Geophysical imaging of watershed subsurface patterns and prediction of soil texture and water holding capacity

aboucher - Posted on 12 May 2009

TitleGeophysical imaging of watershed subsurface patterns and prediction of soil texture and water holding capacity
Publication TypeJournal Article
Year of Publication2008
AuthorsAbdu, H, Robinson DA, Seyfried M, Jones SB
Date PublishedDEC 23
Type of ArticleArticle
AbstractThe spatial distribution of subsurface soil textural properties across the landscape is an important control on the hydrological and ecological function of a watershed. Traditional methods of mapping soils involving subjective assignment of soil boundaries are inadequate for studies requiring a quantitative assessment of the landscape and its subsurface connectivity and storage capacity. Geophysical methods such as electromagnetic induction (EMI) provide the possibility of obtaining high- resolution images across a landscape to identify subtle changes in subsurface soil patterns. In this work we show how EMI can be used to image the subsurface of a similar to 38 ha watershed. We present an imaging approach using kriging to interpolate and sequential Gaussian simulation to estimate the uncertainty in the maps. We also explore the idea of difference ECa mapping to try to exploit changes in soil moisture to identify more hydrologically active locations. In addition, we use a digital elevation model to identify flow paths and compare these with the ECa measurement as a function of distance. Finally, we perform a more traditional calibration of ECa with clay percentage across the watershed and determine soil water holding capacity (SWHC). The values of SWHC range from 0.07 to 0.22 m(3) m(-3) across the watershed, which contrast with the uniform value of 0.13 derived from the traditional soil survey maps. Additional work is needed to appropriately interpret and incorporate EMI data into hydrological studies; however, we argue that there is considerable merit in identifying subsurface soil patterns from these geophysical images.