Abstract

Managed aquifer recharge (MAR) is an emerging solution to effectively replenish overused groundwater resources, but high associated costs often hinder its uptake. There are several parameters to consider when determining the cost of MAR, including recharge types, MAR schemes scale, land acquisition, operation and maintenance period, and the hydrogeological setting. Hydraulic conductivity and its spatial variability are the most significant hydrogeological parameters for predicting infiltration rates at MAR sites, but limited data availability makes accurate predictions often challenging. Hence, it is essential to increase data availability to optimize MAR efficiency and to better assess its economic performance. Therefore, a novel approach for MAR planning is presented in this article to efficiently enhance the data availability during the conceptual stage of MAR planning by combining site exploration, spatially resolved infiltration rate estimation, and cost analysis. The approach was applied at an actual MAR site in Vincenza, Italy, and incorporated an electromagnetic induction survey and direct push profiling as across-scale investigation methods to enhance site delineation and subsequent parameterization of the identified zones using laboratory analysis of collected samples. This MAR site is particularly suitable for its heterogeneous subsurface structure and potential to counteract groundwater depletion. The performed investigation resulted in an image of the lateral variation of subsurface conditions and allowed the delineation of three zones with different infiltration behavior, with 99.5% of infiltration occurring in just two zones, representing only 22.1% of the site. In this particular scenario, the overall cost per cubic meter of recharged water can be reduced by 59.1% by identifying and eliminating unfavorable zones. This study provides scientists and practitioners with a useful tool for MAR planning that can be applied to a wide range of sites with complex geology, thereby reducing water costs, minimizing the environmental impact of infrastructure construction, and reducing land use conflicts.

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