Journal of Geographical Sciences

, Volume 29, Issue 3, pp 465–479 | Cite as

A review of fully coupled atmosphere-hydrology simulations

  • Like Ning
  • Chesheng ZhanEmail author
  • Yong Luo
  • Yueling Wang
  • Liangmeizi Liu


The terrestrial hydrological process is an essential but weak link in global/regional climate models. In this paper, the development status, research hotspots and trends in coupled atmosphere-hydrology simulations are identified through a bibliometric analysis, and the challenges and opportunities in this field are reviewed and summarized. Most climate models adopt the one-dimensional (vertical) land surface parameterization, which does not include a detailed description of basin-scale hydrological processes, particularly the effects of human activities on the underlying surfaces. To understand the interaction mechanism between hydrological processes and climate change, a large number of studies focused on the climate feedback effects of hydrological processes at different spatio-temporal scales, mainly through the coupling of hydrological and climate models. The improvement of the parameterization of hydrological process and the development of large-scale hydrological model in land surface process model lay a foundation for terrestrial hydrological-climate coupling simulation, based on which, the study of terrestrial hydrological-climate coupling is evolving from the traditional unidirectional coupling research to the two-way coupling study of “climate-hydrology” feedback. However, studies of fully coupled atmosphere-hydrology simulations (also called atmosphere- hydrology two-way coupling) are far from mature. The main challenges associated with these studies are: improving the potential mismatch in hydrological models and climate models; improving the stability of coupled systems; developing an effective scale conversion scheme; perfecting the parameterization scheme; evaluating parameter uncertainties; developing effective methodology for model parameter transplanting; and improving the applicability of models and high/super-resolution simulation. Solving these problems and improving simulation accuracy are directions for future hydro-climate coupling simulation research.


land surface hydrology regional climate model fully coupled atmosphere-hydrology simulation water cycle research review 


