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    Author(s): Ge Sun; Karrin Alstad; Jiquan Chen; Shiping Chen; Chelcy R. Ford; al. et.
    Date: 2011
    Source: Ecohydrology 4(2):245-255
    Publication Series: Scientific Journal (JRNL)
    PDF: View PDF  (407.57 KB)

    Description

    Accurately quantifying evapotranspiration (ET) is essential for modelling regional-scale ecosystem water balances. This study assembled an ET data set estimated from eddy flux and sapflow measurements for 13 ecosystems across a large climatic and management gradient from the United States, China, and Australia. Our objectives were to determine the relationships among monthly measured actual ET (ET), calculated FAO-56 grass reference ET (ETo), measured precipitation (P), and leaf area index (LAI)—one associated key parameter of ecosystem structure. Results showed that the growing season ET from wet forests was generally higher than ETo while those from grasslands or woodlands in the arid and semi-arid regions were lower than ETo. Second, growing season ET was found to be converged to within ± 10% of P for most of the ecosystems examined. Therefore, our study suggested that soil water storage in the nongrowing season was important in influencing ET and water yield during the growing season. Lastly, monthly LAI, P, and ETo together explained about 85% of the variability of monthly ET. We concluded that the three variables LAI, P, and ETo, which were increasingly available from remote sensing products and weather station networks, could be used for estimating monthly regional ET dynamics with a reasonable accuracy. Such an empirical model has the potential to project the effects of climate and land management on water resources and carbon sequestration when integrated with ecosystem models.

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    Citation

    Sun, Ge; Alstad, Karrin; Chen, Jiquan; Chen, Shiping; Ford, Chelcy R.; et. al. 2011. A general predictive model for estimating monthly ecosystem evapotranspiration. Ecohydrology 4(2):245-255.

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    Keywords

    climate change, ET, eddy flux, modelling, sap flow, water balance

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