A methodology for uncertainty quantification of dewatering volumes under the context of open-cast mining

Groundwater modelling at the mine sites involves assumptions from the geological model, mining stages, parametrization, and fractures, among others. Modelling work mainly focuses on calibrating against historical measurements before operations (pre-mining) or afterwards (transient calibration). Calibration is carried out mainly with gradient-based algorithms. However, the majorlimitation is the number of model runs, since the number of parameters can easily reach hundreds or more. PEST has become the common tool for parameter estimation. The Jacobin calculation required for the Levenberg Marquardt algorithm requires several model runs. This, a limited factor for the calibration and, subsequently, uncertainty quantification. The next generation of PEST, named PESTPP, is gained popularity in the groundwater community. The great advantage of PESTPP,, compared to the classical PEST, is its new module, Iterative Ensemble Smoother (IES). PESTPP-IES covers both parameter estimation and uncertainty quantification in one goal. Its empirical formulation of the Jacobian matrix reduces the number of runs; thus, the numerical bottleneck can be significantly reduced. PESTPP-IES has been extensively tested in an open-pit mine at the geological complex conditions in the Peruvian Andes. The work involves the task of model simplification, e.g., from a regional model to a detailed local pit model, calibration and uncertainty quantification of pit dewatering volumes. Detailed model was kept calibrated based on hydraulic-head measurements, and dewatering volumes were predicted. All these consider transient changes in the mining plan within the same FEFLOW model. Results validate the methodology and practicability in mining applications.