Accurate estimates of root zone soil moisture (RZSM) at relevant spatio-temporal scales are
essential for many agricultural and hydrological applications. Applications of machine …

Soil moisture content (SMC) information at field scale could have important applications in
agricultural and regional water management. This study presents an operationally …

Soil temperature and moisture are important variables controlling ecological processes, but
continuous high-resolution data are rarely available. Therefore, we used the correlation with …

Obtaining accurate information regarding root zone soil moisture (RZSM) is a critical
element of effective hydrological and agricultural management practices. Previous studies …

The North China Plain is a crucial agricultural region in China, but irregular precipitation
patterns have led to significant water shortages. To address this, analyzing the high …

The sustainability of limited freshwater resources in coastal settings requires an
understanding of the processes that affect them. This is especially relevant for freshwater …

The sustainability of limited freshwater resources in coastal settings requires an
understanding of the processes that affect them. This is especially relevant for freshwater …

Entropy Randomization in Machine Learning presents a new approach to machine learning—
entropy randomization—to obtain optimal solutions under uncertainty (uncertain data and …

The focus of this study is the 1938 Rio Grande Compact water supply. The compact is an
interstate agreement signed in 1938 between the states of Colorado, New Mexico, and …

The prediction of spatial and temporal variation of soil water content brings numerous
benefits in the studies of soil. However, it requires a considerable number of covariates to be …