Parameter estimation of a land surface scheme using multicriteria methods

Attempts to create models of surfaceߚ;atmosphere interactions with greater physical realism have resulted in land surface schemes (LSS) with large numbers of parameters. The hope has been that these parameters can be assigned typical values by inspecting the literature. The potential for using the various observational data sets that are now available to extract plot-scale estimates for the parameters of a complex LSS via advanced parameter estimation methods developed for hydrological models is explored in this paper. Results are reported for two case studies using data sets of typical quality but very different location and climatological regime (ARM-CART and Tucson). The traditional single-criterion methods were found to be of limited value. However, a multicriteria approach was found to be effective in constraining the parameter estimates into physically plausible ranges when observations on at least one appropriate heat flux and one properly selected state variable are available.

[1]  S. Manabe CLIMATE AND THE OCEAN CIRCULATION1 , 1969 .

[2]  Syukuro Manabe,et al.  THE ATMOSPHERIC CIRCULATION AND THE HYDROLOGY OF THE EARTH ’ S SURFACE , 1969 .

[3]  S. Sorooshian,et al.  Stochastic parameter estimation procedures for hydrologie rainfall‐runoff models: Correlated and heteroscedastic error cases , 1980 .

[4]  R. Spear Eutrophication in peel inlet—II. Identification of critical uncertainties via generalized sensitivity analysis , 1980 .

[5]  George Kuczera,et al.  On the relationship between the reliability of parameter estimates and hydrologic time series data used in calibration , 1982 .

[6]  Soroosh Sorooshian,et al.  The relationship between data and the precision of parameter estimates of hydrologic models , 1985 .

[7]  George Kuczera,et al.  On the validity of first-order prediction limits for conceptual hydrologic models , 1988 .

[8]  W. James Shuttleworth,et al.  Calibrating the Simple Biosphere Model for Amazonian Tropical Forest Using Field and Remote Sensing Data. Part I: Average Calibration with Field Data , 1989 .

[9]  S. Sorooshian,et al.  Effective and efficient global optimization for conceptual rainfall‐runoff models , 1992 .

[10]  Ricardo Harboe,et al.  Multiobjective Decision Making Techniques for Reservoir Operation , 1992 .

[11]  S. Sorooshian,et al.  Shuffled complex evolution approach for effective and efficient global minimization , 1993 .

[12]  Ann Henderson-Sellers,et al.  Biosphere-atmosphere transfer scheme(BATS) version 1e as coupled to the NCAR community climate model , 1993 .

[13]  Soroosh Sorooshian,et al.  Calibration of rainfall‐runoff models: Application of global optimization to the Sacramento Soil Moisture Accounting Model , 1993 .

[14]  D. Lettenmaier,et al.  A simple hydrologically based model of land surface water and energy fluxes for general circulation models , 1994 .

[15]  Soroosh Sorooshian,et al.  Optimal use of the SCE-UA global optimization method for calibrating watershed models , 1994 .

[16]  S. Wheatcraft,et al.  Including Multi-Scale Information in the Characterization of Hydraulic Conductivity Distributions , 1994 .

[17]  Paul R. Houser,et al.  Surface flux measurement and modeling at a semi-arid Sonoran Desert site , 1996 .

[18]  Remote-Sensing Soil Moisture Using Four-Dimensional Data Assimilation. , 1996 .

[19]  D. Randall,et al.  A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part I: Model Formulation , 1996 .

[20]  Soroosh Sorooshian,et al.  Sensitivity analysis of the biosphere‐atmosphere transfer scheme , 1996 .

[21]  William James Shuttleworth,et al.  Testing of vegetation parameter aggregation rules applicable to the Biosphere-Atmosphere Transfer Scheme (BATS) and the FIFE site , 1996 .

[22]  S. Sorooshian,et al.  Automatic calibration of conceptual rainfall-runoff models: sensitivity to calibration data , 1996 .

[23]  Keith Beven,et al.  Bayesian estimation of uncertainty in land surface‐atmosphere flux predictions , 1997 .

[24]  Zong-Liang Yang,et al.  Aggregation rules for surface parameters in global models , 1997 .

[25]  Soroosh Sorooshian,et al.  Multi-objective global optimization for hydrologic models , 1998 .

[26]  L. Bastidas,et al.  Parameter estimation for hydrometeorological models using multi-criteria methods , 1998 .

[27]  K. Beven,et al.  On constraining the predictions of a distributed model: The incorporation of fuzzy estimates of saturated areas into the calibration process , 1998 .

[28]  Soroosh Sorooshian,et al.  Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information , 1998 .

[29]  Soroosh Sorooshian,et al.  Sensitivity analysis of a land surface scheme using multicriteria methods , 1999 .