Data and Code for Explainable AI Analysis of Arctic Coastal Groundwater Dynamics

This repository contains the machine-learning-ready datasets and Jupyter Notebook used in the study of groundwater storage and submarine groundwater discharge dynamics along the Arctic coast of Simpson Lagoon, Alaska. The related manuscript investigated the time-dependent influence of atmospheric, thermal, and oceanic controls on groundwater storage and discharge using three deep learning architectures (1D-CNN, LSTM, GRU). The original groundwater and lagoon field observations collected during the 2022 thaw and summer seasons (June-September) are archived separately in Demir et al. (2026a). The datasets provided here consist of processed and quality-controlled groundwater lagoon observations merged with atmospheric and oceanic variables obtained from reanalysis products (MERRA-2 and GLDAS) and weather stations. Reanalysis atmospheric variables were obtained from NASA GES DISC (Acker & Leptoukh, 2007) a ~15 km × 15 km region surrounding the site. This repository also includes code for data pre-processing, deep learning model training, model evaluation, and eXplainable Artificial Intelligence (XAI) analyses using SHapley Additive exPlanations (SHAP). These resources enable full reproduction of the analyses used in the related manuscript, and provide a framework for applying XAI to Arctic coastal groundwater systems and other data-limited hydrologic systems. References: Acker, J. G., & Leptoukh, G. (2007). Online analysis enhances use of NASA earth science data. Eos, Transactions American Geophysical Union, 88(2), 14–17. https://doi.org/10.1029/2007EO020003 Demir, C., J. A. Guimond, E. Bristol, E. Bullock, J. W. McClelland, M. A. Charette, M. B. Cardenas (2026a). Hydrological and thermal field measurements at an Arctic coastal site, Simpson Lagoon, Alaska (2021-2022), HydroShare, https://doi.org/10.4211/hs.b2f0fcd9f2834f79a4b9216ad717eb69 Related manuscript: Demir, C., Gomez-Velez, J. D., Guimond, J. A., McClelland, J. W., Charette, M. A., and Cardenas, M. B. Time-varying hydroclimatic and oceanic controls on Arctic submarine groundwater discharge inferred using explainable AI.