Works matching IS 09204741 AND DT 2024 AND VI 38 AND IP 5
Results: 12
Acknowledgement of Reviewers for 2023.
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- Water Resources Management, 2024, v. 38, n. 5, p. 1607, doi. 10.1007/s11269-024-03771-6
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How Do Structural Safety, Ecological Functions and Social Development Influence Construction of Ecological Seawalls for Coastal Protection and Sustainability?
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- Water Resources Management, 2024, v. 38, n. 5, p. 1807, doi. 10.1007/s11269-024-03768-1
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Analysing Coastal Flood Risk: Assessing the Impact on Critical Water Infrastructures.
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- Water Resources Management, 2024, v. 38, n. 5, p. 1791, doi. 10.1007/s11269-024-03766-3
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Investigating the Non-Linear Effects of Breach Parameters on a Dam Break Study.
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- Water Resources Management, 2024, v. 38, n. 5, p. 1773, doi. 10.1007/s11269-024-03765-4
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A Rapid Assessment Method for Flood Risk Mapping Integrating Aerial Point Clouds and Deep Learning.
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- Water Resources Management, 2024, v. 38, n. 5, p. 1753, doi. 10.1007/s11269-024-03764-5
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Combined Systematic Review and Meta-Analysis of Ground-Level Impacts of Management Transfer to Poor Farmers in Developing Countries.
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- Water Resources Management, 2024, v. 38, n. 5, p. 1737, doi. 10.1007/s11269-024-03763-6
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The Implementation of a New Optimization Method for Hydropower Generation and Multi-Reservoir Systems.
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- Water Resources Management, 2024, v. 38, n. 5, p. 1711, doi. 10.1007/s11269-024-03762-7
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Future Climatic Projections and Hydrological Responses with a Data Driven Method: A Regional Climate Model Perspective.
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- Water Resources Management, 2024, v. 38, n. 5, p. 1693, doi. 10.1007/s11269-024-03753-8
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Prediction of Depth-Averaged Velocity for Flow Though Submerged Vegetation Using Least Squares Support Vector Machine with Bayesian Optimization.
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- Water Resources Management, 2024, v. 38, n. 5, p. 1675, doi. 10.1007/s11269-024-03751-w
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A Novel Runoff Prediction Model Based on Support Vector Machine and Gate Recurrent unit with Secondary Mode Decomposition.
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- Water Resources Management, 2024, v. 38, n. 5, p. 1655, doi. 10.1007/s11269-024-03748-5
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A Machine Learning-Based Probabilistic Approach for Irrigation Scheduling.
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- Water Resources Management, 2024, v. 38, n. 5, p. 1639, doi. 10.1007/s11269-024-03746-7
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Study on Multi-Time Scale Hydrodynamic Model Based on Local Time Stepping Scheme and GPUs and its Application in Urban Inundation.
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- Water Resources Management, 2024, v. 38, n. 5, p. 1615, doi. 10.1007/s11269-024-03742-x
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- Article