UROP Project

Exploring the Adaptability of Machine Learning Models for Predicting Flood Depths Across Different Areas

Flood prediction, machine learning models, adaptability, flood risk management
Weston Brown Beige.jpg
Research Mentor: Maryam Pakdehi,
Department, College, Affiliation: Civil Engineering, FAMU-FSU College of Engineering
Contact Email: mp22bo@fsu.edu
Research Assistant Supervisor (if different from mentor): Dr. Ebrahim Ahmadisharaf
Research Assistant Supervisor Email: eahmadisharaf@eng.famu.fsu.edu
Faculty Collaborators:
Faculty Collaborators Email:
Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Environmental engineering, Civil engineering, Computer engineering
Project Location: On FSU Main Campus
Research Assistant Transportation Required:
Remote or In-person: In-person
Approximate Weekly Hours: 4-5, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link: Not participating in the Roundtable

Project Description

This proposal outlines a collaborative project between an undergraduate student and myself, focusing on examining how machine learning models can predict flood depths in diverse locations. Our initial models showed promise in a coastal area during Hurricane Ida and worked well in other events. However, we want to expand their potential. The project involves collecting and preparing data from various regions, using tools like Excel and ArcGIS. This process will help students become familiar with flood data and prediction. This effort will assess how well the models can predict flood depths in these different contexts, advancing the development of effective flood prediction tools.

Research Tasks: • Gather and organize flood-related existing data from publicly accessible websites.
• Preprocess the data using Excel, ArcGIS, and other existing software.
• Participate in the classification of different regions based on model performance.


Skills that research assistant(s) may need: • Proficiency in data handling using tools like Excel and ArcGIS.
• Analytical skills for interpreting model results.
• Ability to work both independently and collaboratively in a research setting.

Mentoring Philosophy

My mentoring philosophy is rooted in cultivating a dynamic and supportive relationship with students. I believe in guiding students beyond mere task completion, nurturing their growth as researchers and individuals. I emphasize the practical applications of research theories, establish well-defined project tasks, maintain transparent communication, and proactively address challenges. My aim is to empower students to innovate and think creatively, while providing steady guidance to ensure their success. Through this approach, the additional mentor (Dr. Ebrahim Ahmadisharaf) has successfully guided a UROP student to secure a prestigious research internship, illustrating the effectiveness of a holistic mentoring strategy.

Additional Information

Implications of this Work: This research has the potential to reshape flood prediction methods by showing how machine learning models can adapt across different areas. The insights gained can inform the creation of flexible flood prediction tools that transcend geographical boundaries. This work enhances our grasp of flood dynamics and contributes to effective flood risk management, ultimately protecting communities and minimizing the impact of devastating floods.


Link to Publications


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