We present a multi-objective stochastic optimization method for the design of monitoring networks for the initial detection of groundwater contamination at waste disposal facilities. A Monte Carlo approach is used to generate a large number of equally likely realizations of a random hydraulic conductivity field and a leak location. A finite-difference groundwater flow model and a particle-tracking model is used to generate a contaminant plume for each realization. Information from the flow and transport simulations is passed to an optimization model based upon a facility location analogy. The optimization model is a large integer programming problem which is solved by the method of simulated annealing. Optimal trade-off curves among three conflicting objectives are obtained. These objectives are: (1) maximum detection probability, (2) minimum cost (i.e., minimum number of monitoring wells), and (3) minimum volume of contaminated groundwater at the time of detection. The model is applied to a hypothetical scenario in order to examine the sensitivity of the trade-off curves to various model parameters.
|Original language||English (US)|
|Number of pages||9|
|Journal||Models for assessing and monitoring groundwater quality, Proc. symposium, Boulder, 1995|
|State||Published - Dec 1 1995|
ASJC Scopus subject areas
- Earth and Planetary Sciences(all)
- Environmental Science(all)