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References

  • Bates, D. M., D. G. Watts, Nonlinear Regression Analysis and its Applications, John Wiley, New York, 1988.
  • Beck, M. B., Water quality modeling: A review of the analysis of uncertainty, Water Resour. Res., 238, 13931442, 1987.
  • Beck, M. B., Coping with ever larger problems, models, and data bases, Water Sci. Technol., 394, 111, 1999.
  • Belsley, D. A., Conditioning Diagnostics: Collinearity and Weak Data in Regression, John Wiley, New York, 1991.
  • Beven, K., Towards a new paradigm in hydrology, Water for the Future: Hydrology in PerspectiveJ. C. Rodda, N. C. Matalas, IAHS Publ., 164, 393403, 1987.
  • Beven, K., Future of distributed modeling, Hydrol. Processes, 63, 253254, 1992.
  • Beven, K., Prophecy, reality and uncertainty in distributed hydrological modeling, Adv. Water Resour., 161, 4151, 1993.
  • Campolongo, F., A. Saltelli, Sensitivity analysis of an environmental model: An application of different analysis methods, Reliab. Eng. Syst. Safety, 571, 4969, 1997.
  • Chatfield, C., Model uncertainty, data mining and statistical inference (with discussion), J. R. Stat. Soc., Ser. A, 1583, 419466, 1995.
  • Draper, D., Assessment and propagation of model uncertainty (with discussion), J. R. Stat. Soc., Ser. B, 571, 4597, 1995.
  • Draper, D., A. Saltelli, S. Tarantola, andP. Prado, Scenario and parameteric sensitivity and uncertainty analyses in nuclear waste disposal risk assessment: The case of GESAMAC, inMathematical and Statistical Methods for Sensitivity Analysis, edited byA. Saltelli, K. Chan, andM. Scott, chap. 13, pp.275292,John Wiley,New York,2000.
  • Freer, J., K. Beven, B. Ambroise, Bayesian estimation of uncertainty in runoff prediction and the value of data: An application of the GLUE approach, Water Resour. Res., 327, 21612173, 1996.
  • Grieb, T. M., R. J. M. Hudson, N. Shang, R. C. Spear, S. A. Gherini, R. A. Goldstein, Examination of model uncertainty and parameter interaction in a global carbon cycling model (GLOCO), Environ. Int., 256–7, 787803, 1999.
  • Gupta, V. K., S. Sorooshian, Uniqueness and observability of conceptual rainfall runoff model parameters: The percolation process examined, Water Resour. Res., 191, 269276, 1983.
  • Helton, J. C., Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal, Reliab. Eng. Syst. Safety, 422–3, 327367, 1993.
  • Holmberg, A., On the practical identifiability of microbial growth models incorporating Michaelis-Menten type nonlinearities, Math. Biosci., 62, 2343, 1982.
  • Hornberger, G. M., R. C. Spear, An approach to the preliminary analysis of environmental systems, J. Environ. Manage., 12, 718, 1981.
  • Hornberger, G. M., R. C. Spear, An approach to the analysis of behavior and sensitivity in environmental systems, Uncertainty and Forecasting of Water QualityM. Beck, G. vanStraten, 101116, Springer-Verlag, New York, 1983.
  • Jakeman, A. J., G. M. Hornberger, How much complexity is warranted in a rainfall-runoff model?, Water Resour. Res., 298, 26372649, 1993.
  • Jakob, A., J. Zobrist, J. S. Davies, P. Liechti, L. Sigg, NADUF: Langzeitbeobachtung des chemisch-physikalischen Gewässerzustandes, Gas Wasser Abwasser, 74, 171186, 1994.
  • Kleissen, F. M., M. B. Beck, H. S. Wheater, The identifiability of conceptual hydrochemical models, Water Resour. Res., 2612, 29792992, 1990.
  • Kuczera, G., Assessing hydrologic model nonlinearity using response surface plots, J. Hydrol., 1181–4, 143161, 1990.
  • Kuczera, G., M. Mroczkowski, Assessment of hydrologic parameter uncertainty and the worth of multiresponse data, Water Resour. Res., 346, 14811489, 1998.
  • Pastres, R., D. Franco, G. Pecenik, C. Solidoro, C. Dejak, Local sensitivity analysis of a distributed parameters water quality model, Reliab. Eng. Syst. Safety, 571, 2130, 1997.
  • Reichert, P., Aquasim: A tool for simulation and data-analysis of aquatic systems, Water Sci. Technol., 302, 2130, 1994.
  • Reichert, P., AQUASIM 2.0: User manual, technical reportSwiss Fed. Inst. for Environ. Sci. and Technol., Dübendorf, Switzerland, 1998.
  • Reichert, P., M. Omlin, On the usefulness of overparameterized ecological models, Ecol. Modell., 952–3, 289299, 1997.
  • Reichert, P., R. vonSchulthess, D. Wild, The use of AQUASIM for estimating parameters of activated sludge models, Water Sci. Technol., 312, 135147, 1995.
  • Restrepo, P. J., R. L. Bras, A view of maximum-likelihood estimation with large conceptual hydrologic models, Appl. Math. Comput., 175048, 375403, 1985.
  • Saltelli, A., Sensitivity analysis: Could better methods be used?, J. Geophys. Res., 104D3, 37893793, 1999.
  • Saltelli, A., M. Scott, Guest editorial: The role of sensitivity analysis in the corroboration of models and its link to model structural and parametric uncertainty, Reliab. Eng. Syst. Safety, 571, 14, 1997.
  • Saltelli, A., S. Tarantola, K. P. S. Chan, A quantitative model-independent method for global sensitivity analysis of model output, Technometrics, 411, 3956, 1999.
  • Sobol, I. M., Sensitivity estimates for nonlinear mathematical models, Math. Modell. Comput. Exp., 14, 407414, 1993.
  • Sommer, H. M., Variability in microbiological degradation experiments: Analysis and case study, Ph.D. thesis,Inst. of Math. Modell., Tech. Univ. of Den.,Lyngby,1997.
  • Sorooshian, S., V. K. Gupta, Automatic calibration of conceptual rainfall runoff models: The question of parameter observability and uniqueness, Water Resour. Res., 191, 260268, 1983.
  • Spear, R. C., Large simulation models: Calibration uniqueness and goodness of fit, Environ. Modell. Software, 122–3, 219228, 1997.
  • Spear, R. C., T. M. Grieb, N. Shang, Parameter uncertainty and interaction in complex environmental models, Water Resour. Res., 3011, 31593169, 1994.
  • Stewart, G. W., Collinearity and least squares regression (with discussion), Stat. Sci., 2, 68100, 1987.
  • Stigter, J. D., M. B. Beck, A new approach to the identification of model structure, Environmetrics, 5, 315333, 1994.
  • Turányi, T., Sensitivity analysis of complex kinetic systems: Tools and applications, J. Math. Chem., 53, 203248, 1990.
  • Turányi, T., Applications of sensitivity analysis to combustion chemistry, Reliab. Eng. Syst. Safety, 571, 4148, 1997.
  • Uehlinger, U., C. König, P. Reichert, Variability of photosynthesis-irradiance curves and ecosystem respiration in a small river, Freshwater Biol., 443, 493507, 2000.
  • vanStraten, G., Analytical methods for parameter space delimitation and application to shallow lake phytoplankton dynamics modeling, Appl. Math. Comput., 174, 459482, 1985.
  • Weisberg, S., Applied Linear Regression2, John Wiley, New York, 1990.