Data-driven prediction of daily Cryptosporidium river concentrations for water resource management: Use of catchment-averaged vs spatially distributed features in a Bagging-XGBoost model

Cryptosporidium is a waterborne pathogen which poses a major challenge to water utilities because of its resistance to chlorination and its infectivity at very low concentrations. The ability to make predictions of Cryptosporidium concentrations in rivers would aid significantly in abstraction-based...

Ausführliche Beschreibung