Evaluating river morphology change with a geomorphic form variation approach

Geomorphic river design strives for natural resilience by encouraging geomorphic form complexity and morphological processes linked to greater habitat diversity. Increasing availability of high-resolution topographic data and spatial feature mapping methods provide advantages for morphological analysis and river restoration planning. We propose and evaluate an approach to quantifying topographic variability of geomorphic form and pixel-level surface roughness resulting from channel planform geometry differences using spatially continuous variety computation applied to component metrics including flow direction, aspect and planform curvature. We define this as the geomorphic form variation (GFV) approach and found it scalable, repeatable and a multi-stage analytical metric for quantifying physical aspects of river-bed topographic variability. GFV may complement process-based morphological feature mapping applications, hydraulic assessment indices and spatial habitat heterogeneity metrics commonly used for ecological quality evaluation and river restoration. The GFV was tested on controlled synthetic channels derived from River Builder software and quasi-controlled sinuous planform flume experiment channels. Component variety metrics respond independently to specific geometric surface changes and are sensitive to multi-scaled morphology change, including coarser-grained sediment distributions of pixel-level surface roughness. GFV showed systematic patterns of change related to the effects of channel geometry, vertical bed feature (pool-bar) frequency and amplitude, and bar size, shape and orientation. Hotspot analysis found that bar margins were major components of topographic complexity, whereas grain-scale variety class maps further supported the multi-stage analytical capability and scalability of the GFV approach. The GFV can provide an overall variety value that may support river restoration decision-making and planning, particularly when geomorphic complexity enhancement is a design objective. Analysing metric variety values with statistically significant hotspot cluster maps and complementary process-based software and mapping applications allows variety correspondence to systematic feature changes to be assessed, providing an analytical approach for river morphology change comparison, channel design and geomorphic process restoration.     

A new surface runoff parameterization with subgrid-scale soil heterogeneity for land surface models

Soil heterogeneity plays an important role in determining surface runoff generation mechanisms. At the spatial scales represented by land surface models used in regional climate model and/or global general circulation models (GCMs) for numerical weather prediction and climate studies, both infiltration excess (Horton) and saturation excess (Dunne) runoff may be present within a studied area or a model grid cell. Proper modeling of surface runoff is essential to a reasonable representation of feedbacks in the land–atmosphere system. In this paper, a new surface runoff parameterization that dynamically represents both Horton and Dunne runoff generation mechanisms within a model grid cell is presented. The new parameterization takes into account of effects of soil heterogeneity on Horton and Dunne runoff. A series of numerical experiments are conducted to study the effects of soil heterogeneity on Horton and Dunne runoff and on soil moisture storage under different soil and precipitation conditions. The new parameterization is implemented into the current version of the hydrologically based variable infiltration capacity (VIC) land surface model and tested over three watersheds in Pennsylvania. Results show that the new parameterization plays a very important role in partitioning the water budget between surface runoff and soil moisture in the atmosphere–land coupling system. Significant underestimation of the surface runoff and overestimation of subsurface runoff and soil moisture could be resulted if the Horton runoff mechanism were not taken into account. Also, the results show that the Horton runoff mechanism should be considered within the context of subgrid-scale spatial variability of soil properties and precipitation. An assumption of time-invariant spatial distribution of potential infiltration rate may result in large errors in surface runoff and soil moisture. In addition, the total surface runoff from the new parameterization is less sensitive to the choice of the soil moisture shape parameter of the distribution.     

