Advancing Flood Impact Estimation: Comparing Multivariate Continuous Hydrologic-Hydraulic Models with Traditional Approaches

Flood frequency estimation is critical for water resource planning and management; however, traditional methods, typically univariate, often underestimate impacts due to several limitations, such as the use of short observational series (Taleb, 2022) and the lack of consideration for the interdependence among key hydrological variables (e.g., precipitation, discharge, and volume) (G. Salvadori et al., 2011; Serinaldi, 2015) Addressing these shortcomings, we present an innovative methodological framework that integrates continuous hydrologic-hydraulic modeling with multivariate analysis techniques (Brunner et al., 2017; Grimaldi et al., 2013, 2021), enabling a more comprehensive representation of flood impacts and extent. This approach encompasses three distinct hydrological modeling strategies:First, we employ rainfall-based modeling using both observed and synthetic rainfall series to develop rainfall-runoff hydrological models that generate discharge series. These discharge series are used to apply univariate methodologies, resulting in three flood scenarios: one scenario based on discharges derived from observed rainfall, a second scenario using synthetic rainfall, and, finally, an additional scenario derived from continuous hydrologic-hydraulic modeling. A key advantage of the latter approach is the elimination of the need for design hyetographs and hydrographs, which are significant sources of uncertainty in conventional methods (Grimaldi et al., 2012).Second, we focus on discharge-based modeling, utilizing both observed and synthetic discharge series. This process employs a multivariate methodological framework to generate synthetic discharge series derived from observed data. Univariate methodologies are applied to these series to produce two flood scenarios: one exclusively based on observed series and another on synthetic series. Additionally, continuous discharge series generated through the multivariate framework are incorporated into a continuous hydrologic-hydraulic modeling approach, yielding a third scenario that enables more robust and detailed analysis.Finally, joint behavior is evaluated through the analysis of joint return periods, accounting for the spatial dependence of precipitation (Urrea Méndez & Del Jesus, 2023) and the interaction between discharge and volume (Brunner et al., 2017; Fischer & Schumann, 2023). This framework explores distinct approaches that complementarily capture the physical processes underlying floods, thereby reducing uncertainty and improving estimations compared to conventional univariate methods. Validation of this framework will be conducted in the Los Corrales de Buelna region, Spain, demonstrating how the combination of multivariate tools and continuous hydrologic-hydraulic modeling enhances the accuracy of extreme event identification and management, offering more robust and effective solutions for engineering and territorial planning.Brunner, M. I., Viviroli, D., Sikorska, A. E., Vannier, O., Favre, A.-C., & Seibert, J. (2017). Flood type specific construction of synthetic design hydrographs. Water Resources Research, 53(2), 1390–1406. https://doi.org/10.1002/2016WR019535Salvadori, C. De Michele, & F. Durante. (2011). On the return period and design in a multivariate framework. Hydrology and Earth System Sciences, 15(11), 3293–3305. https://doi.org/10.5194/hess-15-3293-2011Grimaldi, S., Nardi, F., Piscopia, R., Petroselli, A., & Apollonio, C. (2021). Continuous hydrologic modelling for design simulation in small and ungauged basins: A step forward and some tests for its practical use. Journal of Hydrology, 595, 125664. https://doi.org/10.1016/j.jhydrol.2020.125664Grimaldi, S., Petroselli, A., Arcangeletti, E., & Nardi, F. (2013). Flood mapping in ungauged basins using fully continuous hydrologic–hydraulic modeling. Journal of Hydrology, 487, 39–47. https://doi.org/10.1016/j.jhydrol.2013.02.023