Agricultural flood risk under seasonally varying rainfall extremes and crop vulnerability

Abstract. Agricultural systems are highly vulnerable to flooding, particularly when extreme precipitation events occur during sensitive crop growth stages. However, most flood-risk assessments rely on static annual hazard scenarios and simplified design storms, neglecting the combined effects of hydrological seasonality, rainfall temporal structure, and crop phenology. In this study, we propose a probabilistic-hydrological-hydraulic framework for agricultural flood-risk assessment under seasonally varying short-duration extreme precipitation. The approach integrates non-asymptotic multivariate frequency analysis, copula-based dependence modelling among rainfall durations, stochastic microcanonical rainfall disaggregation, hydraulic simulations, and crop-specific flood depth-duration vulnerability functions. Flood-hazard maps are generated at the monthly scale and coupled with seasonally varying crop exposure and vulnerability conditions. The framework is applied to a flood-prone agricultural area in northern Italy. Results show that rainfall temporal structure and event duration substantially influence expected annual losses, with long-duration events generally producing the highest damages due to prolonged inundation and waterlogging conditions. The copula-based multi-duration analysis reveals a considerable uncertainty associated with inter-duration dependence, highlighting that the use of a single representative storm duration may significantly bias agricultural flood-risk estimates. The adopted microcanonical rainfall generator also proved effective in reproducing realistic multi-burst rainfall structures and temporally clustered events, which are particularly relevant for representing cumulative soil saturation and flood persistence processes. Overall, the proposed methodology provides a physically consistent and transferable framework for probabilistic agricultural flood-risk assessment and may support climate-risk analyses, adaptation planning, and flood-risk management in agricultural systems exposed to increasingly complex hydrometeorological extremes.