Over the last few decades, the use of artificial intelligence (AI) has experienced a high increase in a wide variety of research fields. This kind of models are characterized as powerful tools to obtain information which would otherwise be very complicated or impossible to get. AI models, together with the large amount of hydrologycal data currently available, provide the ideal conditions to create tools aimed at managing water supply, predicting flood and drought, monitoring water quality, optimizing irrigation schemes, managing dams, determining carbonate saturation, evaluating the sedimentation process, and modeling the contaminant transport, among others. All the AI models, from the simplest to the most complex, such as random forest or neural networks, therefore allow expanding the existing knowledge about the complex water system.
The aim of this Special Issue on “The Application of Artificial Intelligent in Hydrology” is to present the state-of-the-art related (but not limited) to the study of movements, distribution, and management of water in nature.
We invite authors to submit research articles, reviews, communications, and concept papers that demonstrate the high potential of artificial intelligence in the hydrological field.
Keywords
- Artificial intelligence
- Machine learning
- Big data/Cloud computing
- Monitoring/Modelling/Prediction/Optimization
- Flow prediction
- Water quality
- Water supply
- Management
- Risk assessment
- Multidisciplinary research