On the determination of marine magnetotelluric receiver orientation using land magnetic observatory data

Marine magnetotelluric measurements using “free‐fall’’ instruments without effective compasses suffer from the problem of unknown orientation of the receivers at the seafloor. While past works indicate that marine magnetotelluric orientation of the instruments can be estimated by reference to land deployments of known orientation using the transfer tensor method, there is limited published information on how this is implemented in practice. We document this method and propose a set of new time‐ and frequency‐domain approaches to solve this orientation problem of the seafloor receivers. We test these methodologies in onshore and offshore magnetotelluric data whose orientations are well known and apply these techniques to marine magnetotelluric data with unknown orientation. For the controlled tests, both time‐ and frequency‐domain approaches produce overall comparable results. To investigate the effects of the subsurface structure distribution on the orientation process, a dimensionality analysis of a controlled dataset is carried out. In subsequent analysis using the available disoriented marine magnetotelluric data from offshore Brazil and from the Vassouras magnetic observatory on the mainland for remote referencing, frequency‐domain methods yield approximate orientation angles among themselves with low standard deviation each. Time‐domain results are consistent for most cases but differ from frequency‐domain results for some situations.     

Bedform effect on the reorganization of surface and subsurface grain size distribution in gravel bedded channels

Quantification of river bedform variability and complexity is important for sediment transport modeling as well as for characterization of river morphology. Alluvial bedforms are shown to exhibit highly nonlinear dynamics across a range of scales, affect local bed roughness, and vary with local hydraulic, hydrologic, and geomorphic properties. This paper examines sediment sorting on the crest and trough of gravel bedforms and relates it to bed elevation statistics. The data analysed here are the spatial and temporal series of bed elevation, grain size distribution of surface and subsurface bed materials, and sediment transport rates from flume experiments. We describe surface topography through bedform variability in height and wavelength and multiscale analysis of bed elevations as a function of discharge. We further relate bedform migration to preferential distribution of coarse and fine sediments on the troughs and crests, respectively, measuring directly surface and subsurface grain size distributions, and indirectly the small scale roughness variations as estimated from high resolution topographic scans.     

Spatial scale effect on the upper soil effective parameters of a distributed hydrological model

Nonlinear dynamics and spatial variability in hydrological systems make the formulation of scaling theories difficult. Therefore, the development of knowledge related to scale effects, scaling techniques, parameterization and linkages of parameters across scales is highly relevant. The main purpose of this work is to analyse the spatial effect of the static storage capacity parameter H_u and the saturated hydraulic conductivity parameter k_s from microscale (sub‐grid level) to mesoscale (grid level) and its implication to the definition of an optimum cell size. These two parameters describe the upper soil water characteristics in the infiltration process conceptualization of the TETIS hydrological model. At microscale, the spatial heterogeneity of H_u and k_s was obtained generating random parameter fields through probability distribution functions and a spatial dependence model with pre‐established correlation lengths. The effective parameters at mesoscale were calculated by solving the inverse problem for each parameter field. Results indicate that the adopted inverse formulation allows transferring the nonlinearity of the system from microscale to the mesoscale via non‐stationary effective parameters. Their values at each cell and time step are in the range of zero to the mean value of the parameter at microscale. The stochastic simulations showed that the variance of the estimated effective parameters decreases when the ratio between mesoscale cell size and correlation length at microscale increases. For a ratio greater than 1, we found cell sizes having the characteristics of a representative elementary area (REA); in such case, the microscale variability pattern did not affect the system response at mesoscale. Copyright © 2011 John Wiley & Sons, Ltd.     

Charred forests accelerate snow albedo decay: parameterizing the post‐fire radiative forcing on snow for three years following fire

