Automated image analysis for experimental investigations of salt water intrusion in coastal aquifers
- Submitting institution
-
Brunel University London
- Unit of assessment
- 12 - Engineering
- Output identifier
- 239-187830-23981
- Type
- D - Journal article
- DOI
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10.1016/j.jhydrol.2015.09.046
- Title of journal
- Journal Of Hydrology
- Article number
- -
- First page
- 350
- Volume
- 530
- Issue
- -
- ISSN
- 0022-1694
- Open access status
- Out of scope for open access requirements
- Month of publication
- November
- Year of publication
- 2018
- URL
-
http://bura.brunel.ac.uk/handle/2438/16463
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
1 - Energy & Environment
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A novel methodology has been developed to quantify important saltwater intrusion parameters in a sandbox experiment using image analysis. Existing methods found in the literature are based mainly on visual observations, which are subjective, labour intensive and limit the temporal and spatial resolutions that can be analysed. A robust error analysis was undertaken to determine the optimum methodology to convert image light intensity to concentration. This paper, and other papers of the author, led to major EPSRC grant EP/R019258/1 in collaboration with Imperial College London and Queen’s University Belfast where the investigators studying saline water intrusion in field scale.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -