Climate Dynamics

, Volume 29, Issue 1, pp 21–37 | Cite as

Global validation of the ISBA sub-grid hydrology

  • B. DecharmeEmail author
  • H. DouvilleEmail author


Over recent years, many numerical studies have suggested that the land surface hydrology contributes to atmospheric variability and predictability on a wide range of scales. Conversely, land surface models (LSMs) have been also used to study the hydrological impacts of seasonal climate anomalies and of global warming. Validating these models at the global scale is therefore a crucial task, which requires off-line simulations driven by realistic atmospheric fluxes to avoid the systematic biases commonly found in the atmospheric models. The present study is aimed at validating a new land surface hydrology within the ISBA LSM. Global simulations are conducted at a 1° by 1° horizontal resolution using 3-hourly atmospheric forcings provided by the Global Soil Wetness Project. Compared to the original scheme, the new hydrology includes a comprehensive and consistent set of sub-grid parametrizations in order to account for spatial heterogeneities of topography, vegetation, and precipitation within each grid cell. The simulated runoff is converted into river discharge using the total runoff integrating pathways (TRIP) river routing model (RRM), and compared with available monthly observations at 80 gauging stations distributed over the world’s largest river basins. The simulated discharges are also compared with parallel global simulations from five alternative LSMs. Globally, the new sub-grid hydrology performs better than the original ISBA scheme. Nevertheless, the improvement is not so clear in the high-latitude river basins (i.e. Ob, MacKenzie), which can be explained by a too late snow melt in the ISBA model. Over specific basins (i.e. Parana, Niger), the quality of the simulated discharge is also limited by the TRIP RRM, which does not account for the occurrence of seasonal floodplains and for their significant impact on the basin-scale water budget.


Freeze Soil Total Runoff Topographic Index Variable Infiltration Capacity Global Precipitation Climatology Centre 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to thank all their colleagues at Météo-France/CNRM that have participated in the development of this study. Thanks are also due to A. Boone for his useful comments on the multi-layer snow scheme as well as to anonymous reviewers for their constructive comments. Finally, we wish to thank P.-E. Decharme for his supports. This work was supported by Météo-France/CNRM and by the ACI “Observation de la Terre” of the French Research Ministry.


