Investigating the Ability of a Land Surface Model to Simulate Streamflow with the Accuracy of Hydrological Models: A Case Study Using MOPEX Materials

Olga N. Nasonova Institute of Water Problems, Russian Academy of Sciences, Moscow, Russia

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Yeugeniy M. Gusev Institute of Water Problems, Russian Academy of Sciences, Moscow, Russia

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Yeugeniy E. Kovalev Institute of Water Problems, Russian Academy of Sciences, Moscow, Russia

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Abstract

In the Model Parameter Estimation Experiment (MOPEX) project, after calibration of model parameters, complex rainfall–runoff hydrological models (HMs) simulated streamflow better than land surface models (LSMs), including the Soil–Water–Atmosphere–Plant (SWAP) model. A possible explanation for this is that the LSMs may not have been well calibrated. To test this statement, different strategies to calibrate SWAP using daily streamflow from 12 MOPEX basins were investigated. Optimization of parameter values was performed using a combination of an automated optimization algorithm and manual efforts. For automated optimization, two different global optimization algorithms were used: 1) a random search technique and 2) a shuffled complex evolution method developed by the University of Arizona (SCE-UA). Two objective functions, based on the Nash–Sutcliffe coefficient of efficiency and the mean systematic error, were applied. The number of calibrated parameters ranged from 10 to 15. All adjusted parameters were kept within a reasonable range so as not to violate physical constraints while providing a close match between simulated and measured daily streamflow. The results of streamflow simulations with different sets of optimal parameters were compared with each other, with observations, and with simulation results obtained by the HMs that participated in the MOPEX project. The new SWAP calibration strategies resulted in significant improvement of SWAP streamflow simulations, which came close to the best HM results. It was confirmed that model performance depends greatly on the calibration strategy and that the land surface model SWAP, with appropriate calibration, can simulate runoff with the accuracy that is comparable to the accuracy of hydrological models.

Corresponding author address: Olga N. Nasonova, Institute of Water Problems, Gubkina St. 3, 119333 Moscow, Russia. Email: nasonova@aqua.laser.ru

Abstract

In the Model Parameter Estimation Experiment (MOPEX) project, after calibration of model parameters, complex rainfall–runoff hydrological models (HMs) simulated streamflow better than land surface models (LSMs), including the Soil–Water–Atmosphere–Plant (SWAP) model. A possible explanation for this is that the LSMs may not have been well calibrated. To test this statement, different strategies to calibrate SWAP using daily streamflow from 12 MOPEX basins were investigated. Optimization of parameter values was performed using a combination of an automated optimization algorithm and manual efforts. For automated optimization, two different global optimization algorithms were used: 1) a random search technique and 2) a shuffled complex evolution method developed by the University of Arizona (SCE-UA). Two objective functions, based on the Nash–Sutcliffe coefficient of efficiency and the mean systematic error, were applied. The number of calibrated parameters ranged from 10 to 15. All adjusted parameters were kept within a reasonable range so as not to violate physical constraints while providing a close match between simulated and measured daily streamflow. The results of streamflow simulations with different sets of optimal parameters were compared with each other, with observations, and with simulation results obtained by the HMs that participated in the MOPEX project. The new SWAP calibration strategies resulted in significant improvement of SWAP streamflow simulations, which came close to the best HM results. It was confirmed that model performance depends greatly on the calibration strategy and that the land surface model SWAP, with appropriate calibration, can simulate runoff with the accuracy that is comparable to the accuracy of hydrological models.

Corresponding author address: Olga N. Nasonova, Institute of Water Problems, Gubkina St. 3, 119333 Moscow, Russia. Email: nasonova@aqua.laser.ru

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  • Andreassian, V., and Coauthors, 2006: Catalogue of the models used in MOPEX 2004/2005. IAHS Publ., 307 , 4193.

  • Bastidas, L. A., Gupta H. V. , Sorooshian S. , Shuttleworth W. J. , and Yang Z. L. , 1999: Sensitivity analysis of a land surface scheme using multicriteria methods. J. Geophys. Res., 104 , (D16). 1948119490.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Boone, A., and Coauthors, 2004: The Rhône-Aggregation Land Surface Scheme intercomparison project: An overview. J. Climate, 17 , 187208.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Budagovskiy, A. I., 1989: Principles of the method of calculating the duty of water and irrigation regimes. Water Resour., 16 , 2735.

