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 the Two-Source Energy Balance Model (TSEB) 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 biweekly Landsat thermal data sharpened to 30 m. These multiple ET data streams are combined using the Spatial and 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 time series 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 (RMSEs) for NC2 and NC3 were 0.99 and 1.02 mm day−1, respectively, with mean absolute errors of approximately 29 % at the daily time step, 12 % at the monthly time step and 0.7 % over the full study period at the 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 management and land use change on water yield over forested landscapes.

Highlights

  • Evapotranspiration (ET) is a major component of the water balance and connects hydrologic and biological processes (Hanson et al, 2004; Wilson et al, 2001)

  • For DOY 96 (Fig. 4), L7 scan-line corrector (SLC) stripes and a few cloudy areas were filled by combining the direct Landsat retrieval with the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) ET prediction for DOY 96 generated using a Landsat–Moderate Resolution Imaging Spectroradiometer (MODIS) image pair from DOY 104

  • ET retrievals over the growing season of 2013, generated at 30 m spatial resolution, compared well with observed fluxes at AmeriFlux tower sites in a mature pine stand and a recent clear-cut site, demonstrating capability to reasonably capture a range in land-surface conditions within a managed pine plantation

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Summary

Introduction

Evapotranspiration (ET) is a major component of the water balance and connects hydrologic and biological processes (Hanson et al, 2004; Wilson et al, 2001). Current forest ET estimation methods span a range of spatial scales: from individual plants, to tower footprints, to watershed scales (Fang et al, 2015) These methods include in situ measurement, simulation using hydrologic and land surface models which are normally driven by weather data and estimation from satellite remote sensing data. Catchment water balance is a frequently used method, calculating ET from long-term precipitation and streamflow observations with the assumption that the soil water storage change is negligible (Domec et al, 2012; Wilson et al, 2001) All these observation methods have their inherent advantages and limitations, especially when considering both temporal and spatial resolution issues

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