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A Brief Compendium of Use Cases for PEST++

Published Papers on Theory and Background

Published Papers on Applications

  • White, J.T., Foster, L.K., Fienen, M.N., Knowling, M.J., Hemmings, B. and Winterle, J.R., 2020. Toward Reproducible Environmental Modeling for Decision Support: A Worked Example. Frontiers in Earth Science, 8, p.50. https://doi.org/10.3389/feart.2020.00050
  • Mason, J.P., Knight, J.E., Ball, L.B. Kennedy, J.R., Bills, D.J., and Macy, J.P., 2020, Groundwater availability in the Truxton basin, northwestern Arizona, chap. A of Mason, J.P., ed., Geophysical surveys, hydrogeologic characterization, and groundwater flow model for the Truxton basin and Hualapai Plateau, northwestern Arizona: U.S. Geological Survey Scientific Investigations Report 2020–5017, 14 p., https://doi.org/10.3133/sir20205017A.
  • Knowling, M.J., White, J.T. and Moore, C.R., 2019. Role of model parameterization in risk-based decision support: An empirical exploration. Advances in Water Resources, 128, pp.59-73. https://doi.org/10.1016/j.advwatres.2019.04.010
  • Knowling, M.J., White, J.T., Moore, C.R., Rakowski, P. and Hayley, K., 2020. On the assimilation of environmental tracer observations for model-based decision support. Hydrology and Earth System Sciences, 24(4), pp.1677-1689.https://hess.copernicus.org/articles/24/1677/2020/
  • White, J.T., Knowling, M.J., Fienen, M.N., Feinstein, D.T., McDonald, G.W. and Moore, C.R., 2020. A non-intrusive approach for efficient stochastic emulation and optimization of model-based nitrate-loading management decision support. Environmental Modelling & Software, 126, p.104657. https://www.sciencedirect.com/science/article/pii/S1364815219309934
  • Hemmings, B., Knowling, M.J., and Moore, C.R. 2020. Early Uncertainty Quantification for an Improved Decision Support Modeling Workflow: A Streamflow Reliability and Water Quality Example. Frontiers in Earth Science. https://www.frontiersin.org/article/10.3389/feart.2020.565613
  • Knowling, M.J., White, J.T., McDonald, G.W., Kim, J.H., Moore, C.R., and Hemmings, B. (2020). Disentangling environmental and economic contributions to hydro-economic model output uncertainty: An example in the context of land-use change impact assessment. Environmental Modelling and Software.
  • Hunt, R.J., Fienen, M.N. and White, J.T. (2020), Revisiting “An Exercise in Groundwater Model Calibration and Prediction” After 30 Years: Insights and New Directions. Groundwater, 58: 168-182. https://doi.org/10.1111/gwat.12907
  • Foster, L.K., White, J.T., Leaf, A., Houston, N. and Teague, A. (2021), Risk‐based decision‐support groundwater modeling for the lower San Antonio River Basin, Texas, USA. Groundwater. Accepted Author Manuscript. https://doi.org/10.1111/gwat.13107
  • Hunt, R.J., White, J.T., Duncan, L.L., Haugh, C.J. and Doherty, J. (2021), Evaluating lower computational burden approaches for calibration of large environmental models. Groundwater. Accepted Author Manuscript. https://doi.org/10.1111/gwat.13106
  • White, J.T., Foster, L.K. and Fienen, M.N. (2021), Extending the Capture Map Concept to Estimate Discrete and Risk‐Based Streamflow Depletion Potential. Groundwater. https://doi.org/10.1111/gwat.13080
  • White, J.T., Knowling, M.J. and Moore, C.R. (2020), Consequences of Groundwater‐Model Vertical Discretization in Risk‐Based Decision‐Making. Groundwater, 58: 695-709. https://doi.org/10.1111/gwat.12957
  • White, J., Stengel, V., Rendon, S., and Banta, J.: The importance of parameterization when simulating the hydrologic response of vegetative land-cover change, Hydrol. Earth Syst. Sci., 21, 3975–3989, https://doi.org/10.5194/hess-21-3975-2017, 2017.
  • Hayley, K., Valenza, A., White, E., Hutchison, B., & Schumacher, J. (2019). Application of the iterative ensemble smoother method and cloud computing: A groundwater modeling case study. Water, 11(8), 1649.
  • Doble, R., Pickett, T., Janardhanan, S., Crosbie, R., & Gonzalez, D. (2020). Potential impacts on groundwater resources from conventional gas in the South East of SA.
  • Moridnejad, Maryam (2015) Sensitivity analysis of a one dimensional heat transport model in the Ngongotaha Stream, New Zealand. New Zealand hydrological society conference 2015, University of Waikato
  • Heywood, C. E., Kahle, S. C., Olsen, T. D., Patterson, J. D., & Burns, E. (2016). Simulation of groundwater storage changes in the eastern Pasco Basin, Washington (No. 2016-5026). US Geological Survey.
  • Heywood, C. E., Lindaman, M., & Lovelace, J. K. (2019). Simulation of groundwater flow and chloride transport in the “1,500-foot” sand,“2,400-foot” sand, and “2,800-foot” sand of the Baton Rouge area, Louisiana (No. 2019-5102). US Geological Survey.
  • Zhuang, C., Zhou, Z., Illman, W. A., Guo, Q., & Wang, J. (2017). Estimating hydraulic parameters of a heterogeneous aquitard using long-term multi-extensometer and groundwater level data. Hydrogeology Journal, 25(6), 1721-1732.
  • White, J. T., Connor, C. B., Connor, L., & Hasenaka, T. (2017). Efficient inversion and uncertainty quantification of a tephra fallout model. Journal of Geophysical Research: Solid Earth, 122(1), 281-294.
  • Wallis, I., Prommer, H., Berg, M., Siade, A. J., Sun, J., & Kipfer, R. (2020). The river–groundwater interface as a hotspot for arsenic release. Nature Geoscience, 13(4), 288-295.

Conference Proceedings

  • W Kitlasten, ED Morway, RG Niswonger, M Gardner Integrated Hydrology and Operations Models to Investigate Climate Scenarios in Carson Valley, Nevada, a Snowmelt Dominated Agricultural Basin AGU Fall Meeting Abstracts 2018, GC51J-0918 https://agu.confex.com/agu/fm18/prelim.cgi/Paper/467820