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Admin Husic
University of KansasMeeting roles in:
Applications of Machine Learning in Large-Scale Hydrology and Water Quality Modeling I Oral
Event water fraction increases across the conterminous United States under climatic and anthropogenic change
Applications of Machine Learning in Large-Scale Hydrology and Water Quality Modeling II Oral
Dynamic Mixing with Unsteady Transit Time Theory Resolves Source-Specific Water Quality in a One-Water Reservoir
Applications of Machine Learning in Large-Scale Hydrology and Water Quality Modeling III Poster
STREAM: a Comprehensive High-Frequency Sensor Database of Water Quality in Rivers in the United States
Deep Learning Reveals the Bursty and Seasonal Nature of Continental-Scale Sediment Transport
Identifying Dominant Hydrologic Processes Across Continental Landscapes Using Hydrologic Signatures
Observation to Prediction: Toward a National Infrastructure for Headwater Science & Forecasting
Sediment fingerprinting for unmonitored basins using machine learning
Sediment fingerprinting reveals event-driven shifts in sediment sources for a large federal reservoir, Kansas, USA
Frontiers in Water Quality I Oral
Why Are Some Watersheds More Sediment-Productive Than Others?
Frontiers in Water Quality II Oral
Detecting Long-term Freshwater Salinization Trends and Chronic Chloride Exceedance with a Deep Learning Model
Frontiers in Water Quality III Oral
Frontiers in Water Quality IV Poster
From short bursts to long trends: disentangling human and climate influence on sediment connectivity across time and space
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