Jan de Leon
PhD Student
I'm a PhD student in the Water Intelligence Lab whose research bridges hydrology, artificial intelligence, and community resilience. My work ranges from machine-learning models for watershed prediction to understanding how people perceive and respond to flooding risks. By combining environmental data, computational methods, and stakeholder engagement, I aim to help communities make smarter decisions about water in a changing world.
Education
- PhD Geography and Spatial Sciences, University of Delaware, 2029
- MS Civil Engineering, University of Delaware, 2024
- BS Civil Engineering, Mapua Institute of Technology, 2016
Currently working on
- Hybrid Modeling for Fine-Scale Runoff Prediction
Combining physically-based hydrology with machine learning to improve edge-of-field and watershed-scale runoff and risk prediction.
- CHEMMA: Explainable Hydrochemical Endmember Modeling
Using explainable AI to identify the minimal set of solutes that preserves hydrochemical source dynamics across diverse watersheds.
- Flood Risk Perception and Community Engagement in Lewes, Delaware
Studying how coastal communities perceive flood hazards and integrating local knowledge into resilience and hazard-mitigation planning.
- Rain Garden Success Assessment in Washington, DC
Evaluating urban rain-garden performance through an integrated social–ecological–hydrological framework.
Publications (1)
- Assessing Hybrid Modeling for Fine-Scale Runoff Prediction
J. P. De Leon, Y. Hu, A. Meydani, D. N. Yates, L. M. Fry · AGU Fall Meeting Abstracts · 2024