AIMC Topic: Hydrology

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A comprehensive review of deep learning applications in hydrology and water resources.

Water science and technology : a journal of the International Association on Water Pollution Research
The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume, variety and velocity of water-related data are increasing due to large-scale sensor networks and increased attention to topics such as disaster response, water...

Hybrid wavelet-support vector machine approach for modelling rainfall-runoff process.

Water science and technology : a journal of the International Association on Water Pollution Research
Because of the importance of water resources management, the need for accurate modeling of the rainfall-runoff process has rapidly grown in the past decades. Recently, the support vector machine (SVM) approach has been used by hydrologists for rainfa...

Application of transit data analysis and artificial neural network in the prediction of discharge of Lor River, NW Spain.

Water science and technology : a journal of the International Association on Water Pollution Research
Transit data analysis and artificial neural networks (ANNs) have proven to be a useful tool for characterizing and modelling non-linear hydrological processes. In this paper, these methods have been used to characterize and to predict the discharge o...