## 1 Introduction  
In recent decades, the urgency of the climate change-induced increase in the frequency and severity of extreme weather events, particularly floods, has become increasingly evident. The IPCC Sixth Assessment Report (AR6) confirms with high confidence that anthropogenic climate change has already intensified heavy precipitation events in many regions, thereby elevating the risk of both pluvial and fluvial flooding [IPCC, 2021][1]. This is further corroborated by recent studies such as that by Lakshmi, V. [2] which analyzed the Eastern Shore in Virginia using CMIP6-based projections and found a significant increase in flood frequency and severity; an up to 8.9% higher peak flood intensity compared to the 2003-2020 baseline. Their findings also underscore the growing vulnerability of low-lying coastal areas to sea-level rise and hydroclimatic extremes, reinforcing the need for adaptive planning and risk mitigation strategies. These events pose significant threats to community safety and environmental sustainability, causing substantial damage to infrastructure, ecosystems, and human lives [3]. This urgency underscores the need to develop practical predictive tools for risk management. Numerous studies, including those from the IPCC, have demonstrated that the intensification of natural disasters, especially floods, is closely linked to human activities [1]. Uncontrolled urbanization, deforestation, soil sealing, and greenhouse gas emissions all contribute to alterations in the natural hydrological cycle, increasing the frequency and severity of extreme events. The Climate Change 2021 report investigates this relationship's scientific and physical basis, thoroughly addressing short-term climate forcings in the atmosphere [4]. This interaction between natural factors and anthropogenic pressures makes flood risk forecasting a complex but essential challenge for enhancing territorial resilience. In Italy, recent events, including the floods in Emilia-Romagna and an increase in intense weather phenomena in 2024, have underscored the region's vulnerability. Floods, one of the most common natural disasters, are driven by various factors: heavy rainfall, rising sea levels, inadequate drainage systems, and increasing urban development. The consequences can be devastating, impacting human lives, infrastructure, the economy, and the environment. To address these issues, both the European Union and Italy have implemented regulatory measures such as Flood Risk Management Plans (FRMPs) [5] and the Hydrogeological Asset Plan (PAI). These tools aim to prevent and mitigate hydrogeological risks through integrated and up-to-date planning. Scientific research has produced numerous forecasting models for risk areas. Traditional hydrological models, such as deterministic models based on physical equations, have been extensively used to simulate how watersheds respond to meteorological events [6; 7]. However, these models require a detailed understanding of the territorial characteristics and often struggle to adapt to complex and dynamic scenarios. To address these limitations, numerical and probabilistic models have been increasingly adopted. Numerical models, like HEC-RAS, TUFLOW, and OpenFOAM, enable one-dimensional, two-dimensional, or three-dimensional simulations of water flow, offering a more realistic depiction of water propagation [8; 9; 10]. On the other hand, probabilistic models, such as Bayesian networks and the Analytic Hierarchy Process (AHP), facilitate the quantification of uncertainty while integrating multiple criteria into risk assessments [11; 12; 13]. Concurrently, artificial intelligence (AI) has introduced transformative methodologies in environmental modeling, particularly in the domain of flood risk assessment.