Nicolas Fernandez, Ph.D., Data Scientist, UF Water Institute

Join us for the livestream October 15th, 11:45am ET: https://youtube.com/live/JBwnNzkWqww?feature=share

(Please visit our YouTube channel main page for the stream if there are any issues with the direct link.)

ABSTRACT

Defining water quality often requires talking about multiple physicochemical properties, many of them referred to as constituent concentrations. Although the methods to measure these concentrations are widely standardized, where and when the measurements should be done remains as an open question, while the amount of information and samples collected relies highly on the availability of technical capacity and financial resources. Thus, regions having more of both resources count with rich water quality information, whereas data is normally scarce elsewhere. In this talk, I summarize my work in water quality, going from data scarce to data rich regions. First, I start in Andean Paramos where, in the absence of long-term concentration time series, I present methods that allow for identifying key pollutants, simulating their concentration, and solving conflicts between the use and quality of water. I then stop in Michigan where, using a larger yet recent dataset, I show the use of machine learning techniques to predict the occurrence and concentration of emerging contaminants (PFAS) in drinking groundwater sources. Finally, covering the conterminous USA, I present ChemLotUS: a dataset comprising 35 million records of geogenic, biogenic, and anthropogenic constituents collected in 290 thousand riverine locations. Using this dataset as an example, I present current opportunities and challenges for new developments in the field of water quality.

BIO

Nicolas Fernandez, Ph.D., is a chemical engineer (2009) with M.S. (2019) and Ph.D (2023) degrees in Environmental Engineering from Universidad de los Andes (Colombia). He transitioned from an extensive background in the private sector (environmental consulting, technical sales and patents), to focus on the intersection of data science, water quality and hydrology. Specifically, he works on researching new connections between these fields, harnessing the recent and growing availability of large datasets. He also helps stakeholders to manage their water data, a growing need in times when data-driven decisions are, or should be, prioritized. During his journey in research and education, and before joining the Water Institute at the University of Florida in 2025, he occupied a postdoctoral position at the Department of Soil Water and Ecosystem Sciences at the same University (2024) and was a visiting scholar at Michigan State University (2022).

POSTCARD