50 citations as recorded by crossref.

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14. Towards flood risk mapping based on multi-tiered decision making in a densely urbanized metropolitan city of Istanbul Ö. Ekmekcioğlu et al. https://doi.org/10.1016/j.scs.2022.103759
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19. Probabilistic flood inundation mapping through copula Bayesian multi-modeling of precipitation products F. Gomez et al. https://doi.org/10.5194/nhess-24-2647-2024
20. Efficient Data Assimilation Method for Optimizing Prediction of Flow Field and Sediment Transport in Open Channel M. Ahmed & S. Li https://doi.org/10.1002/rra.70092
21. Development of a Fast and Accurate Hybrid Model for Floodplain Inundation Simulations N. Fraehr et al. https://doi.org/10.1029/2022WR033836
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26. Beyond a fixed number: Investigating uncertainty in popular evaluation metrics of ensemble flood modeling using bootstrapping analysis T. Huang & V. Merwade https://doi.org/10.1111/jfr3.12982
27. Quantifying cascading uncertainty in compound flood modeling with linked process-based and machine learning models D. Muñoz et al. https://doi.org/10.5194/hess-28-2531-2024
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34. The use of crowdsourced social media data to improve flood forecasting C. Songchon et al. https://doi.org/10.1016/j.jhydrol.2023.129703
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37. Constraining Flood Forecasting Uncertainties through Streamflow Data Assimilation in the Tropical Andes of Peru: Case of the Vilcanota River Basin H. Llauca et al. https://doi.org/10.3390/w15223944
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41. Dual State‐Parameter Assimilation of SAR‐Derived Wet Surface Ratio for Improving Fluvial Flood Reanalysis T. Nguyen et al. https://doi.org/10.1029/2022WR033155
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49. A probabilistic machine learning framework for daily extreme events forecasting A. Sattari et al. https://doi.org/10.1016/j.eswa.2024.126004
50. Improvement of Flood Extent Representation With Remote Sensing Data and Data Assimilation T. Nguyen et al. https://doi.org/10.1109/TGRS.2022.3147429