Assessing the performance of LISFLOOD-FP and SWMM for a small watershed with scarce data availability

Abstract

Flooding events are becoming more frequent and the negative impacts that they are causing globally are very significant. Current predictions have confirmed that conditions linked with future climate scenarios are worsening; therefore, there is a strong need to improve flood risk modeling and to develop innovative approaches to tackle this issue. However, the numerical tools available nowadays (commercial and freeware) need essential data for calibration and validation purposes and, regrettably, this cannot always be provided in every country for dissimilar reasons. This work aims to examine the quality and capabilities of open-source numerical flood modeling tools and their data preparation process in situations where calibration datasets may be of poor quality or not available at all. For this purpose, EPA’s Storm Water Management Model (SWMM) was selected to investigate 1D modeling and LISFLOOD-FP was chosen for 2D modeling. The simulation results obtained with freeware products showed that both models are reasonably capable of detecting flood features such as critical points, flooding extent, and water depth. However, although working with them is more challenging than working with commercial products, the quality of the results relative to the reference map was acceptable. Therefore, this study demonstrated that LISFLOOD-FP and SWMM can cope with the lack of these variables as a starting point and has provided steps to undertake to generate reliable results for the need required, which is the estimation of the impacts of flooding events and the likelihood of their occurrence.

Publication DOI: https://doi.org/10.3390/w14050748
Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Civil Engineering
College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering
Additional Information: Copyright © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Uncontrolled Keywords: SDG 11 - Sustainable Cities and Communities,SDG 13 - Climate Action,SDG 9 - Industry, Innovation, and Infrastructure
Publication ISSN: 2073-4441
Last Modified: 21 Nov 2024 08:22
Date Deposited: 01 Oct 2024 07:37
Full Text Link:
Related URLs: https://www.mdp ... 3-4441/14/5/748 (Publisher URL)
PURE Output Type: Article
Published Date: 2022-03
Published Online Date: 2022-02-26
Accepted Date: 2022-02-23
Authors: Sadeghi, Farzaneh
Rubinato, Matteo (ORCID Profile 0000-0002-8446-4448)
Goerke, Marcel
Hart, James

Download

[img]

Version: Published Version

License: Creative Commons Attribution

| Preview

Export / Share Citation


Statistics

Additional statistics for this record