As large, high‐severity forest fires increase and snowpacks become more vulnerable to climate change across the western USA, it is important to understand post‐fire disturbance impacts on snow hydrology. Here, we examine, quantify, parameterize, model, and assess the post‐fire radiative forcing effects on snow to improve hydrologic modelling of snow‐dominated watersheds having experienced severe forest fires. Following a 2011 high‐severity forest fire in the Oregon Cascades, we measured snow albedo, monitored snow, and micrometeorological conditions, sampled snow surface debris, and modelled snowpack energy and mass balance in adjacent burned forest (BF) and unburned forest sites. For three winters following the fire, charred debris in the BF reduced snow albedo, accelerated snow albedo decay, and increased snowmelt rates thereby advancing the date of snow disappearance compared with the unburned forest. We demonstrate a new parameterization of post‐fire snow albedo as a function of days‐since‐snowfall and net snowpack energy balance using an empirically based exponential decay function. Incorporating our new post‐fire snow albedo decay parameterization in a spatially distributed energy and mass balance snow model, we show significantly improved predictions of snow cover duration and spatial variability of snow water equivalent across the BF, particularly during the late snowmelt period. Field measurements, snow model results, and remote sensing data demonstrate that charred forests increase the radiative forcing to snow and advance the timing of snow disappearance for several years following fire. Copyright © 2016 John Wiley & Sons, Ltd.     

Stochastic analysis of multiphase flow in porous media: II. Numerical simulations

The first paper (Chang et al., 1995b) of this two-part series described the stochastic analysis using spectral/perturbation approach to analyze steady state two-phase (water and oil) flow in a, liquid-unsaturated, three fluid-phase porous medium. In this paper, the results between the numerical simulations and closed-form expressions obtained using the perturbation approach are compared. We present the solution to the one-dimensional, steady-state oil and water flow equations. The stochastic input processes are the spatially correlated logk where k is the intrinsic permeability and the soil retention parameter, . These solutions are subsequently used in the numerical simulations to estimate the statistical properties of the key output processes. The comparison between the results of the perturbation analysis and numerical simulations showed a good agreement between the two methods over a wide range of logk variability with three different combinations of input stochastic processes of logk and soil parameter . The results clearly demonstrated the importance of considering the spatial variability of key subsurface properties under a variety of physical scenarios. The variability of both capillary pressure and saturation is affected by the type of input stochastic process used to represent the spatial variability. The results also demonstrated the applicability of perturbation theory in predicting the system variability and defining effective fluid properties through the ergodic assumption.     

时变功率谱空间变化性分析

基于我国台湾地区SMART-1密集台阵强震记录资料和Kameda的时变功率谱模型,利用多重滤波技术和非线性最小二乘法拟合得到每条记录的Kameda模型参数值;通过分析模型参数随频率变化的散点图分布规律,建立了时变功率谱模型参数随频率变化的随机模型。采用随机振动理论和多元统计分析方法,分析了沿波传播方向距离、垂直于波传播方向距离及测点所在位置土层厚度等局部空间位置变化对时变功率谱模型参数的影响规律,探讨了时变功率谱模型参数的空间分布形式,建立了各模型参数随空间坐标变化的随机预测模型,从而为重大工程多点输入地震动参数的确定和多点输入加速度时程的合成提供实用模型。     

A stochastic framework for downscaling processes of spatial averages based on the property of spectral multiscaling and its statistical diagnosis on spatio-temporal rainfall fields

Spectral multi-scaling postulates a power-law type of scaling of spectral distribution functions of stationary processes of spatial averages, over nested and geometrically similar sub-regions of the spatial parameter space of a given spatio-temporal random field. Presently a new framework is formulated for down-scaling processes of spatial averages, following naturally from the postulate of spectral multi-scaling, and key ingredients required for its implementation are described. Moreover, results from an extensive diagnostic study are presented, seeking statistical evidence supportive of spectral multi-scaling. Such evidence emerges from two sources of data. One is a 13 year long historical record of radar observations of rainfall in southeastern UK (Chenies radar), with high spatial (2 km) and temporal (5 min) resolution. The other is an ensemble of rain rate fields simulated by a spatio-temporal random pulse model fitted to the historical data. The results are consistent between historical and simulated rainfall data, indicating frequency-dependent scaling relationships interpreted as evidence of spectral multi-scaling across a range of spatial scales.     

