Daily Landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA using multi-satellite data fusion

Abstract

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. Satellite remote sensing provides an effective means for diagnosing ET patterns over heterogeneous landscapes; however, limitations on the spatial and temporal resolution of satellite data, combined with the effects of cloud contamination, constrain the amount of detail that a single satellite can provide. In this study, we describe an application of a multi-sensor ET data fusion system over a mixed forested/agricultural landscape in North Carolina, USA during the growing season of 2013. The fusion system ingests ET estimates from a Two-Source Energy Balance (TSEB) model applied to thermal infrared remote sensing retrievals of land surface temperature from multiple satellite platforms: hourly geostationary satellite data at 4-km resolution, daily 1-km imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS), and bi-weekly Landsat thermal data sharpened to 30-m. These multiple datastreams are combined using the Spatial-Temporal Adaptive Reflectance Fusion Model (STARFM) to estimate daily ET at 30-m resolution to investigate seasonal water use behavior at the level of individual forest stands and land cover patches. A new method, also exploiting the STARFM algorithm, is used to fill gaps in the Landsat ET retrievals due to cloud cover and/or the scan-line corrector (SLC) failure on Landsat 7. The retrieved daily ET timeseries agree well with observations at two AmeriFlux eddy covariance flux tower sites in a managed pine plantation within the modeling domain: US-NC2 located in a mid-rotation (20 year old) loblolly pine stand, and US-NC3 located in a recently clear cut and replanted field site. Root mean square errors (RMSE) for NC2 and NC3 were 0.99 mm d-1 and 1.02 mm d-1, respectively, with mean absolute errors of 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. Analyses of water use patterns over the plantation indicate increasing seasonal ET with stand age for young to mid-rotation stands up to 20 years, but little dependence on age for older stands. An accounting of consumptive water use by major land cover classes representative of the modeling domain is presented, as well as relative partitioning of ET between evaporation (E) and transpiration (T) components obtained with the TSEB. The study provides new insights about the effects of forest management and land use change on hydrological water balance, and the method developed has the potential to be used to routinely monitor hydrology and water use over heterogeneous landscapes using thermal remote sensing data.

Field-scale mapping of evaporative stress indicators of crop yield: An application over Mead, NE, USA

“…Compared with closed observations, RMSE is 1.2 mm d −1 and MAE is 1.0 mm d −1 for ET retrievals on daily time steps, for all three sites combined. These daily accuracies are close to the average obtained from prior ET fusion experiments using this modeling system (Cammalleri et al, 2013(Cammalleri et al, , 2014Semmens et al, 2015;Sun et al, 2017;Yang et al, 2017aYang et al, , 2017b. Because these time series include both direct and interpolated retrievals, and span multiple years, crops and water management strategies, comparisons with ET model accuracies reported in the literature -which may reflect a different diversity in conditions -are not straight forward.…”

“…STARFM compares a pair of Landsat and MODIS images collected on the same day and develops a spatially distributed weighting function that can be used to disaggregate MODIS images to the Landsat scale on neighboring days when clear Landsat data are not available . [For more details regarding the ET data fusion process, the reader is referred to Cammalleri et al, 2014Cammalleri et al, , 2013Semmens et al, 2015;Sun et al, 2017;Yang et al, 2017aYang et al, , 2017b, with recent improvements in STARFM computational efficiency described by Gao et al, 2015. ] …”

Ecohydrological processes and ecosystem services in the Anthropocene: a review

“…However, the potential "negative" effects of planted forests on ecosystem services (e.g., reducing water supply) observed at a forest stand or small watershed scale may not be directly extrapolated to large basins or regions because hydrologic flows at these larger scales represent the integration of mixed land covers/land uses and other landscape components such as wetlands (Amatya et al 2015). For example, planting trees in a small area, such as 10% of the entire basin, the negative hydrological effects on water yield may not be manifested at the watershed outlet, especially during the first few years when the trees are young with low leaf area index (Yang et al 2017). The size and severity of land use disturbances matter at the watershed scale.…”

Landsat 15-m Panchromatic-Assisted Downscaling (LPAD) of the 30-m Reflective Wavelength Bands to Sentinel-2 20-m Resolution

“…It is sometimes termed data fusion, or more specifically, pansharpening, when the higher resolution ancillary data is the panchromatic band [35][36][37][38][39]. Hereafter, for consistency, the term downscaling is used throughout this paper.…”