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Derx J.,Institute of Hydraulic Engineering and Water Resources Management | Derx J.,Vienna University of Technology | Blaschke A.P.,Institute of Hydraulic Engineering and Water Resources Management | Blaschke A.P.,Vienna University of Technology | And 6 more authors.
Journal of Contaminant Hydrology | Year: 2013

Riverbank filtration is an effective process for removing pathogenic viruses from river water. Despite indications that changing hydraulic conditions during floods can affect the efficacy of riverbank filtration to remove viruses, the impact on advection and dispersion of viruses in the riverbank is not well understood. We investigated the effects of fluctuations in river water level on virus transport during riverbank filtration, considering 3-D transient groundwater flow and virus transport. Using constant removal rates from published field experiments with bacteriophages, removal of viruses with distance from the riverbank was simulated for coarse gravel, fine gravel and fine sandy gravel. Our simulations showed that, in comparison with steady flow conditions, fluctuations in river water level cause viruses to be transported further at higher concentrations into the riverbank. A 1-5 m increase in river water levels led to a 2- to 4-log (log10 reduction in concentration relative to the initial concentration in the river) increase in virus concentration and to up to 30 % shorter travel times. For particular cases during the receding flood, changing groundwater flow conditions caused that pristine groundwater was carried from further inland and that simulated virus concentrations were more diluted in groundwater. Our study suggests that the adverse effect of water level fluctuations on virus transport should be considered in the simulation of safe setback distances for drinking water supplies. © 2013 Published by Elsevier B.V. Source

Hollander H.M.,Water Resources University | Hollander H.M.,University of Manitoba | Bormann H.,University of Siegen | Blume T.,German Research Center for Geosciences | And 12 more authors.
Hydrology and Earth System Sciences | Year: 2014

In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information.

Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of added information.

In this qualitative analysis of a statistically small number of predictions we learned (i) that soft information such as the modeller's system understanding is as important as the model itself (hard information), (ii) that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter guessing), and (iii) that added process understanding can be as efficient as adding data for improving parameters needed to satisfy model requirements.©Author(s) 2014. Source

Motamedi A.,Isfahan University of Technology | Motamedi A.,Graz University of Technology | Afzalimehr H.,Isfahan University of Technology | Zenz G.,Institute of Hydraulic Engineering and Water Resources Management
European Journal of Scientific Research | Year: 2011

Acoustic Doppler Velocimeters (ADV) experiments have been conducted over a fixed-dune to examine the effects of interacting dunes on the flow structure. The shape, dimensions and side angle of selected dunes were based upon previous empirical and field studies of dune morphology. Experiments were carried out on flow over a train of fixed 2D rough wall dunes in 12m flume. Dunes are developed in the height of 4 and 8 cm and in wavelength of 1m. This paper investigate the effect of lee angle (steep (>20°) and low (<10°) lee side angles) on separation zone and to study the effect of the dune bed roughness on turbulence structures and the length of separation zone calibrated RANS simulations was compared with experimental data. It is found that the models provide a good overall description measured by ADV. The separation zone also has a strong relation with lee angle and in the situation of low lee angle no flow separation was detected. Also increasing the dune height, roughness, water depth or velocity don't have an effective impact to separate the flow near the crest. © 2011 EuroJournals Publishing, Inc. Source

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