Monitoring and modeling infiltration-recharge dynamics of managed aquifer recharge with desalinated seawater

We study the relation between surface infiltration and groundwater recharge during managed aquifer recharge (MAR) with desalinated seawater in an infiltration pond, at the Menashe site that overlies the northern part of the Israeli Coastal Aquifer. We monitor infiltration dynamics at multiple scales (up to the scale of the entire pond) by measuring the ponding depth, sediment water content and groundwater levels, using pressure sensors, single-ring infiltrometers, soil sensors, and observation wells. During a month (January 2015) of continuous intensive MAR (2.45 x 10(6) m(3) discharged to a 10.7 ha area), groundwater level has risen by 17m attaining full connection with the pond, while average infiltration rates declined by almost 2 orders of magnitude (from similar to 11 to similar to 0.4 m d(-1)). This reduction can be explained solely by the lithology of the unsaturated zone that includes relatively low-permeability sediments. Clogging processes at the pond-surface - abundant in many MAR operations - are negated by the high-quality desalinated seawater (turbidity similar to 0.2 NTU, total dissolved solids similar to 120 mg L-1) or negligible compared to the low-permeability layers. Recharge during infiltration was estimated reasonably well by simple analytical models, whereas a numerical model was used for estimating groundwater recharge after the end of infiltration. It was found that a calibrated numerical model with a one-dimensional representative sediment profile is able to capture MAR dynamics, including temporal reduction of infiltration rates, drainage and groundwater recharge. Measured infiltration rates of an independent MAR event (January 2016) fitted well to those calculated by the calibrated numerical model, showing the model validity. The successful quantification methodologies of the temporal groundwater recharge are useful for MAR practitioners and can serve as an input for groundwater flow models.