bin Hamden, Muhammad Hanif
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Journal : Civil Engineering Journal

Using the Kalman Filter with Satellite Altimetry to Estimate the Water Level of Inland Water Aryan, Murtadha; Bin Rasib, Abd Wahid; Hassan, Muhammad Imzan; bin Hamden, Muhammad Hanif
Civil Engineering Journal Vol. 11 No. 10 (2025): October
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2025-011-10-018

Abstract

The Euphrates River extends for approximately 2,700 km, making it the longest river in Southwest Asia. Reliable water level measurements are obtained through the integration of an advanced outlier rejection system with Kalman filter technology. This study employs water level data from the Database for Hydrological Time Series over Inland Waters (DAHITI) and validates them using in situ measurements collected from gauging stations along the Euphrates River. To improve the accuracy of water level time series across the study area (Lat: 31.9676, Lon: 44.9306 to Lat: 31.0955, Lon: 46.0942), the research incorporates multibeam altimetry data from Envisat, Jason-2, and Sentinel-3A/B/B. Validation of the altimetry techniques is carried out by comparing DAHITI water level records with in situ measurements and other satellite-based datasets. Both the Kalman filter and Hydroweb methods yield Unbiased Root Mean Square Difference (ubRMSD) values ranging between 0.2961–0.3922 cm and 0.536–0.577 cm, respectively. The Nash-Sutcliffe Efficiency coefficient for DAHITI-derived water levels varies between 0.5971 and 0.9831, while Hydroweb produces values from –0.871 to 0.567. Overall, DAHITI-based altimetry height estimates demonstrate superior accuracy compared to other altimeter datasets in most parts of the Euphrates River, with precision strongly influenced by river topography. The application of Kalman filtering further enhances water level monitoring, particularly in regions characterized by complex inland water structures.