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Jorge Leandro

Researcher at Technische Universität München

Publications -  86
Citations -  2079

Jorge Leandro is an academic researcher from Technische Universität München. The author has contributed to research in topics: Flood myth & Turbulence. The author has an hindex of 23, co-authored 82 publications receiving 1623 citations. Previous affiliations of Jorge Leandro include Ruhr University Bochum & Life Sciences Institute.

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Comparison of 1D/1D and 1D/2D Coupled (Sewer/Surface) Hydraulic Models for Urban Flood Simulation

TL;DR: In this paper, a comparison of the simulation results of a 1D/1D model and a 2D/2D model is presented, showing that the definition of the surface pathways, the linking elements sewer/surface, and the inclusion of virtual manholes are key factors for setting up a more accurate 1d/1d model.
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Attribution of flood risk in urban areas

TL;DR: In this paper, two approaches to risk attribution are discussed: Standards-based attribution, which is a deterministic approach, and sensitivity based attribution which apportions risk between the variables that influence the total flood risk.
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A step towards considering the spatial heterogeneity of urban key features in urban hydrology flood modelling

TL;DR: In this paper, a specific conceptual rainfall-runoff model and a fully distributed approach for infiltration processes in urban areas with limited storage capacity dependent on OpenStreetMaps (OSM) are presented.
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A 2D parallel diffusive wave model for floodplain inundation with variable time step (P-DWave)

TL;DR: P-DWave performed well against known analytical solutions and dynamic and diffusive models in a total of seven tests, and kept the solution stable and preserved absolute mass conservation.
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A methodology for linking 2D overland flow models with the sewer network model SWMM 5.1 based on dynamic link libraries.

TL;DR: The novelty herein is that the new methodology can be added to SWMM without the need for editing SWMM's original code, and is directly applicable to other coupled overland flow models aiming to use SWMM 5 as the sewer network model.