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  1. Arnell N W, 1999. A simple water balance model for the simulation of streamflow over a large geographic domain. Journal of Hydrology, 217(3/4): 314–335.CrossRefGoogle Scholar
  2. Barnett T P, Pierce D W, Hidalgo H G et al., 2008. Human-induced changes in the hydrology of the western United States. Science, 319(5866): 1080–1083.CrossRefGoogle Scholar
  3. Bates B, Kundzewicz Z, Wu S, 2008. Climate change and water. Intergovernmental Panel on Climate Change Secretariat, Geneva.Google Scholar
  4. Benke K K, Lowell K E, Hamilton A J, 2008. Parameter uncertainty, sensitivity analysis and prediction error in a water-balance hydrological model. Mathematical and Computer Modelling, 47(11/12): 1134–1149.CrossRefGoogle Scholar
  5. Bergstrom S, Graham L P, 1998. On the scale problem in hydrological modelling. Journal of Hydrology, 211(1–4): 253–265.CrossRefGoogle Scholar
  6. Beven K, Cloke H, Pappenberger F et al., 2015. Hyperresolution information and hyperresolution ignorance in modelling the hydrology of the land surface. Science China–Earth Sciences, 58(1): 25–35.Google Scholar
  7. Beven K J, Cloke H L, 2012. Comment on “Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth’s terrestrial water” by Eric F. Wood et al. Water Resources Research, 48(1): W01801.Google Scholar
  8. Bierkens M F P, 2015. Global hydrology 2015: State, trends, and directions. Water Resources Research, 51(7): 4923–4947.CrossRefGoogle Scholar
  9. Bierkens M F P, Bell V A, Burek P et al., 2015. Hyper-resolution global hydrological modelling: What is next? “Everywhere and locally relevant”. Hydrological Processes, 29(2): 310–320.CrossRefGoogle Scholar
  10. Chen F, Xie Z H, 2010. Effects of interbasin water transfer on regional climate: A case study of the Middle Route of the South-to-North Water Transfer Project in China. Journal of Geophysical Research: Atmospheres, 115(D11): 112.CrossRefGoogle Scholar
  11. Chen Z Q R, Kavvas M L, Ohara N et al., 2011a. Coupled regional hydroclimate model and its application to the Tigris-Euphrates Basin. Journal of Hydrologic Engineering, 16(12): 1059–1070.CrossRefGoogle Scholar
  12. Chen Z Q R, Kavvas M L, Ohara N et al., 2011b. Impact of water resources utilization on the hydrology of mesopotamian marshlands. Journal of Hydrologic Engineering, 16(12): 1083–1092.CrossRefGoogle Scholar
  13. Chiew F H S, Kirono D G C, Kent D M et al., 2010. Comparison of runoff modelled using rainfall from different downscaling methods for historical and future climates. Journal of Hydrology, 387(1/2): 10–23.CrossRefGoogle Scholar
  14. Costa M H, Botta A, Cardille J A, 2003. Effects of large-scale changes in land cover on the discharge of the Tocantins River, Southeastern Amazonia. Journal of Hydrology, 283(1–4): 206–217.CrossRefGoogle Scholar
  15. Dai Y J, Zeng X B, Dickinson R E et al., 2003. The common land model. Bulletin of the American Meteorological Society, 84(8): 1013–1023.CrossRefGoogle Scholar
  16. Decker M, Zeng X B, 2009. Impact of modified richards equation on global soil moisture simulation in the Community Land Model (CLM3.5). Journal of Advances in Modeling Earth Systems, 1(3): 22.CrossRefGoogle Scholar
  17. Fiorentini M, Orlandini S, Paniconi C, 2015. Control of coupling mass balance error in a process-based numerical model of surface-subsurface flow interaction. Water Resources Research, 51(7): 5698–5716.CrossRefGoogle Scholar
  18. Foley J A, DeFries R, Asner G P et al., 2005. Global consequences of land use. Science, 309(5734): 570–574.CrossRefGoogle Scholar
  19. Gregersen J B, Gijsbers P J A, Westen S J P, 2007. OpenMI: Open modelling interface. Journal of Hydroinformatics, 9(3): 175–191.CrossRefGoogle Scholar
  20. Guo S, Liu C, 1997. Large scale hydrological models and its coupling with atmospheric models. Journal of Hydraulic Engineering, 7: 37–41. (in Chinese)Google Scholar
  21. Habets F, Noilhan J, Golaz C et al., 1999. The ISBA surface scheme in a macroscale hydrological model applied to the Hapex-Mobilhy area (Part II): Simulation of streamflows and annual water budget. Journal of Hydrology, 217(1/2): 97–118.CrossRefGoogle Scholar
  22. Haddeland I, Clark D B, Franssen W et al., 2011. Multimodel estimate of the global terrestrial water balance: Setup and first results. Journal of Hydrometeorology, 12(5): 869–884.CrossRefGoogle Scholar
