This paper presents the results of an experimental and numerical study of a vertical slot fishway (VSF). A 2-D depth-averaged shallow water numerical model PCFLOW2D coupled with three different turbulent models (constant eddy viscosity, Smagorinsky and k - ε) was used. A detailed analysis of numerical parameters needed for a correct simulation of the phenomenon was carried out. Besides the velocity field, attention was paid to important hydraulic parameters such as maximum velocity in the slot region and energy dissipation rate ε in order to evaluate the performance of VSF. A scaled physical hydraulic model was built to ensure reliable experimental data for the validation of the numerical model. Simulations of variant configurations of VSF showed that even small changes in geometry can produce more fishfriendly flow characteristics in pools. The present study indicates that the PCFLOW2D program is an appropriate tool to meet the main demands of the VSF design.

Fishways have a great ecological importance as they help mitigate the interruptions of fish migration routes. In the present work, the novel DualSPHysics v4.4 solver, based on the smoothed particle hydrodynamics method (SPH), has been applied to perform three-dimensional (3-D) simulations of water flow in a vertical slot fishway (VSF). The model has been successfully calibrated against published field data of flow velocities that were measured with acoustic Doppler velocity probes. A state-of-the-art algorithm for the treatment of open boundary conditions using buffer layers has been applied to accurately reproduce discharges, water elevations, and average velocity profiles (longitudinal and transverse velocities) within the observed pool of the VSF. Results herein indicate that DualSPHysics can be an accurate tool for modeling turbulent subcritical free surface flows similar to those that occur in VSF. A novel relation between the number of fluid particles and the artificial viscosity coefficient has been formulated with a simple logarithmic fit.

Continuous dissolved gaseous mercury (DGM) measurements were performed during the summer months (May to September 2019) in the Gulf of Trieste (northern Adriatic Sea), a well-studied contaminated site due to releases of mercury from the former mercury mine Idrija in Slovenia. Continuous DGM data were regularly checked by the discrete manual method to assure traceability and comparability of the results and used for the calculation of the upward flux of Hg(0) between the water and the air compartment, using the gas exchange model applied in previous studies in the Mediterranean Sea. DGM concentrations measured by continuous and discrete methods showed good agreement, 68.7 and 73.5 ng·m⁻³, respectively. The diurnal DGM variability examined by sorting the DGM concentrations in 24 1-h intervals was extremely low (68.3–69.2 ng·m⁻³). Various environmental parameters measured at oceanographic buoy Vida, and the nearby stations were used to determine the relationship between DGM and the individual environmental parameters. The correlation with the oxygen saturation was pronounced during the July high DGM event (R² = 0.70, p < 0.05), and the gradient between the bottom and surface temperature was correlated with both DGM peaks in June and July (R² = 0.42 and R² = 0.43, p < 0.05). Transport from the more polluted northern part of the Gulf was determined as the most probable source of both high DGM events. The computed average annual Hg(0) flux across the water–air interface (5.13 ng·m⁻²·h⁻¹) was lower than those reported in recent studies. We assume that for an appropriate assessment of the Hg evasion flux and of the temporal DGM variability in such heterogeneously polluted coastal areas, both spatial and temporal coverage are required.

PublishedJournal Article© 2014 Journal of Mechanical Engineering. All rights reserved. Inverse modelling concentrates on estimating water distribution system (WDS) model parameters that are not directly measurable, e.g. pipe roughness coefficients, which can, therefore, only be estimated by indirect approaches, i.e. inverse modelling. Estimation of the parameter and predictive uncertainty of WDS models is an essential part of the inverse modelling process. Recently, Markov Chain Monte Carlo (MCMC) simulations have gained in popularity in uncertainty analyses due to their effective and efficient exploration of posterior parameter probability density functions (pdf). A Bayesian framework is used to infer prior parameter information via a likelihood function to plausible ranges of posterior parameter pdf. Improved parameter and predictive uncertainty are achieved through the incorporation of prior pdf of parameter values and the use of a generalized likelihood function. We used three prior information sampling schemes to infer the pipe roughness coefficients of WDS models. A hypothetical case study and a real-world WDS case study were used to illustrate the strengths and weaknesses of a particular selection of a prior information pdf. The results obtained show that the level of parameter identifiability (i.e. sensitivity) is an important property for prior pdf selection.We are obliged to Jasper A. Vrugt and Cajo ter Braak\ud for providing the code of the DREAM(ZS) algorithm\ud and graphical post-processing software

A visualization method was employed for accurate non-intrusive measurement of velocity fields at a physical model of a sharp-crested rectangular sideweir under subcritical flow. The experimental observation of velocity vectors at various horizontal planes over the entire width of the main channel confirms that the flow conditions at sideweir are non-uniform. The coefficients of non-uniform velocity distribution were in the range from 1 to 1.1. The present study focuses on the relation between the longitudinal components of the overflow velocities and the corresponding cross-sectional average velocities in the main channel, detailed as a function of flow depth and of location along the sideweir crest. For different sideweir geometries, these coefficients varied between 1 and 1.2.