13 citations as recorded by crossref.

1. A stochastic conceptual-data-driven approach for improved hydrological simulations J. Quilty et al. https://doi.org/10.1016/j.envsoft.2022.105326
2. User-tailored sub-selection of climate model ensemble members for impact studies A. Sikorska-Senoner et al. https://doi.org/10.1016/j.scitotenv.2024.175769
3. Delineating modelling uncertainty in river flow indicators with representative parameter sets A. Sikorska-Senoner https://doi.org/10.1016/j.advwatres.2021.104024
4. Partitioning uncertainties of extreme flood estimates using long continuous simulations E. Kritidou et al. https://doi.org/10.1016/j.jhydrol.2025.134804
5. A novel ensemble-based conceptual-data-driven approach for improved streamflow simulations A. Sikorska-Senoner & J. Quilty https://doi.org/10.1016/j.envsoft.2021.105094
6. Clustering model responses in the frequency space for improved simulation‐based flood risk studies: The role of a cluster number A. Sikorska‐Senoner https://doi.org/10.1111/jfr3.12772
7. Impact of different weather generator scenarios on extreme flood estimates in Switzerland E. Kritidou et al. https://doi.org/10.1007/s00477-024-02843-8
8. Can continuous simulation be used as an alternative for flood regionalisation? A large sample example from Chile P. Acuña & A. Pizarro https://doi.org/10.1016/j.jhydrol.2023.130118
9. The role of antecedent conditions in translating precipitation events into extreme floods at the catchment scale and in a large-basin context M. Staudinger et al. https://doi.org/10.5194/nhess-25-247-2025
10. Evaluation of a stochastic weather generator for long-term ensemble streamflow forecasts S. Sohrabi & F. Brissette https://doi.org/10.1080/02626667.2021.1873343
11. Why do we have so many different hydrological models? A review based on the case of Switzerland P. Horton et al. https://doi.org/10.1002/wat2.1574
12. Ensemble and stochastic conceptual data-driven approaches for improving streamflow simulations: Exploring different hydrological and data-driven models and a diagnostic tool D. Hah et al. https://doi.org/10.1016/j.envsoft.2022.105474
13. Comprehensive space–time hydrometeorological simulations for estimating very rare floods at multiple sites in a large river basin D. Viviroli et al. https://doi.org/10.5194/nhess-22-2891-2022