An experimental study on the ripple–dune transition

Flume experiments were conducted on different bed stages across the ripple–dune transition. As flow velocity increases, an initially flat bed surface (made of fairly uniform sandy material) is gradually transformed into a two‐dimensional rippled bed. With further increase in velocity, two‐dimensional ripples are replaced by irregular, linguoid ripples. As the average velocity necessary for the ripple–dune transition to occur is imposed on the bed surface, these non‐equilibrium linguoid ripples are further transformed into larger, two‐dimensional dunes. For each of these stages across the transition, a concrete mould of the bed was created and the flow structure above each fixed bed surface investigated. An acoustic Doppler velocimeter was used to study the flow characteristics above each bed surface. Detailed profiles were used along a transect located in the middle of the channel. Results are presented in the form of spatially averaged profiles of various flow characteristics and of contour maps of flow fields (section view). They clearly illustrate some important distinctions in the flow structure above the different bedform types associated with different stages during the transition. Turbulence intensity and Reynolds stresses gradually increase throughout the transition. Two‐dimensional ripples present a fairly uniform spatial distribution of turbulent flow characteristics above the bed. Linguoid ripples induce three‐dimensional turbulence structure at greater heights above the bed surface and turbulence intensity tends to increase steadily with height above bed surface in the wake region. A very significant increase in turbulence intensity and momentum exchange occurs during the transition from linguoid ripples to dunes. The turbulent flow field properties above dunes are highly dependent on the position along and above the bed surface and these fields present a very high degree of spatial variability (when compared with the rippled beds). Further investigations under natural conditions emphasizing sediment transport mechanisms and rates during the transition should represent the next step of analysis, together with an emphasis on quadrant analysis. Copyright © 2001 John Wiley & Sons, Ltd.     

Scale effects of hydrostratigraphy and recharge zonation on base flow

Uncertainty regarding spatial variations of model parameters often results in the simplifying assumption that parameters are spatially uniform. However, spatial variability may be important in resource assessment and model calibration. In this paper, a methodology is presented for estimating a critical basin size, above which base flows appear to be relatively less sensitive to the spatial distribution of recharge and hydraulic conductivity, and below which base flows are relatively more sensitive to this spatial variability. Application of the method is illustrated for a watershed that exhibits distinct infiltration patterns and hydrostratigraphic layering. A ground water flow model (MODFLOW) and a parameter estimation code (UCODE) were used to evaluate the influence of recharge zonation and hydrostratigraphic layering on base flow distribution. Optimization after removing spatial recharge variability from the calibrated model altered base flow simulations up to 53% in watersheds smaller than 40 km(2). Merging six hydrostratigraphic units into one unit with average properties increased base flow residuals up to 83% in basins smaller than 50 km(2). Base flow residuals changed <5% in watersheds larger than 40 and 50 km(2) when recharge and hydrostratigraphy were simplified, respectively; thus, the critical basin size for the example area is approximately 40 to 50 km(2). Once identified for an area, a critical basin size could be used to guide the scale of future investigations. By ensuring that parameter discretization needed to capture base flow distribution is commensurate with the scope of the investigation, uncertainty caused by overextending uniform parameterization or by estimating extra parameter values is reduced.     

Geostatistical analysis of ground‐survey elevation data to elucidate spatial and temporal river channel change

