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Computational Geosciences

, Volume 22, Issue 1, pp 163–177 | Cite as

An intermediate-scale model for thermal hydrology in low-relief permafrost-affected landscapes

  • Ahmad Jan
  • Ethan T. Coon
  • Scott L. Painter
  • Rao Garimella
  • J. David Moulton
Original Paper

Abstract

Integrated surface/subsurface models for simulating the thermal hydrology of permafrost-affected regions in a warming climate have recently become available, but computational demands of those new process-rich simu- lation tools have thus far limited their applications to one-dimensional or small two-dimensional simulations. We present a mixed-dimensional model structure for efficiently simulating surface/subsurface thermal hydrology in low-relief permafrost regions at watershed scales. The approach replaces a full three-dimensional system with a two-dimensional overland thermal hydrology system and a family of one-dimensional vertical columns, where each column represents a fully coupled surface/subsurface thermal hydrology system without lateral flow. The system is then operator split, sequentially updating the overland flow system without sources and the one-dimensional columns without lateral flows. We show that the app- roach is highly scalable, supports subcycling of different processes, and compares well with the corresponding fully three-dimensional representation at significantly less computational cost. Those advances enable recently developed representations of freezing soil physics to be coupled with thermal overland flow and surface energy balance at scales of 100s of meters. Although developed and demonstrated for permafrost thermal hydrology, the mixed-dimensional model structure is applicable to integrated surface/subsurface thermal hydrology in general.

Keywords

Multiscale models Permafrost thermal hydrology Integrated surface/subsurface flow modeling Arctic 

