Estimating Concentrations Based on Proxy Data
Obtaining a spatially representative sample data set is important for characterizing complex environmental sites. Often, cost, time, and site access limitations can prevent an adequate sampling density needed to confidently characterize the extent, migration pathways, and source of a contaminant. Proxy, or secondary, sampling technologies, such as membrane interface probe (MIP), LiDAR, geophysics, portable x-ray fluorescence spectroscopy, and other similar proxy sampling technologies are becoming widely used to map sparse, more expensive direct sample observations (for example, soil samples or geologic borings). Proxy sampling technologies are attractive because they collect relatively inexpensive, rapid, and spatially dense data that can correlate with sparse direct observations. Consequently, these technologies can quickly and economically fill sampling gaps in the direct sampling design to generate spatial estimates or simulations. Note that proxy sampling technologies are not a substitute for direct sampling, but rather a support measure.
Proxy sampling technologies can be applied using two approaches:
- In a phased sampling approach, proxy sampling technologies are used as a screening-level assessment to provide a first approximation of spatial heterogeneity of the site. This approach optimizes the subsequent direct sampling regarding sample number, interval, and location, by modeling the spatial heterogeneity in the proxy data set.
- In a nonphased sampling approach, proxy and direct sampling technologies are implemented simultaneously.
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