3:30 PM - 3:45 PM
[AHW17-06] Estimating Hydrogeological Parameters Without Pumping Test Information by Coupling Time Series Analysis Method and Modified Theis Equation
Keywords:Data-driven Method, Storage Coefficient Estimation, Groundwater Level Based, Indirect observation
Fitting the Theis curve to observed drawdown caused by pumping is the common method to obtain hydrogeological parameters. However, this method requires a considerable amount of money to conduct pumping tests, consequently resulting in scarcity of on-site observations. Due to the relatively widespread availability of groundwater level(GWL) monitoring stations, this project attempts to modify the Theis equation and apply it to fit the observed fluctuations in GWL caused by pumping(hp) to obtain the hydrogeological parameters.
In original Theis equation, the pumping time series(Q(t)), GWL fluctuation causing by pumping(hp) and the distance between the pumping well and the observation well(r), need to be specified. The study introduces the "uniform pumping assumption," to derive the modified Theis equation that turn the 'r' into the pumping influence radius 'R', allowing us to no longer rely on the parameter "r." According the concept of time series analysis method, the GWL variations caused by pumping(hp*) can be simulated by the convolution of pumping impulse response function and the Q(t). If the Q(t) is steady, the hp* can be simulated by the product of the constant pumping rate(Q) and the unit step function that is equivalent to modified Theis equation under the uniform pumping assumption. Finally, the optimization method is used to fit the hp* with the hp for obtaining the hydrogeological parameters which be included in modified Theis equation. The R and the Q are concurrently estimated in optimization process, and for convergence, the transmissivity need to be given.
The proposed method is not only demonstrated on synthetic data but is also applied to field observations of GWL data to estimate storage coefficients and their uncertainty intervals. The results are then compared with storage coefficient obtained by pumping test. The result shows that mostly on-site observation is in the uncertainty range.
In original Theis equation, the pumping time series(Q(t)), GWL fluctuation causing by pumping(hp) and the distance between the pumping well and the observation well(r), need to be specified. The study introduces the "uniform pumping assumption," to derive the modified Theis equation that turn the 'r' into the pumping influence radius 'R', allowing us to no longer rely on the parameter "r." According the concept of time series analysis method, the GWL variations caused by pumping(hp*) can be simulated by the convolution of pumping impulse response function and the Q(t). If the Q(t) is steady, the hp* can be simulated by the product of the constant pumping rate(Q) and the unit step function that is equivalent to modified Theis equation under the uniform pumping assumption. Finally, the optimization method is used to fit the hp* with the hp for obtaining the hydrogeological parameters which be included in modified Theis equation. The R and the Q are concurrently estimated in optimization process, and for convergence, the transmissivity need to be given.
The proposed method is not only demonstrated on synthetic data but is also applied to field observations of GWL data to estimate storage coefficients and their uncertainty intervals. The results are then compared with storage coefficient obtained by pumping test. The result shows that mostly on-site observation is in the uncertainty range.