River water level prediction plays an important role in effective planning and flood risk mitigation. In this study, four standalone machine learning (ML) models, M5Rules, Random Forest (RF), Sequential Minimal Optimization (SMO), and Long Short-Term Memory (LSTM), as well as a hybrid LSTM-RF model, were developed to predict weekly water levels of the Rhine River. The models were trained and tested using data collected between...