Integrated approach for characterizing aquifer heterogeneity in alluvial plains

Abstract. This study introduces a robust methodology for characterizing heterogeneity in alluvial aquifers by integrating borehole data, electrical resistivity tomography (ERT) and stochastic modeling. The approach was tested in the Varaždin aquifer to simulate the distribution of four hydrofacies identified from borehole data: gravel (G), gravel, sandy to clayey (Gsc), sand with gravel, clayey to silty (Sgcs), and clay to silt, sandy (CSs). The spatial distribution of hydrofacies was modeled using the combination of geostatistical and stochastic tools. Entropy factor analysis reveals a lack of consistent vertical transition patterns between hydrofacies, highlighting the role of relative proportions in determining their spatial distribution. As the thin Sgcs-CSs layer limited the ERT resolution below 20 m depth, synthetic models were incorporated into the ERT analysis to provide more reliable delineation of hydrofacies at greater depths. The resulting dimensions of the lens-shaped structures revealed horizontal hydrofacies continuity, and were incorporated into horizontal Markov chain models. The 3D Markov chain models were used to generate 10 stochastic realizations of the hydrofacies distribution. The validation results identified the representative hydrofacies model for the Varaždin aquifer with a prediction accuracy of 63 %, which is consistent with findings from similar studies. Results from simulations focused on the Vinokovšćak wellfield area show that the integration of ERT data into the model development improves the hydrofacies prediction accuracy by 0.3 to 5.0 %, depending on the grid resolution. The analysis of different grid resolutions demonstrates that the optimal cell size is closely related to the lens length. While smaller grids fail to capitalize on finer resolution due to oversegmentation, coarser grids provide a simplified hydrofacies model, potentially increasing prediction accuracy but losing spatial resolution. This methodology forms a basis for integrating spatial heterogeneity into groundwater models, serving as a practical tool for sustainable management in alluvial and other sedimentary environments worldwide.