Case Study on the Application of Machine Learning in Hydrology
This thesis presents a case study on the application of artificial intelligence (AI) in hydrology using two approaches. This topic was chosen since AI is an important tool, and water is a vital resource. The first case is on leakage detection with artificial data, while the second is on precipitation prediction with real data. For leakage detection, a random forest (RF) model and an artificial neuWater is the most vital resource, yet globally, 30% is lost through leaks. By implementing artificial intelligence (AI), this thesis has developed methods to locate leaks with high precision, as well as models to improve accuracy on satellite-based precipitation data. This thesis investigates two applications of AI on real-world problems; detecting water leaks and improving precipitation data. Th
