Zach Perzan – Hydrology

Research Interests:

Dr. Zach Perzan’s research seeks to understand the fundamental processes that control the movement of nutrients and contaminants within Earth’s critical zone. To address these questions, he pairs numerical models with novel data streams — geophysical surveys and custom-built in situ sensors, for example — and analyze the results using a suite of geostatistical and machine learning techniques.

While this research has applications across the earth sciences, Dr. Perzan primarily examines these processes in two systems:

1. Nutrient export from mountainous floodplains and
2. Subsurface contaminant transport during managed aquifer recharge.

Read more about his research group here.

Dr. Perzan is looking for students to join our group starting in Fall 2026. If you are interested, please find more information here.

Selected Publications:

(Full publications list)

T. Dai, K. Maher and Z. Perzan (2025). Machine learning surrogates for efficient hydrologic modeling: Insights from stochastic simulations of managed aquifer recharge, Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2024.132606

Z. Perzan, G. Osterman and K. Maher. (2023) Controls on flood managed aquifer recharge through a heterogeneous vadose zone: hydrologic modeling at a site characterized with surface geophysics. Hydrology and Earth System Sciences.

Z. Perzan and T. Chapin. (2023) WellSTIC: A cost-effective sensor for performing point dilution tests to measure groundwater velocity in shallow aquifers. Water Resources Research.

Q. Li, L. Wang, Z. Perzan, J. Caers, et al. (2021) Global sensitivity analysis of a reactive transport model for mineral scale formation during hydraulic fracturing.Environmental Engineering Science.

Z. Perzan, T. Babey, J. Caers, J.R. Bargar and K. Maher. (2021) Local and global sensitivity analysis of a reactive transport model simulating floodplain redox cycling. Water Resources Research.