  1. Alsdorf DE, Lettenmaier DP (2003) Tracking fresh water from space. Science 301:1485–1488CrossRefGoogle Scholar
  2. Arora VK, Boer GJ (1999) A variable velocity flow routing algorithm for GCMs. J Geophys Res 104:30965–30979CrossRefGoogle Scholar
  3. Beljaars ACM, Viterbo P, Miller MJ (1996) The anomalous rainfall over the United States during July 1993: sensitivity to land surface parametrization and soil moisture anomalies. Mon Weather Rev 124:739–805CrossRefGoogle Scholar
  4. Beven KJ, Kirkby MJ (1979) A physically-based variable contributing area model of basin hydrology. Hydrol Sci Bull 24:43–69CrossRefGoogle Scholar
  5. Boone A, Etchevers P (2001) An intercomparison of three snow scheme of varying complexity coupled to the same land surface model: local-scale evaluation at an alpine site. J Hydrometeorol 2:374–394CrossRefGoogle Scholar
  6. Boone A, Calvet JC, Noilhan J (1999) Inclusion of a third soil layer in a land surface scheme using the force-restore method. J Appl Meteorol 38:1611–1630CrossRefGoogle Scholar
  7. Boone A, Masson V, Meyers T, Noilhan J (2000) The influence of the inclusion of soil freezing on simulation by a soil-atmosphere-transfer scheme. J Appl Meteorol 9:1544–1569CrossRefGoogle Scholar
  8. Boone A, et al (2004) The Rhône-aggregation land surface scheme intercomparison project: an overview. J Clim 17:187–208CrossRefGoogle Scholar
  9. Chapelon N, Douville H, Kosuth P, Oki T (2002) Off-line simulation of the Amazon water balance: a sensitivity study with implications for GSWP. Clim Dyn 19:141–154CrossRefGoogle Scholar
  10. Deardorff JW (1977) A parametrization of ground-surface moisture content for use in atmospheric prediction model. J Appl Meteorol 16:1182–1185CrossRefGoogle Scholar
  11. Deardorff JW (1978) Efficient prediction of ground surface temperature and moisture with inclusion of a layer of vegetation. J Geophys Res 20:1889–1903Google Scholar
  12. Decharme B, Douville H (2006a) Introduction of a sub-grid hydrology in the ISBA land surface model. Clim Dyn 26:65–78CrossRefGoogle Scholar
  13. Decharme B, Douville H (2006b) Uncertainties in the GSWP-2 precipitation forcing and their impacts on regional and global hydrological simulations. Clim Dyn 27:695–713CrossRefGoogle Scholar
  14. Decharme B, Douville H, Boone A, Habets F, Noilhan J (2006) Impact of an exponential profile of saturated hydraulic conductivity within the ISBA LSM: simulations over the Rhône basin. J Hydrometeorol 7:61–80CrossRefGoogle Scholar
  15. Delire C, Calvet JC, Noilhan J, Wright I, Manzi A, Nobre C (1997) Physical properties of Amazonian soils: a modeling study using the Anglo-Brazilian Amazonian Climate Observation Study data. J Geophys Res 102:30119–30134CrossRefGoogle Scholar
  16. Dirmeyer PA (2000) Using a global soil wetness dataset to improve seasonal climate simulation. J Clim 13:2900–2922CrossRefGoogle Scholar
  17. Dirmeyer PA (2001) An evaluation of the strength of land–atmosphere coupling. J Hydrometeorol 2:329–344CrossRefGoogle Scholar
  18. Dirmeyer PA, Zeng FJ (1999) Precipitation infiltration in the simplified SiB land surface scheme. J Meteorol Soc Jpn 77:291–303Google Scholar
  19. Dirmeyer PA, Dolman AJ, Sato N (1999) The Global Soil Wetness Project: a pilot project for global land surface modeling and validation. Bull Am Meteorol Soc 80:851–878CrossRefGoogle Scholar
  20. Dirmeyer PA, Gao X, Oki T (2002) The Second Global Soil Wetness Project GSWP2: science and implementation plan. IGPO Publication Series 37, International GEWEX Project Office, pp 65Google Scholar
  21. Dirmeyer PA, Gao X, Zhao M, Guo Z, Oki T, Hanasaki N (2006) The Second Global Soil Wetness Project (GSWP-2): multi-model analysis and implications for our perception of the land surface. Bull Am Meteorol Soc 87:1381–1397CrossRefGoogle Scholar
  22. Dolman AJ, Gregory D (1992) A parameterization of rainfall interception in GCMs. Q J R Meteorol Soc 118:455–467CrossRefGoogle Scholar
  23. Douville H (2002) Influence of soil moisture on the Asian and African monsoons. Part II: interannual variability. J Clim 15:701–720CrossRefGoogle Scholar
  24. Douville H (2003) Assessing the influence of soil moisture on seasonal climate variability with AGCMs. J Hydrometeorol 4:1044–1066CrossRefGoogle Scholar
  25. Douville H, Royer JF, Mahfouf JF (1995) A new snow parameterization for the Météo-France climate model. Part I: validation in stand-alone experiments. Clim Dyn 12:21–35CrossRefGoogle Scholar
