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 #304445

Research Project: Leveraging Remote Sensing, Land Surface Modeling and Ground-based Observations ... Variables within Heterogeneous Agricultural Landscapes

Location: Hydrology and Remote Sensing Laboratory

Title: Iowa flood studies (IFloodS) in the South Fork experimental watershed: soil moisture and precipitation monitoring

Author
item Coopersmith, Evan
item Cosh, Michael
item Petersen, Walter - National Aeronautics And Space Administration (NASA)
item Krajewski, Witold - University Of Iowa
item Prueger, John

Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: 4/5/2014
Publication Date: 4/23/2014
Citation: Coopersmith, E.J., Cosh, M.H., Petersen, W., Krajewski, W., Prueger, J.H. 2014. Iowa flood studies (IFloodS) in the South Fork experimental watershed: soil moisture and precipitation monitoring. 2014 BARC Poster Day. National Agricultural Library, April 23, 2014, Beltsville, MD.

Interpretive Summary:

Technical Abstract: Soil moisture estimates are valuable for hydrologic modeling and agricultural decision support. These estimates are typically produced via a combination of sparse ¬in situ networks and remotely-sensed products or where sensory grids and quality satellite estimates are unavailable, through derived hydrologic and statistical models. For soil moisture estimates produced by modeling efforts, the accuracy of these estimates is determined by the precision and stability of the data products (more specifically the precipitation data) with which they are calibrated. Methods for watershed scale modeling of soil moisture will be investigated in a USDA-ARS watershed in the South Fork of the Iowa River (Iowa, USA). This represents an ideal location for investigating the performance of numerous precipitation data products available. Calibrating a simple, soil moisture model requiring only a precipitation time series and an in situ soil moisture time series, during the IFLOODS initiative in the spring of 2013 will provide insight into the reliability of each of these data products and their suitability for future decision support work. Within the South Fork watershed, each in situ soil moisture sensor is accompanied by a precipitation gauge. These precipitation gauges are then used to calibrate a simple-lumped soil moisture model at each sensor location. In addition, public, radar-driven precipitation estimates are available through NEXRAD at these locations. By comparing the efficacy of models calibrated with local precipitation gauges, models calibrated with public climate data (NEXRAD), and models calibrated with other precipitation data products developed and tested in the South Fork watershed, one can demonstrate the relative value of these precipitation data products for hydrologic modeling.