  • Burnash, R. J. C., Ferral R. L. , and McGuire R. A. , 1973: A generalized streamflow simulation system—Conceptual modeling for digital computers. National Weather Service, NOAA, and the State of California Tech. Rep. Joint Federal and State River Forecast Center, 204 pp.

    • Search Google Scholar
    • Export Citation
  • Clapp, R. B., and Hornberger G. M. , 1978: Empirical equations for some soil hydraulic properties. Water Resour. Res., 14 , 601604.

  • Dickinson, R. E., Henderson-Sellers A. , Kennedy P. J. , and Wilson M. F. , 1986: Biosphere-Atmosphere Transfer Scheme (BATS) for the NCAR Community Climate Model. NCAR Tech. Note NCAR/TN-275+STR, 82 pp.

    • Search Google Scholar
    • Export Citation
  • Duan, Q., Sorooshian S. , and Gupta V. K. , 1992: Effective and efficient global optimization for conceptual rainfall runoff models. Water Resour. Res., 28 , 10151031.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Duan, Q., Gupta H. V. , Sorooshian S. , Rousseau A. N. , and Turcotte R. , Eds.,. 2003: Calibration of Watershed Models. Water Science and Application Series, Vol. 6, Amer. Geophys. Union, 345 pp.

    • Search Google Scholar
    • Export Citation
  • Duan, Q., and Coauthors, 2006: Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops. J. Hydrol., 320 , 317.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Farnsworth, R. K., Thompson E. S. , and Peck E. L. , 1982: Evaporation atlas for the contiguous 48 United States. NOAA Tech. Rep. NWS 33, 26 pp.

    • Search Google Scholar
    • Export Citation
  • Gan, T. Y., and Burges S. J. , 2006: Assessment of soil-based and calibrated parameters of the Sacramento model and parameter transferability. J. Hydrol., 320 , 117131.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gan, T. Y., Gusev Ye M. , Burges S. J. , and Nasonova O. N. , 2006: Performance comparison of a complex, physics-based land surface model and a conceptual, lumped-parameter, hydrologic model at the basin-scale. IAHS Publ., 307 , 196207.

    • Search Google Scholar
    • Export Citation
  • Gusev, E. M., 1998: Evaporation from soil under drying. Eurasian Soil Sci., 31 , 836840.

  • Gusev, E. M., and Nasonova O. N. , 2004a: Simulation of heat and water exchange at the land–atmosphere interface on a local scale for permafrost territories. Eurasian Soil Sci., 37 , 10771092.

    • Search Google Scholar
    • Export Citation
  • Gusev, E. M., and Nasonova O. N. , 2004b: Challenges in studying and modeling heat and moisture exchange in soil–vegetation/snow cover–surface air layer systems. Water Res., 31 , 132147.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gusev, E. M., Nasonova O. N. , and Dzhogan L. Ya , 2006: The simulation of runoff from small catchments in the permafrost zone by the SWAP model. Water Res., 33 , 115126.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gusev, E. M., Nasonova O. N. , Dzhogan L. Ya , and Kovalev E. E. , 2008: The application of the land surface model for calculating river runoff in high latitudes. Water Res., 35 , 171184.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gusev, Ye M., and Nasonova O. N. , 1998: The land surface parameterization scheme SWAP: Description and partial validation. Global Planet. Change, 19 , 6386.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gusev, Ye M., and Nasonova O. N. , 2000: An experience of modelling heat and water exchange at the land surface on a large river basin scale. J. Hydrol., 233 , 118.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gusev, Ye M., and Nasonova O. N. , 2002: The simulation of heat and water exchange at the land-atmosphere interface for the boreal grassland by the land-surface model SWAP. Hydrol. Processes, 16 , 18931919.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gusev, Ye M., and Nasonova O. N. , 2003: The simulation of heat and water exchange in the boreal spruce forest by the land-surface model SWAP. J. Hydrol., 280 , 162191.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gusev, Ye M., and Nasonova O. N. , 2006: Simulating runoff from MOPEX experimental river basins using the land surface model SWAP and different parameter estimation techniques. IAHS Publ., 307 , 188195.

