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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #334541

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

Location: Hydrology and Remote Sensing Laboratory

Title: Deploying temporary networks for upscaling of sparse network stations

Author
item COOPERSMITH, E. - University Of New Hampshire
item Cosh, Michael
item BELL, J. - National Oceanic & Atmospheric Administration (NOAA)
item KELLY, V. - Cary Institute Of Ecosystem Studies
item HALL, M. - National Oceanic & Atmospheric Administration (NOAA)
item PALECKI, M. - National Oceanic & Atmospheric Administration (NOAA)
item TEMIMI, M. - City University Of New York

Submitted to: International Journal of Applied Earth Observation and Geoinformation
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/10/2016
Publication Date: 11/1/2016
Citation: Coopersmith, E., Cosh, M.H., Bell, J., Kelly, V., Hall, M., Palecki, M., Temimi, M. 2016. Deploying temporary networks for upscaling of sparse network stations. International Journal of Applied Earth Observation and Geoinformation. 52:433-444.

Interpretive Summary: Soil moisture networks are simple point measurements which provide a valuable ground truth for many applications. However, these point measurements don't necessarily represent the larger area around them. Therefore, it is necessary to determine a larger ground truth estimate to develop a scaling function for a point measurement to make it applicable to a larger scale. This idea was put to the test at two long term soil moisture stations which are a part of the Climate Reference Network. It was determined that these stations could be scaled accurately to a remote sensing footprint with a short term installation of a temporary soil moisture network. This is useful for any in situ network manager and the remote sensing community which assumes representativeness for most station data.

Technical Abstract: Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, business and consumer applications, or even human health issues. The installation of soil moisture sensors as sparse, national networks is necessitated by limited financial resources. However, this results in the incomplete sampling of the local heterogeneity of soil type, vegetation cover, topography, and the fine spatial distribution of precipitation events. To this end, temporary networks can be installed in the areas surrounding a permanent installation within a sparse network. The temporary networks deployed in this study provide a more representative average at the 3 km and 9 km scales, localized about the permanent gauge. The value of such temporary networks is demonstrated at test sites in Millbrook, New York and Crossville, Tennessee. The capacity of a single U.S. Climate Reference Network (USCRN) sensor set to approximate the average of a temporary network at the 3 km and 9 km scales using a simple linear scaling function is tested. The capacity of a temporary network to provide reliable estimates with diminishing numbers of sensors, the temporal stability of those networks, and ultimately, the relationship of the variability of those networks to soil moisture conditions at the permanent sensor are investigated. In this manner, this work demonstrates the single-season installation of a temporary network as a mechanism to characterize the soil moisture variability at a permanent gauge within a sparse network.