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





- Crow, Wade
- Water Availability and Watershed Management (211)
- Sustainable Agricultural Systems Research (216)

Research Project: **Location:
                            Hydrology and Remote Sensing Laboratory** Project Number: 8042-13610-030-070-I
                        
                        Project Type: Interagency Reimbursable Agreement Start Date: Mar 19, 2021
                        
                        End Date: Mar 31, 2025 **Objective:**
                        
                        Utilize remotely sensed surface soil moisture products from the NASA Soil Moisture Active/Passive mission to improve our ability to model streamflow, root-zone soil moisture and evapotranspiration in agricultural basins that lack ground-based streamflow observations. **Approach:**
                        
                        This proposal will explore the use of SMAP soil moisture products to address systematic sources of error undermining the accuracy of operational stream flow forecasts. The approach will be based on utilizing SMAP soil moisture products to map soil moisture/runoff efficiency coupling in gauged basins. A range of analytical approaches will then be applied to transfer parameterization information acquired in gauged basins into neighboring ungauged basins. Similar "regionalization" approaches have been widely applied to transfer calibrated model parameters between gauged and ungauged basins. Our underlying hypothesis is that, by focusing on the transfer of physically based coupling estimates (rather than non-physical model-specific parameters), we will create a more robust regionalization approach and provide a more effective constraint on rainfall/runoff modelling within ungauged basins. To maximize its relevance for operational activities, the analysis will focus on the NOAH-MP land surface model currently being used as the modelling core of the United States National Water Model (USNWM). Large data sets of daily stream flow and precipitation for lightly regulated, medium-scale basins in North American and Europe will be leveraged via data-denial techniques to objectively evaluate various regionalization approaches. This approach will be of immediate relevance for on-going attempts to improve the calibration of NOAH-MP within the USNWM and will represent an importance benchmark in the use of SMAP data products to address systematic error sources currently degrading USNWM stream flow estimates.


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