The history of digital soil mapping and modeling (DSMM) is marked by adoption of new
mapping tools and techniques, data management systems, innovative delivery of soil data …

The coupled Markov chain (CMC) model is widely employed to simulate geological
uncertainty based on sparse borehole data, owing to its simplicity, parameter efficiency, and …

The stratigraphic uncertainty and rotated anisotropy of soil properties exist widely in nature.
Recent studies have shown that the slope stability was significantly influenced by these two …

Groundwater pollution risk evaluation is an important basis for developing groundwater
protection measures and management strategies, and its accuracy directly affects the …

This study evaluated the spatial variability of hydraulic conductivity (K) along the Han River
watershed in the Jianghan Plain (China) by using different geostatistical methods. The K …

This paper develops a Markov chain‐based geostatistical model for multidimensional field
predictions of the categorical attributes. An efficient conditional probability equation that …

Sustainable aquifer management in coastal cities is becoming critically important due to the
challenges of climate variability amidst population growth. Study of the aquifer heterogeneity …

Two-state Markov chain models of different orders have been used to simulate the pattern of
rainfall during the monsoon season (June-September) over Gangetic West Bengal (India) …

Our study is aimed at assessing the extent at which relying on differing geostatistical
approaches may affect characterization of the connectivity of geomaterials (or facies) and, in …

Modeling geological units such as dykes is a powerful tool in mineral exploration studies.
The most significant issue in modeling of uncertainty in the mineral exploration studies is the …