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References

  1. 1.
    Brown, J., Ferrians, Jr, O., Heginbottom, J., Melnikov, E.: Circum-Arctic map of permafrost and ground-ice conditions, pp. 45 (1997)Google Scholar
  2. 2.
    Jorgenson, M.T., Racine, C.H., Walters, J.C., Osterkamp, T.E.: Permafrost degradation and ecological changes associated with a warmingclimate in Central Alaska. Clim. Chang. 48, 551–579 (2001)CrossRefGoogle Scholar
  3. 3.
    Schuur, E.A.G., McGuire, A.D., Schaedel, C., Grosse, G., Harden, J.W., Hayes, D.J., Hugelius, G., Koven, C.D., Kuhry, P., Lawrence, D.M., Natali, S.M., Olefeldt, D., Romanovsky, V.E., Schaefer, K., Turetsky, M.R., Treat, C.C., Vonk, J.E.: Climate change and the permafrost carbon feedback. Nature 520, 171–179 (2015)CrossRefGoogle Scholar
  4. 4.
    Hugelius, G., Strauss, J., Zubrzycki, S., Harden, J.W., Schuur, E.A.G., Ping, C.-L. , Schirrmeister, L., Grosse, G., Michaelson, G.J., Koven, C.D., O’Donnell, J.A., Elberling, B., Mishra, U., Camill, P., Yu, Z., Palmtag, J., Kuhry, P.: Estimated stocks of circumpolar permafrost carbon with quantified uncertainty ranges and identified data gaps. Biogeosciences 11, 6573–6593 (2014)CrossRefGoogle Scholar
  5. 5.
    Turner, J., Overland, J.E., Walsh, J.E.: An arctic and antarctic perspective on recent climate change. Int. J. Climatol. 27, 277–293 (2007)CrossRefGoogle Scholar
  6. 6.
    Hansen, J., Ruedy, R., Glascoe, J., Sato, M.: Giss analysis of surface temperature change. J. Geophys. Res. Atmosph. 104, 30997–31022 (1999)CrossRefGoogle Scholar
  7. 7.
    Assessment, A.C.I.: Impacts of a Warming Arctic-Arctic Climate Impact Assessment, by Arctic Climate Impact Assessment, vol. 1, p 144. Cambridge University Press, Cambridge, UK (2004). ISBN 0521617782Google Scholar
  8. 8.
    Koven, C.D., Ringeval, B., Friedlingstein, P., Ciais, P., Cadule, P., Khvorostyanov, D., Krinner, G., Tarnocai, C.: Permafrost carbon-climate feedbacks accelerate global warming. Proc. Nat. Acad. Sci. 108, 14769–14774 (2011)CrossRefGoogle Scholar
  9. 9.
    Osterkamp, T.: Response of Alaskan permafrost to climate. In: Fourth International Conference on Permafrost, Fairbanks, Alaska, pp 17–22 (1983)Google Scholar
  10. 10.
    Walvoord, M.A., Striegl, R.G.: Increased groundwater to stream discharge from permafrost thawing in the Yukon River Basin: potential impacts on lateral export of carbon and nitrogen. Geophysical Research Letters, pp. 34 (2007)Google Scholar
  11. 11.
    Lyon, S., Destouni, G., Giesler, R., Humborg, C., Mörth, C.-M. , Seibert, J. , Karlsson, J., Troch, P.: Estimation of permafrost thawing rates in a sub-arctic catchment using recession flow analysis. Hydrol. Earth Syst. Sci. 13, 595–604 (2009)CrossRefGoogle Scholar
  12. 12.
    Pachauri, R.K., Allen, M., Barros, V., Broome, J., Cramer, W., Christ, R., Church, J., Clarke, L., Dahe, Q., Dasgupta, P., et al.: Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (2014)Google Scholar
  13. 13.
    Koven, C.D., Riley, W.J., Stern, A.: Analysis of permafrost thermal dynamics and response to climate change in the CMIP5 Earth System Models. J. Clim. 26, 1877–1900 (2013)CrossRefGoogle Scholar
  14. 14.
    Painter, S., Moulton, J., Wilson, C.: Modeling challenges for predicting hydrologic response to degrading permafrost. Hydrogeology Journal, pp. 1–4Google Scholar
  15. 15.
    Kurylyk, B.L., MacQuarrie, K.T., McKenzie, J.M.: Climate change impacts on groundwater and soil temperatures in cold and temperate regions: implications, mathematical theory, and emerging simulation tools. Earth-Sci. Rev. 138, 313–334 (2014)CrossRefGoogle Scholar
  16. 16.
    Harlan, R.: Analysis of coupled heat-fluid transport in partially frozen soil. Water Resour. Res. 9, 1314–1323 (1973)CrossRefGoogle Scholar
  17. 17.
    Guymon, G.L., Luthin, J.N.: A coupled heat and moisture transport model for arctic soils. Water Resour. Res. 10, 995–1001 (1974)CrossRefGoogle Scholar
  18. 18.
