o:3382 Assessment of water resources system resilience under hazardous events using system dynamic approach and artificial neural networks en ABSTRACT The objective of this research is to propose a novel framework for assessing the consequences of hazardous events on a water resources system using dynamic resilience. Two types of hazardous events were considered: a severe flood event and an earthquake. Given that one or both hazards have occurred and considering the intensity of those events, the main characteristics of flood dynamic resilience were evaluated. The framework utilizes an artificial neural network (ANN) to estimate dynamic resilience. The ANN was trained using a large, generated dataset that included a wide range of situations, from relatively mild hazards to severe ones. A case study was performed on the Pirot water system (Serbia). Dynamic resilience was derived from the developed system dynamics model alongside the hazardous models implemented. The most extreme hazard combination results in the robustness of 0.04, indicating a combination of an earthquake with a significant magnitude and a flood hydrograph with a low frequency of occurrence. In the case of moderate hazards, the system robustness has a median value of 0.2 and a rapidity median value of 162 h. The ANN’s efficacy was quantified using the average relative error metric which equals 2.14% and 1.77% for robustness and rapidity, respectively flood dynamic resilience, flood risk assessment, machine learning, Pirot water resources system, system dynamics modeling approach 1552101 1464-7141 1552099 10.2166/hydro.2023.069 2023-11-28T09:46:58.224Z 44 no 46 Milan Stojković Institute for Artificial Intelligence R&D, Novi Sad Slaviša Trajković Faculty of Civil Engineering and Architecture, University of Niš person Nikola Milivojević Jaroslav Černi Water Institute, Belgrade person 0000-0001-5330-1219 Višnja Simić Faculty of Science, University of Kragujevac person Damjan Ivetić Faculty of Civil Engineering, University of Belgrade person Dragan Rakić Faculty of Engineering, University of Kragujevac person Dušan Marjanović Jaroslav Černi Water Institute, Belgrade person application/pdf 1002959 https://unilib.phaidrabg.rs/o:3382 no yes 16 70 92000001 71A04 Journal of Hydroinformatics 25 2 208 225 IWA Publishing, London, United Kingdom 2023 First received: 12 May 2022; Accepted in revised form 6 January 2023 Available online 21 January 2023