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Validity of First-Order Approximations to Describe Parameter Uncertainty in Soil Hydrologic Models

Jasper A. Vrugt* and Willem Bouten

Institute for Biodiversity and Ecosystem Dynamics, Section Physical Geography, Univ. of Amsterdam, The Netherlands, Nieuwe Achtergracht 166, Amsterdam, 1018 WV



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Fig. 1. Optimized soil water retention curves for the sandy and clayey soil, using the van Genuchten model. Measured retention observations are indicated with symbols.

 


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Fig. 2. (A) Relationship between the jumprate used for sampling from the proposal distribution for the sandy soil and the amount of model calls needed to achieve convergence of the Metropolis sampler, (B) Evolution of the Gelman-Rubin convergence diagnostic for each of the van Genuchten parameters of the sandy soil.

 


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Fig. 3. Scatter plot of {theta}r–n samples generated by the Metropolis algorithm at two different stages during the evolution. Each sequences generated with the Metropolis sampler is coded with a different symbol. For more explanation see text.

 


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Fig. 4. Scatter plot of 2000 combinations of {alpha}-n (A), and {theta}rn (B) parameters sampled for the clayey soil using the Metropolis algorithm.

 


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Fig. 5. Univariate posterior probability distributions of the soil hydraulic parameters {theta}s, {theta}r, {alpha}, n, Ks and l using observed soil water content dynamics during the outflow experiment. The arrows indicate the most likely parameter values, derived using the Shuffled Complex Evolution global optimization algorithm.

 


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Fig. 6. Observed and simulated soil water content dynamics (I) as well as the measured and simulated soil water pressure heads (II) during the multistep outflow (MSO) experiment, using either observed soil water contents (A), or a joint identification using soil water pressure head data and soil water contents simultaneously (B).

 





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