Groundwater quality is very important for human health. Estimation of groundwater pollution concentration to determine groundwater quality is necessary. The concentration of groundwater pollution is estimated using the modified Kalman filter method. The modified Kalman filter method is a method that collaborates the Kalman filter estimation algorithm with the model order reduction method. The model order reduction method used in this research is the LMI (Linear Matrix Inequality) method because the model reduction error using the LMI method is the smallest error compared to the reduction error using the Balanced Truncation method or the Singular Pertrubation Approximation method. The modified Kalman filter method is used in order to obtain accurate estimation results with a short computation time. It is found that the implementation of the Kalman filter algorithm in the original system as well as the implementation of the modified Kalman filter method of the reduced system with the LMI method produces very good estimates, close to the real state variable. The estimation of the original system takes longer time than the reduced system.
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