11 citations as recorded by crossref.

1. Geomorphic flood index 2.0: enhanced tools for delineating flood-prone areas in data-scarce regions S. Manfreda et al. https://doi.org/10.1016/j.catena.2026.110242
2. Improving continental and global scale digital elevation models via estimation of a riverine topobathymetric surface J. Gutenson et al. https://doi.org/10.1016/j.envsoft.2025.106487
3. Urban flood susceptibility mapping using deep and machine learning algorithms as a management tool: A case study of Sanandaj City, Iran A. Shirzadi et al. https://doi.org/10.1016/j.ecolind.2025.113886
4. Intercomparison of flood inundation models across land use types and hydrological flood stages P. Nikrou et al. https://doi.org/10.1016/j.jhydrol.2026.135410
5. Analytical hierarchy process-based mapping of social vulnerability to climate change in mountainous communes across Northwestern Vietnam V. Le Bui et al. https://doi.org/10.1007/s10708-026-11588-6
6. Evaluation of FABDEM vertical accuracy and hydrological suitability in complex terrain regions of China: A case study from Guangdong Province G. Yang et al. https://doi.org/10.1016/j.rsase.2026.101969
7. Population exposure to flooding in Small Island Developing States under climate change L. Archer et al. https://doi.org/10.1088/1748-9326/ad78eb
8. Beyond Vertical Accuracy: Benchmarking Global DEMs for Hydrologic Connectivity and Flood Sensitivity in Flat Coastal Plains J. Fragozo Arevalo et al. https://doi.org/10.3390/hydrology13020074
9. Tropical cyclone induced compound flooding in Madagascar: a coupled modeling approach M. Khan et al. https://doi.org/10.1007/s11069-025-07209-z
10. Modelling the influence of future climate and land-use change on fluvial flood inundation in data-scarce regions using CMIP6 ensembles, FABDEM and a validated 2D hydrodynamic model S. Mugume et al. https://doi.org/10.2166/nh.2026.103
11. Develop an Approach for Mapping an Accurate and Appropriate Flood Susceptibility for Quang Binh Province, Vietnam, Using Machine Learning Algorithms and Remote Sensing H. Tran Dang et al. https://doi.org/10.2478/cee-2026-0089