Estimation of Aquifer Transmissivity and Storage Coefficient by Applying Genetic Algorithm to Theis Model

Abstract

Aquifer management depends on estimation of aquifer parameters. For a confined aquifer it is common to arrange a pumping test and analyze the data by Theis graphic matching procedure to estimate aquifer transmissivity (T) and storage coefficient (S). This method is time-consuming and may lead to errors if matching of field curve to the Theis theoretical type curve is not proper. Therefore, genetic algorithms (GAs) have been used to estimate T and S. They have been applied to the Comilla region aquifer, Bangladesh. Results show that there is a good agreement between the Theis graphic match point method (TGM) and GA. Moreover, this GA is more efficient than that of TGM, because it has minimum sum of square of errors. Results of the parameters sensitivity analysis show that in every observation location there is a unique set of T and S value which would result in minimum sum of square of errors. Therefore, GA could be an efficient tool for aquifer parameters estimation in the near future.