Quantifying the potential of using Soil Moisture Active Passive (SMAP) soil moisture variability to predict subsurface water dynamics

Nayak, Aruna Kumar; Xu, Xiaoyong; Frey, Steven K.; Khader, Omar; Erler, Andre R.; Lapen, David R.; Russell, Hazen A. J.; Sudicky, Edward A.

doi:https://doi.org/10.5194/hess-29-215-2025

Articles | Volume 29, issue 1

https://doi.org/10.5194/hess-29-215-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-29-215-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 29, issue 1

Research article

|

15 Jan 2025

Research article |

| 15 Jan 2025

Quantifying the potential of using Soil Moisture Active Passive (SMAP) soil moisture variability to predict subsurface water dynamics

Aruna Kumar Nayak, Xiaoyong Xu, Steven K. Frey, Omar Khader, Andre R. Erler, David R. Lapen, Hazen A. J. Russell, and Edward A. Sudicky

Data sets

Quantifying the linkage between SMAP soil moisture and fully-integrated hydrologic simulations A. K. Nayak et al. https://doi.org/10.5281/zenodo.8145252

Short summary

Satellite remote sensing only measures the near-surface soil water content. We demonstrate that satellite-based near-surface soil water variability is a strong reflection of deeper subsurface water fluctuation and quantifies the response time differences between dynamics of satellite near-surface soil water and water in the deeper subsurface. Result support the use of satellite near-surface soil water measurements as indicators and/or predictors of water resources in the deeper subsurface.