A high-resolution water table depth (WTD) map for the contiguous United States

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本数据集为美国本土的1角秒（约30米）分辨率地下水位埋深（water table depth, WTD）地图，基于机器学习方法构建，训练数据集整合了1914—2023年间多套地下水数据库中的超100万口地下水井观测数据。研究采用包含300棵决策树的随机森林模型，以80%的数据集进行训练，输入变量涵盖气候学要素（降水、气温、潜在蒸散量PME）、地下介质属性（导水率、土壤质地）及地形特征（海拔、坡度、距河道距离），最终测试集性能指标为：相关系数r=0.79、均方根误差RMSE=14.94米、纳什效率系数NSE=0.62。 Ma Y.、Condon L.E.、Koch J.等. 高分辨率美国地下水位埋深估算结果揭示可开采地下水资源总量. 《通讯-地球与环境》(Commun Earth Environ) 7卷, 第45页 (2026年). https://doi.org/10.1038/s43247-025-03094-3 本数据集亦可通过HydroData平台获取，访问地址为https://hydroframe.org/hydrodata