Testing the anelastic nonhydrostatic model EULAG as a prospective dynamical core of a numerical weather prediction model Part I: Dry benchmarks

In this paper, a feasibility of anelastic approach for numerical weather prediction (NWP) is examined. The study concerns the anelastic nonhydrostatic model EULAG as a prospective candidate for the new dynamical core of a high-resolution NWP model. Such an application requires a series of benchmark tests to be performed. The study presents the results of dry idealized two-dimensional linear and non-linear tests. They include evolution of cold and warm density currents in neutrally stratified atmosphere, inertia-gravity waves in short and long channels, as well as mountain gravity waves for a set of different flow regimes. Detailed comparison of the results with the reference solutions, based mainly on the results of compressible models, indicates a high level of conformity for all of the experiments. It verifies the anelastic approach as strongly consistent with the compressible one for a broad class of atmospheric problems. It also corroborates the robustness of EULAG numerics, an essential requirement of dynamical core of NWP model.     

Evaluating a new landform evolution model: A case study using a proposed mine rehabilitation landform

Landform evolution models are powerful tools for determining long-term erosional stability and denudation rates spanning geological timescales. SIBERIA, CAESAR and CHILD are examples of these model. The newly developed State Space Soil Production and Assessment Model (SSSPAM) coupled soilscape-landform evolution model has the ability to assess overall erosion rates of catchment scale landforms either using short-term precipitation events, variable precipitation or time-averaged precipitation (annual average). In addition, SSSPAM has the capability of developing the subsurface soil profile through weathering and armouring. In SSSPAM, physical processes of pedogenesis such as erosion and armouring, diffusion, sediment deposition and weathering are modelled using a state space matrix approach. In this article we simulate the short-term evolution (100 years) of a proposed post-mining landform using both SIBERIA and SSSPAM and compare the erosion and sediment output results. For the short-term simulations SSSPAM's armouring capability was disabled. The models were then used to simulate the evolution of the catchment for 10,000 years. Results demonstrate that the short-term SSSPAM simulation results compare well with the results from the established landform evolution model SIBERIA. The long-term armouring disabled SSSPAM simulations produces simulated erosion rates comparable with SIBERIA simulations both of which are similar to upper limit of field measured denudation rates. The SSSPAM simulation using armouring demonstrated that armouring reduced the erosion rate of the catchment by a factor of 4 which is comparable with the lower limit of field measured denudation rates. This observation emphasizes the importance of armouring in long-term evolution of landforms. Soil profile cross-sections developed from the same results show that SSSPAM can also reproduce subsurface soil evolution and stratification and spatial variability of soil profile characteristics typically observed in the field.     

Understanding river dune splitting through flume experiments and analysis of a dune evolution model

Forecasts of water level during river floods require accurate predictions of the evolution of river dune dimensions, because the hydraulic roughness of the main channel is largely determined by the bed morphology. River dune dimensions are controlled by processes like merging and splitting of dunes. Particularly the process of dune splitting is still poorly understood and – as a result – not yet included in operational dune evolution models. In the current paper, the process of dune splitting is investigated by carrying out laboratory experiments and by means of a sensitivity analysis using a numerical dune evolution model. In the numerical model, we introduced superimposed TRIAS ripples (i.e. triangular asymmetric stoss side‐ripples) on the stoss sides of underlying dunes as soon as these stoss sides exceed a certain critical length. Simulations with the model including dune splitting showed that predictions of equilibrium dune characteristics were significantly improved compared to the model without dune splitting. As dune splitting is implemented in a parameterized way, the computational cost remains low which means that dune evolution can be calculated on the timescale of a flood wave. Subsequently, we used this model to study the mechanism of dune splitting. Literature showed that the initiation of a strong flow separation zone behind a superimposed bedform is one of the main mechanisms behind dune splitting. The flume experiments indicated that besides its height also the lee side slope of the superimposed bedform is an important factor to determine the strength of the flow separation zone and therefore is an important aspect in dune splitting. The sensitivity analysis of the dune evolution model showed that a minimum stoss side length was required to develop a strong flow separation zone. Copyright © 2014 John Wiley & Sons, Ltd.     

