1-2 Using AI Engines to Design and Implement Groundwater Managed Aquifer Recharge Structures

Session: Advances in Managed Aquifer Recharge

Presenting Author:

Authors:

Abstract:

Freshwater resources are being depleted at a growing rate, yet flooding events continue to damage lives and landscapes. This water paradox reflects a larger issue in geosciences: the gap between academic research and real-world implementation of managed aquifer recharge (MAR) solutions. This research aims to identify gaps in present MAR structure decision making and fill them using an AI tool. After reviewing current literature and design approaches for groundwater recharge structures, we identified patterns in both methodology and limitations. In response, an AI model was developed that supports decision-making by analyzing surface and subsurface site conditions and helping detect patterns that inform structure placement and performance projections. AI in this project functions as a thought partner, a mirror that clarifies decisions and speeds up pattern recognition, not as a replacement for human insight. This work highlights the value of pairing scientific innovation with strategic action, and how AI can help geoscientists bring their ideas closer to the fruition. 

Geological Society of America Abstracts with Program. Vol. 57, No. 6, 2025

doi: 10.1130/abs/2025AM-10968

© Copyright 2025 The Geological Society of America (GSA), all rights reserved.