A digital elevation model (DEM) of a fluvial environment represented landform surface variability well and provided a medium for monitoring morphological change over time. Elevation was measured above an arbitrary datum using a ground‐based three‐dimensional tacheometric survey in two reaches of the River Nent, UK, in July 1998, October 1998 (after flood conditions) and June 1999. A detailed geostatistical analysis of the elevation data was used to model the spatial variation of elevation and to produce DEMs in each reach and for each survey period. Maps of the difference in elevation were produced and volumetric change was calculated for each reach and each survey period. The parameters of variogram models were used to describe the morphological character of each reach and to elucidate the linkages between process and the form of channel change operating at different spatial and temporal scales. The analysis of channel change on the River Nent shows the potential of geostatistics for investigating the magnitude and frequency of geomorphic work in other rivers. A flood modified the channel features, but low magnitude and high frequency flows rationalized the morphology. In spite of relatively small amounts of net flux the channel features changed as a consequence of the reworking of existing material. The blocking of chute entrances and redirection of the channel had a considerable effect on the behaviour of the channel. Such small changes suggested that the distributary system was sensitive to variation in sediment regime. Plots of the kriging variances against sampling intervals were used to quantify the temporal variation in sampling redundancy (ranging between ?11 per cent and +93 per cent). These curves illustrated the importance of bespoke sampling designs to reduce sampling effort by incorporating anisotropic variation in space and geomorphic information on flow regime. Variation in the nugget parameter of the variogram models was interpreted as sampling inaccuracy caused by variability in particle size and is believed to be important for future work on surface roughness. Copyright © 2003 John Wiley & Sons, Ltd.     

Use of terrestrial photosieving and airborne topographic LiDAR to assess bed grain size in large rivers: a study on the Rhine River

Most grain size monitoring is still being conducted by manual sampling in the field, which is time consuming and has low spatial representation. Due to new remote sensing methods, some limitations have been partly overcome, but methodological progress is still needed for large rivers as well as in underwater conditions. In this article, we tested the reliability of two methods along the Old Rhine River (France/Germany) to estimate the grain size distribution (GSD) in above-water conditions: (i) a low-cost terrestrial photosieving method based on an automatic procedure using Digital Grain Size (DGS) software and (ii) an airborne LiDAR topo-bathymetric survey. We also tested the ability of terrestrial photosieving to estimate the GSD in underwater conditions. Field pebble counts were performed to compare and calibrate both methods. The results showed that the automatic procedure of terrestrial photosieving is a reliable method to estimate the GSD of sediment patches in both above-water and underwater conditions with clean substrates. Sensitivity analyses showed that environmental conditions, including solar lighting conditions and petrographic variability, significantly influence the GSD from the automatic procedure in above-water conditions. The presence of biofilm in underwater conditions significantly altered the GSD estimation using the automatic procedure, but the proposed manual procedure overcame this problem. The airborne LiDAR topographic survey is an accurate method to estimate the GSD of above-water bedforms and is able to generate grain size maps. The combination of terrestrial photosieving and airborne topographic LiDAR methods is adapted to assess the GSD over several kilometers long reaches of large rivers. © 2020 John Wiley & Sons, Ltd.     

Using geostatistics and spectral analysis to study spatial patterns in the topography of southeastern Washington State,U.S.A.

Topography for four areas in the Palouse region of southeastern Washington State having different patterns and encompassing areas of about 900 ha each were quantitatively compared and described using two-dimensional semi-variograms and periodograms. The four areas studied were from the Garfield, La Crosse, Thornton, and Wilcox quadrangle topographic maps. Semivariance of elevation residuals were modelled using a combination of spherical, periodic, or linear semivariogram models. The range of the spherical component was interpreted as a relatively short-range scale of correlation which was not periodic. For each of the study areas a model was developed to describe the variation in range with orientation. Values for the range from this model reached maximum values of from about 700 m to 800 m at an orientation of from 35° to 55° (approximately northeast) in each study area. This orientation was interpreted as the dominant direction of non-periodic small-scale landscape features. The wavelength and amplitude of the periodic semivariogram component, which were highly correlated, were interpreted in terms of parallel northeast-trending ridges having relatively long scales of periodic correlation varying in size from about 1350 m to 2100 m. This attempt to identify the dominant orientation of periodic landscape features using models for the wavelength and amplitude was, however, not completely definitive. Two-dimensional spectral analysis provided significantly more detail concerning orientation and wavelengths of the periodic topographic patterns than the semivariogram analysis. In the Garfield study area, spectral analysis identified north-trending ridge systems separated by a wavelength of 1494 m and northeast-trending systems with a wavelength of 747 m. In the La Crosse study area, both north and northeast-trending patterns were identified having periodic spacings of 980 and 735 m. North-trending ridges separated by wavelengths of 996 m and northeast-trending ridges separated by wavelengths of 747 or 996 m were the predominant periodic features of topography in the Thornton study area. In the Wilcox study area, northeast-trending ridge systems separated by wavelengths of 373, 498, or 996 m were detected. A comparison of the results from geostatistical and spectral analysis of these complex topographic surfaces shows that each approach had significant strengths and weaknesses. Two-dimensional analysis with semivariograms was the only method which could be used for identifying the correlation scale and orientation of relatively small non-periodic landscape features. Two-dimensional spectral analysis accurately identified the predominant orientation of relatively large periodic features in topography, whereas semivariogram analysis was somewhat inconclusive. Also, semivariograms were generally unable to detect the presence of multiple or harmonic periodicities operating at different wavelengths along a given orientation.     

