Zusammenfassung
groundwater source identification problem in which
chemical signals at observation wells are used to
reconstruct the pollution loading scenario. This
inverse problem is solved using a
simulation-optimisation approach that uses a genetic
algorithm to conduct the search. As the numerical
pollution-transport model is solved iteratively during
the heuristic search, the evolutionary search can be in
general computationally intensive. This is addressed by
constructing a surrogate modelling approach that is
able to predict quickly the concentration profiles at
the observation wells. A genetic program is used in the
development of the surrogate models that provides an
acceptable prediction performance. The surrogate model,
which replaces the numerical simulation model, is then
coupled with the evolutionary search procedure to solve
the inverse problem. The results will illustrate 1) the
performance of the surrogate model in predicting the
concentration compared with the predictions using the
original numerical model, and 2) the quality of the
solution to the inverse problem obtained using the
surrogate model to that obtained using the numerical
model.
Nutzer