Skip to main content
ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #397748

Research Project: From Field to Watershed: Enhancing Water Quality and Management in Agroecosystems through Remote Sensing, Ground Measurements, and Integrative Modeling

Location: Hydrology and Remote Sensing Laboratory

Title: Late-fall satellite-based soil moisture observations show clear connections to subsequent spring streamflow

item KOSTER, RANDALL - National Aeronautics And Space Administration (NASA)
item LIU, QING - National Aeronautics And Space Administration (NASA)
item Crow, Wade
item REICHLE, ROLF - National Aeronautics And Space Administration (NASA)

Submitted to: Nature Communications
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/7/2023
Publication Date: 6/15/2023
Citation: Koster, R.D., Liu, Q., Crow, W.T., Reichle, R.H. 2023. Late-fall satellite-based soil moisture observations show clear connections to subsequent spring streamflow. Nature Communications. 14:35-45.

Interpretive Summary: We currently live in an era of increasing uncertainty regarding the availability of sufficient water resources for municipal, industrial, and agricultural uses. As a result, new techniques for accurately forecasting future water availability are badly needed. In this paper, we quantify the value of a new type of observation - surface soil moisture estimates obtained from a satellite-based radiometer - for forecasting future variations in streamflow. We find that soil moisture estimates on November 30 of each year explain about 25% of the total inter-annual variability in streamflow for the following spring period (i.e., February to March). This performance is better than many existing long-term streamflow forecasting models and suggests that such models can be significantly improved via the appropriate inclusion of satellite-based soil moisture information. This result will eventually be used by operational forecasting agencies to improve our ability to mitigate inter-annual variations in the availability of springtime streamflow.

Technical Abstract: Soil moisture retrievals obtained with NASA’s Soil Moisture Active Passive (SMAP) instrument within 236 intermediate-scale (2,000 – 10,000 km2) unregulated river basins in the conterminous US are time-averaged with an exponential filter during each fall of 2015-2021 to capture interannual variations in the basins’ profile soil water content. The temporal correlation coefficient (R) between the estimated November 30 profile soil moistures and corresponding total streamflow amounts during the following February to May period are then computed and found to be significant – the R values are positive for 92% of the basins, with an average value of 0.43. The average increases to 0.50 within the subset of 158 basins for which retrievals are known, based on SMAP quality flags, to be more accurate. These correlations highlight the importance of wintertime soil moisture memory for subsequent springtime streamflow prediction. They also demonstrate that SMAP soil moisture retrievals by themselves can potentially serve as useful predictors of seasonally averaged streamflow at multi-month leads.