The Application of Artificial Intelligence in Flood Risk Assessment and Mitigation in the State of Texas

Project summary:

The purpose of this project is to determine the applicability, along with the capabilities and limitations, of artificial intelligence (AI) and machine learning (ML) technologies to enhance flood risk assessment and mitigation. The guidelines, recommendations, and workflows developed in this project will result in a roadmap for TWDB to leverage advanced AI models to optimize current modeling efforts and processes, such as Base Level Engineering (BLE), Coastal Modeling, and Flood Risk Mitigation.

Project deliverable(s):

A technical memorandum presenting key insights from a comprehensive literature review on the capabilities and limitations of various AI techniques for flood risk assessment and mitigation.
A technical memorandum identifying flood-related datasets which can be leveraged to develop and implement AI applications in flood risk assessment and mitigation.
A strategic roadmap for applying AI in flood assessment and mitigation across Texas.
Guidelines for implementing machine learning workflows in Snowflake using various flood-related datasets.
A technical memorandum identifying potential concerns related to data governance and risk reduction for AI applications in flood risk assessment and mitigation.

Contractor (and Principal Investigator, if appropriate):

Texas A&M University Engineering Experiment Station, Dr. Ali Mostafavi

Contract amount:

$125,000

Project lead:

Amin Kiaghadi, Ph.D., P.E.

Project timeline:

March 2025 - June 2026