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Detecting and modelling structures on the micro and the macro scales: Assessing their effects on solute transport behaviour
•Structures on macro- and microscale described by analysis of measurements of K.•Method to identify and model boundary layer separating stationary zones (macroscale).•Geostatistical method to describe and model heterogeneity on microscale.•Macroscale and microscale of K is important to describe solu...
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Published in: | Advances in water resources 2017-09, Vol.107, p.439-450 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •Structures on macro- and microscale described by analysis of measurements of K.•Method to identify and model boundary layer separating stationary zones (macroscale).•Geostatistical method to describe and model heterogeneity on microscale.•Macroscale and microscale of K is important to describe solute transport behaviour.
This paper demonstrates quantitative reasoning to separate the dataset of spatially distributed variables into different entities and subsequently characterize their geostatistical properties, properly. The main contribution of the paper is a statistical based algorithm that matches the manual distinction results. This algorithm is based on measured data and is generally applicable. In this paper, it is successfully applied at two datasets of saturated hydraulic conductivity (K) measured at the Borden (Canada) and the Lauswiesen (Germany) aquifers. The boundary layer was successfully delineated at Borden despite its only mild heterogeneity and only small statistical differences between the divided units. The methods are verified with the more heterogeneous Lauswiesen aquifer K data-set, where a boundary layer has previously been delineated.
The effects of the macro- and the microstructure on solute transport behaviour are evaluated using numerical solute tracer experiments. Within the microscale structure, both Gaussian and non-Gaussian models of spatial dependence of K are evaluated. The effects of heterogeneity both on the macro- and the microscale are analysed using numerical tracer experiments based on four scenarios: including or not including the macroscale structures and optimally fitting a Gaussian or a non-Gaussian model for the spatial dependence in the micro-structure. The paper shows that both micro- and macro-scale structures are important, as in each of the four possible geostatistical scenarios solute transport behaviour differs meaningfully. |
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ISSN: | 0309-1708 1872-9657 |
DOI: | 10.1016/j.advwatres.2017.05.007 |