  23. Haddeland I, Skaugen T, Lettenmaier D P, 2006. Anthropogenic impacts on continental surface water fluxes. Geophysical Research Letters, 33(8): L08406.CrossRefGoogle Scholar
  24. Hanasaki N, Kanae S, Oki T et al., 2008. An integrated model for the assessment of global water resources (Part 1): Model description and input meteorological forcing. Hydrology and Earth System Sciences, 12(4): 1007–1025.CrossRefGoogle Scholar
  25. Heuvelmans G, Muys B, Feyen J, 2004. Evaluation of hydrological model parameter transferability for simulating the impact of land use on catchment hydrology. Physics and Chemistry of the Earth, 29(11/12): 739–747.CrossRefGoogle Scholar
  26. IPCC, 2015. Climate Change 2014: Mitigation of Climate Change. Vol. 3. Cambridge: Cambridge University Press.Google Scholar
  27. Kavvas M L, Kure S, Chen Z Q et al., 2013. WEHY-HCM for modeling interactive atmospheric-hydrologic processes at watershed scale. I: Model description. Journal of Hydrologic Engineering, 18(10): 1262–1271.Google Scholar
  28. Kerandi N, Arnault J, Laux P et al., 2018. Joint atmospheric-terrestrial water balances for East Africa: A WRF-Hydro case study for the upper Tana River basin. Theoretical and Applied Climatology, 131(3): 1337–1355.CrossRefGoogle Scholar
  29. Kollet S J, Maxwell R M, 2008a. Capturing the influence of groundwater dynamics on land surface processes using an integrated, distributed watershed model. Water Resources Research, 44(2): W02402.CrossRefGoogle Scholar
  30. Kollet S J, Maxwell R M, 2008b. Demonstrating fractal scaling of baseflow residence time distributions using a fully-coupled groundwater and land surface model. Geophysical Research Letters, 35(7): L07402.CrossRefGoogle Scholar
  31. Kruk N S, Vendrame I F, Chou S C, 2013. Coupling a mesoscale atmospheric model with a distributed hydrological model applied to a watershed in Southeast Brazil. Journal of Hydrologic Engineering, 18(1): 58–65.CrossRefGoogle Scholar
  32. Landman W A, Kgatuke M J, Mbedzi M et al., 2009. Performance comparison of some dynamical and empirical downscaling methods for South Africa from a seasonal climate modelling perspective. International Journal of Climatology, 29(11): 1535–1549.CrossRefGoogle Scholar
  33. Larsen M A D, Refsgaard J C, Drews M et al., 2014. Results from a full coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model for a Danish catchment. Hydrology and Earth System Sciences, 18(11): 4733–4749.CrossRefGoogle Scholar
  34. Lawrence P J, Chase T N, 2010. Investigating the climate impacts of global land cover change in the community climate system model. International Journal of Climatology, 30(13): 2066–2087.CrossRefGoogle Scholar
  35. Li M X, Ma Z G, Lv M X, 2017. Variability of modeled runoff over China and its links to climate change. Climatic Change, 144(3): 433–445.CrossRefGoogle Scholar
  36. Liang X, Lettenmaier D P, Wood E F et al., 1994. A simple hydrologically based model of land-surface water and energy fluxes for general-circulation models. Journal of Geophysical Research-Atmospheres, 99(D7): 14415–14428.CrossRefGoogle Scholar
  37. Liang X, Wood E F, Lettenmaier D P et al., 1998. The Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) phase 2(c) Red-Arkansas River basin experiment: 2. Spatial and temporal analysis of energy fluxes. Global and Planetary Change, 19(1–4): 137–159.Google Scholar
  38. Liu C, Li D, Tian Y et al., 2003. An application study of dem based distributed hydrological model on macroscale watershed. Progress in Geography, 22(5): 437–445. (in Chinese)Google Scholar
  39. Liu Y, Weerts A H, Clark M et al., 2012. Advancing data assimilation in operational hydrologic forecasting: Progresses, challenges, and emerging opportunities. Hydrology and Earth System Sciences, 16(10): 3863–3887.CrossRefGoogle Scholar
  40. Livneh B, Xia Y L, Mitchell K E et al., 2010. Noah LSM snow model diagnostics and enhancements. Journal of Hydrometeorology, 11(3): 721–738.CrossRefGoogle Scholar
  41. Luo S Q, Lu S H, Zhang Y, 2009. Development and validation of the frozen soil parameterization scheme in Common Land Model. Cold Regions Science and Technology, 55(1): 130–140.CrossRefGoogle Scholar
