Eliminating Noise of Pumping Test Data Using the Theis Solution Implemented in the Kalman Filter

This study presents a novel approach that integrates the Kalman filter and genetic algorithms to obtain the hydraulic parameters of a confined aquifer with precision, eliminating noise that is not normally considered in traditional procedures; these parameters are necessary for the design of wells, the calculation of water balances and the numerical modeling of aquifers. The Theis solution for horizontal radial groundwater flow to an extraction well within a confined aquifer is implemented in the Kalman filter to calibrate the hydraulic transmissivity and the storage coefficient, minimizing the differences between drawdown estimates and the Theis solution by means of genetic algorithms. The estimate error variances provided by the method allowed for the quantification of an approximate average drawdown measurement error of 0.12 m and 0.02 m, respectively, during the execution of two pumping tests.