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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Research Project #437370

Research Project: Integrating Satellite-Based Surface Soil Moisture and Rainfall Accumulation Products for Improved Hydrologic Modeling

Location: Hydrology and Remote Sensing Laboratory

Project Number: 8042-13610-029-61-I
Project Type: Interagency Reimbursable Agreement

Start Date: Jul 17, 2019
End Date: Jul 31, 2020

This project seeks ways of leveraging current (and near-future) satellite observations to improve the ability to estimate the partitioning of rainfall between an infiltration component (into the soil column) and a runoff component (into the stream network). This partitioning is a fundamental aspect of land surface hydrology and a key calculation for efforts to globally water resource availability in agricultural areas. In particular, the project will develop and test a novel data assimilation system which optimally combines satellite-based surface soil moisture and precipitation retrievals within a hydrologic model. The system will be tailored to ingest measurements from the upcoming NASA Soil Moisture Active/Passive (SMAP) and Global Precipitation Measurement (GPM) missions.

The approach is based on the integration of two existing parts: first, the Soil Moisture Analysis Rainfall Tool (SMART) which is used to enhance satellite rainfall accumulation estimates using remotely-sensed surface soil moisture retrievals; second, data assimilation systems which integrate remotely-sensed surface soil moisture retrievals into a hydrologic model driven by satellite-based rainfall estimates. Integrating these two parts will attempt to create a system in which NASA Soil Moisture Active/Passive (SMAP) and Global Precipitation Mission (GPM) observations are optimally leveraged to constrain both the pre- storm characterization of antecedent soil moisture (which determines soil infiltration capacity) and the within-storm accumulation of rainfall. Better constraint of these two components will, in turn, lead to better soil moisture and runoff monitoring for water resource applications.