Papers


This list is far from complete. We will add to it over time. Let us know of anything that you think should be included. See also GMDSI monographs.

Doherty, J. and Simmons, C.T., 2013. Groundwater modelling in decision support: reflections on a unified conceptual framework. Hydrogeology Journal 21: 1531–1537

Doherty, J. and Moore, C., 2020. Decision support modelling: data assimilation, uncertainty quantification and strategic abstraction. Groundwater, 58(3), 327-337. https://doi.org/10.1111/gwat.12969

Fienen, M.N., White, J.T., Hayek, M., 2024. Parameter estimation with the Gauss-Levenberg-Marquardt algorithm: an intuitive guide. Groundwaterhttps://ngwa.onlinelibrary.wiley.com/doi/10.1111/gwat.13433

Haley, L., Schumacher, J., MacMillan, G.J. and Boutin, L.C., 2014. Highly parameterized model calibration with cloud computing: an example of regional flow model calibration in northeast Alberta, Canada. Hydrogeology Journal. 22(3):729-737. https://doi.org/10.1007/s10040-014-1110-8

Haley, K., Valenza, A., White, E., Hutchison, B. and Schumacher, J., 2019. Application of the iterative ensemble smoother method and cloud computing: a groundwater modelling case study. Water, 11 (8), 1649. https://doi.org/10.3390/w11081649

Hugman, R. and Doherty, J., 2022. Complex or simple – does it have to be one or the other? Front. Earth. Sci., V10, https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2022.867379/full

Hugman, R. Lotti, F. and Doherty, J., 2022. Probabilistic contaminant source assessment – getting the most out of field measurements. Groundwater, 61(3), 363-374. https://ngwa.onlinelibrary.wiley.com/doi/full/10.1111/gwat.13246

White, J.T., 2018. A model-independent iterative ensemble smoother for efficient history-matching and uncertainty quantification in very high dimensions. Environmental modelling and software. 109:191-201. https://doi.org/10.1016/j.envsoft.2018.06.009