Wavefield tomography based on local image correlations

The estimation of a velocity model from seismic data is a crucial step for obtaining a high‐quality image of the subsurface. Velocity estimation is usually formulated as an optimization problem where an objective function measures the mismatch between synthetic and recorded wavefields and its gradient is used to update the model. The objective function can be defined in the data‐space (as in full‐waveform inversion) or in the image space (as in migration velocity analysis). In general, the latter leads to smooth objective functions, which are monomodal in a wider basin about the global minimum compared to the objective functions defined in the data‐space. Nonetheless, migration velocity analysis requires construction of common‐image gathers at fixed spatial locations and subsampling of the image in order to assess the consistency between the trial velocity model and the observed data. We present an objective function that extracts the velocity error information directly in the image domain without analysing the information in common‐image gathers. In order to include the full complexity of the wavefield in the velocity estimation algorithm, we consider a two‐way (as opposed to one‐way) wave operator, we do not linearize the imaging operator with respect to the model parameters (as in linearized wave‐equation migration velocity analysis) and compute the gradient of the objective function using the adjoint‐state method. We illustrate our methodology with a few synthetic examples and test it on a real 2D marine streamer data set.     

Statistics and characteristic scales for bed load in a channel flow with sidewall effects

Results are presented for a long-duration sediment transport experiment with a plane bed. High-frequency time series of sediment concentration, sediment velocity and solid discharge per unit width were measured using image analysis of video records. A range of transport intensities from a single experiment has been analysed considering transport at different distances from the sidewalls as an independent variable. First and second order temporal statistics of the spatially-averaged values of the transport parameters are presented, which are in agreement with previous studies. A refined statistical analysis of the sediment concentration dynamics, reflecting bed load process, is also given. The characteristic scales of the sediment concentration dynamics are evaluated and analyzed in conjunction with those of the near-bed and bulk flow fields.     

Detrital Cr-spinel in the Šambron–Kamenica Zone (Slovakia): evidence for an ocean-spreading zone in the Northern Vardar suture?

The Šambron–Kamenica Zone is situated on the northern margin of the Levočské vrchy mountains and Šarišskà vrchovina Highland, where the Central Carpathian Paleogene joins the Pieniny Klippen Belt. Sandstone outcrops in this area. From Cretaceous to Late Oligocene in age, these sediments suggest transport directions from S and SE. The heavy mineral assemblages of this sandstone include Cr-spinel grains, mainly displaying types II and III alpine-peridotite affinities, and are representative of Ocean Island Basalt volcanism. A sample from Upper Eocene sediments at Vit’az shows a clear change in Cr-spinel composition, which turns out to have types I and II peridotite affinities, and to derive from arc and Middle Ocean Ridge Basalt volcanism, with sediment transport directions from SW and WSW. These data indicate major variations in the Upper Eocene tectonic setting, giving constraints to paleogeographic reconstruction of the Slovak Central Carpathians.     

Double-average characteristics of sediment motion in one-dimensional bed load

The sediment transport process on a flat bed was investigated experimentally, with reference to the relationship between the average solid discharge and the concentration and velocity of the moving grains. The instantaneous values of the quantities were measured and, therefore, it was possible to quantify the contribution of the temporal fluctuations of concentration and velocity to the resulting average sediment transport rate. Recognizing that the sediment transport process is an episodic phenomenon, an intermittency factor was defined and its contribution to the solid discharge, typically implicit in earlier formulations of the sediment flux, was highlighted. Conceptual analyses of the spatial scale dependence of the quantities were also made.     

A simulation experiment for optimal design hyetograph selection

The aim of this work is to assess the accuracy of literature design hyetographs for the evaluation of peak discharges during flood events. Five design hyetographs are examined in a set of simulations, based upon the following steps: (i) an ideal river basin is defined, characterized by a Beta distribution shaped unit hydrograph (UH); (ii) 1000 years of synthetic rainfall are artificially generated; (iii) a discharge time‐series is obtained from the convolution of the rainfall time‐series and the UH, and the reference T‐years flood is computed from this series; (iv) for the same return period T, the parameters of the intensity–duration–frequency (IDF) curve are estimated from the 1000 years of synthetic rainfall; (v) five design hyetographs are determined from the IDF curves and are convolved with the discrete UH to find the corresponding design hydrographs; (vi) the hydrograph peaks are compared with the reference T‐years flood and the advantages and drawbacks of each of the five approaches are evaluated. The rainfall and UH parameters are varied, and the whole procedure is repeated to assess the sensitivity of results to the system configuration. We found that all design hyetographs produce flood peak estimates that are consistently biased in most of the climatic and hydrologic conditions considered. In particular, significant underestimation of the design flood results from the adoption of any rectangular hyetograph used in the context of the rational formula. In contrast, the Chicago hyetograph tends to overestimate peak flows. In two cases it is sufficient to multiply the result by a constant scaling factor to obtain robust and nearly unbiased estimates of the design floods. Copyright © 2007 John Wiley & Sons, Ltd.     

