Extended Kalman Filter (EKF) prediction of flood water level

Abstract

This paper addresses Extended Kalman Filter (EKF) algorithm that is uses to predict and estimate flood water level. In this respect, good estimates of the flood water level are needed to enable the filter to generate accurate forecasts. The EKF is the best predictor of the flood water level as it is the extended of the basic Kalman Filter algorithm that is only able to solve linear problems. EKF is developed to solve nonlinear problems and flood phenomenon suite well as the water level fluctuates highly nonlinear. This theory is also supported with the simulation results that produce small value of Root Mean Square Error (RMSE) which is close to zero.