23 citations as recorded by crossref.

1. A new multi-model absolute difference-based sensitivity (MMADS) analysis method to screen non-influential processes under process model and parametric uncertainty J. Yang & M. Ye 10.1016/j.jhydrol.2022.127609
2. Can continuous simulation be used as an alternative for flood regionalisation? A large sample example from Chile P. Acuña & A. Pizarro 10.1016/j.jhydrol.2023.130118
3. Guidance on evaluating parametric model uncertainty at decision-relevant scales J. Smith et al. 10.5194/hess-26-2519-2022
4. Comparative Assessment of Two Global Sensitivity Approaches Considering Model and Parameter Uncertainty H. Dai et al. 10.1029/2023WR036096
5. A Computationally Efficient Method for Estimating Multi‐Model Process Sensitivity Index H. Dai et al. 10.1029/2022WR033263
6. 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. 10.1016/j.envsoft.2022.105474
7. Learning from hydrological models’ challenges: A case study from the Nelson basin model intercomparison project M. Ahmed et al. 10.1016/j.jhydrol.2023.129820
8. The Great Lakes Runoff Intercomparison Project Phase 4: the Great Lakes (GRIP-GL) J. Mai et al. 10.5194/hess-26-3537-2022
9. Towards reducing the high cost of parameter sensitivity analysis in hydrologic modeling: a regional parameter sensitivity analysis approach S. Larabi et al. 10.5194/hess-27-3241-2023
10. Establishment of watershed ecological water requirements framework: A case study of the Lower Yellow River, China H. Wu et al. 10.1016/j.scitotenv.2022.153205
11. Coupled effects of observation and parameter uncertainty on urban groundwater infrastructure decisions M. Mautner et al. 10.5194/hess-26-1319-2022
12. A Robust Strategy to Account for Data Sampling Variability in the Development of Hydrological Models F. Zheng et al. 10.1029/2022WR033703
13. Ten strategies towards successful calibration of environmental models J. Mai 10.1016/j.jhydrol.2023.129414
14. Sensitivity of the land surface hydrological cycle to human activities in China K. Luo & J. Moiwo 10.1016/j.gr.2022.04.006
15. Process Interactions Can Change Process Ranking in a Coupled Complex System Under Process Model and Parametric Uncertainty J. Yang et al. 10.1029/2021WR029812
16. The pie sharing problem: Unbiased sampling of N+1 summative weights J. Mai et al. 10.1016/j.envsoft.2021.105282
17. A step toward global-scale applicability and transferability of flow duration curve studies: A flow duration curve review (2000–2020) C. Leong & Y. Yokoo 10.1016/j.jhydrol.2021.126984
18. The PAVICS-Hydro platform: A virtual laboratory for hydroclimatic modelling and forecasting over North America R. Arsenault et al. 10.1016/j.envsoft.2023.105808
19. The sensitivity of simulated streamflow to individual hydrologic processes across North America J. Mai et al. 10.1038/s41467-022-28010-7
20. Time to Update the Split‐Sample Approach in Hydrological Model Calibration H. Shen et al. 10.1029/2021WR031523
21. RavenR v2.1.4: an open-source R package to support flexible hydrologic modelling R. Chlumsky et al. 10.5194/gmd-15-7017-2022
22. Improving structure identifiability of hydrological processes by temporal sensitivity with a flexible modeling framework L. Zhou et al. 10.1016/j.jhydrol.2022.128843
23. Simultaneous Calibration of Hydrologic Model Structure and Parameters Using a Blended Model R. Chlumsky et al. 10.1029/2020WR029229