23 citations as recorded by crossref.

1. Predicting hourly-based flow discharge hydrographs from level data using genetic algorithms G. Tayfur & T. Moramarco https://doi.org/10.1016/j.jhydrol.2007.12.029
2. Uncertainty in river discharge observations: a quantitative analysis G. Di Baldassarre & A. Montanari https://doi.org/10.5194/hess-13-913-2009
3. Current awareness https://doi.org/10.1002/hyp.419
4. Effect of observation errors on the uncertainty of design floods G. Di Baldassarre et al. https://doi.org/10.1016/j.pce.2011.05.001
5. System identification and subsequent discharge estimation based on level data alone—Gradually varied flow condition H. Damangir & M. Abedini https://doi.org/10.1016/j.flowmeasinst.2014.01.002
6. Rating Curve Development at Ungauged River Sites using Variable Parameter Muskingum Discharge Routing Method B. Sahoo et al. https://doi.org/10.1007/s11269-014-0709-9
7. Discharge and suspended sediment patterns in a small mountainous watershed with widely distributed rock fragments N. Fang et al. https://doi.org/10.1016/j.jhydrol.2015.06.046
8. A systematic review of Muskingum flood routing techniques A. Salvati et al. https://doi.org/10.1080/02626667.2024.2324132
9. A Simulation–Optimization Technique to Estimate Discharge in Open Channels Based on Water Level Data Alone: Gradually Varied Flow Condition B. Balouchi et al. https://doi.org/10.1007/s40996-018-0149-5
10. Identification of temporal consistency in rating curve data: Bidirectional Reach (BReach) K. Van Eerdenbrugh et al. https://doi.org/10.1002/2016WR018692
11. A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations G. Coxon et al. https://doi.org/10.1002/2014WR016532
12. Comparative analysis of rating curve and ADP estimates of instantaneous water discharge through estuaries in two contrasting Brazilian rivers F. da Silva Dias et al. https://doi.org/10.1002/hyp.7972
13. Assessing the Role of Hydrodynamics in Enhancing Height‐Above‐the‐Nearest‐Drainage Derived Synthetic Rating Curves: A Comparative Study in the Wu River Basin, Taiwan C. Yu et al. https://doi.org/10.1111/jfr3.70057
14. Case Study: Improving Real-Time Stage Forecasting Muskingum Model by Incorporating the Rating Curve Model S. Barbetta et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000345
15. Development of the Jamuneswari Flood Forecasting System: Case Study in Bangladesh M. Rahman et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000565
16. Forecasting discharges at the downstream end of a river reach through two simple Muskingum based procedures M. Franchini et al. https://doi.org/10.1016/j.jhydrol.2011.01.009
17. Estimating river discharge from earth observation measurements of river surface hydraulic variables J. Negrel et al. https://doi.org/10.5194/hess-15-2049-2011
18. Relating Local Stage and Remote Discharge with Significant Lateral Inflow T. Moramarco et al. https://doi.org/10.1061/(ASCE)1084-0699(2005)10:1(58)
19. Genetic Algorithm-Based Discharge Estimation at Sites Receiving Lateral Inflows G. Tayfur et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000009
20. A methodology for discharge estimation and rating curve development at ungauged river sites M. Perumal et al. https://doi.org/10.1029/2005WR004609
21. Extrapolation of rating curves by hydraulic modelling, with application to flood frequency analysis M. Lang et al. https://doi.org/10.1080/02626667.2010.504186
22. Enhancement and comprehensive evaluation of the Rating Curve Model for different river sites S. Barbetta et al. https://doi.org/10.1016/j.jhydrol.2012.07.027
23. Flood modelling: parameterisation and inflow uncertainty M. Mukolwe et al. https://doi.org/10.1680/wama.12.00087