A Runoff‐On‐Grid Approach to Embed Hydrological Processes in Shallow Water Models

Author:

Perrini Pasquale123ORCID,Cea Luis2ORCID,Chiaravalloti Francesco4ORCID,Gabriele Salvatore4,Manfreda Salvatore5ORCID,Fiorentino Mauro6,Gioia Andrea3,Iacobellis Vito3

Affiliation:

1. Department of Soil, Plant and Food Science University of Bari Aldo Moro Bari Italy

2. Water and Environmental Engineering Group Center for Technological Innovation in Construction and Civil Engineering (CITEEC) University of A Coruña A Coruña Spain

3. Department of Civil, Environmental, Land, Building Engineering and Chemistry Polytechnic University of Bari Bari Italy

4. Research Institute for Geo‐Hydrological Protection National Research Council Rende Italy

5. Department of Civil, Building and Environmental Engineering University of Naples Federico II Naples Italy

6. Department of European and Mediterranean Cultures: Architecture, Environment and Cultural Heritage University of Basilicata Matera Italy

Abstract

AbstractCatchment‐scale hydrological models encountered dichotomies with the numerical hydrodynamic models when describing surface routing process. We propose a new modeling framework, the so‐called “Runoff‐On‐Grid” approach, for embedding distributed process‐based hydrological modeling into shallow water models, as an alternative to the traditional Fully Hydrodynamic Approach (also known as Rain‐On‐Grid). Antecedent Soil Moisture, subsurface dynamics, and other topsoil hydrological processes are implicitly integrated in the governing hydrodynamic equations via the proposed methodology. The resulting hydrological‐hydrodynamic coupling, based on the DREAM distributed hydrological model and the Iber+ shallow water model, enhances the capabilities of both reference models. Through introducing non‐negligible runoff generation sources, the Runoff‐On‐Grid approach extends the surface hydrodynamic modeling to medium‐sized vegetated and/or (semi)humid catchments, bypassing the limitations of the widespread hydrological losses' empirical formulations. Employed in an event‐based analysis within a High‐Performance Computing framework, the DREAM‐Iber model provides an efficient and reliable reconstruction of the November 2020 flood that occurred in Crotone (Italy), envisaging consequences of similar future scenarios. We show that the proposed modeling technique, nested within emerging environmental technologies and robust on‐site data, details the flood hazard inducing processes merging physical hydrology with advanced hydrodynamics.

Publisher

American Geophysical Union (AGU)

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