Parameter estimation for a karst aquifer with unknown thickness using the genetic algorithm method

The thickness of an aquifer (B) is a critical hydrogeologic parameter in understanding groundwater system, especially in a karst aquifer where the high heterogeneity in this parameter brings more uncertainty to the evaluation of groundwater resources. In this study, the genetic algorithm (GA) method was used to estimate B, as well as five other parameters, including K_r (horizontal hydraulic conductivity), K_z (vertical hydraulic conductivity), S (storativity), S_y (specific yield), and α (delayed coefficient) of a karst aquifer based on a pumping test. The search bounds of the six parameters for the GA method were obtained from numerous hypothetic numerical tests. The feasibility of the GA method for parameter estimation was verified by the results obtained from the gradient method in terms of a pumping test conducted in the Platte River valley in Nebraska. Then, this approach was used to estimate the hydraulic parameters in a karst aquifer with unknown aquifer thickness based on a pumping recovery test conducted in the Houzhai karst basin, southwestern China. The results show that the K_r, K_z, and the anisotropy ratio of K_r to K_z are strongly affected by B. The differences between the estimated parameter values at two observation wells indicate the existence of high heterogeneity in the karst aquifer. The parameter B has the highest absolute normalized sensitivity among these variables, implying that the estimated B may be more reliable as compared to other parameters. This study demonstrates that the GA method is an alternative method of parameter estimation with the unknown aquifer thickness.