New hydrological data assimilation methods offer more accurate flood predictions.
The scientists combined two methods, particle filter and ensemble Kalman filter, to improve hydrological data assimilation. They created two new approaches, CEnPF and PEnPF, and tested them with a rainfall-runoff model. The results showed that both new methods can give better predictions than traditional methods for both deterministic and probabilistic outcomes. Additionally, the computational time for the new methods is manageable, but PEnPF may take longer for large-scale models.