Three-dimensional numerical model for the evolution of convection in a layer of a viscous fluid with six floating continents

A three-dimensional model is developed for describing the long-term evolution of the mantle convection with six continents, which includes the formation and breakup of a supercontinent. In contrast to the theory of floating continents [Trubitsyn, 2000; 2008], in which the drift was calculated from a system of convection equations for the mantle and the Euler equations for the continents, in the present work the continental motion is described in terms of a set of floating markers, which have anomalously high viscosity and are driven by the currents.     

RC structures cyclic behavior simulation with a model integrating plasticity,damage, and bond‐slip

The behavior of reinforced concrete structures under severe demands, as strong ground motions, is highly complex; this is mainly due to the complexity of concrete behavior and to the strong interaction between concrete and steel, with several coupled failure modes. On the other hand, given the increasing awareness and concern on the worldwide seismic risk, new developments have arisen in earthquake engineering; nonetheless, some developments are mainly based on simple analytical tools that are widely used, given their moderate computational cost. This research aims to provide a solid basis for validation and calibration of such developments by using computationally efficient continuum mechanics‐based tools. Within this context, this paper presents a model for 3D simulation of cyclic behavior of RC structures. The model integrates a bond‐slip model developed by one of the authors and the damage variable evolution methodology for concrete damage plastic model developed by some authors. In the integrated model, a new technique is derived for efficient 3D analysis of bond‐slip of 2 or more crossing reinforcing bars in beam‐column joints, slabs, footings, pile caps, and other similar members. The analysis is performed by implementing the bond‐slip model in a user element subroutine of Abaqus and the damage variable evolution methodology in the original concrete damage plastic model in the package. Two laboratory experiments consisting of a column and a frame subjected to cyclic displacements up to failure are simulated with the proposed formulation.     

Parameterized thermal model of a mixed mantle convection

IntroductionTectonicevolutionisinfluencedbythermalhistoryoftheEarth.TheEarthhasabout4.6Gahistory.ThermalenergyfromtheinterioroftheEachprovidesthemainpowerfortectonicevolution.ItnotonlycontrolstheformationofthelayeredstructuresinsidetheEarth,butalsopromotesthetectonicmovementsofthesurfaceplatesduringthegeologicalera.ThestudyofthethermalhistoryoftheEarthhaspassedseveralstages.Inearlystudies,onlyconductivemechanism(Lubimova,1958)isdiscussedinthethermalevolution.However,theimpotalceofthermalco…     

Calibration of a numerical ionospheric model with EISCAT observations

A set of EISCAT UHF and VHP observations is used for calibrating a coupled fluid-kinetic model of the ionosphere. The data gathered in the period 1200–2400 UT on 24 March 1995 had various intervals of interest for such a calibration. The magnetospheric activity was very low during the afternoon, allowing for a proper examination of a case of quiet ionospheric conditions. The radars entered the auroral oval just after 1900 UT: a series of dynamic events probably associated with rapidly moving auroral arcs was observed until after 2200 UT. No attempts were made to model the dynamical behaviour during the 1900–2200 UT period. In contrast, the period 2200–2400 UT was characterised by quite steady precipitation: this latter period was then chosen for calibrating the model during precipitation events. The adjustment of the model on the four primary parameters observed by the radars (namely the electron concentration and temperature and the ion temperature and velocity) needed external inputs (solar fluxes and magnetic activity index) and the adjustments of a neutral atmospheric model in order to reach a good agreement. It is shown that for the quiet ionosphere, only slight adjustments of the neutral atmosphere models are needed. In contrast, adjusting the observations during the precipitation event requires strong departures from the model, both for the atomic oxygen and hydrogen. However, it is argued that this could well be the result of inadequately representing the vibrational states of N₂ during precipitation events, and that these factors have to be considered only as ad hoc corrections.     

