The importance of wind forcing in fjord wave modelling

Ocean Dynamics - Accurate predictions of surface ocean waves in coastal areas are important for a number of marine activities. In complex coastlines with islands and fjords, the quality of wind...     

The effect of geometry and tidal forcing on hydrodynamics and net sediment transport in semi-enclosed tidal basins

A new depth-averaged exploratory model has been developed to investigate the hydrodynamics and the tidally averaged sediment transport in a semi-enclosed tidal basin. This model comprises the two-dimensional (2DH) dynamics in a tidal basin that consists of a channel of arbitrary length, flanked by tidal flats, in which the water motion is being driven by an asymmetric tidal forcing at the seaward side. The equations are discretized in space by means of the finite element method and solved in the frequency domain. In this study, the lateral variations of the tidal asymmetry and the tidally averaged sediment transport are analyzed, as well as their sensitivity to changes in basin geometry and external overtides. The Coriolis force is taken into account. It is found that the length of the tidal basin and, to a lesser extent, the tidal flat area and the convergence length determine the behaviour of the tidally averaged velocity and the overtides and consequently control the strength and the direction of the tidally averaged sediment transport. Furthermore, the externally prescribed overtides can have a major influence on tidal asymmetry in the basin, depending on their amplitude and phase. Finally, for sufficiently wide tidal basins, the Coriolis force generates significant lateral dynamics.     

A simple approach to estimating freshwater discharge in branched estuarine systems

In tidal estuaries, quantifying freshwater discharge is still a difficult problem that has not yet been overcome due to the inherent difficulty in measuring and analysing the tidal discharge, especially during periods of low river flow. Because observations are often made in the stations further upstream, where the ratio of river to tidal discharge is large, it remains difficult to determine the discharge rate in the saline region. Freshwater discharge estimation is even more difficult in a branched estuary system having multiple diversion channels that connect with each other at a junction. To date, several methods have been developed for estimating freshwater discharge in estuaries. The most widely used are analytical and conceptual models that employ salinity as the principal trace and numerical simulations. However, these methods are very time consuming and costly as they require large sets of observations before the computations can take place. This paper presents a simple approach to investigating the discharge distribution over branched channels by considering the energy loss due to friction. We develop an analytical model that can obtain the discharge rate quantitatively at a junction where the main flow bifurcates into two branches. The model uses the bed roughness, tidal water level, and cross‐sectional profile under tidally averaged conditions as input data. Two selected estuarine systems in the Hiroshima delta in Japan and the Mekong delta in Vietnam have been investigated. Computations of the newly developed model show good agreement with earlier published results computed by sophisticated analytical and numerical models.     

On the influence of stratification and tidal forcing upon mixing in sill regions

A cross-sectional non-hydrostatic model with idealized topography was used to examine the processes influencing tidal mixing in the region of sills. Initial calculations with appropriate parameters for the sill at the entrance to Loch Etive showed that the model could reproduce the main features of the observed mixing in the region. In particular, the hydraulic jump in the sill region was reproduced, as was an intense mid-water jet that was observed to separate from the lee side of the sill. Shear instabilities associated with the jet appeared to be a source of mixing within the thermocline. In addition, internal lee waves were generated on the lee side of the sill, with the observed amplification because of trapping during the flood stage. Their magnitude and hence the mixing increased with increasing Froude number (F _r). In the case of vertically varying buoyancy frequency, its value near the sill top determined the F _r number, with its value below influencing internal waves magnitude at depth. At high F _r values particularly with strong currents, short waves and overturning occurred.     

