17 citations as recorded by crossref.

1. A lumped conceptual model to simulate groundwater level time-series J. Mackay et al. https://doi.org/10.1016/j.envsoft.2014.06.003
2. Ideal point error for model assessment in data-driven river flow forecasting C. Dawson et al. https://doi.org/10.5194/hess-16-3049-2012
3. Symbiotic adaptive neuro-evolution applied to rainfall–runoff modelling in northern England C. Dawson et al. https://doi.org/10.1016/j.neunet.2006.01.009
4. Comparison of four updating models for real-time river flow forecasting L. XIONG & K. O'CONNOR https://doi.org/10.1080/02626660209492964
5. Concepts of Information Content and Likelihood in Parameter Calibration for Hydrological Simulation Models K. Beven & P. Smith https://doi.org/10.1061/(ASCE)HE.1943-5584.0000991
6. GLUE: 20 years on K. Beven & A. Binley https://doi.org/10.1002/hyp.10082
7. Assessment of evaluation methods using infiltration data measured in heterogeneous mountain soils L. Jačka et al. https://doi.org/10.1016/j.geoderma.2016.04.023
8. Prediction of Runoff in Watersheds Located within Data-Scarce Regions A. Ghanim et al. https://doi.org/10.3390/su14137986
9. HydroTest: A web-based toolbox of evaluation metrics for the standardised assessment of hydrological forecasts C. Dawson et al. https://doi.org/10.1016/j.envsoft.2006.06.008
10. Single-porosity and dual-porosity modeling of water flow and solute transport in subsurface-drained fields using effective field-scale parameters N. Haws et al. https://doi.org/10.1016/j.jhydrol.2005.03.035
11. A short history of philosophies of hydrological model evaluation and hypothesis testing K. Beven https://doi.org/10.1002/wat2.1761
12. The influence of biogeochemical conditions and level of model complexity when simulating cometabolic biodegradation in sorbent-water systems N. Haws et al. https://doi.org/10.1016/j.advwatres.2005.06.009
13. Functional classification and evaluation of hydrographs based on Multicomponent Mapping (Mx) F. Pappenberger & K. Beven https://doi.org/10.1080/15715124.2004.9635224
14. Multi-Objective Sensitivity Analysis of a Fully Distributed Hydrologic Model WetSpa J. Yang et al. https://doi.org/10.1007/s11269-011-9908-9
15. Smoothing the seasonal means of rainfall and runoff in the linear perturbation model (LPM) using the kernel estimator L. Xiong et al. https://doi.org/10.1016/j.jhydrol.2005.09.020
16. Timing error correction procedure applied to neural network rainfall—runoff modelling R. ABRAHART et al. https://doi.org/10.1623/hysj.52.3.414
17. Experimental evaluation of the effect of storm movement on peak discharge J. Liang & C. Melching https://doi.org/10.1016/j.ijsrc.2015.03.004