(*denotes advisee author)
28. Anurag*, H., & Ng, G. H. C. (2022). Assessing future climate change impacts on groundwater recharge in Minnesota. Journal of Hydrology, 612, 128112.
27. Zhi, W., Shi, Y., Wen, H., Saberi*, L., Ng, G. H. C., Sadayappan, K., Kerins, D., Stewart, B., & Li, L. (2022). BioRT-Flux-PIHM v1.0: A biogeochemical reactive transport model at the watershed scale. Geoscientific Model Development, 15(1), 315–333. https://doi.org/10.5194/gmd-15-315-2022
26. Anurag*, H., Ng, G. H. C., Tipping, R., & Tokos*, K. (2021). Modeling the impact of spatiotemporal vegetation dynamics on groundwater recharge. Journal of Hydrology, 601, 126584. https://doi.org/10.1016/j.jhydrol.2021.126584
25. Liu*, S., & Ng, G. H. C. (2021). Assessing the Spatiotemporal Variability of Leaf Functional Traits and Their Drivers Across Multiple Amazon Evergreen Forest Sites: A Stochastic Parameterization Approach With Land-Surface Modeling. Journal of Geophysical Research: Biogeosciences, 126(6), 1–19. https://doi.org/10.1029/2020JG006228
24. Ziegler, B. A., Ng, G.-H. C., Cozzarelli, I. M., Dunshee*, A. J., & Schreiber, M. E. (2021). Arsenic in Petroleum-Contaminated Groundwater near Bemidji, Minnesota Is Predicted to Persist for Centuries. Water, 13(11), 1485. https://doi.org/10.3390/w13111485
23. Saberi*, L., G.-H.C. Ng, L. Nelson*, W. Zhi, L. Li, J. La Frenierre, M. Johnstone* (in press), Spatiotemporal Drivers of Hydrochemical Variability in a Tropical Glacierized Watershed in the Andes, Water Resources Research.
22. McEachran, Z.P., D. L. Karwan, S.D. Sebestyen, R.A. Slesak, and G.-H. C. Ng (2021). Nonstationary flood-frequency analysis to assess effects of harvest and cover type conversion on peak flows at the Marcell Experimental Forest, Minnesota, USA. Journal of Hydrology, 596(February), 126054. https://doi.org/10.1016/j.jhydrol.2021.126054
21. Matson*, L., G.-H. C. Ng, M. Dockry, M. Nyblade*, H.J. King, M. Bellcourt, J. Bloomquist, P. Bunting, E. Chapman, D. Dalbotten, M.A. Davenport, K. Diver, M. Duquain, W. Graveen, K. Hagsten, K. Hedin, S. Howard*, T. Howes, J. Johnson, … A. Waheed* (2021). Transforming research and relationships through collaborative tribal-university partnerships on Manoomin (wild rice), Environmental Science and Policy, 115, 108–115. https://doi.org/10.1016/j.envsci.2020.10.010
20. Feng, X., M. J. Deventer, R. Lonchar, G.-H.C. Ng, S.D. Sebestyen, D.T. Roman, T.J. Griffis, D.B. Millet, & R.K. Kolka (2020). Climate Sensitivity of Peatland Methane Emissions Mediated by Seasonal Hydrologic Dynamics. Geophysical Research Letters, 47(17), 1–9. https://doi.org/10.1029/2020GL088875.
19. Liu*, S. and G.-H. C. Ng (2020). The role of spatiotemporal plant trait variability in model predictions of ecohydrological responses to climate change in a desert shrubland. Journal of Hydrology, 588(March), 125088. https://doi.org/10.1016/j.jhydrol.2020.125088
18. Ng, G.-H.C., C. Rosenfeld, C. Santelli, A.R. Yourd*, J. Lange*, K. Duhn, and N.W. Johnson (2020), Microbial and Reactive Transport Modeling Evidence for Hyporheic Flux-Driven Cryptic Sulfur Cycling and Anaerobic Methane Oxidation in a Sulfate-Impacted Wetland-Stream System, Journal of Geophysical Research – Biogeosciences, doi:10.1029/2019JG005185.
17. Somers, L.D., J.M. McKenzie, B.G. Mark, P. Lagos, G.-H.C. Ng, A.D. Wickert, C. Yarleque, M. Baraër, Y. Silva (2019), Climate impacts on Andean water resources using a mountain systems approach, Geophysical Research Letters, doi:10.1029/2019GL084730.
16. Liu*, S. and G.-H. C. Ng (2019), A data-conditioned stochastic parameterization of temporal plant trait variability in an ecohydrological model and the potential for plasticity, Agricultural and Forest Meteorology.