  42. Manabe S, 1969. Climate and the ocean circulation: I. The atmospheric circulation and the hydrology of the earth’s surface. Monthly Weather Review, 97(11): 739–774.Google Scholar
  43. Maxwell R M, Lundquist J K, Mirocha J D et al., 2011. Development of a coupled groundwater-atmosphere model. Monthly Weather Review, 139(1): 96–116.CrossRefGoogle Scholar
  44. Maxwell R M, Miller N L, 2005. Development of a coupled land surface and groundwater model. Journal of Hydrometeorology, 6(3): 233–247.CrossRefGoogle Scholar
  45. Ning L K, Xia J, Zhan C S et al., 2016. Runoff of arid and semi-arid regions simulated and projected by CLM-DTVGM and its multi-scale fluctuations as revealed by EEMD analysis. Journal of Arid Land, 8(4): 506–520.CrossRefGoogle Scholar
  46. Niu G Y, Yang Z L, Dickinson R E et al., 2005. A simple TOPMODEL-based runoff parameterization (SIMTOP) for use in global climate models. Journal of Geophysical Research-Atmospheres, 110(D21): D21106.CrossRefGoogle Scholar
  47. Notter B, MacMillan L, Viviroli D et al., 2007. Impacts of environmental change on water resources in the Mt. Kenya region. Journal of Hydrology, 343(3/4): 266–278.Google Scholar
  48. Oleson K W, Lawrence D M, Gordon B et al., 2010. Technical description of version 4.0 of the Community Land Model (CLM).Google Scholar
  49. Oubeidillah A A, Kao S C, Ashfaq M et al., 2014. A large-scale, high-resolution hydrological model parameter data set for climate change impact assessment for the conterminous US. Hydrology and Earth System Sciences, 18(1): 67–84.CrossRefGoogle Scholar
  50. Patil S D, Stieglitz M, 2015. Comparing Spatial and temporal transferability of hydrological model parameters. Journal of Hydrology, 525: 409–417.CrossRefGoogle Scholar
  51. Peng T, Shen T, Gao Y et al., 2014. Research and application progress on basin hydro-meteorology coupling flood forecasting. Advances in Meteorological Science and Technology, 2(4): 52–58. (in Chinese)Google Scholar
  52. Pokhrel Y, Hanasaki N, Koirala S et al., 2012. Incorporating anthropogenic water regulation modules into a land surface model. Journal of Hydrometeorology, 13(1): 255–269.CrossRefGoogle Scholar
  53. Ragab R, Bromley J, 2010. IHMS-integrated hydrological modelling system. Part 1. Hydrological processes and general structure. Hydrological Processes, 24(19): 2663–2680.Google Scholar
  54. Sahoo A K, Dirmeyer P A, Houser P R et al., 2008. A study of land surface processes using land surface models over the Little River Experimental Watershed, Georgia. Journal of Geophysical Research: Atmospheres, 113(D20): D20121.CrossRefGoogle Scholar
  55. Salamon P, Feyen L, 2009. Assessing parameter, precipitation, and predictive uncertainty in a distributed hydrological model using sequential data assimilation with the particle filter. Journal of Hydrology, 376(3/4): 428–442.CrossRefGoogle Scholar
  56. Senatore A, Mendicino G, Gochis D J et al., 2015. Fully coupled atmosphere-hydrology simulations for the central Mediterranean: Impact of enhanced hydrological parameterization for short and long time scales. Journal of Advances in Modeling Earth Systems, 7(4): 1693–1715.CrossRefGoogle Scholar
  57. Seuffert G, Gross P, Simmer C et al., 2002. The influence of hydrologic modeling on the predicted local weather: Two-way coupling of a mesoscale weather prediction model and a land surface hydrologic model. Journal of Hydrometeorology, 3(5): 505–523.CrossRefGoogle Scholar
  58. Sheng M, Lei H, Jiao Y et al., 2017. Evaluation of the runoff and river routing schemes in the community land model of the Yellow River Basin. Journal of Advances in Modeling Earth Systems, 9(8): 2993–3018.CrossRefGoogle Scholar
  59. Shrestha P, Sulis M, Masbou M et al., 2014. A scale-consistent terrestrial systems modeling platform based on COSMO, CLM, and ParFlow. Monthly Weather Review, 142(9): 3466–3483.CrossRefGoogle Scholar
  60. Singh R S, Reager J T, Miller N L et al., 2015. Toward hyper-resolution land-surface modeling: The effects of fine-scale topography and soil texture on CLM4.0 simulations over the southwestern US. Water Resources Research, 51(4): 2648–2667.CrossRefGoogle Scholar
  61. Sood A, Smakhtin V, 2015. Global hydrological models: A review. Hydrological Sciences Journal-Journal Des Sciences Hydrologiques, 60(4): 549–565.CrossRefGoogle Scholar