Shear velocity estimates in rough‐bed open‐channel flow

Shear velocity u_* is an important parameter in geophysical flows, in particular with respect to sediment transport dynamics. In this study, we investigate the feasibility of applying five standard methods [the logarithmic mean velocity profile, the Reynolds stress profile, the turbulent kinetic energy (TKE) profile, the wall similarity and spectral methods] that were initially developed to estimate shear velocity in smooth bed flow to turbulent flow over a loose bed of coarse gravel (D₅₀ = 1·5 cm) under sub‐threshold conditions. The analysis is based on quasi‐instantaneous three‐dimensional (3D) full depth velocity profiles with high spatial and temporal resolution that were measured with an Acoustic Doppler Velocity Profiler (ADVP) in an open channel. The results of the analysis confirm the importance of detailed velocity profile measurements for the determination of shear velocity in rough‐bed flows. Results from all methods fall into a range of ± 20% variability and no systematic trend between methods was observed. Local and temporal variation in the loose bed roughness may contribute to the variability of the logarithmic profile method results. Estimates obtained from the TKE and Reynolds stress methods reasonably agree. Most results from the wall similarity method are within 10% of those obtained by the TKE and Reynolds stress methods. The spectral method was difficult to use since the spectral energy of the vertical velocity component strongly increased with distance from the bed in the inner layer. This made the choice of the reference level problematic. Mean shear stress for all experiments follows a quadratic relationship with the mean velocity in the flow. The wall similarity method appears to be a promising tool for estimating shear velocity under rough‐bed flow conditions and in field studies where other methods may be difficult to apply. This method allows for the determination of u_* from a single point measurement at one level in the intermediate range (0·3 < h < 0·6). Copyright © 2013 John Wiley & Sons, Ltd.     

An automated procedure to calculate the morphological parameters of superimposed rhythmic bedforms

Subaqueous dunes are often observed to be superimposed on larger dunes, sand bars and tidal ridges, while smaller dunes may also be found superimposed on larger dunes. In this study an automated method has been developed by which the geometry of superimposed rhythmic bedforms can be analysed. The method combines two-dimensional (2D) Fourier analysis, wavelet transform, zero-crossing analysis and a variety of filters. Instead of applying conventional manual procedures, the wavelength of interest can be automatically determined by a series of 2D Fourier analyses, which is a critical first step for automated analysis of dune geometries. Based on such efficient data preprocessing, the method can accurately determine dune orientation, separate target bedform profiles, and identify crests and troughs. With the input of bathymetry, the dominant regional dune orientation can be determined together with the geometric parameters of individual dunes (wavelength, height, leeside angles) and their spatial distribution. The method was applied to both synthetic and observed bathymetries of a tidal ridge off the Jiangsu coast, China, and a sand bank in the Dover Strait, UK. The results show that almost all dunes in the domain were detected and their geometric parameters accurately calculated, especially in areas of bedform superimposition. © 2020 John Wiley & Sons, Ltd.     

