Optimizing aquifer storage and recovery performance through reactive transport modeling

Water quality deterioration is a common phenomenon that may limit the recovery of injected water during aquifer storage and recovery (ASR). Quality deterioration is often caused by the oxidation of reduced aquifer components by oxygenated source water, the subsequent pH decline, and induced dissolution of carbonate minerals. We use a previously calibrated reactive transport model (PHREEQC) to optimize ASR depending on source water quality and kind of pretreatment. We give quantitative projections on the performance increase over successive cycles with respect to specific water quality indicators. We simulate the response of a representative, deeply anoxic aquifer upon injection of three different commonly applied oxygenated water types: pre-treated drinking water, desalinated seawater, and urban storm water. The model is coupled to a Python script that automatically stops recovery and starts the next injection phase when certain specified concentration thresholds are exceeded. This setup enables realistic simulations to gradually create a buffer zone around the ASR well that allows 100% recovery at a specific stage of aquifer development. Each source water type was associated with different issues causing the deterioration of the abstracted water quality with respect to Fe(II), Mn(II), and As. The injection of pre-treated drinking water caused Mn(II) exceedances that disappeared after a number of cycles, provided that the recovery would halt as soon as the Mn(II) exceedances would occur. The injection of desalinated water caused persisting Fe(II) exceedances, which substantially slowed the creation of an effective buffer zone; whereas, the injection of urban storm water caused similar issues with respect to arsenic. For both cases, it was shown that enriching the source water with O2 and/or NaOH had major positive effects by accelerating the creation of an efficient buffer zone. Finally, we simulated a long-term operational rest of the ASR plant to evaluate water quality effects during potential migration of the stored water due to lateral groundwater flow, as dependent on source water composition and pretreatment method. Exceedances of drinking water guidelines occurred long before the arrival of the native water. Fe(II) and Mn(II) exceedances, after having used desalinated and drinking water, respectively, were observed after a bubble migration of 9% and 40%, respectively, and were associated with the slightly acidic pH conditions promoting the dissolution of Mn-carbonate and preventing an efficient sorptive removal. The arsenic exceedances, after using urban storm water, were associated with the arsenic wave deriving from the pyrite oxidation and reaching the ASR well after 34% of bubble migration. Enrichment of the source water with O2 and/or NaOH was also helpful in protecting the water quality around the ASR well for a longer time during a bubble migration scenario. The Fe(II) breakthrough occurred after 59% of desalinated bubble migration (instead of 9%) whereas As broke through after 70% of urban storm bubble migration (instead of 34%). This study illustrates that reactive transport modeling with a calibrated model is a useful tool to a-priori test the potential effectiveness of various operational options in ASR application on improving recovered water quality and the recovery efficiency.