Evaluating Regional Variability in Road Closure Outcomes Due to Rainfall: a Logistic Regression Approach
<p>This study investigated the probability of road closure due to flooding. Logistic regression model was developed using the road closure data and the daily rainfall data for Houston, TX, USA during 2017 and 2018. The road network was further divided into flood prone zones. The spatial analys...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2024-11-01
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| Series: | Proceedings of the International Association of Hydrological Sciences |
| Online Access: | https://piahs.copernicus.org/articles/386/345/2024/piahs-386-345-2024.pdf |
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| Summary: | <p>This study investigated the probability of road closure due to flooding. Logistic regression model was developed using the road closure data and the daily rainfall data for Houston, TX, USA during 2017 and 2018. The road network was further divided into flood prone zones. The spatial analysis revealed that the rainfall at the road segment level could be sufficiently represented by that recorded by nearest sensors. Within a 4 d window, the rainfall in the current day and 3 d prior played a more influential role in predicting road closure. The differential outcomes due to distinct regional features were explained. Finally, a watershed delineation approach substantially improved the model's predictive power and sensitivity.</p> |
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| ISSN: | 2199-8981 2199-899X |