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Coupling Time and Non-Time Series Models to Simulate the Flood Depth at Urban Flooded Area

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Outgoing claims: the papers this work cites, builds on, or argues with.

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Preface: Flood-risk analysis and integrated management

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Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.5125234openalex-extracted
Using Explainable Artificial Intelligence (Xai) to Understand Compound Flooding Arising from Rainstorms and Tides
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Simulation of Urban Flood Process Based on a Hybrid LSTM-SWMM Model
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A GPU-Accelerated Full 2D Shallow Water Model Using an Edge Loop Method on Unstructured Meshes: Implementation and Performance Analysis
inferred← citeshttps://doi.org/10.1007/s11269-024-04020-6openalex-snapshot
Urban Flood Depth Prediction and Visualization Based on the XGBoost-SHAP Model
inferred← citeshttps://doi.org/10.1007/s13753-025-00639-0openalex-snapshot
A Comprehensive Review of Machine Learning Approaches for Flood Depth Estimation
inferred← citeshttps://doi.org/10.1016/j.jenvman.2025.125858openalex-snapshot
Formation mechanism analysis and the prediction for compound flood arising from rainstorm and tide using explainable artificial intelligence
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2024.131482openalex-snapshot
A novel strategy for flood flow Prediction: Integrating Spatio-Temporal information through a Two-Dimensional hidden layer structure
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Improved understanding of tropical urban catchment hydrology by SWMM modeling and sensitivity analysis: a case study of Udon Thani City, Thailand
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