A. Efstratiadis, P. Dimas, G. Pouliasis, I. Tsoukalas, P. Kossieris, V. Bellos, G.-K. Sakki, C. Makropoulos, and S. Michas, Revisiting flood hazard assessment practices under a hybrid stochastic simulation framework, *Water*, 14 (3), 457, doi:10.3390/w14030457, 2022.

[doc_id=2170]

[English]

We propose a novel probabilistic approach to flood hazard assessment, aiming to address the major shortcomings of everyday deterministic engineering practices in a computationally efficient manner. In this context, the principal sources of uncertainty are defined across the overall modelling procedure, namely, the statistical uncertainty of inferring annual rainfall maxima through distribution models that are fitted to empirical data, and the inherently stochastic nature of the underlying hydrometeorological and hydrodynamic processes. Our work focuses on three key facets, i.e., the temporal profile of storm events, the dependence of flood generation mechanisms to antecedent soil moisture conditions, and the dependence of runoff propagation over the terrain and the stream network on the intensity of the flood event. These are addressed through the implementation of a series of cascade modules, based on publicly available and open-source software. Moreover, the hydrodynamic processes are simulated by a hybrid 1D/2D modelling approach, which offers a good compromise between computational efficiency and accuracy. The proposed framework enables the estimation of the uncertainty of all flood-related quantities, by means of empirically-derived quantiles for given return periods. Finally, a set of easily applicable flood hazard metrics are introduced for the quantification of flood hazard.

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https://www.mdpi.com/2073-4441/14/3/457

**Our works referenced by this work:**

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**Our works that reference this work:**

1. | G. Moraitis, I. Tsoukalas, P. Kossieris, D. Nikolopoulos, G. Karavokiros, D. Kalogeras, and C. Makropoulos, Assessing cyber-physical threats under water demand uncertainty, Environmental Sciences Proceedings, 21 (1), 18, doi:10.3390/environsciproc2022021018, October 2022. |

2. | S. Tsattalios, I. Tsoukalas, P. Dimas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Advancing surrogate-based optimization of time-expensive environmental problems through adaptive multi-model search, Environmental Modelling and Software, 162, 105639, doi:10.1016/j.envsoft.2023.105639, 2023. |

3. | P. Dimas, G.-K. Sakki, P. Kossieris, I. Tsoukalas, A. Efstratiadis, C. Makropoulos, N. Mamassis, and K. Pipili, Outlining a master plan framework for the design and assessment of flood mitigation infrastructures across large-scale watersheds, 12th World Congress on Water Resources and Environment (EWRA 2023) “Managing Water-Energy-Land-Food under Climatic, Environmental and Social Instability”, 75–76, European Water Resources Association, Thessaloniki, 2023. |

4. | E. Dimitriou, A. Efstratiadis, I. Zotou, A. Papadopoulos, T. Iliopoulou, G.-K. Sakki, K. Mazi, E. Rozos, A. Koukouvinos, A. D. Koussis, N. Mamassis, and D. Koutsoyiannis, Post-analysis of Daniel extreme flood event in Thessaly, Central Greece: Practical lessons and the value of state-of-the-art water monitoring networks, Water, 16 (7), 980, doi:10.3390/w16070980, 2024. |

**Other works that reference this work (this list might be obsolete):**

1. | Tegos, A., A. Ziogas, V. Bellos, and A. Tzimas, Forensic hydrology: a complete reconstruction of an extreme flood event in data-scarce area, Hydrology, 9(5), 93, doi:10.3390/hydrology9050093, 2022. |

2. | Afzal, M. A., S. Ali, A. Nazeer, M. I. Khan, M. M. Waqas, R. A. Aslam, M. J. M. Cheema, M. Nadeem, N. Saddique, M. Muzammil, and A. N. Shah, Flood inundation modeling by integrating HEC–RAS and satellite imagery: A case study of the Indus river basin, Water, 14(19), 2984, doi:10.3390/w14192984, 2022. |

3. | Vangelis, H., I. Zotou, I. M. Kourtis, V. Bellos, and V. A. Tsihrintzis, Relationship of rainfall and flood return periods through hydrologic and hydraulic modeling, Water, 14(22), 3618, doi:10.3390/w14223618, 2022. |

4. | Maranzoni, A., M. D’Oria, and C. Rizzo, Quantitative flood hazard assessment methods: A review, Journal of Flood Risk Management, 16(1), e12855, doi:10.1111/jfr3.12855, 2022. |

5. | Szeląg, B., P. Kowal, A. Kiczko, A. Białek, D. Majerek, P. Siwicki, F. Fatone, and G. Boczkaj, Integrated model for the fast assessment of flood volume: Modelling – management, uncertainty and sensitivity analysis, Journal of Hydrology, 625(A), 129967, doi:10.1016/j.jhydrol.2023.129967, 2023. |

6. | Rozos, E., V. Bellos, J. Kalogiros, and K. Mazi, efficient flood early warning system for data-scarce, karstic, mountainous environments: A case study, Hydrology, 10(10), 203, doi:10.3390/hydrology10100203, 2023. |

7. | Szeląg, B., D. Majerek, A. L. Eusebi, A. Kiczko, F. de Paola, A. McGarity, G. Wałek, and F. Fatone, Tool for fast assessment of stormwater flood volumes for urban catchment: A machine learning approach, Journal of Environmental Management, 355, 120214, doi:10.1016/j.jenvman.2024.120214, 2024. |

**Tagged under:**
Floods,
Hydraulic models,
Hydrological models,
Rainfall models,
Most recent works,
Uncertainty