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March 29, 20260 citationsOpen Access

Understanding and improving the functioning of stormwater nature-based solutions under climate extremes – Towards a unified modeling framework for the GreenStorm project

EBEmmanuel BerthierAOAhmeda Assann OuédraogoJSJérémie Sage

Key Points

  • The aim is to develop a unified modeling framework to enhance the design and performance assessment of nature-based stormwater solutions under climate extremes.
  • Developed a generic hydrological operating diagram illustrating key physical processes.
  • Selected Hydrus software for modeling despite pre-identified limitations.
  • Implemented a method combining simulations with varying parameters for predictive modeling.
  • Conducted sensitivity studies to identify influential parameters.
  • Analyzed the distribution of parameters against accepted norms.
  • Proposed a framework for better deployment of nature-based stormwater solutions.
  • Identified specific areas to consolidate the modeling approach for improved accuracy.
  • Demonstrated how simulations can predict performance under various climate extremes.

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.

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Cite This Study

Berthier et al. (2026) studied this question.

synapsesocial.com/papers/69c8c371de0f0f753b39e3fdhttps://doi.org/10.71573/1eas3g80
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