A Copula-Based Framework for Quantifying Compound Pluvial and Fluvial Flood Risks

Floods constitute one of the most catastrophic natural hazards globally, precipitating extensive socio-economic disruption, infrastructure failure, and loss of life. Despite their severity, traditional flood hazard assessments frequently rely on univariate paradigms that assume independence between pluvial and fluvial drivers. Such approaches often overlook the critical reality of compound events, where synchronized or successive drivers amplify the total magnitude of the hazard. This study addresses this gap by proposing a rigorous copula-based framework for assessing Compound Pluvial–Fluvial Flood (CPFF) risk. The methodology employs a block maxima approach to capture extreme events, which are subsequently paired through a lag-time analysis to identify temporal synchronization between extreme precipitation and peak streamflow. A significant refinement in this framework is the integration of a bankfull discharge threshold; this serves as a physical constraint to filter the block maxima data, ensuring that only hydraulically significant fluvial events are analyzed. The joint probabilistic behavior of these flood pairs is quantified using bivariate copula functions, facilitating the estimation of joint return periods for both conjunction and disjunction scenarios. This study validated the framework in the Tapi River basin, India, where intense monsoon seasonality prevails. The findings show that flood risk varies significantly across the basin; rather, it is a function of monsoon-driven precipitation patterns, antecedent soil moisture conditions, and basin-scale hydrodynamic responses. A key finding reveals a spatial gradient in synchronization: upstream catchments exhibit lower correlation between pluvial and fluvial extremes, whereas the downstream reaches demonstrate high synchronization and significantly elevated CPFF risk. By quantifying these interactions, this study highlights that conventional univariate models substantially underestimate the hazard potential in downstream areas, providing a more robust evidence base for regional flood mitigation and infrastructure design.

 

Keywords: Compound floods, Copula, Statistical analysis, Joint return period, Flood risk assessment.