Assessing and Addressing stakeholder needs when implementing machine learning in natural resources management.
Used machine learning models for streamflow prediction applications.
Integrating hydrology model outputs and demographics data to aid risk assessment and climate change adaptation efforts in North Carolina.
Lab study measuring the impact of alternating anaerobic/aerobic conditions on stream biofilms.
Created an ecohydrology stable isotope model to test the two-water-world hypothesis.
Tested two spatial statistics approaches to predict in-stream water quality.
Developing a web-based application to evaluate agricultural best management practices.