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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 #326054
Title: Daily Landsat-scale evapotranspiration estimation over a managed pine plantation in North Carolina, USA using multi-satellite data fusion

Author
item Yang, Yun
item Anderson, Martha
item Gao, Feng
item HAIN, C. - University Of Maryland
item SEMMENS, K. - Collaborator
item Kustas, William - Bill
item NOORMETS, A. - North Carolina State University
item WYNNE, R.H. - Virginia Polytechnic Institution & State University
item THOMAS, V.A. - Virginia Polytechnic Institution & State University
item SUN, G. - Forest Service (FS)

Submitted to: Hydrology and Earth System Sciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/19/2017
Publication Date: 2/17/2017
Citation: Yang, Y., Anderson, M.C., Gao, F.N., Hain, C., Semmens, K., Kustas, W.P., Noormets, A., Wynne, R., Thomas, V., Sun, G. 2017. Daily Landsat-scale evapotranspiration estimation over a managed pine plantation in North Carolina, USA using multi-satellite data fusion. Hydrology and Earth System Sciences. 21:1017-1037. doi:10.5194/hess-21-1017-2017.

Interpretive Summary: Evapotranspiration (ET) represents the rate at which soil water is consumed by plants. Being able to accurately estimate ET at landscape scales is essential for monitoring plant health status and water yield from a watershed. This is especially important for downstream water users in dry areas. Many studies have been applied to estimate ET over global, local or watershed scales at time steps of month to years, but there are fewer studies that have focused on estimating ET at field or plot scale (on the order of 100 m in dimension) and at daily time steps. This research employed a multi-satellite ET modeling system over a managed pine plantation area in North Carolina during the 2013 growing season to determine daily plot-scale ET. The simulated results compared well with the observations of ET from two flux towers in the study area: one in a mature plantation site (20-year old stand) and a second in a recently clear-cut stand. Variations in plot-scale water use with land cover type and pine stand age were also analyzed. These analyses showed that natural forest areas and mid-rotation pine plantations had higher ET than the young plantations and cropped areas, and seasonal water use patterns varied significantly with stand age. This study demonstrates the capability of the multi-satellite ET model to estimate daily field-scale ET over forested landscape, providing useful information for local water resource management.

Technical Abstract: As a primary flux in the global water cycle, evapotranspiration (ET) connects hydrologic and biological processes and is directly affected by water and land management, land use change and climate variability. The Two Source Energy Balance (TSEB) model has been widely applied to quantify field- to global-scale ET using thermal infrared remote sensing retrievals of land surface temperature. However, limitations on the spatial and temporal resolution of the satellite data combined with the effects of cloud contamination constrain the amount of detail that a single satellite can provide. Fusing multi-satellite data with varying spatial and temporal resolutions can give a more continuous estimation of daily ET at field scale. In this study, continental scale ET maps generated with the regional TSEB modeling system (Atmosphere-Land Exchange Inverse; ALEXI) at 4-km resolution using thermal infrared geostationary satellite imagery were spatially disaggregated to 1-km using Moderate Resolution Imaging Spectroradiometer (MODIS) thermal data and down to 30-m with Landsat data using the associated flux disaggregation algorithm (DisALEXI), applied over a managed pine plantation in North Carolina, USA during the main growing season (Day of Year (DOY) 50 - 330) for 2013. The MODIS-retrieved ET (daily, 1 km) and Landsat-retrieved ET (8 scenes during the growing season, 30 m) were combined using the Spatial-Temporal Adaptive Reflectance Fusion Model (STARFM) to estimate daily ET at 30-m resolution. A new method was developed for filling gaps in the Landsat ET retrievals, due to cloud cover and missing data causing stripes in the imagery resulting from the Landsat 7 scan-line corrector (SLC) failure, also exploiting the STARFM algorithm. The modeled daily ET was then compared with observations at two AmeriFlux eddy covariance flux tower sites: US-NC2 located in a mid-rotation (20 year old) pine stand, and US-NC3 located in a recently clear cut and replanted field site. The modeled daily ET was in good agreement with the observed ET at both sites, with root mean square errors (RMSE) for NC2 and NC3 of 0.99 mm d-1 and 1.02 mm d-1, respectively. Mean absolute errors were approximately 29% at the daily time step, 12% at the monthly time step, and 3% over the full study period at two flux tower sites. The influence of land cover type and stand age on seasonal water use was investigated using the daily Landsat-scale ET dataset. The analysis showed that seasonal ET patterns vary significantly with stand age, with higher rates of ET from mid-rotation stands in comparison with younger stands. For stands older than approximately 20 years, there was little dependence of water use on stand age. The dataset also showed that natural forest areas and mid-rotation plantations had higher ET than the young plantation and cropped areas. The method presented in this study provides new insights about the effects of forest management and land use change on hydrological water balance, and has the potential to be used to routinely monitor hydrology and water use in forested systems using thermal remote sensing data.