Zac McEachran

Zac McEachran
Research Hydrologist, MCAP
he/him/his
[email protected]
Education

PhD

Areas of Interest

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

Biography

Dr. Zac McEachran is a hydrologist and catchment scientist. His research focuses on using advanced physics based and machine learning modeling tools to help understand the fundamental physical processes of how streamflow is generated at the catchment scale. He is particularly interested in creating feedbacks between developing better operational environmental forecasts and better understanding of catchment processes.

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)