Publications, Presentations and Posters

Conference Presentations
Norm Jones, Gus Williams, Donna Rizzo, Prabhakar Clement. (2024). Advancing Science to Better Characterize Drought and Groundwater-Driven Low-Flow Conditions in NOAA and USGS National-Scale Models. CIROH Training and Developers Conference 2024; Salt Lake City, UT; https://ciroh.ua.edu/abstracts/advancing-science-to-better-characterize-drought-and-groundwater-driven-low-flow-conditions-in-noaa-and-usgs-national-scale-models/

Norm Jones, Gus William, T. Prabhakar Clement, Donna Rizzo. (2023). Advancing Science to Better Characterize Drought and Groundwater-Driven Low-Flow Conditions in NOAA and USGS National-Scale Models. CIROH Training and Developers Conference 2023; Tuscaloosa, AL;


Posters
Xueyi Li, Amin Aghababaei, Norm Jones, and Gustavious Williams – Brigham Young University; Eniola Webster-Esho, Prabhakar Clement – The University of Alabama; Ryan Van Der Heijden, Donna Rizzo – University of Vermont. (2024). BASEFLOW: A Python package for digital baseflow separation and analysis. CIROH Training and Developers Conference 2024; Salt Lake City, UT; https://ciroh.ua.edu/abstracts/baseflow-a-python-package-for-digital-baseflow-separation-and-analysis/

Eniola Webster-Esho, T. Prabhakar Clement, Xueyi Li, Amin Aghababaei, Gustavious Williams, Norm Jones, Ryan van der Heijden, Donna M. Rizzo. (2024). Gradient-based Method for Automatically Generating Labelled Baseflow Dataset. CIROH Training and Developers Conference 2024; Salt Lake City, UT; https://ciroh.ua.edu/abstracts/gradient-based-method-for-automatically-generating-labelled-baseflow-dataset/

Amin Aghababaei, Xueyi Li, Norm Jones, Gustavious Williams, Eniola Webster-Esho, Prabhakar Clement, Ryan van der Heijden, Donna Rizzo. (2024). Nationwide Identification of Baseflow Dominant Periods: Integrating Manual Expertise into Machine Learning. CIROH Training and Developers Conference 2024; Salt Lake City, UT; https://ciroh.ua.edu/abstracts/nationwide-identification-of-baseflow-dominant-periods-integrating-manual-expertise-into-machine-learning/