Preprints
https://doi.org/10.5194/egusphere-2025-2831
https://doi.org/10.5194/egusphere-2025-2831
29 Sep 2025
 | 29 Sep 2025
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

Development and evaluation of a Sustainable Drainage System module into TEB (v 9.0) model

José Manuel Tunqui Neira, Katia Chancibault, Marie-Christine Gromaire, and Ghassan Chebbo

Abstract. Addressing urban stormwater management challenges, this study integrates a novel Sustainable Drainage System (SUDS) module into the Town Energy Balance (TEB) model to enhance urban hydro energetic simulations. The SUDS module is developed using the Equivalent Sustainable Drainage System (E–SUDS) approach, which aggregates various SUDS based on their hydrological processes and compatibility with TEB, providing a simplified representation for large-scale urban models. This study successfully develops this module, focusing on the hydrological conceptualization tailored to specific SUDS processes. A rigorous evaluation was conducted, including a comparison with the bioretention module of the SWMM model, to validate the accuracy of hydrological process dynamics and water balance simulated by the TEB SUDS module. The initial results demonstrated that the TEB SUDS module effectively simulates most of the targeted hydrological processes and the key parameters involved in water balance calculations. This module offers a comprehensive tool for analysing the cumulative and spatial effects of different SUDS at an urban scale.

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José Manuel Tunqui Neira, Katia Chancibault, Marie-Christine Gromaire, and Ghassan Chebbo

Status: open (until 24 Nov 2025)

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José Manuel Tunqui Neira, Katia Chancibault, Marie-Christine Gromaire, and Ghassan Chebbo
José Manuel Tunqui Neira, Katia Chancibault, Marie-Christine Gromaire, and Ghassan Chebbo
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Short summary
We developed and evaluated a computer model that supports sustainable urban stormwater management. It simulates how green areas and drainage systems capture, store, and release rainwater, and performs well when compared with an established model. The results show it can reliably reproduce key water processes, providing a practical tool to help improve urban rainwater management.
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