Hydrologic process representation
I study how infiltration, baseflow, preferential flow, and soil water retention shape model skill, especially in dry regions.
I am Mohammad Ali Farmani, a Ph.D. student in Hydrology and Atmospheric Sciences at the University of Arizona with a minor in Data Science. My work focuses on improving how we represent groundwater recharge, soil moisture persistence, and streamflow generation in large-scale hydrologic models.
I care deeply about making hydrologic science useful beyond academic spaces. That means not only building better models, but also building better computational workflows, clearer analyses, and more decision-relevant interpretations for communities, agriculture, and climate resilience.
I study how infiltration, baseflow, preferential flow, and soil water retention shape model skill, especially in dry regions.
I explore how precipitation intensity, drought, and land-atmosphere interactions affect water availability and risk.
I build scalable workflows in Python and HPC environments to process large geospatial and hydrologic datasets.
I turn parts of my work into reusable software so other researchers can reproduce and extend hydrologic analyses.
I’m especially interested in collaborations at the intersection of hydrology, climate science, environmental data analysis, and open-source scientific software.
Contact: farmani@arizona.edu | LinkedIn | Google Scholar