Leveraging ensemble meteorological forcing data to improve parameter estimation of hydrologic models

As continental to global scale high-resolution meteorological datasets continue to be developed, there are sufficient meteorological datasets available now for modellers to construct a historical forcing ensemble. The forcing ensemble can be a collection of multiple deterministic meteorological datasets or come from an ensemble meteorological dataset. In hydrological model calibration, the forcing ensemble can be used to represent forcing data uncertainty. This study examines the potential of using the forcing ensemble to identify more robust parameters through model calibration. Specifically, we compare an ensemble forcing-based calibration with two deterministic forcing-based calibrations and investigate their flow simulation and parameter estimation properties and the ability to resist poor-quality forcings. The comparison experiment is conducted with a six-parameter hydrological model for 30 synthetic studies and 20 real data studies to provide a better assessment of the average performance of the deterministic and ensemble forcing-based calibrations. Results show that the ensemble forcing-based calibration generates parameter estimates that are less biased and have higher frequency of covering the true parameter values than the deterministic forcing-based calibration does. Using a forcing ensemble in model calibration reduces the risk of inaccurate flow simulation caused by poor-quality meteorological inputs, and improves the reliability and overall simulation skill of ensemble simulation results. The poor-quality meteorological inputs can be effectively filtered out via our ensemble forcing-based calibration methodology and thus discarded in any post-calibration model applications. The proposed ensemble forcing-based calibration method can be considered as a more generalized framework to include parameter and forcing uncertainties in model calibration.     

A statistical-dynamical approach to parameterize subgrid-scale land-surface heterogeneity in climate models

Land surface interacts strongly with the atmosphere at all scales. This has a considerable impact on the hydrologic cycle and the climate. Therefore, in order to produce realistic simulations with climate models, their land-surface processes must be parameterized accurately. Because continental surfaces are usually extremely heterogeneous over the resolvable scales considered in these models, surface parameterizations based on the big leaf-big stoma approach (that assume grid-scale homogeneity) fail to represent the land-atmosphere interactions that occur at much smaller scales.A parameterization based on a statistical-dynamical approach is suggested here. With this approach, each surface grid element of the numerical model is divided into homogeneous land patches (i.e., patches with similar internal heterogeneity). Assuming that horizontal fluxes between the different patches within a grid element are small as compared to the vertical fluxes, patches of the same type located at different places in the grid can be regrouped into one subgrid surface class. Then, for each one of the subgrid surface classes, probability density functions (pdf) are used to characterize the variability of the different parameters of the soil-plant-atmosphere system. These pdf are combined with the equations of the model that describe the dynamic and the energy and mass conservations in the atmosphere.The potential application of this statistical-dynamical parameterization is illustrated by simulating (i) the development of an agricultural area in an arid region and (ii) the process of deforestation in a tropical region. Both cases emphasize the importance of land-atmosphere interactions on regional hydrologic processes and climate.     

On the comparison of tidal gravity parameters with tidal models in central Europe

Two accurately calibrated superconducting gravimeters (SGs) provide high quality tidal gravity records in three central European stations: C025 in Vienna and at Conrad observatory (A) and OSG050 in Pecný (CZ). To correct the tidal gravity factors from ocean loading effects we compared the load vectors from different ocean tides models (OTMs) computed with different software: OLFG/OLMP by the Free Ocean Tides Loading Provider (FLP), ICET and NLOADF. Even with the recent OTMs the mass conservation is critical but the methods used to correct the mass imbalance agree within 0.1 nm/s². Although the different software agrees, FLP probably provides more accurate computations as this software has been optimised. For our final computation we used the mean load vector computed by FLP for 8 OTMs (CSR4, NAO99, GOT00, TPX07, FES04, DTU10, EOT11a and HAMTIDE). The corrected tidal factors of the 3 stations agree better than 0.04% in amplitude and 0.02° in phase. Considering the weighted mean of the three stations we get for O1 δ_c = 1.1535 ± 0.0001, for K1 δ_c = 1.1352 ± 0.0003 and for M2 δ_c = 1.1621 ± 0.0003. These values confirm previous ones obtained with 16 European stations. The theoretical body tides model DDW99/NH provides the best agreement for M2 (1.1620) and MATH01/NH for O1 (1.1540) and K1 (1.1350). The largest discrepancy is for O1 (0.05%). The corrected phase α_c does not differ significantly from zero except for K1 and S2. The calibrations of the two SG's are consistent within 0.025% and agree with Strasbourg results within 0.05%.     