  26. Douville H, Planton S, Royer JF, Stephenson DB, Tyteca S, Kergoat L, Lafont S, Betts RA (2000a) Importance of vegetation feedbacks in doubled-CO2 time-slice experiments. J Geophys Res 105:14841–14861CrossRefGoogle Scholar
  27. Douville H, Royer JF, Polcher J, Cox P, Gedney N, Stephenson DB, Valdes P (2000b) Impact of CO2 doubling on the Asian summer monsoon: robust versus model-dependent responses. J Meteorol Soc Japan 78:421–439Google Scholar
  28. Douville H, Chauvin F, Broqua H (2001) Influence of soil moisture on the Asian and African monsoons. Part I: mean monsoon and daily precipitation. J Clim 14:2381–2403CrossRefGoogle Scholar
  29. Ducharne A, Koster DR, Suarez MJ, Stieglitz M, Kumar P (2000) A catchment-based approach to modeling land surface process in a general circulation model: 2. Parameter estimation and model demonstration. J Geophys Res 105:24823–24838CrossRefGoogle Scholar
  30. Dümenil L, Todini E (1992) A rainfall-runoff scheme for use in the Hamburg climate model. Adv Theor Hydrol 9:129–157Google Scholar
  31. Ek MB, Mitchell KE, Lin Y, Grunmann P, Rogers E, Gayno G, Koren V, Tarpley JD (2003) Implementation of the upgraded Noah land-surface model in the NCEP operational mesoscale Eta model. J Geophys Res 108:8851. DOI 10.1029/2002JD003296Google Scholar
  32. Entekhabi D, Eagleson PS (1989) Land surface hydrology parameterization for atmospheric general circulation models including subgrid spatial variability. J Clim 2:816–831CrossRefGoogle Scholar
  33. Entin JK, Robock A, Vinnikov KY, Zabelin V, Liu S, Namkhai A (1999) Evaluation of Global Soil Wetness Project soil moisture simulations. J Meteorol Soc Jpn 77:183–198Google Scholar
  34. Essery RL, Best MJ, Betts A, Cox PM, Taylor CM (2003) Explicit representation of subgrid heterogeneity in a GCM land surface scheme. J Hydrometeorol 4:530–543CrossRefGoogle Scholar
  35. Etchevers P, Colaz C, Habets F (2001) Simulation of the water budget and the rivers flows of the Rhône basin from 1981 to 1994. J Hydrol 244:60–85CrossRefGoogle Scholar
  36. Fan Y, Wood EF, Baeck ML, Smith JA (1996) The fractional coverage of rainfall over a grid: analyses of NEXRAD data over the southern plains. Water Resour Res 32:2787–2802CrossRefGoogle Scholar
  37. Fekete BM, Vörösmarty CJ, Road JO, Willmott CJ (2003) Uncertainties in precipitation and their impacts on runoff estimates. J Clim 17:294–304CrossRefGoogle Scholar
  38. Gedney N, Cox PM (2003) The sensitivity of global climate model simulations to the representation of soil moisture heterogeneity. J Hydrometeorol 4:1265–1275CrossRefGoogle Scholar
  39. Gedney N, Cox PM, Douville H, Polcher J, Valdes PJ (2000) Characterising GCM land surface schemes to understand their responses to climate change. J Clim 13:3066–3079CrossRefGoogle Scholar
  40. Grippa M, Mognard NM, Letoan T, Josberger EG (2004) Siberia snow depth climatology from SSM/I data using a combined dynamic and static algorithm. Remote Sens Environ 93:30–41CrossRefGoogle Scholar
  41. Gusev YM, Nasonova ON (2003) The simulation of heat and water exchange in the boreal spruce forest by the land-surface model SWAP. J Hydrol 280:162–191CrossRefGoogle Scholar
  42. Habets F, Saulnier GM (2001) Subgrid runoff parameterization. Phys Chem Earth 26:455–459Google Scholar
  43. Habets F, Noilhan J, Golaz C, Goutorbe JP, Lacarrère P, Leblois E, Ledoux E, Martin E, Ottlé C, Vidal-Madjar D (1999a) The ISBA surface scheme in a macroscale hydrological model applied to the HAPEX-MOBILHY area. Part I: model and database. J Hydrol 217:75–96CrossRefGoogle Scholar
  44. Habets F, Etchevers P, Golaz C, Leblois E, Ledoux E, Martin E, Noilhan J, Ottlé C (1999b) Simulation of the water budget and the river flows of the Rhône basin. J Geophys Res 104:31145–31172CrossRefGoogle Scholar
  45. Koster DR, Suarez MJ (1992) Modeling the land surface boundary in climate models as a composite of independent vegetation stands. J Geophys Res 97:2697–2715Google Scholar
  46. Koster DR, Suarez MJ, Heiser M (2000a) Variability and predictability of precipitation at seasonal to interannual time-scales. J Hydrometeorol 1:26–46CrossRefGoogle Scholar
  47. Koster DR, Suarez MJ, Ducharne A, Stieglitz M, Kumar P (2000b) A catchment-based approach to modeling land surface process in a general circulation model: 1. Model structure. J Geophys Res 105:24809–24822CrossRefGoogle Scholar
