For the general purposes of morphodynamic computations in coastal zones, simple formula-based models are usually employed to evaluate sediment transport. Sediment transport rates are computed as a function of the bottom shear stress or the near bed flow velocity and it is generally assumed that the sediment particles react immediately to changes in flow conditions. It has been recognized, through recent laboratory experiments in both rippled and plane bed sheet flow conditions that sediment reacts to the flow in a complex manner, involving non-steady processes resulting from memory and settling/entrainment delay effects. These processes may be important in the cross-shore direction, where sediment transport is mainly caused by the oscillatory motions induced by surface short gravity waves.The aim of the present work is to develop a semi-unsteady, practical model, to predict the total (bed load and suspended load) sediment transport rates in wave or combined wave-current flow conditions that are characteristic of the coastal zone. The unsteady effects are reproduced indirectly by taking into account the delayed settling of sediment particles. The net sediment transport rates are computed from the total bottom shear stress and the model takes into account the velocity and acceleration asymmetries of the waves as they propagate towards the shore.A comparison has been carried out between the computed net sediment transport rates with a large data set of experimental results for different flow conditions (wave-current flows, purely oscillatory flow, skewed waves and steady currents) in different regimes (plane bed and rippled bed) with fine, medium and coarse uniform sand. The numerical results obtained are reasonably accurate within a factor of 2. Based on this analysis, the limits and validity of the present formulation are discussed.
The south arm of the Mondego estuary, located in the central western Atlantic coast of Portugal, is almost silted up in the upstream area. So, the water circulation is mostly driven by tides and the tributary river Pranto discharges. Eutrophication has been taking place in this ecosystem during last twelve years, where macroalgae reach a luxuriant development covering a significant area of the intertidal muddy flat. A sampling program was carried out from June 1993 to June 1994. Available data on salinity profiles and on nutrients loading into the south arm were used in order to get a better understanding of the ongoing changes. River Pranto flow discharges, controlled by a sluice, were also monitored. Integral formulations are typically based on assumptions of steady state and well-mixed systems and thus cannot take into account the space and time variability of estuarine residence times, due to river discharge flow, tidal coefficients, discharge(s) location and time of release during the tidal cycle. This work presents the hydrodynamics modelling (2D-H) of this system in order to estimate the residence times variability and to assess their effect on the estuarine eutrophication vulnerability, contributing to better environmental management strategies selection.
Flood events are dependent on meteorological conditions but also depend on several other factors that are case specific, with relevance for reservoir operation. Hydrological and hydrodynamic models are valuable tools for understanding complex river hydrodynamics during flood events. These tools have been applied to improve understanding of the causes for an urban flood event that occurred between 9 and 11 January 2016 in the Mondego river basin, at Coimbra city (Portugal). Seven different factors that can, independently, influence the river flow at the study site were identified: three of them can be associated with the operational discharge schemes of the three upstream dams; two factors with the runoff flows from uncontrolled contributing sub-basins; another one related to discharge measurement uncertainty at a downstream dam; and finally, the seventh studied factor was sedimentation occurring in the main channel of the flooded river stretch.Hydroinformatic tools were applied in different scenarios allowing the characterization and identification of each one of the identified key factors responsible for the flood event. A proposal for a flood early warning system is presented based on the knowledge resulting from the studied flood event.
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