Behavior of indicator variograms and transition probabilities in relation to the variance in lengths of hydrofacies

By R. Ritzi. 2000

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Why did Sudicky [1986] find an exponential‐like spatial correlation structure for hydraulic conductivity at the Borden research site? (2006, methodology): “Ritzi [2000] showed that sample autotransition probabilities, t̂o,o(h), can be largely influenced by the variance in length and take on an asymptotic, exponential-like shape if the coefficient of variation for unit length (cv, defined as the standard deviation in length normalized by mean length, l)”
Representing aquifer architecture in macrodispersivity models with an analytical solution of the transition probability matrix (2007, background): “In the Markov chain model, both conceptual facies model and quantitative information (proportions, lengths, juxtapositioning frequency) can be combined to mathematically represent facies architecture [ Ritzi, 2000; Zhang, 2002; Rubin, 2003; Ritzi et al., 2004; Dai et al., 2004a, 2005].”
Transiograms for Characterizing Spatial Variability of Soil Classes (2007, methodology): “‡ The linear, spherical, exponential, and Gaussian models for auto-transiograms were also provided in Ritzi (2000).”
Transport in heterogeneous sediments with multimodal conductivity and hierarchical organization across scales (2004, methodology): “As applied to measuring spatial continuity, the transition probability denotes the conditional probability (Carle and Fogg, 1996; Ritzi, 2000).”