Image analysis method for the measurement of water saturation in a two-dimensional experimental flow tank

Abstract

A novel, non-invasive imaging technique is proposed that determines 2D maps of water content in unsaturated porous media. This method directly relates digitally measured intensities to the water content of the porous medium. This method requires the classical image analysis steps, i.e., normalization, filtering, background subtraction, scaling and calibration. The main advantages of this approach are that no calibration experiment is needed, because calibration curve relating water content and reflected light intensities is established during the main monitoring phase of each experiment and that no tracer or dye is injected into the flow tank. The procedure enables effective processing of a large number of photographs and thus produces 2D water content maps at high temporal resolution. A drainage / imbibition experiment in a 2D flow tank with inner dimensions of 40 cm x 14 cm x 6 cm (L x W x D) is carried out to validate the methodology. The accuracy of the proposed approach is assessed using a statistical framework to perform an error analysis and numerical simulations with a state-of-the-art computational code that solves the Richards' equation. Comparison of the cumulative mass leaving and entering the flow tank and water content maps produced by the photographic measurement technique and the numerical simulations demonstrate the efficiency and high accuracy of the proposed method for investigating vadose zone flow processes. Finally, the photometric procedure has been developed expressly for its extension to heterogeneous media. Other processes may be investigated through different laboratory experiments which will serve as benchmark for numerical codes validation.

Quantification of Uncertainties from Image Processing and Analysis in Laboratory-Scale DNAPL Release Studies Evaluated by Reflective Optical Imaging

“…In most DNAPL migration and entrapment experiments, images are sequentially taken over time (e.g., [34,45]). Temporal fluctuations in light intensity (due to, e.g., light power supply) can make comparison of sequential images challenging, as threshold values for delineating DNAPL can change (e.g., [66]). Spatial variations in light intensity within a single image can lead to similar issues [14,30].…”

“…In many cases, multi-channel images must be converted to single-channel images (e.g., grayscale spectrum) and resolution is further lost. Filtering approaches can be used to minimize optical noise for contrast enhancement (e.g., [66]), but they may lead to information loss.…”

“…The latter should be tested for different experimental setups (e.g., water-unsaturated soils, LNAPL compounds, saltwater intrusion), other non-consolidated porous media (e.g., silty sand, clay lenses, combinations of several sediment fractions), and fractured rock (e.g., sandstone, limestone) in order to point out the flexibility and transferability of the IPA framework presented here. [34,49,80] [ 56,62,66,68,76,78,79] Converting to gray scale [48] [ 82,83] Correction of spatially non-uniform illumination Correction using a reference image, either flat-field image or without tracer and then dividing, subtracting or normalizing to the image - [62,84,85] Converting by using adaptive thresholding algorithm using percent distance between peaks…”

“…Image normalization using black and white cards or grey cards [56] [ 66,76] Correction using white card or gray card or reference areas [29,30] [ 60,77,78] Standardization of image - [69,79] Color model change to uncover required information Conversion to HSI or YCbCr [42,49,68,80] -…”

Laboratory Experiments of Drainage, Imbibition and Infiltration under Artificial Rainfall Characterized by Image Analysis Method and Numerical Simulations

“…For our study, LRM was used because it can be conducted with non-transparent porous media and wide flow tanks; LTM is dedicated rather to transparent media of small dimensions, while MIAM is much more expensive to access saturation of different phases in porous media. Image analysis based on reflected light has largely been used for intermediate-scale experiments (e.g., [23,[25][26][27][28][29][30][31][32][33][34][35][36][37][38]). Application of quantitative photometric procedures for unsaturated flow characterization is less widespread, and even less so with the LRM.…”