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Reduced-complexity probabilistic reconstruction of alluvial aquifer stratigraphy, and application to sedimentary fans in northwestern India.

van Dijk, W.M. and Densmore, A.L. and Sinha, R. and Singh, A. and Voller, V.R. (2016) 'Reduced-complexity probabilistic reconstruction of alluvial aquifer stratigraphy, and application to sedimentary fans in northwestern India.', Journal of hydrology., 541 (B). pp. 1241-1257.


Generating a realistic model of subsurface stratigraphy that fits data from multiple well locations is a well-established problem in the field of aquifer characterization. This is particularly critical for the alluvial fan-hosted aquifers in northwestern India, as they have some of the highest rates of groundwater extraction in the world and spatially limited subsurface observations. The objective of this study is to develop a reduced-complexity model that generates probabilistic estimates of aquifer body occurrence within a sedimentary fan, based loosely on the northwestern Indian aquifer system. We propose a parsimonious, inverse-weighted random walk model that reconstructs potential channel belt pathways within a discrete depth range or slice by (i) connecting known aquifer locations with the fan apex, (ii) filling adjacent cells with non-aquifer material based on estimated channel-body dimensions, and (iii) random filling of the remaining cells until the model fraction of aquifer material is comparable to the bulk aquifer fraction observed from well data. Once filled, individual depth slices can be stacked to produce a three-dimensional representation of aquifer-body geometry, allowing informed inference and testable predictions about the configuration of aquifer units in the subsurface. A receiver operating characteristic (ROC) curve shows that the model performs better than fully random filling, both in matching the locations of aquifer material in the subsurface and in reconstructing the geometry of relict channel bodies preserved on the fan surface. The model differs from purely statistical-empirical approaches by incorporating some geomorphic knowledge of fluvial channel belt geometry within the fan system. In contrast to a fully process-based approach, the model is computationally fast and is easily refined as new subsurface data become available.

Item Type:Article
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Publisher statement:This article is available under the terms of the Creative Commons Attribution License (CC BY). You may copy and distribute the article, create extracts, abstracts and new works from the article, alter and revise the article, text or data mine the article and otherwise reuse the article commercially (including reuse and/or resale of the article) without permission from Elsevier. You must give appropriate credit to the original work, together with a link to the formal publication through the relevant DOI and a link to the Creative Commons user license above. You must indicate if any changes are made but not in any way that suggests the licensor endorses you or your use of the work.
Date accepted:15 August 2016
Date deposited:02 September 2016
Date of first online publication:20 August 2016
Date first made open access:No date available

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