15. Wickert, A. D., C. T. Sandell, B. Schulz, and G.-H. C. Ng (2019), Open-source Arduino-derived data loggers designed for field research, Hydrology and Earth System Sciences, 23, 2065-2076, https://doi.org/10.5194/hess-23-2065-2019.
14. Saberi*, L., R.T. McLaughlin*, G.-H.C. Ng, J. La Frenierre, A.D. Wickert, M. Baraer, W. Zhi, L. Li, and B.G. Mark (2019), Multi-scale temporal variability in meltwater contributions in a tropical glacierized watershed, Hydrology and Earth System Sciences, 23, 405-425, https://doi.org/10.5194/hess-23-405-2019.
13. Ng, G.-H.C., A.D. Wickert, L.D. Somers, L. Saberi*, C. Cronkite-Ratcliff, R.G. Niswonger, and J.M. McKenzie (2018), GSFLOW–GRASS v1.0.0: GIS-enabled hydrologic modeling of coupled groundwater–surface-water systems, Geoscientific Model Development, 11, 4755-4777, https://doi.org/10.5194/gmd-11-4755-2018.
12. Ng, G.-H.C., A.R. Yourd*, N.W. Johnson, A.E. Myrbo (2017), Modeling hydrologic controls on sulfur processes in sulfate-impacted wetland and stream sediments, Journal of Geophysical Research – Biogeosciences, doi: 10.1002/2017JG003822.
11. Ziegler, B.A., M.E. Schreiber, I.M. Cozzarelli, and G.-H.C. Ng (2017), A mass balance approach to investigate arsenic cycling in a petroleum plume, Environmental Pollution, doi: 10.1016/j.envpol.2017.08.110
10. Kent, D.B., Blondes, M.S., Cozzarelli, I.M., Geboy, N., LeBlanc, D.R., Ng, G.H., Repert, D. and Smith, R.L. (2016), Sewage disposal, petroleum spills, eutrophic lakes, and wastewater from oil and gas production: Potential drivers of arsenic mobilization in the sub-surface. In Arsenic Research and Global Sustainability: Proceedings of the Sixth International Congress on Arsenic in the Environment (As2016), June 19-23, 2016, Stockholm, Sweden (p. 25). CRC Press.
9. Ng, G.-H.C., D. Bedford, and D. Miller (2015), Identifying multiple timescale rainfall controls on Mojave Desert ecohydrology using an integrated data and modeling approach for Larrea tridentata, Water Resources Research, doi: 10.1002/2015WR017240.
8. Ng, G.-H.C., B.A. Bekins, I. Cozzarelli, M.J. Baedecker, P.C. Bennett, R.T. Amos, and W.N. Herkelrath (2015), Reactive Transport Modeling of Geochemical Controls on Secondary Water Quality Impacts at a Crude Oil Spill Site near Bemidji, MN, Water Resources Research, doi: 10.1002/2015WR016964.
7. Ng, G.-H.C., B.A. Bekins, I. Cozzarelli, M.J. Baedecker, P.C. Bennett, and R.T. Amos (2014), A Mass balance approach to investigating geochemical controls on secondary water quality impacts at a Crude Oil Spill Site near Bemidji, MN, Journal of Contaminant Hydrology, 164, doi: 10.1016/j.jconhyd.2014.04.006.
6. Ng, G.-H.C., D. Bedford, and D. Miller (2014), Development of a mechanistic model and data assimilation framework for assessing desert ecohydrology, Water Resources Research, doi: 10.1002/2014WR015281.
5. Miller, D.M., Ng, G-H.C., and Maher, K. (2014), Improving paleoecology studies for future predictions—Role of spatial and temporal scales for understanding ecology of the arid and semiarid landscape of the Southwest: U.S. Geological Survey Open-File Report 2014–1029, 25 p., http://dx.doi.org/10.3133/ofr20141029
4. Ng, G.-H.C., D. McLaughlin, D. Entekhabi, and A. Ahanin (2011), The role of model dynamics in EnKF performance for chaotic systems, Tellus A, 63(5), doi: 1600-0870.2011.00539.
3. Ng, G.-H.C., D. McLaughlin, D. Entekhabi, and B. R. Scanlon (2010), Probabilistic Analysis of the Effects of Climate Change on Groundwater Recharge, Water Resources Research, 46, W07502, doi:10.1029/2009WR007831.
2. Ng, G.-H.C., D. McLaughlin, D. Entekhabi, and B. Scanlon (2009), Using data assimilation to identify diffuse recharge mechanisms from chemical and physical data in the unsaturated zone, Water Resources Research, 45, W09409, doi:10.1029/2009WR007831.
1. Y. Zhou, D. McLaughlin, D. Entekhabi, and G.C. Ng (2008), An ensemble multiscale filter for large nonlinear data assimilation problems, Monthly Weather Review, 136, 678-698.