The paper presents a probabilistic framework for mapping hazard induced by river floods in levee-protected floodplains. Large-scale hazard maps of water depth (or any other hazard variable) are derived from their cumulative probability distributions, estimated throughout the domain from a set of flood simulations that combine different inflow hydrographs and multiple levee-failure scenarios. For each simulation, levee breach probabilities are estimated using fragility functions conditioned on the local hydraulic loading. By accounting for the joint probability of hydrological and breaching events, the method enables a probabilistic characterization of hazard metrics and produces hazard maps associated with any exceedance probability, not constrained by the discrete return periods of the hydrological inputs. Flood simulations require integrated two-dimensional hydrodynamic models to include flood routing, breach formation, and ensuing floodplain inundation. To limit the computational load, a scalable parent–child strategy is proposed to reduce the number of simulations while retaining acceptable accuracy in the estimated probability field. Moreover, the available simulations can be reused to recompute hazard maps at negligible cost to consider varied probability of hydrological and/or breaching events (due to climate change, levee reinforcements, etc.). The framework is applied to a pilot case study in the Adige River (Northern Italy), considering fragility functions for overflow-induced failures and a flood-prone area of ∼ 100 km2. The results suggest that, if supplied with realistic estimations of levee fragility, P-FLOOD can provide improved hazard predictions than traditional approaches, especially for frequent flood events, thereby supporting more informed flood risk management and planning.
Understanding the influence of hydrologic processes on nutrient transport remains a critical challenge in agricultural watersheds, where nitrate (N) and phosphorus (P) often exhibit contrasting export patterns. In this study, we developed a coupled surface–subsurface modeling framework using SWAT + integrated with the gwflow module to simulate hydrologic fluxes and nutrient transport in the Choptank River watershed, USA. An unstructured (quadtree) groundwater grid was implemented in the SWAT + gwflow module to improve representation of groundwater gradients near tile drains and channels. The model was calibrated and tested using the iterative ensemble smoother (iES) and evaluated against streamflow, groundwater head, and annual nutrient loading observations. The Morris global sensitivity analysis method was applied to identify and rank the dominant hydrologic controls on streamflow, groundwater dynamics, and nutrient transport.The coupled SWAT + gwflow framework identified distinct hydrologic controls governing streamflow, groundwater dynamics, and nutrient transport. Streamflow is primarily controlled by surface runoff generation, soil water retention, and channel conveyance, whereas groundwater dynamics are governed by aquifer properties and drainage mechanisms. The sensitivity analysis indicates that simulated nitrate transport is primarily influenced by soil nutrient processes and subsurface flow pathways (e.g., percolation and groundwater connectivity), whereas simulated phosphorus transport appears to be more strongly associated with fertilizer inputs and surface/aquatic processes, reflecting event-based mobilization through runoff and sediment transport. Basin-scale flux analysis further indicates that surface processes control short-term variability, whereas subsurface processes regulate longer-term (“legacy”) transport.These findings demonstrate the capability of the coupled surface–subsurface framework to diagnose hydrologic pathway partitioning governing nutrient transport within the critical zone. They also highlight limitations of single-objective calibration, as parameters controlling subsurface processes (relevant to nitrate) differ from those governing surface processes (relevant to phosphorus). This study provides a mechanistic framework linking hydrologic controls to nutrient-specific transport pathways and offers guidance for improved model calibration and targeted nutrient management in agricultural systems.
