46 citations as recorded by crossref.

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19. What Is Controlling Our Control Rules? Opening the Black Box of Multireservoir Operating Policies Using Time‐Varying Sensitivity Analysis J. Quinn et al. 10.1029/2018WR024177
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27. Supporting M5 model trees with sensitivity information derived from conceptual hydrological models C. Massmann 10.2166/hydro.2015.111
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29. On characterizing the temporal dominance patterns of model parameters and processes B. Guse et al. 10.1002/hyp.10764
30. Rainstorm Magnitude Likely Regulates Event Water Fraction and Its Transit Time in Mesoscale Mountainous Catchments: Implication for Modelling Parameterization J. Lee et al. 10.3390/w12041169
31. Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding C. Kelleher et al. 10.5194/hess-21-3325-2017
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33. Improved understanding of vegetation dynamics and wetland ecohydrology via monthly UAV‐based classification S. Wu et al. 10.1002/hyp.14988
34. A multi-method Generalized Global Sensitivity Matrix approach to accounting for the dynamical nature of earth and environmental systems models S. Razavi & H. Gupta 10.1016/j.envsoft.2018.12.002
35. Analysing spatio-temporal process and parameter dynamics in models to characterise contrasting catchments B. Guse et al. 10.1016/j.jhydrol.2018.12.050
36. Sensitivity Analysis of Fully Distributed Parameterization Reveals Insights Into Heterogeneous Catchment Responses for Water Quality Modeling X. Yang et al. 10.1029/2019WR025575
37. Identifying Dominant Processes in Time and Space: Time‐Varying Spatial Sensitivity Analysis for a Grid‐Based Nitrate Model S. Wu et al. 10.1029/2021WR031149
38. Simultaneously determining global sensitivities of model parameters and model structure J. Mai et al. 10.5194/hess-24-5835-2020
39. Parameter uncertainty and sensitivity analysis of water quality model in Lake Taihu, China L. Jiang et al. 10.1016/j.ecolmodel.2018.02.014
40. Parameter Estimation and Uncertainty Analysis: A Comparison between Continuous and Event-Based Modeling of Streamflow Based on the Hydrological Simulation Program–Fortran (HSPF) Model H. Xie et al. 10.3390/w11010171
41. Understanding the time‐varying importance of different uncertainty sources in hydrological modelling using global sensitivity analysis F. Pianosi & T. Wagener 10.1002/hyp.10968
42. Spatiotemporal sensitivity analysis of vertical transport of pesticides in soil T. Hong & S. Purucker 10.1016/j.envsoft.2018.03.018
43. Multicriteria sensitivity analysis as a diagnostic tool for understanding model behaviour and characterizing model uncertainty A. Haghnegahdar et al. 10.1002/hyp.11358
44. Sensitivity analysis of hydrological models: review and way forward M. Devak & C. Dhanya 10.2166/wcc.2017.149
45. Time-varying sensitivity analysis of hydrologic and sediment parameters at multiple timescales: Implications for conservation practices H. Xie et al. 10.1016/j.scitotenv.2017.04.074
46. Multivariate sensitivity analysis based on the direction of eigen space through principal component analysis S. Xiao et al. 10.1016/j.ress.2017.03.011