- H13R-1331: The Inverse Predictor-Corrector Data Assimilation method for discharge estimation in rivers (IPCDA): development, sensitivity analysis and application
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Board 1331‚ Hall EFG (Poster Hall)NOLA CC
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David Poblete, Universidad de Valparaíso (First Author, Presenting Author)
Rodrigo Meneses, University of Valparaiso
Valeria Madrid, Universidad de Valparaíso
This study presents a new method called IPCDA, which helps estimate how much water flows through rivers or channels using only information that can be collected remotely—such as from drones or satellites. The method uses basic river features like surface water level, flow speed, and channel width, along with estimated values for riverbed roughness and slope. It is based on simplified equations that describe how water moves through a river.The IPCDA method was tested using thousands of computer simulations and showed highly accurate results, with over 90% of discharge estimates within ±5% of the true value. The study also examined how sensitive the method is to uncertainties in input data. It found that small errors in estimating riverbed roughness can lead to significant errors in discharge calculations.
Finally, the method was applied to a real 7-kilometer section of the Biobío River in Chile. While IPCDA worked well in many cases, it showed some weaknesses in certain parts of the river, especially under changing flow conditions. Future improvements aim to apply this method to more complex river systems and include real-world data from satellites like SWOT and drone-based observations.
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