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BibEntryCargo > Volume : 16 or 708 & Note: Auto downloaded ref at: 2020-06-26

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A Three-Dimensional Hydro-Environmental Model of Dublin Bay (1) · A coupled wave–3-D hydrodynamics model of the Taranto Sea (Italy): a multiple-nesting approach (1) · Agricultural Adaptation to Global Warming in the Tibetan Plateau (1) · Deriving the Characteristic Scale for Effectively Monitoring Heavy Metal Stress in Rice by Assimilation of GF-1 Data with the WOFOST Model (1) · Effect of uncertainty of grid DEM on TOPMODEL: Evaluation and analysis (1) · Effects of digital elevation model resolution on topography-based runoff simulation under uncertainty (1) · FORECAST STRUCTURE DEVELOPMENT FOR MODELLING THE SOUTHERN BRAZILIAN CONTINENTAL SHELF HYDRODYNAMIC (1) · Flood forecasting that considers the impact of hydraulic projects by an improved TOPMODEL model in the Wudaogou basin, Northeast China (1) · Land use effect and hydrological control on nitrate yield in subtropical mountainous watersheds (1) · Modelling of spatial controls on denitrification at the landscape scale (1) · Multiobjective Optimization of Pump-and-Treat-Based Optimal Multilayer Aquifer Remediation Design with Flexible Remediation Time (1) · Numerical model of pore‐pressure diffusion associated with the initiation of the 2010–2011 Guy–Greenbrier, Arkansas earthquakes (1) · Rainfall-runoff modelling of a humid tropical catchment: the TOPMODEL approach (1) · Research on the process-based risk evaluation method of groundwater pollution for contaminated site (1) · Resistance and reconfiguration of natural flexible submerged vegetation in hydrodynamic river modelling (1) · State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy (1) · Teaching hydrological modeling with a user-friendly catchment-runoff-model software package (1) · Tidal current and tidal energy changes imposed by a dynamic tidal power system in the Taiwan Strait, China (1) · TopModel: Template-Based Protein Structure Prediction at Low Sequence Identity Using Top-Down Consensus and Deep Neural Networks (1)
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