Evaluation of Data-Driven Methods for Hydrological Modeling: A Case Study of the Etobicoke Creek Watershed

In the past two decades, data-driven modeling has become a popular approach for different modeling tasks. This paper presents an evaluation of the performance of five widely used data-driven approaches (i.e., generalized linear model, lasso regression, support vector machine, neural networks, and random forest) for the modeling of the Etobicoke Creek watershed in Ontario, Canada. The models are built with eleven years of meteorological and …