A high-resolution water table depth (WTD) map for the contiguous United States
Authors/Creators
Description
A 1-arcsec (~30 m) resolution water table depth (WTD) map for the contiguous United States using machine learning methods trained on over one million well observations compiled from multiple groundwater databases spanning 1914-2023. A random forest model with 300 decision trees was trained on 80% of these data using input variables including climatology (precipitation, temperature, PME), subsurface properties (hydraulic conductivity, soil texture), and topographic features (elevation, slope, distances to streams), achieving test performance of r = 0.79, RMSE = 14.94 m, and NSE = 0.62.
Ma, Y., Condon, L.E., Koch, J. et al. High resolution US water table depth estimates reveal quantity of accessible groundwater. Commun Earth Environ 7, 45 (2026). https://doi.org/10.1038/s43247-025-03094-3
Data also accessible via the HydroData platform https://hydroframe.org/hydrodata
Files
wtd_mean_estimate_RF_additional_inputs_dummy_drop0LP_1s_CONUS2_m_v_20240813.tif
Files
(36.6 GB)
| Name | Size | Download all |
|---|---|---|
|
md5:6487e280a07161e1b418fa82a5d958e6
|
36.6 GB | Preview Download |
Additional details
Funding
- U.S. National Science Foundation
- U.S. National Science Foundation Convergence Accelerator Program CA-2040542
Software
- Repository URL
- https://github.com/HydroFrame-ML/high-res-WTD-static