Latest Research in Hydrology and Sediment Transport Processes
15 research papers · 2026 median publication year
Top Research Topics in Hydrology and Sediment Transport Processes
- Geotechnical Engineering and Analysis — 5 papers
- Hydrology and Sediment Transport Processes — 2 papers
- Geotechnical Engineering and Underground Structures — 2 papers
- Rock Mechanics and Modeling — 2 papers
- Ocean Waves and Remote Sensing — 1 papers
- Soil Mechanics and Vehicle Dynamics — 1 papers
- Powder Metallurgy Techniques and Materials — 1 papers
- Geotechnical Engineering and Soil Mechanics — 1 papers
Highest-Cited Papers
- Probabilistic assessment of supported excavations under demand-based sequential strut loss considering soil spatial variability
- Three-Dimensional Numerical Simulation of Spanwise Scour Propagation Beneath a Submarine Pipeline
- A novel seismic-continuous geological predicting method in shield tunnels
- Experimentally Derived Scour Fragility Curves for Pile-Supported Bridge Piers under Lateral Loading: A Risk-Oriented Framework for Flood Hazards
- Developing a universal tunnel span classification from global tunnel databases
- Geometry of Breaking Waves Under Natural Sea Conditions
- Influence of Terrain Parameters on Tire Forces and Moments Under Multi-Pass Loading
- A two-stage physics-driven graph neural network framework for predicting tunnelling-induced deformation of frame structures
- Study on the Vibration Effects of Rock Slopes Under Blasting Loads
- Cloud–Model–Based Dynamic Assessment of Deformation Risk on the Traffic–Bearing Side During Tunnel Reconstruction and Expansion Considering Existing Tunnel Defects
- Field Evaluations of Intelligent Compaction Measurement Values for Quality Control of Trackbed Compaction
- A Semi-Analytical Solution for Topographic Amplification and Broadband Scattering of SH Waves by Step-like Rock Slopes
- Inversion-based reconstruction of equivalent single-source waveforms for predicting blast-induced vibrations in adjacent tunnels
- Probabilistic and Interpretable Machine Learning Framework for Predicting Pile Unit Base Resistance in Soft Soil
- Structural Damage Assessment and Resilience Evolution Prediction of Immersed Tunnels During Sand Foundation Loss Using In Situ Sensing Data