Automated image analysis for experimental investigations of salt water intrusion in coastal aquifers

Abstract

General rights Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Abstract 10A novel methodology has been developed to quantify important saltwater intrusion parameters in a 11 sandbox experiment using image analysis. Existing methods found in the literature are based mainly 12 on visual observations, which are subjective, labour intensive and limit the temporal and spatial 13 resolutions that can be analysed. A robust error analysis was undertaken to determine the optimum 14 methodology to convert image light intensity to concentration. Results showed that defining a 15 relationship on a pixel-wise basis provided the most accurate image to concentration conversion and 16 allowed quantification of the width of the mixing zone between saltwater and freshwater. A high 17 image sample rate was used to investigate the transient dynamics of saltwater intrusion, which 18 rendered analysis by visual observation unsuitable. This paper presents the methodologies developed 19 to minimise human input and promote autonomy, provide high resolution image to concentration 20 conversion, and allow the quantification of intrusion parameters under transient conditions. 21

Experimental saltwater intrusion in coastal aquifers using automated image analysis: Applications to homogeneous aquifers

“…The sandbox and instrumentation used in the experiment are described in Robinson et al (2015). The tank consisted of a central viewing chamber of dimensions (Length x Height x Depth) 0.38 m x 0.15 m x 0.01 m made from clear Perspex, and flanked by two large chambers at either side to provide the hydrostatic pressure boundary conditions.…”

“…Ten images were taken each time the camera was triggered (every 30 seconds) and the average of these images was used in the analysis. The light intensity-concentration conversion is determined through a calibration procedure, which is discussed in detail in Robinson et al (2015).…”

An Advanced Calibration Method for Image Analysis in Laboratory-Scale Seawater Intrusion Problems

“…Recently, Robinson et al (2015) proposed an automated image analysis approach based on a pixel-wise regression method, which provided low errors in converting light intensity to concentration, and allowed for the analysis of density variations across the saltwaterfreshwater interface. The main disadvantage of the pixel-wise regression method is that the calibration is entirely specific to the test domain.…”

“…A new calibration was required for each test case, even for homogeneous cases of the same bead diameter. In the case of Robinson et al (2015) the calibration process took at least 4 h to complete, and contributed significantly to the 7-12 h required for preparing each domain for testing. For larger scale experiments the calibration process could be considerably longer.…”

“…For larger scale experiments the calibration process could be considerably longer. Furthermore, Robinson et al (2015) observed significant air pockets accumulating within a saturated sandbox of porous media that was left for an extended period of time. Air pockets appear as dark spots in the captured images and introduce errors into the image light intensity to concentration conversion.…”