Global Surface Soil Moisture Drydown Patterns

Understanding the global soil moisture (SM) dynamics and its governing controls beyond the Darcy Scale is critical for various hydrological, meteorological, agricultural, and environmental applications. In this study, we parameterize the pathways of global surface SM (theta(RS)) drydowns using seasonal observation from Soil Moisture Active Passive (SMAP) satellite (between 2015 and 2019) at 36 km resolution. We develop a new data-driven nonparametric approach to identify the canonical forms of theta(RS) drydown, followed by a nonlinear least squares parameterization of the seasonal drydown pathways at each SMAP footprint. The derived parameters provide the effective soil water retention parameters (SWRPeff), land-atmospheric coupling strength and soil hydrologic regimes for SMAP footprint. Depending on the footprint heterogeneity, climate, and season, the characteristics curves comprising different drydown phases are discovered at SMAP footprints. Drydown curves respond to the within-footprint changes in the meteorological drivers, land-surface characteristics, and the soil-vegetative and atmospheric dynamics. Drydown parameters display high interseasonal variability, especially in the grasslands, croplands, and savannah landscapes due to significant changes in the landscape characteristics and moisture patterns at the subgrid-scale. Soil texture exerts influence on the soil water retention and drydown parameters only when the footprint mean theta(RS) is low, specifically in arid and sparsely vegetated regions. The interseasonal variability of the SWRPeff is primarily driven by the landuse and climate of the SMAP footprint. A global understanding of the SM drydown features at SMAP footprint provides a significant step toward a scale-specific, effective soil hydrologic parameterization for various applications.

Automated summary

Understanding the seasonal patterns of global surface soil moisture drydowns is crucial for various applications in hydrology, meteorology, agriculture, and the environment. This study developed a data-driven approach to parameterize the drydown pathways at each SMAP footprint, revealing significant interseasonal variability and the influence of soil texture and climate on soil water retention and drydown parameters. This research represents a significant step towards scale-specific, effective soil hydrologic parameterization for diverse applications.