Data-Driven Methods for Modelling Drainage Water Outflow
This paper presents predictive models for identification of drainage periods and amount of drained water from
tile-drained agricultural fields. The study utilizes data mining methodology over data collected in Western France. The
learning of the models encompasses data preprocessing and the building itself, as well as model evaluation using unseen
data. The results show that by considering the data mining methodology, the process of drainage water outflow can be
accurately described and predicted using descriptive climatic, soil and crop data. The discussion encompasses possible
applicability of the generated models for the purpose of ground-water protection from plant protection products used in
Index terms- Tile-drained water, ground water protection, outflow prediction, data mining.