Machine Learning (ML) in Water Resources

Machine LearningMachine learning (ML) algorithms are gaining popularity as these can improve the understanding and analysis of hydrologic complexities. In addition, the interaction between ML methods and process-based models may lead to new routes in mechanistic modelling. This chapter includes the classification of ML algorithms, the history of ML, and day-to-day examples of the usage of ML techniques. Besides, the chapter briefly introduces a few ML techniques/algorithms. Among these, support vector machines (SVMs)Support vector machines (SVMs), convolutional neural networks (CNNs)Convolutional neural networks (CNNs) and random forestsRandom forests appear to be the most actively investigated algorithms, but new ones are emerging.