The ensemble particle filter (EnPF) in rainfall-runoff models

Rainfall-runoff models play a very important role in flood forecasting. However, these models contain large uncertainties caused by errors in both the model itself and the input data. Data assimilation techniques are being used to reduce these uncertainties. The ensemble Kalman filter (EnKF) and the particle filter (PF) both have their own...

Improving the operational forecasting system of the stratified flow in Osaka Bay using an ensemble Kalman filter–based steady state Kalman filter

Numerical models of a water system are always based on assumptions and simplifications that may result in errors in the model's predictions. Such errors can be reduced through the use of data assimilation and thus can significantly improve the success rate of the predictions and operational forecasts. The ensemble Kalman filter (EnKF) is a...