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ARS Home » Midwest Area » West Lafayette, Indiana » National Soil Erosion Research Laboratory » Research » Publications at this Location » Publication #269828
Title: Multi-scale temporal stability analysis of surface and subsurface soil moisture within the Upper Cedar Creek Watershed, Indiana

Author
item Heathman, Gary
item Cosh, Michael
item MERWADE, VENKATESH - Purdue University
item HAN, EUNJIN - Purdue University

Submitted to: Catena
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/20/2012
Publication Date: 4/1/2012
Citation: Heathman, G.C., Cosh, M.H., Merwade, V., Han, E. 2012. Multi-scale temporal stability analysis of surface and subsurface soil moisture within the Upper Cedar Creek Watershed, Indiana. Catena. 95:91-103.

Interpretive Summary: In this study temporal stability analyses (TSA) of 5 and 20 cm soil moisture were conducted in an effort to improve the use and representation of permanent in situ sensor data at multiple scales within the Upper Cedar Creek Watershed (UCCW) in northeastern Indiana. In general, results indicate that the analyses are sensitive to the scale of observational data (2.5 to 6,200 ha). Spatio-temporal analysis revealed persistent patterns in surface soil moisture and identified sites that were temporally stable at both study scales. However, soil water patterns differed between preferred states (wet/dry) and were primarily controlled by lateral and vertical fluxes, respectively. At the field scale, locations that were optimal for estimating the area-average water contents were different from permanent sensor locations. However, minimum offset values could be applied to the permanent sensor data to obtain representative field average values of 5 cm surface soil moisture. TSA of 20 cm soil moisture showed little correlation with surface soil moisture TSA results in terms of comparable stable sites at either scale. Recommendations include additional installations of temporary sensors during remote sensing campaigns or special field projects, as well as, investigating new approaches for geospatial data analysis in regards to upscaling or downscaling of soil moisture information and interpolation schemes.

Technical Abstract: Soil moisture is a key state variable that varies considerably in space and time. From a hydrologic viewpoint, soil moisture controls runoff, infiltration, storage and drainage. Soil moisture determines the partitioning of the incoming radiation between latent and sensible heat fluxes. Although soil moisture is highly variable, if measurements of soil moisture at the field or small watershed scale are repeatedly observed, certain locations can often be identified as being temporally stable and representative of an area average. Temporal stability analysis (TSA) is a statistical approach for describing the persistence of spatial patterns and characteristic behavior of soil moisture. Using TSA, this study is aimed at determining the adequacy of long term point-scale surface and subsurface soil moisture (soil moisture) measurements in representing field and watershed scale averages that will serve as in situ ground truth locations for remotely sensed soil moisture calibration and validation programs, as well as applications for hydrologic modeling. Soil moisture data were obtained from frequency-domain reflectometry (FDR) sensors permanently installed at depths of 5, 20, 45, and 60 cm at seven sites located within the USDA, Upper Cedar Creek Watershed (UCCW) monitoring network in northeastern Indiana. In two agricultural fields, twenty additional FDR sensors, spaced 70 m apart, were installed at depths of 5 and 20 cm in each field with automated data collection being transmitted every 30 min from June 29 through September 21, 2010. Additionally, meteorological data (i.e., rainfall, air temperature, humidity) were obtained from existing UCCW network weather stations. Spatio-temporal analysis revealed persistent patterns in surface soil moisture and identified sites that were temporally stable at both study scales. However, soil water patterns differed between preferred states (wet/dry) and were primarily controlled by lateral and vertical fluxes, respectively. At the field scale, locations that were optimal for estimating the area-average water contents were different from the permanent sensor locations. However, minimum offset values could be applied to the permanent sensor data to obtain representative field average values of surface soil moisture. TSA of 20 cm soil moisture showed little correlation with surface soil moisture TSA results in terms of comparable stable sites at either scale. The results are of relevance for interpreting and downscaling coarser resolution soil moisture data such as that retrieved from remotely sensed active and passive microwave platforms and in terms of modeling soil moisture at multiple scales.