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 #331098

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

Location: Hydrology and Remote Sensing Laboratory

Title: On the temporal and spatial variability of near-surface soil moisture for the identification of representative in situ soil moisture monitoring stations

item YEE, M. - Monash University
item WALKER, J. - Monash University
item MONERRIS, A. - Monash University
item RUDIGER, C. - Monash University
item Jackson, Thomas

Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/1/2016
Publication Date: 9/30/2016
Publication URL:
Citation: Yee, M., Walker, J., Monerris, A., Rudiger, C., Jackson, T.J. 2016. On the temporal and spatial variability of near-surface soil moisture for the identification of representative in situ soil moisture monitoring stations. Journal of Hydrology. 537:367-381.

Interpretive Summary: The representativeness of soil moisture stations within a spatial domain in Australia was investigated based on both temporal and spatial statistical methods. Analysis indicated that intensive measurements are required to identify stations which are representative of the area average for applications such as validation of remote sensing soil moisture products. The resources involved in installing and maintaining a large soil moisture monitoring network are typically prohibitive. A solution utilizing airborne remote sensing was developed that will lead to more efficient identification of representative locations a priori. This approach could lead to improved validation of satellite soil moisture products for agricultural hydrology.

Technical Abstract: The high spatio-temporal variability of soil moisture complicates the validation of remotely sensed soil moisture products using in-situ monitoring stations. Therefore, a standard methodology for selecting the most repre- sentative stations for the purpose of validating satellites and land surface models is essential. Based on temporal stability and geostatistical studies using long-term soil moisture records, intensive ground measurements and airborne soil moisture products, this study investigates the representative- ness of soil moisture monitoring stations within the Yanco study area for the validation of NASA’s Soil Moisture Active Passive (SMAP) products at 3 km for radar, 9 km for radar-radiometer and 36 km for radiometer pixels. This resulted in the identification of a number of representative stations according to the different scales. Although the temporal stability method was found to be suitable for identifying representative stations, stations based on the mean relative difference (MRD) are not necessarily the most representative of the areal average. Moreover, those identified from standard deviation of the relative difference (SDRD) may be dry-biased. It was also found that in the presence of heterogeneous land use, stations should be weighted based on proportions of agricultural land. Airborne soil moisture products were also shown to provide useful a priori information for identifying representative locations. Finally, recommendations are made regarding the design of future networks for satellite validation, and specifically the most representative stations for the Yanco area.