Effects of 4-nonylphenol exposure in mussels (Mytilus galloprovincialis) and crabs (Carcinus aestuarii) with particular emphasis on vitellogenin induction

Since it is often difficult to estimate possible adverse effects due to contamination in selected ecosystems, multi-species biomonitoring may provide more information, taking into account different routes of exposure, ecological roles and metabolic capabilities of animals. In this context, we exposed for 7 days the mussel Mytilus galloprovincialis and the crab Carcinus aestuarii to 4-nonylphenol (NP), a well-known xenoestrogen. In mussels (0–0.2 mg NP l⁻¹), we measured NP bioaccumulation in soft tissues and vitellogenin (Vg)-like protein levels in digestive glands from both males and females by the alkali-labile phosphate assay (ALP). As no reference data were available for crab exposure, the NP 96-h LC₅₀ value was previously determined. Then, in sublethally exposed (0–1.0 mg NP l⁻¹) male crabs, NP bioaccumulation and Vg levels were measured in hemolymph, gonads and digestive gland. Bioaccumulation of NP increased from 43 to 371 μg g⁻¹ d.w. in mussels, and from 3.6 to 37 μg g⁻¹ d.w. in crabs, depending on the NP concentration in water. Dose-dependent Vg-like protein induction was observed in both species, appearing to be related to NP bioaccumulation, although a partial decrease was recorded at the highest concentration tested. A similar trend was observed in both digestive gland and gonad of exposed crabs; Vg increased to a lesser extent, although significantly, in hemolymph. Results demonstrated that NP induces Vg synthesis both in male and female mussels, as well as in male crabs. On the basis of the responsiveness of both species investigated, a multi-species approach is indicated in biomonitoring programmes.     

Modeling radar-rainfall estimation uncertainties using parametric and non-parametric approaches

There are large uncertainties associated with radar estimates of rainfall, including systematic errors as well as the random effects from several sources. This study focuses on the modeling of the systematic error component, which can be described mathematically in terms of a conditional expectation function. The authors present two different approaches: non-parametric (kernel-based) and parametric (copula-based). A large sample (more than six years) of rain gauge measurements from a dense network located in south-west England is used as an approximation of the true ground rainfall. These data are complemented with rainfall estimates by a C-band weather radar located at Wardon Hill, which is about 40 km from the catchment. The authors compare the results obtained using the parametric and non-parametric schemes for four temporal scales of hydrologic interest (5 and 15 min, hourly and three-hourly) by means of several different performance indices and discuss the strengths and weaknesses of each approach.     

Incorporating multiple observations for distributed hydrologic model calibration: An approach using a multi-objective evolutionary algorithm and clustering

The use of distributed data for model calibration is becoming more popular in the advent of the availability of spatially distributed observations. Hydrological model calibration has traditionally been carried out using single objective optimisation and only recently has been extended to a multi-objective optimisation domain. By formulating the calibration problem with several objectives, each objective relating to a set of observations, the parameter sets can be constrained more effectively. However, many previous multi-objective calibration studies do not consider individual observations or catchment responses separately, but instead utilises some form of aggregation of objectives. This paper proposes a multi-objective calibration approach that can efficiently handle many objectives using both clustering and preference ordered ranking. The algorithm is applied to calibrate the MIKE SHE distributed hydrologic model and tested on the Karup catchment in Denmark. The results indicate that the preferred solutions selected using the proposed algorithm are good compromise solutions and the parameter values are well defined. Clustering with Kohonen mapping was able to reduce the number of objective functions from 18 to 5. Calibration using the standard deviation of groundwater level residuals enabled us to identify a group of wells that may not be simulated properly, thus highlighting potential problems with the model parameterisation.