Soil moisture is a key environmental variable. There is a lack of software to facilitate non-
specialists in estimating and analyzing soil moisture at the field scale. This study presents a
new open-sourced R package mlhrsm, which can be used to generate Machine Learning-
based high-resolution (30 to 500 m, daily to monthly) soil moisture maps and uncertainty
estimates at selected sites across the contiguous USA at 0–5 cm and 0–1 m. The model is
based on the quantile random forest algorithm, integrating in situ soil sensors, satellite …

Soil moisture is a key variable for a variety of applications including agricultural
management, ecological modeling, weather forecasting, and environmental monitoring. It
varies from the field to global scales and from seconds to decades as a function of
meteorological forcing, vegetation, soil texture, topography, and water resources
management. Combinations of observations from ground-based sensors and/or remote
sensing platforms and empirical or mechanistic models have provided soil moisture maps …