Predictive uncertainty of a nearshore bed evolution model

Predictions of nearshore depth evolution using process-based numerical simulation models contain inherent uncertainties owing to model structural deficiencies, measurement errors, and parameter uncertainty. This paper quantifies the parameter-induced predictive uncertainty of the cross-shore depth evolution model Unibest-TC by applying the Bayesian Generalised Likelihood Uncertainty Estimation methodology to modelling depth evolution at Egmond aan Zee (Netherlands). This methodology works with multiple sets of parameter values sampled uniformly in feasible parameter space and assigns a likelihood value to each parameter set. Acceptable simulations (i.e., based on parameter sets with a nonzero likelihood) were found for a wide range of parameter values owing to parameter interdependence and insensitivity. The 95% uncertainty prediction interval of bed levels after the 33 days prediction period was largest (0.5–1 m) near the sandbar crests that characterize the Egmond depth profile, reducing to near-zero values in the sandbar troughs and the offshore area. The prediction interval built up during storms (when sediment transport rates are largest) and remained the same or even reduced slightly during less-energetic conditions. The prediction uncertainty ranges bracket the observations near the inner-bar crest, its seaward flank, and at the seaward flank of the outer bar, suggesting that elsewhere model structural errors (and, potentially, measurement errors) dominate over parameter errors. The interdependence and the non-Gaussian marginal posterior distribution functions of the free model parameters cast doubt on the ability of commonly applied multivariate normal distribution functions to estimate parameter uncertainty.     

Multicriteria sensitivity analysis as a diagnostic tool for understanding model behaviour and characterizing model uncertainty

Complex hydrological models are being increasingly used nowadays for many purposes such as studying the impact of climate and land‐use change on water resources. However, building a high‐fidelity model, particularly at large scales, remains a challenging task, due to complexities in model functioning and behaviour and uncertainties in model structure, parameterization, and data. Global sensitivity analysis (GSA), which characterizes how the variation in the model response is attributed to variations in its input factors (e.g., parameters and forcing data), provides an opportunity to enhance the development and application of these complex models. In this paper, we advocate using GSA as an integral part of the modelling process by discussing its capabilities as a tool for diagnosing model structure and detecting potential defects, identifying influential factors, characterizing uncertainty, and selecting calibration parameters. Accordingly, we conduct a comprehensive GSA of a complex land surface–hydrology model, Modélisation Environmentale–Surface et Hydrologie (MESH), which combines the Canadian land surface scheme with a hydrological routing component, WATROUTE. Various GSA experiments are carried out using a new technique, called Variogram Analysis of Response Surfaces, for alternative hydroclimatic conditions in Canada using multiple criteria, various model configurations, and a full set of model parameters. Results from this study reveal that, in addition to different hydroclimatic conditions and SA criteria, model configurations can also have a major impact on the assessment of sensitivity. GSA can identify aspects of the model internal functioning that are counter‐intuitive and thus help the modeller to diagnose possible model deficiencies and make recommendations for improving development and application of the model. As a specific outcome of this work, a list of the most influential parameters for the MESH model is developed. This list, along with some specific recommendations, is expected to assist the wide community of MESH and Canadian land surface scheme users, to enhance their modelling applications.     

Links, comparisons and extensions of the geographically weighted regression model when used as a spatial predictor

