Incorporating Below Ground City Textures into Urban Flood Modeling for Enhanced Flood Prediction and Risk Assessment: A Case Study of the MIT CAMPUS

Conference Proceedings Paper
Incorporating Below Ground City Textures into Urban Flood Modeling for Enhanced Flood Prediction and Risk Assessment: A Case Study of the MIT CAMPUS
Strzepek, K.M. and K. Boukin (2023)
American Geophysical Union (AGU) Fall Meeting, NH21A-04

Abstract/Summary:

Abstract

Pluvial (rain-driven) flooding poses a significant threat to urban areas worldwide, necessitating accurate flood prediction for effective flood risk adaptation and damage mitigation. This research explores the impact of incorporating below ground city textures, such as basements, garages, and tunnels, into urban flood models on the extent and propagation of surface and subsurface flooding and damages. A high-resolution 1&2D Rain On Mesh (ROM) hydrodynamic flood model for the city of Cambridge was developed. The model integrated various layers of geospatial data and the city's DEM. An extended version of the model, the Basement Model, applies an approach to incorporate below ground city textures within a surface flooding model and was developed for the MIT campus neighborhood, approximately 10% of the case study area. The Campus has a unique feature that 33 of the buildings of the main campus are connected via their basements. A recent crowd-sources activity revealed that there are over 1000 potential points where water can enter the buildings.

Our simulation results showed significant basement flooding that altered the spatial-temporal pattern of surface flooding in the study area as compared to the surface model. The basement model identified significant water inflow to the basement reducing the volume of surface flood waters and reducing much of the surface flooding observed in the surface model. Moreover, this model detected flooding within buildings that lacked directed surface flooding due to flow between the basements.

These models were compared in a flood risk study. Using the basement model the expected damages from the 100-year flood were 33% of the expected damages using state of the art USACE surface flood damage methods. Additionally, there was significant differenced in which buildings were at risk, the total amount of flooding volume, the spatial-temporal propagation, and the damage assessments within structures.

The incorporation of basements and below ground city textures into flood modeling proves to be invaluable in accurately predicting flood extent and propagation. These findings contributed to MIT’s Climate Resilience Pathway to develop of a resilient flood management plan incorporating climate change into campus design processes.

Plain-language Summary

Incorporating the flood storage capacities of basement in urban flood modeling can have a significant impact on the potential flood damage in at building and neighborhood scale. A case study of the MIT Campus shows expected damages can be over 70% less if basements are modeled.

Citation:

Strzepek, K.M. and K. Boukin (2023): Incorporating Below Ground City Textures into Urban Flood Modeling for Enhanced Flood Prediction and Risk Assessment: A Case Study of the MIT CAMPUS. American Geophysical Union (AGU) Fall Meeting, NH21A-04 (https://agu.confex.com/agu/fm23/meetingapp.cgi/Paper/1430644)
  • Conference Proceedings Paper
Incorporating Below Ground City Textures into Urban Flood Modeling for Enhanced Flood Prediction and Risk Assessment: A Case Study of the MIT CAMPUS

Strzepek, K.M. and K. Boukin

Abstract/Summary: 

Abstract

Pluvial (rain-driven) flooding poses a significant threat to urban areas worldwide, necessitating accurate flood prediction for effective flood risk adaptation and damage mitigation. This research explores the impact of incorporating below ground city textures, such as basements, garages, and tunnels, into urban flood models on the extent and propagation of surface and subsurface flooding and damages. A high-resolution 1&2D Rain On Mesh (ROM) hydrodynamic flood model for the city of Cambridge was developed. The model integrated various layers of geospatial data and the city's DEM. An extended version of the model, the Basement Model, applies an approach to incorporate below ground city textures within a surface flooding model and was developed for the MIT campus neighborhood, approximately 10% of the case study area. The Campus has a unique feature that 33 of the buildings of the main campus are connected via their basements. A recent crowd-sources activity revealed that there are over 1000 potential points where water can enter the buildings.

Our simulation results showed significant basement flooding that altered the spatial-temporal pattern of surface flooding in the study area as compared to the surface model. The basement model identified significant water inflow to the basement reducing the volume of surface flood waters and reducing much of the surface flooding observed in the surface model. Moreover, this model detected flooding within buildings that lacked directed surface flooding due to flow between the basements.

These models were compared in a flood risk study. Using the basement model the expected damages from the 100-year flood were 33% of the expected damages using state of the art USACE surface flood damage methods. Additionally, there was significant differenced in which buildings were at risk, the total amount of flooding volume, the spatial-temporal propagation, and the damage assessments within structures.

The incorporation of basements and below ground city textures into flood modeling proves to be invaluable in accurately predicting flood extent and propagation. These findings contributed to MIT’s Climate Resilience Pathway to develop of a resilient flood management plan incorporating climate change into campus design processes.

Plain-language Summary

Incorporating the flood storage capacities of basement in urban flood modeling can have a significant impact on the potential flood damage in at building and neighborhood scale. A case study of the MIT Campus shows expected damages can be over 70% less if basements are modeled.

Posted to public: 

Friday, October 6, 2023 - 16:40