Precipitation Interception Modelling Using Machine Learning Methods - The Dragonja River Basin Case Study

The machine learning methods M5 for generating regression and model tree models and J4.8 for generating classification tree models were selected as the methods for analysis of the results of experimental measurements in the Dragonja River basin. Many interesting and useful details about the process of precipitation interception by the forest in the Dragonja River basin were found. The resulting classification and regression tree models clearly show the degree of influence and interactions between different climatic factors, which importantly influence the process of precipitation interception.