M.Sc Student | Shlomi Shahar |
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Subject | Development of Methodologies for Optimal Groundwater Quality Monitoring |

Department | Department of Civil and Environmental Engineering |

Supervisors | Professor Hillel Rubin |

Professor Avi Ostfeld |

Groundwater, the primary source of drinking water worldwide, is easily contaminated. This contamination has to be quantified by sampling the aquifer at a number of wells and mathematically interpolating or physically modeling discrete values into maps of contaminant plumes . However, the number of available samples is limited. Previous studies have shown that the apparent shape of a contaminant plume is extremely sensitive to the choice of wells. Thus, the objective of this work is to develop an algorithm which would choose the optimal wells for sampling.

The algorithms developed in this thesis are all based on the following factors which encourage sampling at a specific site:

- Concentration.
- Pumping discharge.
- Total contaminant mass.
- Uncertainty.

The Well Utility Function presented in this work simply sums up these factors, weighted according to user-defined weights. The Cell Utility Function considers rectangular area cells, an improvement from the WUF; however, it was plagued by too many undetermined parameters (size of grid, threshold) and by the rigidity of the rectangular cells.

Finally, the Utility Density Function was defined as a continuous function, whose integral over an area returned that area’s utility for sampling. A genetic algorithm found the best partition of the aquifer, in which the variance of the utility functions of the different polygonal cells was minimal. In the next step, one well was chosen for sampling in each cell.

The algorithms were tested on several environmental settings, and in general the results of each algorithm surpassed its precedents.