24 citations as recorded by crossref.

1. Least-Squares Based and Gradient Based Iterative Parameter Estimation Algorithms for a Class of Linear-in-Parameters Multiple-Input Single-Output Output Error Systems C. Wang et al. 10.1155/2014/673197
2. Development of Multivariable Dynamic System Response Curve Method for Real‐Time Flood Forecasting Correction Y. Sun et al. 10.1029/2018WR022555
3. Real-time error correction for flood forecasting based on machine learning ensemble method and its uncertainty assessment C. Xu et al. 10.1007/s00477-022-02336-6
4. Improving real-time inflow forecasting into hydropower reservoirs through a complementary modelling framework A. Gragne et al. 10.5194/hess-19-3695-2015
5. On the prediction of persistent processes using the output of deterministic models H. Tyralis & D. Koutsoyiannis 10.1080/02626667.2017.1361535
6. Case Study: A Real-Time Flood Forecasting System with Predictive Uncertainty Estimation for the Godavari River, India S. Barbetta et al. 10.3390/w8100463
7. Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities Y. Liu et al. 10.5194/hess-16-3863-2012
8. Improving Forecast Skill of Lowland Hydrological Models Using Ensemble Kalman Filter and Unscented Kalman Filter Y. Sun et al. 10.1029/2020WR027468
9. Epistemic uncertainties and natural hazard risk assessment – Part 1: A review of different natural hazard areas K. Beven et al. 10.5194/nhess-18-2741-2018
10. Deriving optimal operating rules for flood control considering pre-release based on forecast information G. Wei et al. 10.1016/j.jhydrol.2022.128665
11. Short-term ensemble streamflow forecasting using operationally-produced single-valued streamflow forecasts – A Hydrologic Model Output Statistics (HMOS) approach S. Regonda et al. 10.1016/j.jhydrol.2013.05.028
12. Parameter identification of a class of nonlinear systems based on the multi-innovation identification theory C. Wang & L. Zhu 10.1016/j.jfranklin.2015.07.003
13. Testing probabilistic adaptive real‐time flood forecasting models P. Smith et al. 10.1111/jfr3.12055
14. The Science of NOAA's Operational Hydrologic Ensemble Forecast Service J. Demargne et al. 10.1175/BAMS-D-12-00081.1
15. Investigating the interactions between data assimilation and post-processing in hydrological ensemble forecasting F. Bourgin et al. 10.1016/j.jhydrol.2014.07.054
16. A cloud based tool for knowledge exchange on local scale flood risk M. Wilkinson et al. 10.1016/j.jenvman.2015.06.009
17. Recursively updating the error forecasting scheme of a complementary modelling framework for improved reservoir inflow forecasts A. Gragne et al. 10.1016/j.jhydrol.2015.05.039
18. Deterministic and probabilistic flood modeling for contemporary and future coastal and inland precipitation inundation C. Thompson & T. Frazier 10.1016/j.apgeog.2014.01.013
19. Nierji reservoir flood forecasting based on a Data-Based Mechanistic methodology G. Wei et al. 10.1016/j.jhydrol.2018.10.026
20. Application of data-based mechanistic modelling for flood forecasting at multiple locations in the Eden catchment in the National Flood Forecasting System (England and Wales) D. Leedal et al. 10.5194/hess-17-177-2013
21. Characterizing the uncertainty in river stage forecasts conditional on point forecast values J. Yan et al. 10.1029/2012WR011818
22. Method for Probabilistic Flood Forecasting Considering Rainfall and Model Parameter Uncertainties X. Jiang et al. 10.1061/(ASCE)HE.1943-5584.0001861
23. On noise specification in data assimilation schemes for improved flood forecasting using distributed hydrological models S. Noh et al. 10.1016/j.jhydrol.2014.07.049
24. A data based mechanistic real-time flood forecasting module for NFFS FEWS D. Leedal et al. 10.5194/hessd-9-7271-2012