  62. Su F, Hao Z, 2001. Review of land-surface hydrological processes parameterization. Advance in Earth Sciences, 16(6): 795–801. (in Chinese)Google Scholar
  63. Subin Z M, Riley W J, Mironov D, 2012. An improved lake model for climate simulations: Model structure, evaluation, and sensitivity analyses in CESM1. Journal of Advances in Modeling Earth Systems, 4(1): M02001.Google Scholar
  64. van Beek L P H, Wada Y, Bierkens M F P, 2011. Global monthly water stress: 1. Water balance and water availability. Water Resources Research, 47(7): W07517.Google Scholar
  65. van Dijk A I J M, Gash J H, van Gorsel E et al., 2015. Rainfall interception and the coupled surface water and energy balance. Agricultural and Forest Meteorology, 214/215: 402–415.CrossRefGoogle Scholar
  66. Vrettas M D, Fung I Y, 2015. Toward a new parameterization of hydraulic conductivity in climate models: Simulation of rapid groundwater fluctuations in Northern California. Journal of Advances in Modeling Earth Systems, 7(4): 2105–2135.CrossRefGoogle Scholar
  67. Wagner S, Fersch B, Yuan F et al., 2016. Fully coupled atmospheric-hydrological modeling at regional and long-term scales: Development, application, and analysis of WRF-HMS. Water Resources Research, 52(4): 3187–3211.CrossRefGoogle Scholar
  68. Wang C, Wang Y Y, Wang P F, 2006. Water Quality Modeling and Pollution Control for the Eastern Route of South to North Water Transfer Project in China. Journal of Hydrodynamics, 18(3): 253–261.CrossRefGoogle Scholar
  69. Wilby R L, Wigley T M L, 2000. Precipitation predictors for downscaling: Observed and general circulation model relationships. International Journal of Climatology, 20(6): 641–661.CrossRefGoogle Scholar
  70. Wood E F, Roundy J K, Troy T J et al., 2011. Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth’s terrestrial water. Water Resources Research, 47(5): W05301.CrossRefGoogle Scholar
  71. Xu Y, Gao X, Zhu Q et al., 2015. Coupling a regional climate model and a distributed hydrological model to assess future water resources in Jinhua River Basin, East China. Journal of Hydrologic Engineering, 20(4): 04014054.CrossRefGoogle Scholar
  72. Yang C, Lin Z, Hao Z et al., 2007. Revview of coupling atmospheric and hydrologic models. Advances in Earth Science, 22(8): 810–817. (in Chinese)Google Scholar
  73. Yong B, Ren L, Chen X et al., 2009. Development of a large-scale hydrological model TOPX and its coupling with regional integrated environment modeling system RIEMS. Chinese Journal of Geophysics, 52(8): 1954–1965. (in Chinese)Google Scholar
  74. Yong B, Zhang W, Liu C, 2006. Advances in the coupling study of hydrological models and land-surface models. Journal of Glaciology and Geocryology, 28(6): 961–970. (in Chinese)Google Scholar
  75. Yu F, Cao Y, 2008. Research progress summarization of the impacts of global climate change to the regional water resources. Journal of Water Resources and Water Engineering, 19(4): 92–97. (in Chinese)Google Scholar
  76. Yu Z B, Pollard D, Cheng L, 2006. On continental-scale hydrologic simulations with a coupled hydrologic model. Journal of Hydrology, 331(1/2): 110–124.CrossRefGoogle Scholar
  77. Zeng X M, Zhao M, Su B K et al., 2003. Simulations of a hydrological model as coupled to a regional climate model. Advances in Atmospheric Sciences, 20(2): 227–236.CrossRefGoogle Scholar
  78. Zou J, Xie Z H, Yu Y et al., 2014. Climatic responses to anthropogenic groundwater exploitation: A case study of the Haihe River Basin, Northern China. Climate Dynamics, 42(7/8): 2125–2145.CrossRefGoogle Scholar

Copyright information

© Science in China Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Like Ning
    • 1
    • 2
  • Chesheng Zhan
    • 3
    Email author
  • Yong Luo
    • 1
    • 2
  • Yueling Wang
    • 3
  • Liangmeizi Liu
    • 3
    • 4
  1. 1.Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System ScienceTsinghua UniversityBeijingChina
  2. 2.Joint Center for Global Change StudiesBeijingChina
  3. 3.Key Laboratory of Water Cycle and Related Land Surface ProcessesInstitute of Geographic Sciences and Natural Resources Research, CASBeijingChina
  4. 4.University of Chinese Academy of SciencesBeijingChina

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