Exploring the Model Space of Airborne Electromagnetic Data to Delineate Large‐Scale Structure and Heterogeneity Within an Aquifer System
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Abstract Airborne electromagnetic (AEM) data can be inverted to recover models of the electrical resistivity of the subsurface; these, in turn, can be transformed to obtain models of sediment type. AEM data were acquired in Butte and Glenn Counties, California, USA to improve the understanding of the aquifer system. Around 800 line‐kilometers of high‐quality data were acquired, imaging to a depth of ∼300 m. We developed a workflow designed to obtain, from the AEM data, information about the large‐scale structure and heterogeneity of the aquifer system to better understand the vertical connectivity. Using six different inversions incorporating various forms of available information and posterior sampling of the recovered resistivity models, we produced 6,006 resistivity models. These models were transformed to models of sediment type and estimates of percentage of sand/gravel. Exploring the model space, containing the resistivity models and the derived models, allowed us to delineate the large‐scale structure of the aquifer system in a way that captures and communicates the uncertainty in the identified sediment type. The uncertainty increased, as expected, with depth, but also served to indicate, as areas of high uncertainty in sediment type, the location of both large‐scale and small‐scale interfaces between sediment types. A plan view map of the integrated percentage of sand/gravel, when compared to existing hydrographs, revealed the extent of lateral changes in vertical connectivity within the aquifer system throughout the study area.Keywords:
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Abstract A general method is proposed which measures the increase in uncertainty when sampling effort is reduced in sediment fingerprinting. The method gives quantitative measures of how reduced sampling of material in one of the source areas, and/or of suspended sediment in streams, increases the uncertainties in the proportions of sediment contributed from the sources. Because the proportions of sediment contributed by the source areas must add to one, standard errors of the estimated proportions cannot be used as the usual measures of uncertainty: the paper uses instead the volume of the joint 95% confidence region for the estimated proportions. The paper shows how the uncertainty in this volume changes as numbers of suspended sediment samples, and the numbers of samples collected from cropped fields, are reduced by successive steps from 24 ( 20 , in the case of cropped fields) to 16 , 12 , 8 , 4 and 2 samples. As expected, uncertainty increases rapidly as the number of samples – whether of suspended sediment or from cropped fields – is reduced drastically. The pattern of increasing uncertainty is similar both for reductions in suspended sediment sampling, and for reduced sampling from cropped areas. When the number of suspended sediment samples, and the number of samples from cropped fields, are reduced to the same values, the increase in uncertainty from fewer suspended sediment samples was always slightly greater than the increased uncertainty from the reduced sampling of cropped areas, although this finding took no account of differences in the costs of field sampling and laboratory analysis. Copyright © 2016 John Wiley & Sons, Ltd.
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