Understanding and improving the functioning of stormwater nature-based solutions under climate extremes – Towards a unified modeling framework for the GreenStorm project
Year: 2026
Type: article
Abstract: The European GreenStorm project aims to better deploy nature-based solutions for the adaptation to different climate extremes. The project focuses on stormwater management solutions (NBSSW ), across a diversity of types and climates. A key step in the project is to develop and use a unified modeling framework at the facility scale to improve both their design and performance assessment. Based on a set of previously monitored of NBSSW constituted by the GreenStorm project consortium, a generic hydrological operating diagram is first proposed, illustrating the main physical processes to consider. Drawing from this diagram, the Hydrus software has been selected but some limitations have at the same time been pre-identified, pointing to areas for consolidating the modeling approach. A single method for evaluating and using the modeling framework is also proposed, in a view to its use in predictive mode: for a given NBSSW, it combines a large number of simulations run with prior parameters intervals, the characterization of the observations corresponding to the climatic extremes of interest, a sensitivity study to identify influential and non-influential parameters, an identification of acceptable simulation and set of parameters, and an analyze how close/different is the accepted parameter distribution compared to prior one.
Source: OJS-Service ULBT
DOI: 10.71573/1eas3g80
Institutions: Centre d'Études et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement, Agricultural University of Athens, Luleå University of Technology, University of Genoa, École nationale des ponts et chaussées, Université Paris-Est Créteil, Laboratoire Eau, Environnement et Systèmes Urbains, Institut Polytechnique de Paris
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7141568297
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