In this study, we link and compare the geographically weighted regression (GWR) model with the kriging with an external drift (KED) model of geostatistics. This includes empirical work where models are performance tested with respect to prediction and prediction uncertainty accuracy. In basic forms, GWR and KED (specified with local neighbourhoods) both cater for nonstationary correlations (i.e. the process is heteroskedastic with respect to relationships between the variable of interest and its covariates) and as such, can predict more accurately than models that do not. Furthermore, on specification of an additional heteroskedastic term to the same models (now with respect to a process variance), locally-accurate measures of prediction uncertainty can result. These heteroskedastic extensions of GWR and KED can be preferred to basic constructions, whose measures of prediction uncertainty are only ever likely to be globally-accurate. We evaluate both basic and heteroskedastic GWR and KED models using a case study data set, where data relationships are known to vary across space. Here GWR performs well with respect to the more involved KED model and as such, GWR is considered a viable alternative to the more established model in this particular comparison. Our study adds to a growing body of empirical evidence that GWR can be a worthy predictor; complementing its more usual guise as an exploratory technique for investigating relationships in multivariate spatial data sets.     

The application of integrated urban inundation model in Republic of Korea

In urban areas with a high building density, features such as roads, buildings and river dykes significantly affect flow dynamics and flood propagation. This should therefore be accounted for in the model set‐up. While 2D hydraulic models of densely urban areas are at the forefront of current research into flood inundation mechanisms, these models are constrained by inadequate parameters of topography and insufficient data. In order to solve these problems, topographic information obtained from digital elevation model (DEM) is directly programmed into the urban inundation model for a densely urban area, without exchanging the input data. In this paper, the extraction of building area is described using a tight coupling approach within a GIS environment, and its influence on the extent of flood inundation with a high building density is estimated. Copyright © 2009 John Wiley & Sons, Ltd.     

Emulation of a process-based estuarine hydrodynamic model

Emulation modelling can be an effective alternative to traditional mechanistic approaches for complex environmental systems and, if carefully conceived, can offer significantly reduced run times and user expertise requirements. We present a case study of dynamic emulation for the domain of estuarine water quality modelling, by reporting the development and evaluation of a one-dimensional hydrodynamic model emulator. The proposed “neuroemulator” retains the dynamic nature of the process-based model utilizing a set of artificial neural networks. The underlying hydrodynamic model is routinely used for analysis and management of the northern reach of the San Francisco Bay-Delta estuary, a large complex region of strategic importance for water supply and ecosystem services on the Pacific coast of California, USA. The reduced computational expense of the emulator affords opportunities for direct use, as well as embedded use within other modelling frameworks such as those developed for reservoir operations and socio-hydrology.     

Cluster computing-aided model updating for a high-fidelity finite element model of a long-span cable-stayed bridge

Accurate and high-fidelity finite element (FE) models are in great demand in the design, performance assessment, and life-cycle maintenance of long-span cable-stayed bridges. The structural system of a long-span cable-stayed bridge is often huge in size and complex with many components connected and various materials constituted. Therefore, the FE model of a long-span cable-stayed bridge involves a large number of elements and nodes with many uncertainties. The model updating of the FE model to best represent a real bridge is necessary but very challenging. One of the challenging issues is that the numerical computation needed for searching the global optimum of a large set of structural parameters is so extensive that the existing FE (not surrogate) model-based updating methods cannot fulfill this task. In this study, a cluster computing-aided FE model updating framework is proposed for the high-performance FE model updating of large and complex structures. In the framework, several computer software packages, including MSC.Marc, Python, and MATLAB, are interconnected for making use of their respective functions of strength. The shake table test of a scaled physical structure of the Sutong cable-stayed bridge in China is used to validate the accuracy and efficiency of the proposed framework. The simulated bridge responses based on the updated FE model are in good agreement with the measured ones from the shake table test. The successful application of the proposed framework provides a reference for the model updating of other types of large and complex structures.     

A geochemical model of mid-ocean ridge magma chambers

A computer model of mid-ocean ridge basalt generation using trace element geochemistry has been developed. The model simulates a periodically replenished, continually cooled and fractionated magma chamber, with periodic lava extrusion. Primitive basalts from the ocean floor are used to generate likely evolution paths for the magma chamber. The steady state variant of this model has led to the isolation of several variables which critically affect the basalt composition. Although the fraction of cumulates is an important parameter, other variables such as the volume of incoming magma batches, their frequency, and the volume of the mixing cell, play a critical part especially on slow-spreading ridges. The growing magma chamber model uses random number generators to simulate the initiation and growth of a chamber. This model predicts a rapid increase in incompatible element concentrations, immediately after chamber initiation on a fast-spreading ridge. This would occur in situations such as propagating rifts and may help in the understanding of ferrobasalt generation.     

