Here are some datasets from work that the research group has done. Please cite if you use these data!

• Groundwater withdrawals over Kansas (predicted with machine learning and observed) from 2002-2019

  • Observed groundwater withdrawals and ancillary data for predictions:  https://github.com/montimaj/HydroMST/tree/master/Inputs/Files_Apr_Sept/Actual_GW_Rasters

  • Predicted groundwater withdrawals: https://github.com/montimaj/HydroMST/tree/master/Outputs/Output_Apr_Sept/Predicted_Rasters 

  • Citation: Majumdar, S., Smith, R., Butler Jr, J. J., & Lakshmi, V. (2020). Groundwater withdrawal prediction using integrated multitemporal remote sensing data sets and machine learning. Water Resources Research, 56(11), e2020WR028059. 

• Airborne electromagnetic soundings at three locations in the San Joaquin Valley, CA

  • https://scholarsmine.mst.edu/research_data/1/ 

  • Citation: Smith, R., & Knight, R. (2019). Modeling land subsidence using InSAR and airborne electromagnetic data. Water Resources Research, 55, 2801– 2819. https://doi.org/10.1029/2018WR024185 

• Groundwater storage change in the Parowan Valley, Utah, estimated using pumping, water level and satellite (Interferometric Synthetic Aperture Radar, or InSAR) data

  • Citation: Smith, R., Li, J., Grote, K., & Butler, J. (2023). Estimating aquifer system storage loss with water levels, pumping and InSAR data in the Parowan Valley, Utah. Water Resources Research, 59, e2022WR034095. https://doi.org/10.1029/2022WR034095