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EO data may improve flood monitoring and forecasting
Review of Earth Observation data capabilities for enhancing riverine flood monitoring and forecasting systems, analyzing accuracy, latency, and assimilation constraints.
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Forestation in China is linked to water and ecosystem trade-offs
Synthesis of forest hydrological research in China examining ecohydrological processes, ecosystem service trade-offs, and management implications of large-scale forestation programs.
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Integrated calibration improved Nile River model performance
Integrated sensitivity-optimisation framework for calibrating hydrodynamic and water-quality models applied to the Nile River using Brute-Force analysis and Dual-Annealing optimisation.
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DeepDiscover infers bucket-type hydrological models from data
Framework for autonomous inference of bucket-type conceptual hydrological models using physics-embedded machine learning, demonstrating improved predictive performance and physical coherence.
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Dataset covers sewer flow, pollution, and rain observations from 2008 to 2011
Four years of continuous sewer hydraulic and water quality data from Austria with precipitation records and hydrodynamic model for combined sewer system analysis and pollutant transport research
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Hydrological ML accuracy depends on training data quantity and quality
Analysis of how information quantity and quality in training data affect machine learning prediction accuracy for hydrological variables, using information theory and mechanistic model integration.
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Human water management alters streamflow in key U.S. regions
Diagnostic framework and data inventory for analyzing human water-management interventions on streamflow regimes in the Contiguous United States, with application to the Mississippi River Basin.
