1. Sheikholeslami, R., Razavi, S., and Haghnegahdar, A., (2019), “What should we do when a model crashes? Recommendations for global sensitivity analysis of Earth and environmental systems models“, Geoscientific Model Development, 12, doi: 10.5194/gmd-12-4275-2019

  2. Razavi, S., Sheikholeslami, R., Gupta, H.V., and Haghnegahdar, A., (2019), VARS-TOOL: A toolbox for comprehensive, efficient, and robust sensitivity and uncertainty analysis, Environmental Modelling & Software, 112. doi:10.1016/j.envsoft.2018.10.005

  3. Razavi, S., and Gupta, H., (2019), A Multi-Method Generalized Global Sensitivity Matrix Approach to Accounting for the Dynamical Nature of Earth and Environmental Systems Models,Environmental Modelling & Software. doi:10.1016/j.envsoft.2018.12.002

  4. Razavi, S., and Gupta, H., (2019), A Multi-Method Generalized Global Sensitivity Matrix Approach to Accounting for the Dynamical Nature of Earth and Environmental Systems Models,Environmental Modelling & Software. doi:10.1016/j.envsoft.2018.12.002

  5. Gupta, H. V., and Razavi, S., (2018), Revisiting the basis of sensitivity analysis for Dynamical Earth System Models. Water Resources Research, 54, 8692–8717. doi:10.1029/2018WR022668

  6. Gupta, H. V., and Razavi, S., (2018), Revisiting the basis of sensitivity analysis for Dynamical Earth System Models. Water Resources Research, 54, 8692–8717. doi:10.1029/2018WR022668

  7. Sheikholeslami, R., Razavi, S., Gupta, H.V., Becker, W., and Haghnegahdar, A., (2019), Global sensitivity analysis for high-dimensional problems: How to objectively group factors and measure robustness and convergence while reducing computational cost. Environmental Modelling & Software, 111, 282-299. doi:10.1016/j.envsoft.2018.09.002

  8. Haghnegahdar A., Razavi. S., Yassin F., Wheater H., (2017), Multi-criteria sensitivity analysis as a diagnostic tool for understanding model behavior and characterizing model uncertainty, Hydrological Processes, doi:10.1002/hyp.11358

  9. Sheikholeslami, R., Yassin, F., Lindenschmidt, K., and Razavi, S., (2017), Improved Understanding of River Ice Processes Using Global Sensitivity Analysis Approaches, ASCE Journal of Hydrologic Engineering, 22(11), doi:10.1061/(ASCE)HE.1943-5584.0001574

  10. Haghnegahdar, A., and Razavi, S., (2017), Insights into sensitivity analysis of Earth and environmental systems models: On the impact of parameter perturbation scale, Environmental Modelling & Software, 95: 115–131, doi: 10.1016/j.envsoft.2017.03.031

  11. Sheikholeslami, R., and Razavi. S., (2017), Progressive Latin Hypercube Sampling: An efficient approach for robust sampling-based analysis of environmental models, Environmental Modelling & Software, 93, 109-126.

  12. Razavi, S. and Gupta, H. V., (2016), A new framework for comprehensive, robust, and efficient global sensitivity analysis: II. Application, Water Resources Research, 51, doi:10.1002/2015WR017559

  13. Razavi, S. and Gupta, H. V., (2016), A new framework for comprehensive, robust, and efficient global sensitivity analysis: I. Theory, Water Resources Research, 51, doi:10.1002/2015WR017558

  14. Razavi, S. and H. V. Gupta, (2015), What do we mean by sensitivity analysis? The need for comprehensive characterization of ‘‘global’’ sensitivity in Earth and Environmental systems models, Water Resour. Res., 51, 3070–3092, doi:10.1002/2014WR016527

  15. Gupta, H., and Razavi, S., (2017), Chapter 20 – Challenges and Future Outlook of Sensitivity Analysis, In “Sensitivity Analysis in Earth Observation Modelling”, Edited by Petropoulos and Srivastava, Elsevier Pages 397-415, ISBN 9780128030110, doi: 10.1016/B978- 0-12-803011-0.00020-3

  1. Holmes, T. L., Stadnyk, T. A., Asadzadeh, M., & Gibson, J. J. (2022). Variability in flow and tracer-based performance metric sensitivities reveal regional differences in dominant hydrological processes across the Athabasca River basin. Journal of Hydrology: Regional Studies, 41, 101088. https://doi.org/10.1016/j.ejrh.2022.101088

  2. Krogh, S. A., & Pomeroy, J. W. (2021). Simulating site-scale permafrost hydrology: Sensitivity to modelling decisions and air temperature. Journal of Hydrology, 602, 126771. https://doi.org/10.1016/j.jhydrol.2021.126771

  3. ‌Meles, M. B., Goodrich, D. C., Gupta, H. V., Shea Burns, I., Unkrich, C. L., Razavi, S., & Guertin, D. P. (2021). Multi-criteria, time dependent sensitivity analysis of an event-oriented, physically-based, distributed sediment and runoff model. Journal of Hydrology, 598, 126268. https://doi.org/10.1016/j.jhydrol.2021.126268

  4. Tsvetkova, O., & Ouarda, T. B. M. J. (2021). A review of sensitivity analysis practices in wind resource assessment. Energy Conversion and Management, 238, 114112. https://doi.org/10.1016/j.enconman.2021.114112

  5. Abbasnezhadi, K., Rousseau, A. N., Foulon, É., & Savary, S. (2021). Verification of Regional Deterministic Precipitation Analysis Products Using Snow Data Assimilation for Application in Meteorological Network Assessment in Sparsely Gauged Nordic Basins. Journal of Hydrometeorology, 22(4), 859–876. https://doi.org/10.1175/jhm-d-20-0106.1

  6. Sheikholeslami, R., & Razavi, S. (2020). A Fresh Look at Variography: Measuring Dependence and Possible Sensitivities Across Geophysical Systems From Any Given Data. Geophysical Research Letters, 47(20). https://doi.org/10.1029/2020gl089829

  7. Korgaonkar, Y., Meles, M. B., Guertin, D. P., Goodrich, D. C., & Unkrich, C. (2020). Global sensitivity analysis of KINEROS2 hydrologic model parameters representing green infrastructure using the STAR-VARS framework. Environmental Modelling & Software, 132, 104814. https://doi.org/10.1016/j.envsoft.2020.104814

  8. Medina, Y., & Muñoz, E. (2020). A Simple Time-Varying Sensitivity Analysis (TVSA) for Assessment of Temporal Variability of Hydrological Processes. Water, 12(9), 2463. https://doi.org/10.3390/w1209246‌

  9. Bajracharya, A., Awoye, H., Stadnyk, T., & Asadzadeh, M. (2020). Time Variant Sensitivity Analysis of Hydrological Model Parameters in a Cold Region Using Flow Signatures. Water, 12(4), 961. https://doi.org/10.3390/w12040961

  10. Douglas-Smith, D., Iwanaga, T., Croke, B. F. W., & Jakeman, A. J. (2020). Certain trends in uncertainty and sensitivity analysis: An overview of software tools and techniques. Environmental Modelling & Software, 124, 104588. https://doi.org/10.1016/j.envsoft.2019.104588