Time series of water surface for estimating of mean water level in shallow areas

standard processing schemes of altimetry lead to the solution with relatively lower accuracy in shallow waters and inland water bodies. In order to get more accurate solution one needs to process the data with more specific processing algorithms. In this paper, we intend to review some retracking methods for shallow water level determination. Moreover, we introduce a new method for time series of water level using the well-known outlier detection of Baarda hypothesis testing. The achieved results are then compared with the dataset which is publicly available from Technical University of Denmark (TUD) as the standard data. The results show that the water levels estimated by the Baarda test are consistent with those of the robust mean water level. The accuracy of results obtained by the new method is at the same order of the robust mean water levels. the differences of baarda method with the standard method and tidegauge data in optimistic method are 2.7 and 28 cm.