o:1116 Control theory-based data assimilation for open channel hydraulic models: tuning PID controllers using multi-objective optimization en ABSTRACT: Reliable water resources management requires decision support tools to successfully forecast hydraulic data (stage and flow hydrographs). Even though data-driven methods are nowadays trendy to apply, they still fail to provide reliable forecasts during extreme periods due to a lack of training data. Therefore, model-driven forecasting is still needed. However, the model-driven forecasting approach is affected by numerous uncertainties in initial and boundary conditions. To improve the real-time model’s operation, it can be regularly updated using measured data in the data assimilation (DA) procedure. Widely used DA techniques are computationally expensive, which reduce their real-time applications. Previous research shows that tailor-made, time-efficient DA methods based on the control theory could be used instead. This paper presents further insights into the control theory-based DA for 1D hydraulic models. This method uses Proportional– Integrative–Derivative (PID) controllers to assimilate computed water levels and observed data. This paper describes the two-stage PID controllers’ tuning procedure. Multi-objective optimization by Nondominated Sorting Genetic Algorithm II (NSGA-II) was used to determine optimal parameters for PID controllers. The proposed tuning procedure is tested on a hydraulic model used as a decision support tool for the transboundary Iron Gate 1 hydropower system on the Danube River, showing that the average discrepancy between modeled and observed water levels can be less than 0.05 m for more than 97% of assimilation window. data assimilation, NSGA-II, PID controllers, tuning controllers 1552102 https://grafar.grf.bg.ac.rs/bitstream/handle/123456789/2693/bitstream_10407.pdf?sequence=1&isAllowed=y 1552099 10.2166/hydro.2022.034 1552101 1464-7141 2022-12-27T09:41:34.609Z 44 no 46 Miloš Milašinović Građevinski fakultet Univerziteta u Beogradu Dušan Prodanović Građevinski fakultet Univerziteta u Beogradu person Miloš Stanić Građevinski fakultet Univerziteta u Beogradu person Budo Zindović Građevinski fakultet Univerziteta u Beogradu person Boban Stojanović Department of Mathematics and Informatics, Faculty of Science, University of Kragujevac person Nikola Milivojević Institut za vodoprivredu "Jaroslav Černi" person 0000-0001-5330-1219 application/pdf 1387760 https://unilib.phaidrabg.rs/o:1116 no yes 18 70 92000001 71A04 Journal of Hydroinformatics 24 4 898 916 IWA Publishing 2022 First received 18 March 2022; Accepted in revised form 20 May 2022. Available online 3 June 2022