ALBERT

Description: Levee failures due to floods often cause considerable economic damage and life losses in inundated dike-protected areas, and significantly change flood hazard upstream and downstream the breach location during the event. We present a new extension for the LISFLOOD-FP hydrodynamic model which allows levee breaching along embankments in fully two-dimensional (2D) mode. Our extension allows for breach simulations in 2D structured grid hydrodynamic models at different scales and for different hydraulic loads in a computationally efficient manner. A series of tests performed on synthetic and historic events of different scale and magnitude show that the breaching module is numerically stable and reliable. We simulated breaches on synthetic terrain using unsteady flow as an upstream boundary condition and compared the outcomes with an identical setup of a full-momentum 2D solver. The synthetic tests showed that differences in the maximum flow through the breach between the two models were less than 1%, while for a small-scale flood event on the Secchia River (Italy), it was underestimated by 7% compared to a reference study. A large scale extreme event simulation on the Po River (Italy) resulted in 83% accuracy (critical success index).

Description: The increase in frequency and intensity of extreme precipitation events caused by the changing climate (e.g., cloudbursts, rainstorms, heavy rainfall, hail, heavy snow), combined with the high population density and concentration of assets, makes urban areas particularly vulnerable to pluvial flooding. Hence, assessing their vulnerability under current and future climate scenarios is of paramount importance. Detailed hydrologic-hydraulic numerical modeling is resource intensive and therefore scarcely suitable for performing consistent hazard assessments across large urban settlements. Given the steadily increasing availability of LiDAR (Light Detection And Ranging) high-resolution DEMs (Digital Elevation Models), several studies highlighted the potential of fast-processing DEM-based methods, such as the Hierarchical Filling-&-Spilling or Puddle-to-Puddle Dynamic Filling-&-Spilling Algorithms (abbreviated herein as HFSAs). We develop a fast-processing HFSA, named Safer_RAIN, that enables mapping of pluvial flooding in large urban areas by accounting for spatially distributed rainfall input and infiltration processes through a pixel-based Green-Ampt model. We present the first applications of the algorithm to two case studies in Northern Italy. Safer_RAIN output is compared against ground evidence and detailed output from a two-dimensional (2D) hydrologic and hydraulic numerical model (overall index of agreement between Safer_RAIN and 2D benchmark model: sensitivity and specificity up to 71% and 99%, respectively), highlighting potential and limitations of the proposed algorithm for identifying pluvial flood-hazard hotspots across large urban environments.