Zac McEachran

Zac McEachran
Assistant Professor of Soil Physics and Ecohydrology
he/him/his
[email protected]

Areas of Interest

Hydrology, catchment science, machine learning, data science, forecasting, agricultural systems and envirotyping

Biography

Dr. Zac McEachran is a physical hydrologist with expertise in modeling, data science, and environmental physics. His research focuses on using advanced physics based and machine learning modeling tools to make better forecasts for complex environmental systems, and help understand the fundamental processes of water flow through landscapes. He has a BS in Physics from the University of St. Thomas, MS and PhD in Forest Hydrology from the University of Minnesota, and work experience ranging from environmental consulting to real-time flood forecasting and flood model development at the National Weather Service.

Research

Recent advances in computational modeling and machine learning are powerful tools for predicting river levels, floods, and droughts. However, it is unclear how data-driven modeling can generalize enough to get stable, reliable estimates into the future. I seek to develop knowledge-guided machine learning modeling to enhance both real time and long-term, climate-informed, forecasts that are reliable and interpretable, supporting better environmental modeling decisions.

Select Publications

McEachran, Z. P., Kietzmann, J., & Johnston, M. (2024). Parsimonious streamflow forecasting system based on a dynamical systems approach. Journal of Hydrology, 641, 131776.

Honors and Awards

NOAA Administrators Award for Outstanding Hydrology Support during Record Flooding in the Rainy River Basin (2022); Minnesota Federal Executive Board Innovation Award (2024)