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Open AccessArticle

Characterization of Hydraulic Heterogeneity of Alluvial Aquifer Using Natural Stimuli: A Field Experience of Northern Italy

Department of Engineering and Architecture, University of Parma, 43121 Parma, Italy
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Water 2019, 11(1), 176; https://doi.org/10.3390/w11010176
Received: 14 December 2018 / Revised: 10 January 2019 / Accepted: 15 January 2019 / Published: 20 January 2019
(This article belongs to the Special Issue Heterogeneous Aquifer Modeling: Closing the Gap)
This study investigates the hydraulic heterogeneity of the alluvial aquifer underneath the dam and the stilling basin of a flood protection structure in Northern Italy. The knowledge of the interactions between the water in the reservoir upstream of the dam and the groundwater levels is relevant for the stability of the structure. A Bayesian Geostatistical Approach (BGA) combined with a groundwater flow model developed in MODFLOW 2005 has been used to estimate the hydraulic conductivity (HK) field in a context of a highly parameterized inversion. The transient hydraulic heads collected in 14 monitoring points represent the calibration dataset; these observations are the results of the hydraulic stresses induced by the variations of the lake stage upstream of the dam (natural stimuli). The geostatistical inversion was performed by means of a computer code, bgaPEST, developed according to the free PEST software concept. The results of the inversion show a moderate degree of heterogeneity of the estimated HK field, consistent with the alluvial nature of the aquifer and the other information available. The calibrated groundwater model is useful for simulating the interactions between the reservoir and the studied aquifer under different flood scenarios and for forecasting the hydraulic head levels due to strong flood events. The use of natural stimuli is useful for obtaining information for aquifer heterogeneity characterization. View Full-Text
Keywords: inverse modeling; Bayesian geostatistical approach; natural stimuli; parameter estimation; hydraulic heterogeneity inverse modeling; Bayesian geostatistical approach; natural stimuli; parameter estimation; hydraulic heterogeneity
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D’Oria, M.; Zanini, A. Characterization of Hydraulic Heterogeneity of Alluvial Aquifer Using Natural Stimuli: A Field Experience of Northern Italy. Water 2019, 11, 176.

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