DARWIN'S THEORY of natural selection is being used to determine the best groundwater monitoring schemes for contaminated sites.
The University of Illinois has developed an 'optimisation tool' that it claims reduces the cost of long term sampling and monitoring of contaminated groundwater.
There are three primary components: a groundwater fate-and-transport simulation; several plume-interpolation modules; and a monitoring plan selection process, which uses a genetic algorithm.
The selection process is 'analogous to the Darwinian concept of natural selection,' explained professor of civil and environmental engineering at the University of Illinois Barbara Minsker. The algorithm identifies the best set of monitoring wells to describe the contaminant plume accurately, while keeping monitoring costs to a minimum.
Each monitoring plan is assigned a 'fitness', based on cost and error (the difference between the best estimate of plume mass and each plan's estimate). The fittest plans are allowed to 'breed' and survive into later generations, evolving into even better designs.
'Whether the goal is to contain the contaminant or to remediate it, wells must be drilled on site and routinely sampled and monitored,' Minsker said. The approach takes away the need to use trial and error to determine the best monitoring plan, which is 'complicated, tedious and time consuming', she added.
'Results have shown that our methodology is very effective at both reducing monitoring costs and accurately quantifying the mass of contaminant in the plume.'