    Taylor, G.S., Luthin, J.N.: A model for coupled heat and moisture transfer during soil freezing. Can. Geotechn. J. 15, 548–555 (1978)CrossRefGoogle Scholar
  19. 19.
    Takata, K., Emori, S., Watanabe, T.: Development of the minimal advanced treatments of surface interaction and runoff. Glob. Planet. Chang. 38, 209–222 (2003)CrossRefGoogle Scholar
  20. 20.
    Nicolsky, D., Romanovsky, V., Alexeev, V., Lawrence, D.: Improved modeling of permafrost dynamics in a GCM land-surface scheme. Geophysical research letters, pp. 34 (2007)Google Scholar
  21. 21.
    Lawrence, D.M., Slater, A.G., Swenson, S.C.: Simulation of present-day and future permafrost and seasonally frozen ground conditions in CCSM4. J. Clim. 25, 2207–2225 (2012)CrossRefGoogle Scholar
  22. 22.
    McKenzie, J.M., Voss, C.I., Siegel, D.I.: Groundwater flow with energy transport and water–ice phase change: numerical simulations, benchmarks, and application to freezing in peat bogs. Adv. water Resour. 30, 966–983 (2007)CrossRefGoogle Scholar
  23. 23.
    Bense, V., Ferguson, G., Kooi, H.: Evolution of shallow groundwater flow systems in areas of degrading permafrost, Geophysical Research Letters, pp. 36 (2009)Google Scholar
  24. 24.
    Painter, S.L., Karra, S.: Constitutive model for unfrozen water content in subfreezing unsaturated soils, Vadose Zone Journal, pp. 13 (2014)Google Scholar
  25. 25.
    Painter, S.L.: Three-phase numerical model of water migration in partially frozen geological media: model formulation, validation, and applications. Comput. Geosci. 15, 69–85 (2011)CrossRefGoogle Scholar
  26. 26.
    Grimm, R.E., Painter, S.L.: On the secular evolution of groundwater on Mars. Geophys. Res. Lett. 36, n/a–n/a (2009). L24803CrossRefGoogle Scholar
  27. 27.
    Frampton, A., Painter, S., Lyon, S.W., Destouni, G.: Non-isothermal, three-phase simulations of near-surface flows in a model permafrost system under seasonal variability and climate change. J. Hydrol. 403, 352 – 359 (2011)CrossRefGoogle Scholar
  28. 28.
    Karra, S., Painter, S., Lichtner, P.: Three-phase numerical model for subsurface hydrology in permafrost-affected regions. Cryosphere Discuss 8, 149–185 (2014)CrossRefGoogle Scholar
  29. 29.
    Lichtner, P.C., Hammond, G.E., Lu, C., Karra, S., Bisht, G., Andre, B., Mills, R.T., Kumar, J.: PFLOTRAN Web page. http://www.pflotran.org (2013)
  30. 30.
    Kumar, J., Collier, N., Bisht, G., Mills, R.T., Thornton, P.E., Iversen, C.M., Romanovsky, V.: Modeling the spatiotemporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape. Cryosphere 10, 2241–2274 (2016)CrossRefGoogle Scholar
  31. 31.
    Painter, S.L., Coon, E.T., Atchley, A.L., Berndt, M., Garimella, R., Moulton, J.D., Svyatskiy, D., Wilson, C.J.: Integrated surface/subsurface permafrost thermal hydrology: model formulation and proof-of-concept simulations. Water Resour. Res. 52, 6062–6077 (2016)CrossRefGoogle Scholar
  32. 32.
    Coon, E.T., Moulton, J.D., Painter, S.L.: Managing complexity in simulations of land surface and near-surface processes. Environ. Modell. Softw. 78, 134–149 (2016)CrossRefGoogle Scholar
  33. 33.
    Dall’Amico, M., Endrizzi, S., Gruber, S., Rigon, R.: A robust and energy-conserving model of freezing variably-saturated soil. Cryosphere 5, 469–484 (2011)CrossRefGoogle Scholar
  34. 34.
    Pikul, M.F., Street, R.L., Remson, I.: A numerical model based on coupled one-dimensional Richards and Boussinesq equations. Water Resour. Res. 10, 295–302 (1974)CrossRefGoogle Scholar
  35. 35.
    Zhu, Y., Zha, Y., Tong, J., Yang, J.: Method of coupling 1-D unsaturated flow with 3-D saturated flow on large scale. Water Sci. Eng. 4, 357–373 (2011)Google Scholar
  36. 36.
    Hazenberg, P., Fang, Y., Broxton, P., Gochis, D., Niu, G.-Y. , Pelletier, J.D., Troch, P.A., Zeng, X.: A hybrid-3D hillslope hydrological model for use in earth system models. Water Resour. Res. 51, 8218–8239 (2015)CrossRefGoogle Scholar
  37. 37.