The role of constant optimal forcing in correcting forecast models

In this paper,the role of constant optimal forcing(COF) in correcting forecast models was numerically studied using the well-known Lorenz 63 model.The results show that when we only consider model error caused by parameter error,which also changes with the development of state variables in a numerical model,the impact of such model error on forecast uncertainties can be offset by superimposing COF on the tendency equations in the numerical model.The COF can also offset the impact of model error caused by stochastic processes.In reality,the forecast results of numerical models are simultaneously influenced by parameter uncertainty and stochastic process as well as their interactions.Our results indicate that COF is also able to significantly offset the impact of such hybrid model error on forecast results.In summary,although the variation in the model error due to physical process is time-dependent,the superimposition of COF on the numerical model is an effective approach to reducing the influence of model error on forecast results.Therefore,the COF method may be an effective approach to correcting numerical models and thus improving the forecast capability of models.     

A multigrid methodology for assimilation of measurements into regional tidal models

This paper presents a rigorous, yet practical, method of multigrid data assimilation into regional structured-grid tidal models. The new inverse tidal nesting scheme, with nesting across multiple grids, is designed to provide a fit of the tidal dynamics to data in areas with highly complex bathymetry and coastline geometry. In these areas, computational constraints make it impractical to fully resolve local topographic and coastal features around all of the observation sites in a stand-alone computation. The proposed strategy consists of increasing the model resolution in multiple limited area domains around the observation locations where a representativeness error is detected in order to improve the representation of the measurements with respect to the dynamics. Multiple high-resolution nested domains are set up and data assimilation is carried out using these embedded nested computations. Every nested domain is coupled to the outer domain through the open boundary conditions (OBCs). Data inversion is carried out in a control space of the outer domain model. A level of generality is retained throughout the presentation with respect to the choice of the control space; however, a specific example of using the outer domain OBCs as the control space is provided, with other sensible choices discussed. In the forward scheme, the computations in the nested domains do not affect the solution in the outer domain. The subsequent inverse computations utilize the observation-minus-model residuals of the forward computations across these multiple nested domains in order to obtain the optimal values of parameters in the control space of the outer domain model. The inversion is carried out by propagating the uncertainty from the control space to model tidal fields at observation locations in the outer and in the nested domains using efficient low-rank error covariance representations. Subsequently, an analysis increment in the control space of the outer domain model is computed and the multigrid system is steered optimally towards observations while preserving a perfect dynamical balance. The method is illustrated using a real-world application in the context of the Philippines Strait Dynamics experiment.     

Parameter identification in tidal models with uncertain boundary conditions

In this paper a parameter estimation algorithm is developed to estimate uncertain parameters in two dimensional shallow water flow models. Since in practice the open boundary conditions of these models are usually not known accurately, the uncertainty of these boundary conditions has to be taken into account to prevent that boundary errors are interpreted by the estimation procedure as parameter fluctuations. Therefore the open boundary conditions are embedded into a stochastic environment and a constant gain extended Kalman filter is employed to identify the state of the system. Defining a error functional that measures the differences between the filtered state of the system and the measurements, a quasi Newton method is employed to determine the minimum of this functional. To reduce the computational burden, the gradient of the criterium that is required using the quasi Newton method is determined by solving the adjoint system.     

A novel simple procedure to consider seismic soil structure interaction effects in 2D models

A method is proposed to estimate the seismic soil-structure-interaction (SSI) effects for use in engineering practice. It is applicable to 2D structures subjected to vertically incident shear waves supported by homogenous half-spaces. The method is attractive since it keeps the simplicity of the spectral approach, overcomes some of the difficulties and inaccuracies of existing classical techniques and yet it considers a physically consistent excitation. This level of simplicity is achieved through a response spectra modification factor that can be applied to the free-field 5%-damped response spectra to yield design spectral ordinates that take into account the scattered motions introduced by the interaction effects. The modification factor is representative of the Transfer Function (TF) between the structural relative displacements and the free-field motion, which is described in terms of its maximum amplitude and associated frequency. Expressions to compute the modification factor by practicing engineers are proposed based upon a parametric study using 576 cases representative of actual structures. The method is tested in 10 cases spanning a wide range of common fundamental vibration periods.     

