Jerónimo Puertas

Prediction and modeling of the rainfall-runoff transformation of a typical urban basin using ann and gp

This paper proposes an application of Genetic Programming (GP) and Artificial Neural Networks (ANN) in hydrology, showing how these two techniques can work together to solve a problem, namely for modeling the effect of rain on the runoff flow in a typical urban basin. The ultimate goal of this research is to design a real-time alarm system to warn of floods or subsidence in various types of urban basins. Results look promising and appear to offer some improvement for analyzing river basin systems over stochastic methods such as unitary hydrographs.

Dam-break flows over mobile beds: Experiments and benchmark tests for numerical models

In this paper, the results of a benchmark test launched within the framework of the NSF–PIRE project “Modelling of Flood Hazards and Geomorphic Impacts of Levee Breach and Dam Failure” are presented. Experiments of two-dimensional dam-break flows over a sand bed were conducted at Université catholique de Louvain, Belgium. The water level evolution at eight gauging points was measured as well as the final bed topography. Intense scour occurred close to the failed dam, while significant deposition was observed further downstream. From these experiments, a benchmark was proposed to the scientific community, consisting of blind test simulations, that is, without any prior knowledge of the measurements. Twelve different teams of modellers from eight countries participated in the study. Here, the numerical models used in this test are briefly presented. The results are commented upon, in view of evaluating the modelling capabilities and identifying the challenges that may open pathways for further research.

Optical Fish Trajectory Measurement in Fishways through Computer Vision and Artificial Neural Networks

Vertical slot fishways are hydraulic structures that allow the upstream migration of fish through obstructions in rivers. The appropriate design of a vertical slot fishway depends on the interplay between hydraulic and biological variables because the hydrodynamic properties of the fishway must match the requirements of the fish species for which it is intended. One of the primary difficulties associated with studies of real fish behavior in fishway models is that the existing mechanisms to measure the behavior of the fish in these assays, such as direct observation or placement of sensors on the specimens, are impractical or unduly affect the animal behavior. This paper proposes a new procedure for measuring the behavior of the fish. The proposed technique uses artificial neural networks and computer vision techniques to analyze images obtained from the assays by means of a camera system designed for fishway integration. It is expected that this technique will provide detailed information about the fish behavior, and it will help to improve fish passage devices, which is currently a subject of interest in the area of civil engineering. A series of assays has been performed to validate this new approach in a full-scale fishway model with living fish. We have obtained very promising results that allow accurate reconstruction of the movements of the fish within the fishway.

Prediction and Modelling of the Flow of a Typical Urban Basin through Genetic Programming

Genetic Programming (GP) is an evolutionary method that creates computer programs that represent approximate or exact solutions to a problem. This paper proposes an application of GP in hydrology, namely for modelling the effect of rain on the run-off flow in a typical urban basin. The ultimate goal of this research is to design a real time alarm system to warn of floods or subsidence in various types of urban basin. Results look promising and appear to offer some improvement over stochastic methods for analysing river basin systems such as unitary radiographs.

Uncertainty and sensitivity analysis of a depth-averaged water quality model for evaluation of Escherichia Coli concentration in shallow estuaries

Sensitivity and uncertainty analysis investigate the robustness of numerical model predictions and provide information about the factors that contribute most to the variability of model output, identifying the most important parameters for model calibration. This paper presents a sensitivity and uncertainty analysis of a 2D depth-averaged water quality model applied to a shallow estuary. The model solves the mass transport equation for Escherichia Coli, including the effects of water temperature, salinity, solar radiation, turbulent diffusion and short wave dispersion. The sensitivity of the concentration of E. Coli in the estuary to input parameters and the different sources of uncertainty are studied using Global Sensitivity Analysis based on Monte Carlo simulation methods and sensitivity measures based on linear and non-linear regression analysis, in order to aid modellers in the calibration process and in the interpretation of model output. The extinction coefficient of light in water and the depth of the vertical layer over which the E. coli spread were found to be the most relevant parameters of the model. In the shallowest regions of the estuary errors in the bathymetry are also an important source of uncertainty on model output. Globally, the combination of these three parameters was found to be very effective for calibration purposes in the whole estuary.

