Tag: Hydrological modelling
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.
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.
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.
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
Projected land cover change slightly increases flood discharge
Hydrologic impact assessment of projected land cover changes in Cijangkelok Watershed using ANN-based spatial prediction and HEC-HMS design flood simulation.
Hydrological ML accuracy depends on training data quantity and quality
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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.
Model-based planning improved watershed saturation planning in a semi-arid basin
SWAT-based hydrological framework optimizing soil and water conservation practices for watershed saturation and water availability in semi-arid regions through ridge-to-valley spatial planning.
Human water management alters streamflow in key river 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.
