Melissa A Lombard

In the broadest sense, my work is at the intersection of humans and the environment.  My research interests include connecting environmental geochemistry with human and ecosystem health, and using machine learning models to understand, estimate, and predict contaminant occurrence and water use.  


Since joining the USGS in 2017, much of my work has focused on building and using models as a tool for understanding and predicting water quality and water use.  I have worked on two projects related to arsenic occurrence in private wells across the conterminous US; developing machine learning models in collaboration with epidemiologists to predict arsenic occurrence for the purpose of comparing to human health data, and investigating how drought impacts arsenic and the human population exposed to elevated levels of arsenic.  Currently, I am building models to predict daily water withdrawals and water consumption from thermoelectic power plants across the US.  I am interested in applying machine learning techniques for understanding, quantifying, and predicting processes within the environment and relationships between humans and the environment. 

My previous research was field and laboratory based and included examining the potential human health effects from exposure to biodiesel and petroleum diesel emissions, the occurrence of mercury in rainwater, and the occurrence of pesticides and herbicides in groundwater.  I have also worked with K-12 science educators and taught college level courses in geology and environmental science.  


Ph.D., Earth and Environmental Science, University of New Hampshire, 2012

M.S., Geology, Rensselaer Polytechnic Institute, 2002

B.A., Geoscience, William Smith College, 1995