  48. Koster DR, Dirmeyer PA, Hahmann AN, Ijpelaar R, Tyahla L, Cox P, Suarez MJ (2002) Comparing the degree of land–atmosphere interaction in four atmospheric general circulation model. J Hydrometeorol 3:363–375CrossRefGoogle Scholar
  49. Liang X, Lettenmaier DP, Wood EF, Burges SJ (1994) A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J Geophys Res 99:14415–14428CrossRefGoogle Scholar
  50. Lohmann D, et al (1998) The project for intercomparison of land-surface parameterization schemes (PILPS) phase-2c Red-Arkansas river basin experiment: III. Spatial and temporal analysis of water fluxes. Glob Planet Change 19:161–180CrossRefGoogle Scholar
  51. Mahfouf JF, Noilhan J (1996) Inclusion of gravitational drainage in a land surface scheme based on the force-restore method. J Appl Meteorol 35:987–992CrossRefGoogle Scholar
  52. Mahfouf JF, Manzi AO, Noilhan J, Giordani H, Déqué M (1995) The land surface scheme ISBA within the Météo-France climate ARPEGE. Part I: implementation and preliminary results. J Clim 8:2039–2057CrossRefGoogle Scholar
  53. Manabe S (1969) Climate and ocean circulation. 1. The atmospheric circulation and the hydrology of the earth’s surface. Mon Weather Rev 97:739–805CrossRefGoogle Scholar
  54. Masson V, Champeaux JL, Chauvin F, Mériguet C, Lacaze R (2003) A global database of land surface parameters at 1 km resolution for use in meteorological and climate models. J Clim 16:1261–1282. Google Scholar
  55. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models. 1. A discussion of principles. J Hydrol 10:282–290CrossRefGoogle Scholar
  56. Ngo-Duc T, Polcher J, Laval K (2005) A 53-year forcing data set for land surface models. J Geophys Res 110:D06116. DOI 10.1029/2004JD005434Google Scholar
  57. Noilhan J, Planton S (1989) A simple parameterization of land surface processes for meteorological models. Mon Weather Rev 117:536–549CrossRefGoogle Scholar
  58. Oki T, Sud YC (1998) Design of total runoff integrating pathways (TRIP). A global river channel network. Earth Interact 2:1–36. Google Scholar
  59. Oki T, Nishimura T, Dirmeyer P (1999) Assessment of annual runoff from land surface models using Total Runoff Integrating Pathways (TRIP). J Meteorol Soc Jpn 77:235–255Google Scholar
  60. Peters-Lidard CD, Zion MS, Wood EF (1997) A soil–vegetation–atmosphere transfer scheme for modeling spatially variable water and energy balance processes. J Geophys Res 102:4303–4324CrossRefGoogle Scholar
  61. Prigent C, Matthews E, Aires F, Rossow WB (2001) Remote sensing of global wetland dynamics with multiple satellite data sets. Geophys Res Lett 24:4631–4634CrossRefGoogle Scholar
  62. Robock A, Vinnikov KY, Srinivasan G, Entin JK, Hollinger SE, Speranskaya NA, Liu S, Namkhai A (2000) The global soil moisture data bank. Bull Am Meteorol Soc 81:1281–1299CrossRefGoogle Scholar
  63. Sivapalan M, Beven KJ, Wood EF (1987) On hydrologic similarity: 2. A scaled model of storm runoff production. Water Resour Res 23:2266–2278CrossRefGoogle Scholar
  64. Vérant S, Laval K, Polcher J, De Castro M (2004) Sensitivity of the continental hydrological cycle to the spatial resolution over the Iberian peninsula. J Hydrometeorol 5:267–285CrossRefGoogle Scholar
  65. Warrach K, Stieglitz M, Mengelkamp HT, Raschke E (2002) Advantages of topographically controlled runoff simulation in a soil–vegetation–atmosphere transfer model. J Hydrometeorol 3:131–148CrossRefGoogle Scholar
  66. Wigneron JP, Calvet JC, Pellarin T, Van de Griend A, Berger M, Ferrazzoli P (2003) Retrieving near-surface soil moisture from microwave radiometric observations: current status and future plans. Remote Sens Environ 85:489–506CrossRefGoogle Scholar
  67. Wood EF, Lettenmaier DP, Zartarian VG (1992) A land-surface hydrology parameterization with subgrid variability for general circulation models. J Geophys Res 97:2717–2728Google Scholar
  68. Zhao RJ (1977) The Xinanjiang model applied in China. J Hydrol 134:317–381Google Scholar
  69. Zhao M, Dirmeyer PA (2003) Production and analysis of GSWP-2 near-surface meteorology data sets. COLA Technical Report 159. Center for Ocean-Land-Atmosphere Studies, Calverton, 36 pp

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  1. 1.CETP-IPSL-CNRSVelizy-VillacoublayFrance
  2. 2.Météo-FranceCNRM/GMGEC/UDCToulouseFrance

Personalised recommendations