Search Results (4)

Flood-control reservoirs are often used as a structural measure to mitigate fluvial floods, and numerical models are a fundamental tool for assessing their effectiveness. This work aims to analyze the suitability of fully 2D shallow-water models to simulate these systems by adopting internal boundary conditions to describe hydraulic structures (i.e., dams) and by using a parallelized code to reduce the computational burden. The 2D results are also compared with the more established approach of coupling a 1D model for the river and a 0D model for the reservoir. Two test cases, including an in-stream reservoir and an off-stream basin, both located in Italy, are considered. Results show that the fully 2D model can effectively handle the simulation of a complex flood-control system. Moreover, compared with the 0D–1D model, it captures the velocity field and the filling/emptying process of the reservoir more realistically, especially for off-stream reservoirs. Conversely, when the basin is characterized by very limited flood dynamics, the two approaches provide similar results (maximum levels in the reservoir differ by less than 10 cm, and peak discharges by about 5%). Thanks to parallelization and the inclusion of internal boundary conditions, fully 2D models can be applied not only for local hydrodynamic analyses but also for river-scale studies, including flood-control reservoirs, with reasonable computational effort (i.e., ratios of physical to computational times on the order of 30–100). Full article

Mine tailings are commonly stored in off-stream reservoirs and are usually composed of water with high concentrations of fine particles (microns). The rupture of a mine-tailings pond promotes, depending on the characteristics of the stored material, the fluidization and release of hyper-concentrated flows that typically behave as non–Newtonian fluids. The simulation of non–Newtonian fluid dynamics using numerical modelling tools is based on the solution of mass and momentum conservation equations, particularizing the shear stress terms by means of a rheological model that accounts for the properties of the fluid. This document presents the extension of Iber, a two-dimensional hydrodynamic numerical tool, for the simulation of non–Newtonian shallow flows, especially those related to mine tailings. The performance of the numerical tool was tested throughout benchmarks and real study cases. The results agreed with the analytical and theoretical solutions in the benchmark tests; additionally, the numerical tool also revealed itself to be adequate for simulating the dynamic and static phases under real conditions. The outputs of this numerical tool provide valuable information, allowing researchers to assess flood hazard and risk in mine-tailings spill propagation scenarios. Full article

Off-stream reservoirs are hydraulic structures that might cause severe flood damages in case of failure or improper operation. Their safety regulations usually require hydraulic studies for flood hazard and inundation zone mapping. The selection of the break point is not trivial because the topography in its surroundings is commonly highly anthropic. A wrong selection would not provide the worst scenario in terms of maximum flood hazard extent. This work presents a probabilistic approach based on a stochastic definition of the break point along the dyke. A number of failure scenarios are generated automatically, corresponding to different breach formations. Then, an in-cascade calculation process simulates each scenario, providing a framework to carry out statistical analysis. The simulation of the breach formation and the flood wave propagation is performed through a GPU parallelised two-dimensional hydraulic numerical model, which provides a probabilistic inundation zone and flood hazard mapping of all scenarios simulated in a suitable timeframe. Full article

Approximately 70,000 Spanish off-stream reservoirs, many of them irrigation ponds, need to be evaluated in terms of their potential hazard to comply with the new national Regulation of the Hydraulic Public Domain. This requires a great engineering effort to evaluate different scenarios with two-dimensional hydraulic models, for which many owners lack the necessary resources. This work presents a simplified methodology based on machine learning to identify risk zones at any point in the vicinity of an off-stream reservoir without the need to elaborate and run full two-dimensional hydraulic models. A predictive model based on random forest was created from datasets including the results of synthetic cases computed with an automatic tool based on the two-dimensional numerical software Iber. Once fitted, the model provided an estimate on the potential hazard considering the physical characteristics of the structure, the surrounding terrain and the vulnerable locations. Two approaches were compared for balancing the dataset: the synthetic minority oversampling and the random undersampling. Results from the random forest model adjusted with the random undersampling technique showed to be useful for the estimation of risk zones. On a real application test the simplified method achieved 91% accuracy. Full article