Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model

[1] Current land surface models use increasingly complex descriptions of the processes that they represent. Increase in complexity is accompanied by an increase in the number of model parameters, many of which cannot be measured directly at large spatial scales. A Monte Carlo framework was used to evaluate the sensitivity and identifiability of ten parameters controlling surface and subsurface runoff generation in the Variable Infiltration Capacity model (VIC). Using the Monte Carlo Analysis Toolbox (MCAT), parameter sensitivities were studied for four U.S. watersheds along a hydroclimatic gradient, based on a 20-year data set developed for the Model Parameter Estimation Experiment (MOPEX). Results showed that simulated streamflows are sensitive to three parameters when evaluated with different objective functions. Sensitivity of the infiltration parameter (b) and the drainage parameter (exp) were strongly related to the hydroclimatic gradient. The placement of vegetation roots played an important role in the sensitivity of model simulations to the thickness of the second soil layer (thick2). Overparameterization was found in the base flow formulation indicating that a simplified version could be implemented. Parameter sensitivity was more strongly dictated by climatic gradients than by changes in soil properties. Results showed how a complex model can be reduced to a more parsimonious form, leading to a more identifiable model with an increased chance of successful regionalization to ungauged basins. Although parameter sensitivities are strictly valid for VIC, this model is representative of a wider class of macroscale hydrological models. Consequently, the results and methodology will have applicability to other hydrological models. Citation: Demaria, E. M., B. Nijssen, and T. Wagener (2007), Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model, J. Geophys. Res., 112, D11113, doi:10.1029/2006JD007534.

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

[2]  A. Pitman The evolution of, and revolution in, land surface schemes designed for climate models , 2003 .

[3]  Vijay P. Singh,et al.  Rainfall-runoff modeling , 1988 .

[4]  Soroosh Sorooshian,et al.  Evaluation and Transferability of the Noah Land Surface Model in Semiarid Environments , 2005 .

[5]  K. Beven,et al.  Shenandoah Watershed Study: Calibration of a Topography‐Based, Variable Contributing Area Hydrological Model to a Small Forested Catchment , 1985 .

[6]  Steven W. Running,et al.  Comparisons of land cover and LAI estimates derived from ETM+ and MODIS for four sites in North America: a quality assessment of 2000/2001 provisional MODIS products , 2003 .

[7]  D. Lettenmaier,et al.  Streamflow simulation for continental‐scale river basins , 1997 .

[8]  R. H. Brooks,et al.  Hydraulic properties of porous media , 1963 .

[9]  M. Sivapalan,et al.  Climate and landscape controls on water balance model complexity over changing timescales , 2002 .

[10]  Xi Chen,et al.  Sensitivity analysis and determination of streambed leakance and aquifer hydraulic properties , 2003 .

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

[12]  Thorsten Wagener,et al.  Risk-based modelling of surface water quality: a case study of the Charles River, Massachusetts , 2003 .

[13]  Eric F. Wood,et al.  Predicting the Discharge of Global Rivers , 2001, Journal of Climate.

[14]  Soroosh Sorooshian,et al.  A framework for development and application of hydrological models , 2001, Hydrology and Earth System Sciences.

[15]  D. Lettenmaier,et al.  A Long-Term Hydrologically Based Dataset of Land Surface Fluxes and States for the Conterminous United States* , 2002 .

[16]  D. Lettenmaier,et al.  Surface soil moisture parameterization of the VIC-2L model: Evaluation and modification , 1996 .

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

[18]  Bart Nijssen,et al.  Land‐Atmosphere Models for Water and Energy Cycle Studies , 2006 .

[19]  M. Hansen,et al.  A comparison of the IGBP DISCover and University of Maryland 1 km global land cover products , 2000 .

[20]  Ann Henderson-Sellers,et al.  A Factorial Assessment of the Sensitivity of the BATS Land-Surface Parameterization Scheme , 1993 .

[21]  G. Hornberger,et al.  Approach to the preliminary analysis of environmental systems , 1981 .