    • Search Google Scholar
    • Export Citation
  • Gusev, Ye M., Nasonova O. N. , Dzhogan L. Ya , and Kovalev Ye E. , 2007: Hydrological predictability investigation of global data sets for high-latitude river basins. IAHS Publ., 313 , 127133.

    • Search Google Scholar
    • Export Citation
  • Kistler, R., and Coauthors, 2001: The NCEP–NCAR 50-Year Reanalysis: Monthly means CD-ROM and documentation. Bull. Amer. Meteor. Soc., 82 , 247267.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuczera, G., 1997: Efficient subspace probabilistic parameter optimization for catchment models. Water Resour. Res., 33 , 177185.

  • Leavesley, G. H., Lichty R. W. , Troutman B. M. , and Saindon L. G. , 1983: Precipitation-runoff modeling system: User’s manual. USGS Rep. 83-4238, Water-Resources Investigation Report Series, 207 pp.

    • Search Google Scholar
    • Export Citation
  • Manabe, S., 1969: Climate and the ocean circulation. 1: The atmospheric circulation and the hydrology of the earth’s surface. Mon. Wea. Rev., 97 , 739805.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mengelkamp, H-T., Warrach K. , Ruhe C. , and Raschke E. , 2001: Simulation of runoff and streamflow on local and regional scales. Meteor. Atmos. Phys., 76 , 107117.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nash, J. E., and Sutcliffe J. V. , 1970: River flow forecasting through conceptual models part I—A discussion of principles. J. Hydrol., 10 , 282290.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nasonova, O. N., and Gusev Ye M. , 2007: Can a land surface model simulate runoff with the same accuracy as a hydrological model? IAHS Publ., 313 , 258265.

    • Search Google Scholar
    • Export Citation
  • Nasonova, O. N., Gusev Ye M. , and Kovalev Ye E. , 2008: Global estimates of the land heat and water balance components using the land surface model and different data sets (in Russian). Izv. Russ. Acad. Sci. Ser. Geogr., 1 , 819.

    • Search Google Scholar
    • Export Citation
  • Nelder, J. A., and Mead R. , 1965: A simplex method for function minimization. Comput. J., 7 , 308313.

  • Noilham, J., and Mahfouf J-F. , 1996: The ISBA land surface parameterization scheme. Global Planet. Change, 13 , 145159.

  • Perrin, C., Michel C. , and Andreassian V. , 2003: Improvement of a parsimonious model for streamflow simulation. J. Hydrol., 279 , 275289.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Polcher, J., 2001: The Global Land-Atmosphere System Study (GLASS). BAHC–GEWEX News joint issue, BAHC News, No. 9, and GEWEX News, Vol. 11, No. 2, International GEWEX Project Office, Silver Spring, MD, 5–6.

    • Search Google Scholar
    • Export Citation
  • Sellers, P. J., Mintz Y. , Sud Y. C. , and Dalcher A. , 1986: A Simple Biosphere Model (SiB) for use within general circulation models. J. Atmos. Sci., 43 , 505531.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Solomatine, D. P., Dibike Y. B. , and Kukuric N. , 1999: Automatic calibration of groundwater models using global optimization techniques. Hydrol. Sci. J., 44 , 879894.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Verseghy, D. L., 1991: CLASS – A Canadian land surface sheme for GCMs. 1. Soil model. Int. J. Climatol., 11 , 111113.

  • Wood, E. F., and Coauthors, 1998: The Project for Intercomparison of land-surface Parameterization Schemes (PILPS) phase 2(c) Red-Arkansas River basin experiment: 1. Experiment description and summary intercomparisons. Global Planet. Change, 19 , 115135.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xia, Y., 2007: Calibration of LaD model in the northeast United States using observed annual streamflow. J. Hydrometeor., 8 , 10981110.

  • Zhao, M., and Dirmeyer P. A. , 2003: Production and analysis of GSWP-2 near-surface meteorology data sets. COLA Tech. Rep. 159, 38 pp.

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