar discussões acerca da heterogeneidade de regiões presentes na BHRC e do impacto das espacialização dos parâmetros λ e CS sobre a modelagem hidrológica na BHRC, sendo uma ferramenta poderosa na gestão dos recursos hídricos; iii) a implementação do AMALGAM permitiu conduzir comparações em relação ao Shuffled Complex Evolution (SCE-UA), e apresentou ligeira superioridade nas calibrações para as funções objetivo utilizadas; iv) a utilização do AMALGAM tem potencial para diminuir as incertezas e equifinalidade relacionadas aos parâmetros calibráveis do LASH; e v) a formulação do LASH em MATLAB® trouxe excelentes ganhos, em termos de execução computacional. In view of the current situation of water resources management, studies on watersheds are essential for supporting projects and, when applicable, watershed committees and master plans. In this sense, hydrological models are strongly recommended and, among them, the Lavras Simulation of Hydrology (LASH) has been successfully used in Brazilian watersheds. The main contribution of this study was the implementation of the LASH model in MATrix LABoratory language (MATLAB®), enhancement of its river routing and calibration modules, and its evaluation taking the Camaquã river watershed (CRW) as a case study, which has a watershed committee and a watershed master plan. Chapter 1 addressed technical and computational issues, such as the development of the LASH in MATLAB®, implementation of the river routing module according to the Kinematic Wave method and the insertion of a multi-objective optimization algorithm, known as A Multi-Algorithm Genetically Adaptive Multiobjective (AMALGAM). On the other hand, chapter 2 focused on the evaluation of LASH coded in MATLAB® taking CRW as a case study. Furthermore, two calibration schemes were considered in this study: i) scheme 1: all the LASH parameters were calibrated following a lumped scheme and; ii) scheme 2: two parameters – initial abstraction coefficient (λ) and response time of the surface reservoir (CS) - were calibrated by subwatershed. The results of chapter 1 evidenced some benefits of coding the model in MATLAB® language, mainly with regard to the: i) river routing module based on the Kinematic Wave method; ii) ease of coupling the AMALGAM multi-objective calibration algorithm with LASH; iii) computational strategies applied to optimize the model's processing time; and iv) ease of editing, updating and enhancing the script, which are considered the the major strength in the implementation of LASH in MATLAB®. The results of chapter 2 were satisfactory and allowed to infer that the: i) formulation of LASH in MATLAB® improved the river routing, adding a hydraulic structure to the model, and enabled the implementation and appraisal of scheme 2; ii) scheme 2 made it possible some discussions about both the heterogeneity of regions present in CRW and the impact of spatialization of λ and CS on hydrological modeling at CRW, such that this scheme can be considered as a powerful tool for the water resources management; iii) implementation of AMALGAM along with LASH allowed comparisons between it and the Shuffled Complex Evolution (SCE-UA), such that the former algorithm presented a slightly superior performance for the objective functions used; iv) use of AMALGAM has the potential to reduce the level of uncertainties and equifinality related to the LASH calibration parameters; and v) formulation of LASH in MATLAB® brought excellent benefits in terms of computational performance.

Landscape morphology reflects drivers such as tectonics and climate but is also modulated by underlying rock properties. While geomorphologists may attempt to quantify the influence of rock strength through direct comparisons of landscape morphology and rock strength metrics, recent work has shown that the contact migration resulting from the presence of mixed lithologies may hinder such an approach. Indeed, this work counterintuitively suggests that channel slopes within weaker units can sometimes be higher than channel slopes within stronger units. Here, we expand upon previous work with 1-D stream power numerical models in which we have created a system for quantifying contact migration over time. Although previous studies have developed theories for bedrock rivers incising through layered stratigraphy, we can now scrutinize these theories with contact migration rates measured in our models. Our results show that previously developed theory is generally robust and that contact migration rates reflect the pattern of kinematic wave speed across the profile. Furthermore, we have developed and tested a new approach for estimating kinematic wave speeds. This approach utilizes channel steepness, a known base-level fall rate, and contact dips. Importantly, we demonstrate how this new approach can be combined with previous work to estimate erodibility values. We demonstrate this approach by accurately estimating the erodibility values used in our numerical models. After this demonstration, we use our approach to estimate erodibility values for a stream near Hanksville, UT. Because we show in our numerical models that one can estimate the erodibility of the unit with lower steepness, the erodibilities we estimate for this stream in Utah are likely representative of mudstone and/or siltstone. The methods we have developed can be applied to streams with temporally constant base-level fall, opening new avenues of research within the field of geomorphology.