[22]  Andrew J. Pitman,et al.  Assessing the Sensitivity of a Land-Surface Scheme to the Parameter Values Using a Single Column Model , 1994 .

[23]  Dennis P. Lettenmaier,et al.  Development of regional parameter estimation equations for a macroscale hydrologic model , 1997 .

[24]  E. Todini The ARNO rainfall-runoff model , 1996 .

[25]  M. Trosset,et al.  Bayesian recursive parameter estimation for hydrologic models , 2001 .

[26]  A. D. Bradshaw,et al.  The Importance of Soil , 2003 .

[27]  Soroosh Sorooshian,et al.  Exploring parameter sensitivities of the land surface using a locally coupled land-atmosphere model , 2004 .

[28]  P. van der Kloet,et al.  Two algorithms for parameter estimation in groundwater flow problems , 1985 .

[29]  Keith Beven,et al.  The future of distributed models: model calibration and uncertainty prediction. , 1992 .

[30]  A non-linear optimization method for the estimation of aquifer parameters , 1978 .

[31]  S. Uhlenbrook,et al.  Sensitivity analyses of a distributed catchment model to verify the model structure , 2005 .

[32]  Jeffrey P. Walker,et al.  In situ measurement of soil moisture: a comparison of techniques | NOVA. The University of Newcastle's Digital Repository , 2004 .

[33]  Xu Liang,et al.  On the assessment of the impact of reducing parameters and identification of parameter uncertainties for a hydrologic model with applications to ungauged basins , 2006 .

[34]  Henrik Madsen,et al.  Comparison of different automated strategies for calibration of rainfall-runoff models , 2002 .

[35]  K. Beven,et al.  Bayesian Estimation of Uncertainty in Runoff Prediction and the Value of Data: An Application of the GLUE Approach , 1996 .

[36]  Eric F. Wood,et al.  A land-surface hydrology parameterization with subgrid variability for general circulation models , 1992 .

[37]  Roni Avissar,et al.  An Evaluation with the Fourier Amplitude Sensitivity Test (FAST) of Which Land-Surface Parameters Are of Greatest Importance in Atmospheric Modeling , 1994 .

[38]  M. B. Beck,et al.  Identification of model structure for aquatic ecosystems using regionalized sensitivity analysis. , 2001, Water science and technology : a journal of the International Association on Water Pollution Research.

[39]  Jeffrey P. Walker,et al.  Importance of soil moisture measurements for inferring parameters in hydrologic models of low-yielding ephemeral catchments , 2003, Environ. Model. Softw..

[40]  Luis A. Bastidas,et al.  Multicriteria parameter estimation for models of stream chemical composition , 2002 .

[41]  Soroosh Sorooshian,et al.  Evaluating model performance and parameter behavior for varying levels of land surface model complexity , 2006 .

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

[43]  Soroosh Sorooshian,et al.  Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops , 2006 .

[44]  Neil McIntyre,et al.  Towards reduced uncertainty in conceptual rainfall‐runoff modelling: dynamic identifiability analysis , 2003 .

[45]  Ann Henderson-Sellers,et al.  Assessing the Sensitivity of A Land‐Surface Scheme to Parameters Used In Tropical‐Deforestation Experiments , 1992 .

[46]  Xu Liang,et al.  Intercomparison of land-surface parameterization schemes: sensitivity of surface energy and water fluxes to model parameters , 2003 .

[47]  Thorsten Wagener,et al.  Numerical and visual evaluation of hydrological and environmental models using the Monte Carlo analysis toolbox , 2007, Environ. Model. Softw..

[48]  Andrea Emilio Rizzoli,et al.  Identification of model structure via qualitative simulation , 1992, IEEE Trans. Syst. Man Cybern..

[49]  W. J. Shuttleworth,et al.  Parameter estimation of a land surface scheme using multicriteria methods , 1999 .

[50]  A. Saltelli,et al.  Sensitivity analysis: Could better methods be used? , 1999 .

[51]  George M. Hornberger,et al.  Eutrophication in peel inlet—III. A model for the nitrogen scenario and a retrospective look at the preliminary analysis , 1984 .