Predicting Flash Flood Economic Damage at the Community Scale: Empirical Zero-Inflated Model with Semicontinuous Data
Abstract
Rainfall-induced flash floods are characterized by their rapid onset and small spatial scale. With little lead time for warning, floodwater can accumulate rapidly and its force can damage roads, swamp houses, destroy bridges, and scour out channels. Having data-driven estimates of potential economic losses from flash floods (before they occur) helps authorities make informed decisions about planning and prioritizing mitigation projects. This article provides a probabilistic predictive model to estimate flash flood economic damage at the census tract scale. To simplify model utilization and avoid strong assumptions about property value and replacement costs, the model predicts the total cost of property and infrastructure damages for individual census tracts (expressed in 2019 prices). The model was developed based on a flash flood data set for a 15-year period (2005–2019) in Texas. The data set was assembled by integrating disparate data from multiple platforms. The occurrence of economic damage was found to be a zero-inflated problem. Therefore, we developed a two-part mixed-effect model. The model first estimates the probability that economic damage will occur (zero-inflated part) and then predicts the dollar amount of the economic damage (continuous part). Utilization of the developed model was demonstrated in an application to Harris County, Texas.
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Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author, Shi Chang. The data will be publicly available at a future date with the completion and assessment of the NSF Project.
Acknowledgments
This material is based on work supported by the National Science Foundation under Grant No. 1931301. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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Published In
Natural Hazards Review
Volume 24 • Issue 4 • November 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Aug 4, 2022
Accepted: Mar 24, 2023
Published online: Jun 27, 2023
Published in print: Nov 1, 2023
Discussion open until: Nov 27, 2023
ASCE Technical Topics:
- Analysis (by type)
- Benefit cost ratios
- Business management
- Economic factors
- Engineering fundamentals
- Financial management
- Flash floods
- Floods
- Hydrologic data
- Hydrologic engineering
- Hydrology
- Mathematics
- Models (by type)
- Practice and Profession
- Probability
- Scale models
- Spatial analysis
- Spatial data
- Water and water resources
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