    Coon, E.T.: ATS: The Advanced Terrestrial Simulator. http://github.com/amanzi/ats (2016)
  38. 38.
    Moulton, J.D., Berndt, M., Garimella, R., Prichett-Sheats, L., Hammond, G., Day, M., Meza, J.: High-level design of Amanzi, the multi-process high performance computing simulator, Office of Environmental Management, United States Department of Energy, Washington DC (2012)Google Scholar
  39. 39.
    Heroux, M., Bartlett, R., Hoekstra, V.H., Hu, J., Kolda, T., Lehoucq, R., Long, K., Pawlowski, R., Phipps, E., Salinger, A., Thornquist, H., Tuminaro, R., Wil-lenbring, J., Williams, A.: An overview of trilinos. Technical report sand2003-2927, Sandia National Laboratory (2003)Google Scholar
  40. 40.
    Garimella, R.V., Perkins, W.A., Buksas, M.W., Berndt, M., Lipnikov, K., Coon, E., Moulton, J.D., Painter, S.L.: Mesh infrastructure for coupled multiprocess geophysical simulations. Procedia Engineering 82, 34 – 45 (2014)CrossRefGoogle Scholar
  41. 41.
    Da Veiga, L.B., Lipnikov, K., Manzini, G.: The mimetic finite difference method for elliptic problems, vol. 11, Springer (2014)Google Scholar
  42. 42.
    Lipnikov, K., Manzini, G., Shashkov, M.: Mimetic finite difference method. J. Comput. Phys. 257, 1163–1227 (2014)CrossRefGoogle Scholar
  43. 43.
    Calef, M.T., Fichtl, E.D., Warsa, J.S., Berndt, M., Carlson, N.N.: Nonlinear Krylov acceleration applied to a discrete ordinates formulation of the k-eigenvalue problem. J. Comput. Phys. 238, 188–209 (2013)CrossRefGoogle Scholar
  44. 44.
    Carlson, N.N., Miller, K.: Design and application of a gradient-weighted moving finite element code I: in one dimension. SIAM J. Sci. Comput. 19, 728–765 (1998)CrossRefGoogle Scholar
  45. 45.
    Atchley, A.L., Painter, S.L., Harp, D.R., Coon, E.T., Wilson, C.J., Liljedahl, A.K., Romanovsky, V.E.: Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83). Geosci. Model Develop. 8, 2701–2722 (2015)CrossRefGoogle Scholar
  46. 46.
    Atchley, A.L., Coon, E.T., Painter, S.L., Harp, D.R., Wilson, C.J.: Influences and interactions of inundation, peat, and snow on active layer thickness. Geophys. Res. Lett. 43, 5116–5123 (2016). 2016GL068550CrossRefGoogle Scholar
  47. 47.
    Lawrence Livermore National Laboratory, A mesh and field I/O library and scientific database. https://wci.llnl.gov/simulation/computer-codes/silo (2016)
  48. 48.
    Jorgenson, M.T., Shur, Y.L., Pullman, E.R.: Abrupt increase in permafrost degradation in Arctic Alaska, Geophysical Research Letters, pp. 33 (2006)Google Scholar
  49. 49.
    Liljedahl, A., Hinzman, L., Schulla, J.: Ice-wedge polygon type controls low-gradient watershed-scale hydrology. In: Proceedings of the Tenth International Conference on Permafrost, vol. 1, pp 231–236 (2012)Google Scholar
  50. 50.
    Hinzman, L.D., Bettez, N.D., Bolton, W.R., Chapin, F.S., Dyurgerov, M.B., Fastie, C.L. , Griffith, B., Hollister, R.D., Hope, A., Huntington, H.P., et al.: Evidence and implications of recent climate change in Northern Alaska and other Arctic regions. Clim. Chang. 72, 251–298 (2005)CrossRefGoogle Scholar
  51. 51.
    Rowland, J.C., Jones, C.E., Altmannm, G., Bryan, R., Crosby, B.T., Hinzman, L.D., Kane, D.L., Lawrence, D.M., Mancino, A., Marsh, P., McNamara, J.P., Romanvosky, V.E., Toniolo, H., Travis, B.J., Trochim, E., Wilson, C.J., Geernaert, G.L.: Arctic landscapes in transition: responses to thawing permafrost. Eos, Trans. Amer. Geophys Union 91, 229–230 (2010)CrossRefGoogle Scholar

Copyright information

© US Government (outside the USA) 2017

Authors and Affiliations

  1. 1.Climate Change Science Institute and Environmental Sciences DivisionOak Ridge National LaboratoryOak RidgeUSA
  2. 2.Computational Earth Sciences Group, Earth and Environmental Sciences DivisionLos Alamos National LaboratoryLos AlamosUSA
  3. 3.Applied Mathematics and Plasma Physics Group, Theoretical DivisionLos Alamos National LaboratoryLos AlamosUSA

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