Parameter identification in tidal models with uncertain boundary conditions

In this paper a parameter estimation algorithm is developed to estimate uncertain parameters in two dimensional shallow water flow models. Since in practice the open boundary conditions of these models are usually not known accurately, the uncertainty of these boundary conditions has to be taken into account to prevent that boundary errors are interpreted by the estimation procedure as parameter fluctuations. Therefore the open boundary conditions are embedded into a stochastic environment and a constant gain extended Kalman filter is employed to identify the state of the system. Defining a error functional that measures the differences between the filtered state of the system and the measurements, a quasi Newton method is employed to determine the minimum of this functional. To reduce the computational burden, the gradient of the criterium that is required using the quasi Newton method is determined by solving the adjoint system.     

中国大陆精密重力潮汐改正模型

利用理论和实验重力固体潮模型,充分考虑全球海潮和中国近海潮汐的负荷效应,建立了中国大陆的精密重力潮汐改正模型.结果表明,采用不同的固体潮模型会对重力潮汐结果产生相对变化幅度小于0.06％的差异;在沿海地区海潮负荷的影响约为整个潮汐的4％,而中部地区约为1％,其中中国近海潮汐模型的影响约占整个海潮负荷的10%,内插或外推潮波的负荷约占海潮负荷的3％.通过比较实测的重力数据表明,本文给出的重力潮汐改正模型的精度远远优于0.5×10-8 m·s-2,说明了本文构建的模型的实用性,可为中国大陆高精度重力测量提供有效参考和精密的改正模型.     

Sensitivity of tidal sand wavelength to environmental parameters: A combined data analysis and modelling approach

An integrated field data-modelling approach is employed to investigate relationships between the wavelength of tidal sand waves and four environmental parameters: tidal current amplitude, water depth, tidal ellipticity and median grain size. From echo sounder data at 23 locations on the Dutch continental shelf, the average wavelengths of observed sand waves are determined and compared with the wavelengths obtained with a process-based model. The latter describes the initial formation of these bedforms due to feedbacks between the tidal current and the erodible bed and uses environmental parameters for the 23 locations as input. Good agreement between observed and modelled wavelengths is found if the bottom stress experienced by tidal currents is adequately quantified. Model results show that the wavelength of sand waves increases with increasing water depth, tidal ellipticity and grain size (coarse sand), whilst it decreases with increasing tidal current amplitude and grain size (fine sand). Due to the limited number of stations and the fact that all four parameters change from location to location, the modelled relationships are only partly supported by the field observations.     

A watershed rainfall data recovery approach with application to distributed hydrological models

Watershed areal rainfall estimation, which is one of the most important and fundamental aspects in hydrological forecasting and various kinds of catchment‐scale hydrological models, is widely used in the analysis of hydrological regime change, and its precision has a direct influence on the accuracy of hydrological forecasting and hydrological simulation. In China, it is difficult to obtain the watershed areal rainfall estimate with reliable precision and avoid the phenomenon of ‘the same effect of different parameters’ because of the low density of the rain gauge network. Therefore, a watershed rainfall data recovery approach of improving the precision of watershed areal rainfall estimation is proposed here. This approach is to build new observatories, establish the time–space relations of rainfall between newly built observatories and previously built observatories in a relatively short interval and then recover the rainfall data of newly built observatories prior to their construction through simulating the relations over a longer time. As a result, watershed rainfall information could be elaborated to improve the precision of watershed areal rainfall estimate and avoid the phenomenon of ‘the same effect of different parameters’ to a certain degree in the process of hydrological simulation. The approach is used in the hydrological simulation of Hali River catchment. In combination with the Soil Water Assessment Tool model, a better result can be obtained in the hydrological simulation. Therefore, the approach can be used in other similar catchments. Copyright © 2011 John Wiley & Sons, Ltd.     

