Browsing by Author "Farfán-Durán, Juan F."
Now showing items 1-8 of 8
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A Hybrid Neural Network-Based Technique to Improve the Flow Forecasting of Physical and Data-Driven Models: Methodology and Case Studies in Andean Watersheds
Farfán-Durán, Juan F.; Palacios Gárate, Karina Fernanda; Ulloa, Jacinto; Avilés, Alex (Elsevier, 2020)[Abstract] Study region The present study was conducted in the Machángara Alto and Chulco rivers, which belong to the Paute basin in the provinces of Azuay and Cañar in southern Ecuador. Study focus Andean watersheds ... -
A robust method to update local river inundation maps using global climate model output and weather typing based statistical downscaling
Bermúdez, María; Cea, Luis; Van Uytven, Els; Willems, Patrick; Farfán-Durán, Juan F.; Puertas, Jerónimo (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 ... -
Assessing the Effects of Climate Change on Compound Flooding in Coastal River Areas
Bermúdez, María; Farfán-Durán, Juan F.; Willems, Patrick; Cea, Luis (AGU Journals, 2021)[Abstract] Flood assessment in coastal river areas is subject to complex dependencies and interactions between flood drivers. In addition, coastal areas are especially vulnerable to climate change, and thus its effects ... -
Coupling artificial neural networks with the artificial bee colony algorithm for global calibration of hydrological models
Cea, Luis; Farfán-Durán, Juan F. (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 ... -
Enhancing Hydrological Modeling with Artificial Intelligence
Farfán-Durán, Juan F. (2024)[Resumo] Os modelos hidrolóxicos son esenciais para aplicacións como a simulación do fluxo de ríos, a previsión de inundacións e a xestión de recursos hídricos. Non obstante, a súa eficacia depende frecuentemente de ... -
Improving the predictive skills of hydrological models using a combinatorial optimization algorithm and artificial neural networks
Cea, Luis; Farfán-Durán, Juan F. (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 ... -
Regional streamflow prediction in northwest Spain: A comparative analysis of regionalisation schemes
Cea, Luis; Farfán-Durán, Juan F. (Elsevier, 2023)[Abstract:] Study Region: The present study was conducted in 24 watersheds located in the region of Galicia, in the northwest of Spain, covering an extension of approximately 13,000 km. Study focus: This study is focused ... -
Surrogate-Assisted Evolutionary Algorithm for the Calibration of Distributed Hydrological Models Based on Two-Dimensional Shallow Water Equations
Farfán-Durán, Juan F.; Heidari, Arash; Dhaene, Tom; Couckuyt, Ivo; Cea, Luis (MDPI, 2024)[Abstract:] Distributed hydrological models based on shallow water equations have gained popularity in recent years for the simulation of storm events, due to their robust and physically based routing of surface runoff ...
