engleski

Implementation of a Long Short-Term Memory Neural Network based hydrological model in a snow dominated Alpine basin

Snow dominated Alpine basins are of great importance for the surrounding areas. Due to complex terrain and weather phenomena, hydrological modelling in these areas is often difficult. In this article a state-of-the-art approach based on data-driven models, in form of Recurrent Artificial Neural Networks is presented. In order to investigate the influence of different input data types three models were created. The results proved that adding more input data features can improve model prediction capabilities (R2 increased from 0.91 to 0.93 for the testing period), although fine tuning of model hyperparameters is mandatory to achieve such results. The results of this study show that Long Short-term memory neural network based hydrological models can be used in mid to high elevation snowmelt dominated basins of the Danube tributaries.

hydrological model ; snow dominated basin ; Artificial Neural Network ; Long Short-Term memory ; Drava river

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