13 citations as recorded by crossref.

1. Subgrid FD: a model balancing computational efficiency and accuracy for salinity simulation in tidal river systems Z. Wang et al. https://doi.org/10.1080/19942060.2026.2667555
2. Beyond the 100-year flood: probabilistic flood hazard assessment for King and Pierce Counties under future climate scenarios K. Nederhoff et al. https://doi.org/10.5194/nhess-26-3231-2026
3. Modified Horton’s infiltration model integrated with a Sub-Grid shallow water equation solver for High-Resolution flooding simulation A. Saha et al. https://doi.org/10.1016/j.jhydrol.2025.133326
4. Spatiotemporal quantification of relative contributions of compound flood drivers using Shapley value-based approach M. Chowdhury et al. https://doi.org/10.1016/j.jhydrol.2026.135808
5. Accelerating compound flood risk assessments through active learning: A case study of Charleston County (USA) L. Terlinden-Ruhl et al. https://doi.org/10.5194/nhess-25-1353-2025
6. Climate and impact attribution of compound flooding induced by tropical cyclone Idai in Mozambique D. Vertegaal et al. https://doi.org/10.5194/nhess-26-1417-2026
7. Unraveling uncertainty in compound flood modeling: sensitivity of simulations to forcings and model parameters C. Wang et al. https://doi.org/10.1016/j.jhydrol.2026.135424
8. Validation of the open-source hydrodynamic model SFINCS on historical river floods at the global scale T. Sadana et al. https://doi.org/10.5194/hess-30-5491-2026
9. The importance of waves in large-scale coastal compound flooding: A case study of Hurricane Florence (2018) T. Leijnse et al. https://doi.org/10.1016/j.coastaleng.2025.104726
10. PyFlood: Rapid high-resolution coastal flood mapping with digital elevation model, land cover and water level data A. Santos Cruz et al. https://doi.org/10.1016/j.envsoft.2026.107010
11. Assessment of tsunami hazards at the north coast of Egypt by means of numerical modelling A. Zed et al. https://doi.org/10.1016/j.ecss.2026.110143
12. Tropical cyclone induced compound flooding in Madagascar: a coupled modeling approach M. Khan et al. https://doi.org/10.1007/s11069-025-07209-z
13. Leveraging Coupled Hydrodynamic with Data-Driven GeoAI Models for Advancing Systemic Compound Flood Risk Evaluation in Coastal Urban Areas T. Atmaja et al. https://doi.org/10.1007/s11831-025-10394-6