Pedestrian flow models are useful for the design and operation of pedestrian spaces. This article describes a macroscopic model of pedestrian flows through networks composed of bidirectional corridors that are connected by multidirectional intersections. The proposed model builds on an existing pedestrian bidirectional fundamental diagram to define bidirectional sending and receiving flows, and it relies on the incremental transfer principle to model bidirectional flows across nodes with an arbitrary number of adjacent links. The model is solved in a cell-transmission formulation that is in all of its unidirectional properties consistent with the kinematic wave model. (C) 2021 The Authors. Published by Elsevier Ltd. Funding Agencies|PETRA project - European Commission [609042]

The draw resonance instability of viscoelastic Giesekus fluids was studied by correlating the spinline extensional features and transit times of several kinematic waves in an isothermal melt spinning process. The critical drawdown ratios were critically dependent on the Deborah number (De, the ratio of material relaxation time to process time) and a single material parameter (&alpha, G) of the Giesekus fluid. In the intermediate range of &alpha, G, the stability status changed distinctively with increasing De, i.e., the spinning system was initially stabilized and subsequently destabilized, as De increases. In this &alpha, G regime, the level of velocity and extensional-thickening rheological property in the spinline became gradually enhanced at low De and weakened at high De. The draw resonance onsets for different values of &alpha, G were determined precisely using a simple indicator composed of several kinematic waves traveling the entire spinline and period of oscillation. The change in transit times of kinematic waves for varying De adequately reflected the effect of &alpha, G on the change in stability.

Wildfires increase flow and sediment load through removal of vegetation, alteration of soils, decreasing infiltration, and production of ash commonly generating a wide variety of geophysical flows (i.e., hyperconcentrated flows, mudflows, debris flows, etc.). Numerical modellers have developed a variety of Non-Newtonian algorithms to simulate each of these processes, and therefore, it can be difficult to understand the assumptions and limitations in any given model or replicate work. This diversity in the processes and approach to non-Newtonian simulations makes a modular computation library approach advantageous. A computational library consolidates the algorithms for each process and discriminates between these processes and algorithms with quantitative non-dimensional thresholds. This work presents a flexible numerical library framework (DebrisLib) to simulate large-scale, post-wildfire, non-Newtonian geophysical flows using both kinematic wave and shallow-water models. DebrisLib is derived from a variety of non-Newtonian closure approaches that predict a range of non-Newtonian flow conditions. It is a modular code designed to operate with any Newtonian, shallow-water parent code architecture. This paper presents the non-Newtonian model framework and demonstrates its effectiveness by calling it from two very different modelling frameworks developed by the U.S. Army Corp of Engineers (USACE), specifically, within the one-dimensional and two-dimensional Hydrologic Engineering Centre River Analysis System (HEC-RAS) and two-dimensional Adaptive Hydraulics (AdH) numerical models. The development and linkage-architecture were verified and validated using two non-Newtonian flume experiments selected to represent a range of non-Newtonian flow conditions (i.e., hyperconcentrated flow, mudflow, debris flow) commonly associated with post-wildfire flooding.

Hydrological models apply different methods to estimate runoff and route flows. Suitability of these methods is not unique, but varies with catchment conditions. This study aims to find the suitable overland runoff and flow routing methods for a catchment in Hyderabad, India, using customised Storm Water Management Model (SWMM-C). Currently, SWMM adapts only non-linear reservoir (NLR) method to estimate overland runoff. Linear reservoir (LR) and kinematic wave overland flow (KWO) have been incorporated as additional overland runoff methods. For flow routing, SWMM currently has kinematic wave (KW) and dynamic wave (DW) methods. Muskingum, Muskingum Cunge (MC) and lag methods have been included as additional methods in this customised version. SWMM-C was calibrated with four event rainfalls and tested with six event rainfalls using all possible combinations of overland runoff and flow routing methods. Efficiency of SWMM-C in simulating runoff was evaluated using performance indices. Results showed that for low magnitude event rainfalls, NLR, LR and KWO simulated runoff with a maximum deviation of 50%, 60% and 40% from observed runoff, respectively. In high magnitude event rainfalls, NLR, LR and KWO simulated runoff with maximum deviations of 20%, 40% and 20%, respectively, from the observed runoff. It was inferred from model outputs that NLR method could simulate runoff reasonably well for rainfalls that have duration greater than the time of concentration of catchment. LR method could simulate peak runoff better. KWO method was found to be suitable for chosen catchment for all rainfall durations. Flow routing methods KW, DW and MC are found to have minor influences on the runoff.

The well-known Lighthill-Whitham-Richards (LWR) theory is the fundamental pillar for most macroscopic traffic models. In the past, many methods were developed to numerically derive solutions for LWR problems. Examples for such numerical solution schemes are the cell transmission model, the link transmission model, and the variational theory (VT) of traffic flow. So far, the latter framework found applications in the fields of traffic modelling, macroscopic fundamental diagram estimation, multi-modal traffic analyses, and data fusion. However, these studies apply VT only at the link or corridor level. To the best of our knowledge, there is no methodology yet to apply VT at the network level. We address this gap by developing a VT-based framework applicable to networks. Our model allows us to account for source terms (e.g. inflows and outflows at intersections) and the propagation of spillbacks between adjacent corridors consistent with kinematic wave theory. We show that the trajectories extracted from a microscopic simulation fit the predicted traffic states from our model for a simple intersection with both source terms and spillbacks. We also use this simple example to illustrate the accuracy of the proposed model. Additionally, we apply our model to the Sioux Falls network and again compare the results to those from a microscopic simulation. Our results indicate a close fit of traffic states, but with substantially lower computational cost. The developed methodology is useful for network-wide traffic state estimations in real-time, or other applications within a model-based optimization framework.