A lattice Boltzmann model coupled with a Large Eddy Simulation model for flows around a groyne

This present paper proposes a two-dimensional lattice Boltzmann model coupled with a Large Eddy Simulation (LES) model and applies it to flows around a non-submerged groyne in a channel. The LES of shallow water equations is efficiently performed using the Lattice Boltzmann Method (LBM) and the turbulence can be taken into account in conjunction with the Smagorinsky Sub-Grid Stress (SGS) model. The bounce-back scheme of the non-equilibrium part of the distribution function is used to determine the unknown distribution functions at inflow boundary, the zero gradient of the distribution function is set normal to outflow boundary to obtain the unknown distribution functions here and the bounce-back scheme, which states that an incoming particle towards the boundary is bounced back into fluid, is applied to the solid wall to ensure non-slip boundary conditions. The initial flow field is defined firstly and then is used to calculate the local equilibrium distributions as initial conditions of the distribution functions. These coupled models successfully predict the flow characteristics, such as circulating flow, velocity and water depth distributions. The comparisons between the simulated results and the experimental data show that the model scheme has the capacity to solve the complex flows in shallow water with reasonable accuracy and reliability.     

Improved petrographic-coded model and its evaluation to determine a thermal conductivity log

Thermal conductivity is one of the crucial properties for thermal modelling as well as tunnelling or geological modelling. Available data are mainly from laboratory measurements. Therefore, additional ways, such as correlations with other properties to derive the petrophysical parameter, will be an advantage. The research presented here continues and improves the petrographic-coded model concept with an increased set of data, including a variety of lithologies, and, furthermore, the correlations, including the electrical resistivity. Input parameters are no longer taken from the literature, but are derived directly from measurements. In addition, the results are compared with other published approaches. Results show good correlations with measured data. The comparison with the multi-linear regression method shows acceptable outcome, in contrast to a geometric-mean method, where data scatter. In summary, it can be said that the improved model delivers for both correlation (compressional wave velocity and electrical resistivity with thermal conductivity) positive results.     

河砂岩屑磷灰石裂变径迹模拟流域热史——以藏东南察隅河为例

河砂岩屑热年代学被广泛应用于揭示造山带和流域范围内热演化历史.由于受到地貌特征、剥蚀速率的空间分布、年龄与高程关系等多种因素的影响,河砂岩屑热年代学年龄所代表的意义存在多解性.本文提出了一种利用地貌形态特征和实测河砂热年代学数据模拟流域热史的计算模型.该模型首先利用DEM数据计算流域高程分布特征,通过数据中各象元对应的坡度角大小定量计算剥蚀速率的空间分布,以确定不同高程区域对河砂岩屑样品组分的贡献量.然后根据区域地质特征建立多种可能的热史年龄-高程关系,并模拟计算出与设定的年龄-高程关系相对应的河砂年龄概率分布曲线.最后,通过对模拟河砂年龄概率分布曲线与实测分布曲线的匹配度进行卡方检验,选取最可能形成实测河砂年龄分布的年龄-高程关系,即代表了流域真实的热史演化.通过河砂岩屑磷灰石裂变径迹方法将该模型应用于藏东南地区察隅河两条支流桑曲和贡日嘎布曲流域,模拟计算结果表明两个地区的热史演化均具有多阶段的特征,桑曲流域在38~7Ma之间均匀冷却,对应的剥露速率约为0.14km/Ma,7 Ma以来剥露速率加快,达到1.62km/Ma;贡日嘎布曲的热史年龄记录比桑曲新,18~14 Ma的隆升速率为0.32km/Ma,14~8 Ma比较稳定;8 Ma以来隆升速率逐渐加快,8~5 Ma对应的隆升速率为0.21km/Ma,5~3 Ma为0.43km/Ma,3~1.1 Ma为0.83km/Ma.桑曲的模拟计算结果与前人利用该区域基岩年龄数据所揭示的热史演化特征及剥露速率基本吻合,表明该方法可以准确模拟河砂岩屑年龄所代表的流域热史特征.因此,在地形险峻或者冰川覆盖而无法获取基岩样品的野外地区,可以通过采集河砂样品替代基岩剖面模拟地质体热史特征.     

