Focal Interest
Focal Interest

Hydrology (agriculture)

  1. Hydrology strongly controlled nitrate cycling in a tidal freshwater river
    Study reveals how discharge and residence time control nitrogen cycling in tidal freshwater zones, with denitrification dominating during low-flow periods and implications for managing estuarine.
  2. Freshwater and carbon export to northern Alaska estuaries increased
    Model-based analysis reveals intensified freshwater and organic carbon discharge to northern Alaska's Beaufort Sea estuaries driven by permafrost thaw and hydrological cycle changes.
  3. Graph neural networks identified flood-vulnerable river segments
    Graph neural network framework for assessing flood vulnerability in river basins. Identifies high-risk segments and flood-prone sub-basins by combining hydrological attributes with network topology.
  4. Soil moisture drove vegetation change on the Qinghai-Tibetan Plateau
    Soil moisture constraints override atmospheric aridity in governing vegetation dynamics across the warming Qinghai-Tibetan Plateau, with regional variation depending on basin hydrogeography.
  5. River stage dynamics drive dissolved oxygen in riparian aquifers
    Global sensitivity analysis with deep learning identifies river stage dynamics as primary control on dissolved oxygen in riparian aquifers, with implications for subsurface redox prediction.
  6. Bankruptcy rules guided pollutant allocation in Abbas-Abad River
    Integrated water quality modeling approach using bankruptcy rules and particle swarm optimization for equitable pollution load allocation in a semiarid mountainous river system.
  7. 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.
  8. 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.
  9. Mega-flood increased nutrient loads and altered water quality
    Mega-flood impact on Murray-Darling Basin water quality: analysis of nutrient dynamics, hysteresis patterns, and climate-driven flood risks across spatial gradients.
  10. 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
  11. 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.
  12. Sentinel-2 classifies Yellow River ice types with high accuracy
    Sentinel-2 remote sensing classifies Yellow River ice types with 94.91% accuracy using support vector machine algorithm, enabling operational monitoring for water resource and hazard management in.
  13. Model-based planning reduced runoff in a semi-arid watershed
    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.
  14. 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.