基于HVSR的DONET1海底地震动场地效应研究

为基于谱比方法研究海底地震动场地效应,选取日本DONET1台网的20个海底台站2014—2021年记录的1634组地震数据,对其进行筛选和处理后,利用水平与竖向谱比(HVSR)方法考虑不同布设对海底5组节点台站(KMA、KMB、KMC、KMD、KME)谱比特征的影响.研究结果表明:KMA与KME节点台站具有相似的场地特...     

Regional scale spatial and temporal variability of soil moisture in a prairie region

Understanding the dynamics of spatial and temporal variability of soil moisture at the regional scale and daily interval, respectively, has important implications for remote sensing calibration and validation missions as well as environmental modelling applications. The spatial and temporal variability of soil moisture was investigated in an agriculturally dominated region using an in‐situ soil moisture network located in central Saskatchewan, Canada. The study site evaluated three depths (5, 20, 50 cm) through 139 days producing a high spatial and temporal resolution data set, which were analysed using statistical and geostatistical means. Processes affecting standard deviation at the 5‐cm depth were different from the 20‐cm and 50‐cm depths. Deeper soil measurements were well correlated through the field season. Further analysis demonstrated that lag time to maximum correlation between soil depths increased through the field season. Temporal autocorrelation was approximately twice as long at depth compared to surface soil moisture as measured by the e‐folding frequency. Spatial correlation was highest under wet conditions caused by uniform rainfall events with low coefficient of variation. Overall soil moisture spatial and temporal variability was explained well by rainfall events and antecedent soil moisture conditions throughout the Kenaston soil moisture network. It is expected that the results of this study will support future remote sensing calibration and validation missions, data assimilation, as well as hydrologic model parameterization for use in agricultural regions. Copyright © 2016 John Wiley & Sons, Ltd.     

Spatial variability effects of ground motions on cable-stayed bridges

In this paper, stochastic analysis of a cable-stayed bridge subjected to spatially varying ground motions is performed. While the ground motion is described by power spectral density (PSD) function, the spatial variability of ground motions is taken into account with the incoherence and the wave-passage effects. The incoherence effect is examined by taking into account two extensively used models. As the effect of the wave-passage effect is investigated by using various wave velocities, the effect of local soil conditions where the bridge supports are constructed is outlined by using homogeneous firm, medium and soft soil conditions. Solutions obtained for the spatially varying ground motions are compared with those of the specialised cases of the ground motion model. Stationary as well as the transient response analyses are performed for the considered bridge model. It is concluded that spatial variability and propagation effects of ground motions have important effects on the dynamic behaviour of the bridge and the variability of the ground motions should be included in the stochastic analysis of cable-stayed bridges.     

Diagnostic calibration and cross‐catchment transferability of a simple process‐consistent hydrologic model

The transferability of hydrologic models is of ever increasing importance for making improved hydrologic predictions and testing hypothesized hydrologic drivers. Here, we present an investigation into the variability and transferability of the recently introduced catchment connectivity model (Smith et al., 2013 ). The catchment connectivity model was developed following extensive experimental observations identifying the key drivers of streamflow in the Tenderfoot Creek Experimental Forest (Jencso et al., 2009 ; Jencso et al., 2010 ), with the goal of creating a simple model consistent with internal observations of catchment hydrologic connectivity patterns. The model was applied across seven catchments located within Tenderfoot Creek Experimental Forest to investigate spatial variability and transferability of model performance and parameterization. The results demonstrated that the model resulted in historically good fits (based on previous studies at the sites) to both the hydrograph and internal water table dynamics (corroborated with experimental observations). The impact of a priori parameter limits was also examined. It was observed that enforcing field‐based limits on model parameters resulted in slight reductions to streamflow hydrograph fits, but significant improvements to model process fidelity (as hydrologic connectivity), as well as moderate improvement in the transferability of model parameterizations from one catchment to the next. Copyright © 2016 John Wiley & Sons, Ltd.