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Donna Rizzo
University of VermontMeeting roles in:
What Controls River Turbidity? Uncovering the Roles of Climate, Land Use, and Landscape Heterogeneity with a Deep Learning Model
Scalable Nested Deep Learning Framework for Real-Time Water Quality Forecasting Across Tributary Networks
Spatiotemporal Turbidity Prediction in River Systems using Graph Neural Networks
Evaluating National Water Model streamflow prediction bias during identified drought events in the Colorado River Basin
Spatiotemporal Interrogation of Crop Yield Patterns to Identify Key Variables and Feature Interactions using a Tandem Evolutionary Algorithm
Post-Processing HAB Forecasts: A Bias Correction and Elasticity Assessment Using Ensemble and Machine Learning Methods
Partnering Across Intelligences: Interdisciplinary Approaches to Water Quality and AI
Drivers and Confounding Factors Influencing Dissolved Organic Carbon and Nitrogen in Continental U.S. Streams
Leveraging Discrete Choice Experiments to Co-Configure Features of Trustworthy AI augmented Decision Support Systems for Sustaining Climate Services at the Nexus of Agriculture and Water
Performance-based Incentives and Knowledge Co-Production Using Precision Technologies for Agri-Environmental Governance
Multi Modal Learning for Forecasting Maximum Chlorophyll Index and Peak Height in Lake Champlain
A machine learning approach to improve the spatiotemporal resolution of actual evapotranspiration estimates by upscaling eddy covariance tower measurements to the field scale
HydroGem: A Domain-Informed Foundation Model for Hydrological Anomaly Detection, Imputation, and Forecasting
Advancing Predictive Skill of a Cyanobacterial HAB Integrated Early Warning System in Northeastern Lake Champlain Toward Operational Implementation
Winter Is a Hot Moment of Nitrate Export in the Mountains of Northern New England
Leveraging Expert Knowledge for Automated Baseflow Dominance Detection Across the Continental United States
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