14 citations as recorded by crossref.

1. Bayesian hierarchical network model for forecasting daily river stage for rainfed river networks N. Rastogi et al. https://doi.org/10.1016/j.jhydrol.2025.132894
2. Leveraging multi-source satellite imagery for improving daily reservoir water storage and inflow estimation in a catchment hydrological model Q. Ma et al. https://doi.org/10.1016/j.jhydrol.2025.133761
3. Coupled intelligent prediction model for medium- to long-term runoff based on teleconnection factors selection and spatial-temporal analysis J. Li et al. https://doi.org/10.1371/journal.pone.0313871
4. Investigations of Multi-Platform Data for Developing an Integrated Flood Information System in the Kalu River Basin, Sri Lanka M. Rasmy et al. https://doi.org/10.3390/w15061199
5. Spatio-temporal Variability, Trends and Key Drivers of Rainfall over Narmada River Basin, India J. Sharma & O. Singh https://doi.org/10.1007/s00024-025-03722-1
6. Quantifying and reducing flood forecast uncertainty by the CHUP-BMA method Z. Cui et al. https://doi.org/10.5194/hess-28-2809-2024
7. Was the extreme rainfall that caused the August 2022 flood in Pakistan predictable? I. Malik et al. https://doi.org/10.1088/2752-5295/acfa1a
8. Sensitivity of snow magnitude and duration to hydrology model parameters B. Singh et al. https://doi.org/10.1016/j.jhydrol.2024.132193
9. Sub-seasonal prediction of compound hot and dry extremes in India I. Malik & V. Mishra https://doi.org/10.1007/s00382-025-07668-x
10. Understanding Complex Processes of Flood Inundation in a Regulated Coastal Lowland River: A Modelling Framework Integrating Hydrological, Hydraulic, Tidal and Geomorphic Data Z. Beg et al. https://doi.org/10.1002/hyp.70227
11. LSTM-based flood-stage forecasting under limited flood-event samples: Effects of forecasting scheme, spatial input configuration, and input-window length in the Pajiang River basin S. Li et al. https://doi.org/10.1016/j.ejrh.2026.103993
12. A prototype multi-hazard early warning system integrating flood and landslide forecasting: application in the upper Garonne River Basin F. Asurza et al. https://doi.org/10.1016/j.jhydrol.2026.136580
13. Calibrating macroscale hydrological models in poorly gauged and heavily regulated basins D. Vu et al. https://doi.org/10.5194/hess-27-3485-2023
14. Sub-seasonal to seasonal (S2S) prediction of dry and wet extremes for climate adaptation in India I. Malik & V. Mishra https://doi.org/10.1016/j.cliser.2024.100457