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A robust method to update local river inundation maps using global climate model output and weather typing based statistical downscaling
(Springer, 2020)
[Abstract:] Global warming is changing the magnitude and frequency of extreme precipitation events. This requires updating local rainfall intensity-duration-frequency (IDF) curves and flood hazard maps according to the ...
Global and local sensitivity analysis to improve the understanding of physically-based urban wash-off models from high-resolution laboratory experiments
(Elsevier, 2019)
[Abstract:] Physically-based urban wash-off models are a promising means of studying the transport of finer suspended solids and their associated pollutants during rain events, considering spatial and temporal heterogeneities. ...
A rapid flood inundation model for hazard mapping based on least squares support vector machine regression
(Wiley, 2019)
[Abstract:] Two-dimensional shallow water models are widely used tools for flood inundation mapping. However, even if High Performance Computing techniques have greatly decreased the computational time needed to run a 2D ...
Investigation of uniform and graded sediment wash-off in an urban drainage system: numerical model validation from a rainfall simulator in an experimental facility
(Elsevier, 2024)
[Abstract:] Understanding sediment wash-off in urban environments plays an essential role in sediment transport management; and is critical for accurate pluvial flood control to assist in adaptation and mitigation strategies. ...
A Risk-Based Approach for the Analysis of Flood Impact in Villahermosa (Tabasco, Mexico)
(MDPI, 2023)
[Abstract:] Floods in Villahermosa are events that have occurred frequently over the centuries, due to the city’s location at the mouth of two of the most powerful rivers in Mexico. Flooding effects on residents have become ...
Improving the predictive skills of hydrological models using a combinatorial optimization algorithm and artificial neural networks
(Springer, 2023)
[Abstract:] Ensemble modelling is a numerical technique used to combine the results of a number of different individual models in order to obtain more robust, better-fitting predictions. The main drawback of ensemble ...
Quantifying the role of individual flood drivers and their correlations in flooding of coastal river reaches
(Springer, 2019)
[Abstract:] Flooding in coastal river reaches is the result of complex interactions between coastal and inland drivers. Flood hazard assessments need to consider how these drivers interact in space and time, for which a ...
Coupling artificial neural networks with the artificial bee colony algorithm for global calibration of hydrological models
(Springer, 2021)
[Abstract:] Hydrological models are widely used tools in water resources management. Their successful application requires an efficient calibration of the model parameters. Nowadays, there are very powerful global search ...
Hydraulic modeling of bridges in two-dimensional shallow water models
(American Society of Civil Engineers, 2022)
[Abstract:] The backwater effect generated by bridges can significantly increase the risk of flooding. In this work we compare two different methods to include the effect of bridges in two-dimensional (2D) shallow water ...
Impact of model simplifications on soil erosion predictions: application of the GLUE methodology to a distributed event-based model at the hillslope scale
(Wiley, 2016)
[Abstract:] In this paper, we analyse how the performance and calibration of a distributed event-based soil erosion model at the hillslope scale is affected by different simplifications on the parameterizations used to ...