Imaging estimates risk of groundwater contamination
Image analysis tracks tracer dye in water as it flow through soils to calibrate propagation.
Understanding the risk of contamination spreading through soil enables better control and remediation. Dye-tracer experiments have been a well established method of studying the flow of contaminated water in soils, and a recent study by researchers at the University of Bayreuth (Bayreuth, Germany;www.uni-bayreuth.de) advances this technique.
Prof. Bernd Huwe and his colleagues Christina Bogner, Benjamin Wolf, Andreas Kolb, and Iris Schmiedinger from the soil physics group have developed an image-analysis method to study dye tracer results in soils of the vadose zone, which extends from the ground surface down to the water table. Image analysis is performed using HALCON from MVTec Software (Munich, Germany;www.mvtec.com).
In their work, the researchers show how to extract numerical information about dye coverage from digital photographs for further modeling. The data are used to estimate the risk of vertical solute propagation in the upper vadose zone and thus a possible risk of groundwater contamination.
The group used brilliant blue FCF dye tracer because of its low toxicity and good visibility against a large number of soil colors. Since the principal data acquired are digital photographs of stained soil profiles, special emphasis was given to analysis techniques such as geometrical image correction and image classification.
The field work consisted of applying the tracer solution to a plot with an automated sprinkler system, then excavating soil profiles and photographing the profiles and a calibration plate. To determine the correct color, images were taken in RAW format. Then HALCON was used to correct for radial distortion and the relative position of the camera to the soil profile.
When classifying the images, it proved difficult to distinguish the blue color of the tracer from soil color in the RGB color space, since color information is encoded in three channels. Therefore, the researchers used the hue-saturation-intensity color space, in which the color information is stored only in the first channel. A double threshold in the hue channel is sufficient to separate brilliant blue from the soil.
MATLAB from The MathWorks (Natick, MA, USA;www.mathworks.com) was used to extract dye coverage information. The blue stained areas of an image are coded black and the nonstained parts white. From this binary image, information about the number of stained pixels per depth--the dye coverage function--is extracted. This function serves as qualitative characteristics of flow dynamics and as input for a stochastic model that estimates the risk of vertical solute propagation.