Dr. Lei Zou has recently co-authored a technical paper.
The images above showcases some of the results of the work: Probability of economic damage and Dollar amount of economic damage in extreme rainfall events.
Predicting Flash Flood Economic Damage at the Community Scale: Empirical Zero-Inflated Model with Semicontinuous Data
Authors: Shi Chang, Rohan Singh Wilkho, Nasir G Gharaibeh, Stacey Lyle, Lei Zou
This article presents a probabilistic predictive model for estimating flash flood economic damage at the census tract scale. The model utilizes a 15-year flash flood dataset from Texas and incorporates a two-part mixed-effect model to address the zero-inflated nature of economic damage occurrence. By predicting the probability of damage and the associated dollar amount, the model provides valuable information for decision-making and mitigation planning. The practical application of the model in Harris County, Texas demonstrates its effectiveness in estimating flash flood economic losses at the community level.
Chang Shi, Singh Wilkho Rohan, Gharaibeh Nasir, Lyle Stacey, & Zou Lei. (2023). Predicting Flash Flood Economic Damage at the Community Scale: Empirical Zero-Inflated Model with Semicontinuous Data. Natural Hazards Review, 24(4), 04023030.
Congratulations to Dr. Zou, and we look forward to hearing more achievements and publications from GEAR Lab! Gig'em!