Modeling Urban Flood Risks

We create statistical, machine learning, and physics-based models to forecast and nowcast floods and assess their socioeconomic impacts. For instance, our rapid flood estimation model, GISSR, delivers real-time forecasts and nowcasts of flood events within seconds, facilitating prompt responses and effective risk management. Additionally, we employ statistical models to analyze the frequency and magnitude of hurricanes, providing valuable insights for preparedness and mitigation.

Flood risk assessment for subway systems in NYC with GISSR methodology
Y. Miura*, C.Y. Blackshow, M. Zhang, K.T. Mandli, G. Deodatis. (2024). Under Review.

High-speed GIS-based simulation of storm surge induced flooding accounting for sea level rise
Y. Miura*, K.T. Mandli, G. Deodatis. Natural Hazards Review (2021) 22(3): 04021018. [DOI]

The paper introduces the GIS-based subdivision-redistribution (GISSR) methodology for efficiently simulating storm surge floods in coastal urban areas. It combines GIS with Manning’s equation to calculate and redistribute water flow, accounting for protective measures and sea level rise. GISSR is highly accurate and computationally efficient compared to tools. It also can be used for nowcast using storm surge data.

GISSR – High-Speed GIS-based Subdivision Redistribution Methodology Tool
Yuki Miura. (2020). [GitHub]

GIS-based high-speed flood estimate tool. GIS-based Subdivision Redistribution methodology tool (GISSR). The technical paper (Miura et al., 2021) is available from Natural Hazards Review.

Tropical cyclone-storm surge
T. Kijewski-Correa, G. Deodatis, Y. Miura (G.G. Deierlein & A. Zsarnoczay, eds.). State-of-Art in Computational Simulation for Natural Hazards Engineering (2019) 24-30. [DOI]

This report is a product of the NSF NHERI SimCenter and provides an overview and review of simulation requirements and software tools for natural hazards engineering of the built environment. The chapter covers models for tropial cyclone-storm surges.