Validation of a 1D-2D dual drainage model under unsteady part-full and surcharged sewer conditions

This paper presents a 1D-2D dual drainage model to compute the rainfall-runoff transformation in urban environments. Overland flow in major drainage systems is modelled with the 2D shallow water equations, whereas the flow in a sewer network is computed with the 1D Saint-Venant equations using the two-component pressure approach to model pressure-flow conditions. The surface and sewer network models are linked through manholes, which allow water interchange in both directions. A new series of rainfall–runoff experiments in a real-scale physical model of a street section is used to validate the model under unsteady part-full and pressure flow conditions. The experimental measurements of water depth and discharge at several locations in a drainage network show a very satisfactory performance of the numerical model.

Overland flow computations in urban and industrial catchments from direct precipitation data using a two-dimensional shallow water model

This paper presents the experimental validation and the application to a real industrial catchment of a two-dimensional depth-averaged shallow water model used for the computation of rainfall-runoff transformation from direct precipitation data. Instead of using the common approach in flood inundation modelling, which consists in computing the water depth and velocity fields given the water discharge, in this study the rainfall intensity is imposed directly in the model, the surface runoff being generated automatically. The model considers infiltration losses simultaneously with flow simulation. Gullies are also included in the model, although the coupling between the surface runoff and the sewer network is not considered. Experimental validation of the model is presented in several simplified laboratory configurations of urban catchments, in which the surface runoff has been measured for different hyetographs. The application to a real industrial catchment includes a sewer network flow component, which is solved with the SWMM model. The numerical predictions of the discharge hydrograph generated by a 12 hours storm event are compared with field measurements, providing encouraging results.

Estimation of Drag Coefficient and Settling Velocity of the Cockle Cerastoderma edule Using Particle Image Velocimetry (PIV)

Abstract This paper presents the results of a hydrodynamic study of a cockle population from the Ullas estuary in Galicia (Spain). An analysis of the parameters has made it possible to determine the hydraulic characteristics of whole cockles during their threshold of movement and suspension. Dynamic analysis of the forces exerted on the submerged cockles led to a detailed characterization of a final population of 11 cockles, including their characteristic dimensions in addition to shell and body density. The friction angle between the existing sediment in the Ullas estuary and the cockle shells was also recorded. The particle image velocimetry (PIV) laser technique was successfully applied to obtain an accurate calculation of the threshold velocity fields. This experimental tool provides the means to experiment with various approaches of the velocity governing the onset of motion and to obtain a more detailed definition of the parameters involved. Applying the PIV technique, three drag entrainment coefficients were obtained with different velocity profiles. Using the depth-averaged velocity profile, a constant entrainment drag coefficient value of 0.43 was obtained for this cockle family, whereas the use of the upper tangential velocity on the cockle resulted in a value of 0.56 with a wider range of variation. This velocity may be considered a more intrinsic parameter of the movement of the cockle. The process of cockle sedimentation was also monitored, enabling us to ascertain the settling velocity and to calculate the settling drag coefficient. Both parameters present constant values in the group of cockles analyzed, with mean values of 0.36 m s−1 and 1.08, respectively. The settling drag coefficient was also calculated. A comparison of these two experimental values with other existing reports exhibited similar results, thus validating both the procedures used and the effect of the shape factor on the settling drag coefficient value.

Global Sensitivity and GLUE-Based Uncertainty Analysis of a 2D-1D Dual Urban Drainage Model

AbstractThis paper presents a global sensitivity and uncertainty analysis of a dual drainage model applied to a 0.049 km2 (4.9-ha) urban catchment based on generalized likelihood uncertainty estimation (GLUE). The model solves the nonlinear bidimensional (2D) and one-dimensional (1D) Saint-Venant equations to compute respectively the surface runoff and the flow in the sewer network. The sensitivity of the outlet hydrograph to the input parameters of the model was determined by using variance-based Sobol sensitivity indices. These indices highlight the great effect of the overland flow parameters on the model output, in contrast with the limited effect of the sewer-network parameters. The Manning coefficient of the impervious terrains was identified as the most influential model parameter. The effect on model calibration of two subjective factors of the GLUE methodology (the acceptability threshold and the shaping factor of the likelihood function) was analyzed. From this analysis, a NSE acceptability thre...

Scour of rock due to the impact of plunging high velocity jets Part I: A state-of-the-art review

ERIK BOLLAERT and ANTON SCHLEISS, Journal of Hydraulic Research, IJHR, Volume 41, 2003, Number 5, pp. 451–464