Theory and application of nonlinear river dynamics

A theoretical model for river evolution including riverbed formation and meandering pattern formation is presented in this paper.Based on nonlinear mathematic theory,the nonlinear river dynamic theory is set up for river dynamic process.Its core content includes the stability and tropism characteristics of flow motion in river and river selves＇ evolution.The stability of river dynamic process depends on the response of river selves to the external disturbance,if the disturbance and the resulting response will eventually attenuate,and the river dynamics process can be restored to new equilibrium state,the river dynamic process is known as stable;otherwise,the river dynamic process is unstable.The river dynamic process tropism refers to that the evolution tendency of river morphology after the disturbance.As an application of this theory,the dynamical stability of the constant curvature river bend is calculated for its coherent vortex disturbance and response.In addition,this paper discusses the nonlinear evolution of the river peristaltic process under a large-scale disturbance,showing the nonlinear tendency of river dynamic processes,such as river filtering and butterfly effect.     

Assessing the hydrological and geomorphic behaviour of a landscape evolution model within a limits-of-acceptability uncertainty analysis framework

Landscape evolution models (LEMs) have the capability to characterize key aspects of geomorphological and hydrological processes. However, their usefulness is hindered by model equifinality and paucity of available calibration data. Estimating uncertainty in the parameter space and resultant model predictions is rarely achieved as this is computationally intensive and the uncertainties inherent in the observed data are large. Therefore, a limits-of-acceptability (LoA) uncertainty analysis approach was adopted in this study to assess the value of uncertain hydrological and geomorphic data. These were used to constrain simulations of catchment responses and to explore the parameter uncertainty in model predictions. We applied this approach to the River Derwent and Cocker catchments in the UK using a LEM CAESAR-Lisflood. Results show that the model was generally able to produce behavioural simulations within the uncertainty limits of the streamflow. Reliability metrics ranged from 24.4% to 41.2% and captured the high-magnitude low-frequency sediment events. Since different sets of behavioural simulations were found across different parts of the catchment, evaluating LEM performance, in quantifying and assessing both at-a-point behaviour and spatial catchment response, remains a challenge. Our results show that evaluating LEMs within uncertainty analyses framework while taking into account the varying quality of different observations constrains behavioural simulations and parameter distributions and is a step towards a full-ensemble uncertainty evaluation of such models. We believe that this approach will have benefits for reflecting uncertainties in flooding events where channel morphological changes are occurring and various diverse (and yet often sparse) data have been collected over such events.     

Numerical simulation of overflow at vertical weirs using a hybrid level set/VOF method

This paper presents the applications of a newly developed free surface flow model to the practical, while challenging overflow problems for weirs. Since the model takes advantage of the strengths of both the level set and volume of fluid methods and solves the Navier-Stokes equations on an unstructured mesh, it is capable of resolving the time evolution of very complex vortical motions, air entrainment and pressure variations due to violent deformations following overflow of the weir crest. In the present study, two different types of vertical weir, namely broad-crested and sharp-crested, are considered for validation purposes. The calculated overflow parameters such as pressure head distributions, velocity distributions, and water surface profiles are compared against experimental data as well as numerical results available in literature. A very good quantitative agreement has been obtained. The numerical model, thus, offers a good alternative to traditional experimental methods in the study of weir problems.