Abstract
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.
Highlights
In the last two decades, several flood events occurred and caused loss of life and huge damages to infrastructures [1,2,3]
The flood control reservoirs aim to dampen the river flood waves storing, in a reservoir, the excess water and releasing it downstream at a controlled rate. These structures are located close to the riverbed and, since the reservoir water levels can rapidly increase during a flood event, it is important to study the interactions between the formed lake and the underneath aquifer
In the last two decades, the challenge of determining the aquifer hydraulic parameters starting from field data is still motivating the development of new approaches; see, for instance, references [4,5,6,7,8,9,10,11,12]
Summary
In the last two decades, several flood events occurred and caused loss of life and huge damages to infrastructures [1,2,3]. The flood control reservoirs aim to dampen the river flood waves storing, in a reservoir, the excess water and releasing it downstream at a controlled rate These structures are located close to the riverbed and, since the reservoir water levels can rapidly increase during a flood event, it is important to study the interactions between the formed lake and the underneath aquifer. In the last two decades, the challenge of determining the aquifer hydraulic parameters starting from field data (transmissivity measurements and/or hydraulic heads) is still motivating the development of new approaches; see, for instance, references [4,5,6,7,8,9,10,11,12] These references are by no means exhaustive and serve only to highlight the importance of the overall problem of parameter estimation. The Bayesian Geostatistical Approach (BGA) [13] has become popular for estimating aquifer hydraulic parameters [14,15,16], inflow time series to river sections [17,18] or flow hydrograph in different contexts [19,20] and has been implemented in a freeware software named bgaPEST [21]
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