A re-evaluation of equivalent linear models for simple yielding systems

Commonly used equivalent linear models for simple yielding systems subjected to harmonic and earthquake excitations are re-evaluated. It is shown that with respect to damping, these models contain the same basic information. Reported differences in the literature are simply due to scaling: since the product of the equivalent stiffness and equivalent damping is a constant, smaller damping values would be obtained by the use of the small amplitude equivalent stiffnesses. It is argued that for harmonic excitation, the secant stiffness is an appropriate representation of equivalent stiffness, leading to large equivalent damping values that increase with ductility. For earthquake excitation the Iwan proposal is shown to be the preferred model leading to larger damping values than previously reported. A comparison of the models for harmonic and earthquake excitations shows that, in general, and at comparable ductilities, damping values due to harmonic excitation are about five times those due to earthquake excitation, and the period changes due to harmonic excitation are about twice those due to earthquake excitation.     

A simple LMS‐based approach to the structural health monitoring benchmark problem

A structure's health or level of damage can be monitored by identifying changes in structural or modal parameters. However, the fundamental modal frequencies can sometimes be less sensitive to (localized) damage in large civil structures, although there are developing algorithms that seek to reduce this difficulty. This research directly identifies changes in structural stiffness due to modeling error or damage using a structural health monitoring method based on adaptive least mean square (LMS) filtering theory. The focus is on computational simplicity to enable real‐time implementation. Several adaptive LMS filtering based approaches are used to analyze the data from the IASC–ASCE Structural Health Monitoring Task Group Benchmark problem. Results are compared with those from the task group and other published results. The proposed methods are shown to be very effective, accurately identifying damage to within 1%, with convergence times of 0.4–13.0 s for the twelve different 4 and 12 degree of freedom benchmark problems. The resulting modal parameters match to within 1% those from the benchmark problem definition. Finally, the methods developed require 1.4–14.0 Mcycles of computation and therefore could easily be implemented in real time. Copyright © 2004 John Wiley & Sons, Ltd.     

A simple hydrophobicity-based approach to predict the toxicity of unknown organic micropollutant mixtures in marine water

In this study, we propose a simple hydrophobicity-based approach to predict the toxicity of mixtures of marine organic micropollutants. Fifty mixtures were chosen, comprising individual chemicals randomly chosen from three halogenated benzenes, three phenols, two petroleum hydrocarbons, three polychlorinated biphenyls (PCBs), four organochlorine pesticides (OCPs) and two herbicides, with the intention of simulating the mixtures of organic micropollutants that may exist in some marine waters. The hydrophobicity of the mixtures was quantified by measuring the C(18)-Empore(TM) disk/water partition coefficients (K(MD)). A K(MD)-based approach was proposed to describe their toxicity to Photobacterium phosphoreum, and the application of this approach to another 10 related mixtures proved its predictive capability, as indicated by the consistency between the predicted and observed toxicities (r(2)=0.905, SE=0.101, and F=76.325 at P<0.001). This predictive capability convinces us that the K(MD)-based approach provides a general approach to predicting the toxicity of mixtures of organic micropollutants in marine water.     

A simple overland flow calculation method for distributed groundwater recharge models

A method to improve the calculation of overland flow in distributed groundwater recharge models is presented and applied to two sub‐catchments in the Thames Basin, UK. Recharge calculation studies tend to simulate the runoff flow component of river flow in a simplistic way, often as a fraction of rainfall over a particular period. The method outlined in this study intends to improve the calculation of groundwater recharge estimates in distributed recharge models but does not present an alternative to complex overland flow simulators. This method uses seasonally varying coefficients to calculate runoff for specified hydrogeological classes or runoff zones, which are used to model baseflow index variations across the basin. It employs a transfer function model to represent catchment storage. Monte Carlo simulation was applied to refine the runoff values. Decoupling the runoff zones between the two sub‐catchments produces a better match between the simulated and observed values; however, the difference between observed runoff and the simulated output indicates other factors, such as landuse and topographical characteristics that affect the generation of runoff flow, need to be taken into account when classifying runoff zones. British Geological Survey © NERC 2011. Hydrological Processes © 2011 John Wiley & Sons, Ltd.