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ARS Home » Southeast Area » Jonesboro, Arkansas » Delta Water Management Research » Research » Publications at this Location » Publication #407415

Research Project: Optimizing the Management of Irrigated Cropping Systems in the Lower Mississippi River Basin

Location: Delta Water Management Research

Title: Optimizing the quantity of recharge water into a sedimentary aquifer through infiltration galleries using a surrogate assisted coupled simulation-optimization approach

Author
item ROY, DILIP - Arkansas State University
item LESLIE, DEBORAH - University Of Memphis
item Reba, Michele
item HASHEM, AHMED - Arkansas State University
item BELLIS, EMILY - Arkansas State University
item NOWLIN, JOHN - Arkansas State University

Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/22/2024
Publication Date: 4/6/2024
Citation: Roy, D., Leslie, D., Reba, M.L., Hashem, A.A., Bellis, E., Nowlin, J. 2024. Optimizing the quantity of recharge water into a sedimentary aquifer through infiltration galleries using a surrogate assisted coupled simulation-optimization approach. Journal of Hydrology. 635(131183):1-19. https://doi.org/10.1016/j.jhydrol.2024.131183.
DOI: https://doi.org/10.1016/j.jhydrol.2024.131183

Interpretive Summary: Excessive irrigation water removal leads to groundwater depletion in the Mississippi River Valley Alluvial Aquifer (MRVAA). The MRVAA is crucial for agriculture in the Lower Mississippi River Basin, making it important to find a sustainable solution to preserve this vital water source. To address the problem, we proposed a Managed Aquifer Recharge (MAR) approach to inject surface water from an on-farm storage reservoir back into the aquifer through an infiltration gallery. We used a simulation-optimization (S-O) approach, including surrogate models, to determine the optimal amount of water to inject and mitigate groundwater depletion. The study found that the planned groundwater recharge strategy based on the S-O approach and surrogate models effectively minimized groundwater depletion in the MRVAA. This approach shows promise for addressing groundwater depletion issues in other aquifers and geographic locations affected by extensive agricultural practices. Water resource managers, agricultural stakeholders, and researchers in areas with extensive agricultural practices and groundwater depletion issues, particularly those relying on alluvial aquifers, would benefit from and be interested in this research to develop sustainable management strategies.

Technical Abstract: The Mississippi River Valley Alluvial Aquifer (MRVAA) is the main irrigation source for the Lower Mississippi River Basin. Irrigation water abstraction to meet the demands for extensive agricultural practices has contributed to groundwater depletion in this area. A managed aquifer recharge (MAR) approach has been proposed in this geographic location to minimize the impact of pumping on groundwater depletion. However, it is essential to determine the optimal amount of water to be injected through a MAR technique to reduce the decline in groundwater heads. This paper utilizes a coupled simulation-optimization (S-O) approach to estimate the optimal recharge volume into the alluvial aquifer through infiltration galleries. The aquifer processes were simulated using a physically based, three-dimensional finite-difference numerical code, MODFLOW. The MODFLOW model was calibrated and validated using the injection rates and available groundwater head data for 26 months (27 February 2020 to 27 May 2022). The calibrated and validated models were then deployed within the coupled S-O approach to develop an aquifer recharge management model to estimate optimal groundwater injection rates to minimize groundwater decline. Computational efficiency of the aquifer recharge management model was achieved using surrogate models emulating the flow processes of MODFLOW. Our evaluation demonstrates that a planned transient groundwater recharge strategy, obtained as a solution of the surrogate model based coupled S-O approach, is a useful management strategy for optimized water injection and groundwater depletion control. This study shows the promise of the surrogate model based coupled S-O approach to potentially reduce the groundwater depletion in the MRVAA through using optimized injection rates at the infiltration galleries. This work has potential applications to other aquifers and geographic locations to mitigate groundwater depletion issues due to extensive agricultural practices.