40 citations as recorded by crossref.

1. Value of different precipitation data for flood prediction in an alpine catchment: A Bayesian approach A. Sikorska & J. Seibert 10.1016/j.jhydrol.2016.06.031
2. Parameter estimation of hydrologic models using a likelihood function for censored and binary observations O. Wani et al. 10.1016/j.watres.2017.05.038
3. Modeling Suspended Sediment Concentration in the Stormwater Outflow from a Small Detention Pond A. Krajewski et al. 10.1061/(ASCE)EE.1943-7870.0001258
4. Efficient treatment of climate data uncertainty in ensemble Kalman filter (EnKF) based on an existing historical climate ensemble dataset H. Liu et al. 10.1016/j.jhydrol.2018.11.047
5. Calibrating a hydrological model in stage space to account for rating curve uncertainties: general framework and key challenges A. Sikorska & B. Renard 10.1016/j.advwatres.2017.04.011
6. Effective precipitation duration for runoff peaks based on catchment modelling A. Sikorska et al. 10.1016/j.jhydrol.2017.11.028
7. Describing the catchment‐averaged precipitation as a stochastic process improves parameter and input estimation D. Del Giudice et al. 10.1002/2015WR017871
8. Estimating the Uncertainty of Hydrological Predictions through Data-Driven Resampling Techniques A. Sikorska et al. 10.1061/(ASCE)HE.1943-5584.0000926
9. Comparison of two stochastic techniques for reliable urban runoff prediction by modeling systematic errors D. Del Giudice et al. 10.1002/2014WR016678
10. The multi temporal/multi-model approach to predictive uncertainty assessment in real-time flood forecasting S. Barbetta et al. 10.1016/j.jhydrol.2017.06.030
11. A review of pollution-based real-time modelling and control for sewage systems R. da Silva Gesser et al. 10.1016/j.heliyon.2024.e31831
12. Separately accounting for uncertainties in rainfall and runoff: Calibration of event-based conceptual hydrological models in small urban catchments using Bayesian method S. Sun & J. Bertrand-Krajewski 10.1002/wrcr.20444
13. The value of streamflow data in improving TSS predictions – Bayesian multi-objective calibration A. Sikorska et al. 10.1016/j.jhydrol.2015.09.051
14. Case Study: A Real-Time Flood Forecasting System with Predictive Uncertainty Estimation for the Godavari River, India S. Barbetta et al. 10.3390/w8100463
15. Estimating hydrologic model uncertainty in the presence of complex residual error structures S. Samadi et al. 10.1007/s00477-017-1489-6
16. Bayesian parameter inference in hydrological modelling using a Hamiltonian Monte Carlo approach with a stochastic rain model S. Ulzega & C. Albert 10.5194/hess-27-2935-2023
17. Appropriate temporal resolution of precipitation data for discharge modelling in pre-alpine catchments A. Sikorska & J. Seibert 10.1080/02626667.2017.1410279
18. Developing an Empirical Relations between Nash Model Parameters and Watersheds Topographical Characteristics for Predicting Direct Runoff Hydrograph K. Khidir 10.25130/tjes.30.2.9
19. Model bias and complexity – Understanding the effects of structural deficits and input errors on runoff predictions D. Del Giudice et al. 10.1016/j.envsoft.2014.11.006
20. Implications of changes in temperature and precipitation on the discharge of Brahmaputra River in the urban watershed of Guwahati, India I. Ahmed et al. 10.1007/s10661-021-09284-8
21. Bayesian neural networks for stock price forecasting before and during COVID-19 pandemic R. Chandra et al. 10.1371/journal.pone.0253217
22. Probabilistic assessment of failure of infiltration structures under model and parametric uncertainty A. Dell’Oca et al. 10.1016/j.jenvman.2023.118466
23. A novel ensemble-based conceptual-data-driven approach for improved streamflow simulations A. Sikorska-Senoner & J. Quilty 10.1016/j.envsoft.2021.105094
24. Estimating sediment yield from a small urban catchment of a heterogeneous structure A. Krajewski et al. 10.1002/ldr.4932
25. Considering rating curve uncertainty in water level predictions A. Sikorska et al. 10.5194/hess-17-4415-2013
26. State-of-the-Art Development of Two-Waves Artificial Intelligence Modeling Techniques for River Streamflow Forecasting W. Tan et al. 10.1007/s11831-022-09763-2
27. Regionalisation of hydrological responses under land-use change and variable data quality S. Visessri & N. McIntyre 10.1080/02626667.2015.1006226
28. Improving uncertainty estimation in urban hydrological modeling by statistically describing bias D. Del Giudice et al. 10.5194/hess-17-4209-2013
29. Improving the efficiency of Monte Carlo Bayesian calibration of hydrologic models via model pre-emption M. Shafii et al. 10.2166/hydro.2015.043
30. Impacts of observational uncertainty on analysis and modelling of hydrological processes: Preface H. McMillan et al. 10.1002/hyp.14481
31. Hydrological uncertainty processor based on a copula function Z. Liu et al. 10.1080/02626667.2017.1410278
32. Variability of the Initial Abstraction Ratio in an Urban and an Agroforested Catchment A. Krajewski et al. 10.3390/w12020415
33. Regional water balance modelling using flow-duration curves with observational uncertainties I. Westerberg et al. 10.5194/hess-18-2993-2014
34. Accounting for variation in rainfall intensity and surface slope in wash-off model calibration and prediction within the Bayesian framework M. Muthusamy et al. 10.1016/j.watres.2018.06.022
35. Flood‐type classification in mountainous catchments using crisp and fuzzy decision trees A. Sikorska et al. 10.1002/2015WR017326
36. Uncertainty of Deardorff’s soil moisture model based on continuous TDR measurements for sandy loam soil A. Brandyk et al. 10.1515/johh-2016-0007
37. Uncertainty Assessment of Synthetic Design Hydrographs for Gauged and Ungauged Catchments M. Brunner et al. 10.1002/2017WR021129
38. Long-Term Changes of Hydrological Variables in a Small Lowland Watershed in Central Poland A. Krajewski et al. 10.3390/w11030564
39. Rainfall-runoff modeling: A modification of the EBA4SUB framework for ungauged and highly impervious urban catchments A. Petroselli et al. 10.1016/j.jhydrol.2021.127371
40. A Bayesian method for missing rainfall estimation using a conceptual rainfall–runoff model S. Sun et al. 10.1080/02626667.2017.1390317