Comparing evapotranspiration from eddy covariance measurements, water budgets, remote sensing, and land surface models over Canada

Shusen Wang, Ming Pan, Qiaozhen Mu, Xiaoying Shi, Jiafu Mao, Christian Brümmer, Rachhpal S. Jassal, Praveena Krishnan, Junhua Li, T. Andrew Black

Research output: Contribution to journalArticlepeer-review

79 Scopus citations

Abstract

This study compares six evapotranspiration ET products for Canada's landmass, namely, eddy covariance EC measurements; surface water budget ET; remote sensing ET from MODIS; and land surface model (LSM) ET from the Community Land Model (CLM), the Ecological Assimilation of Land and Climate Observations (EALCO) model, and the Variable Infiltration Capacity model (VIC). The ET climatology over the Canadian landmass is characterized and the advantages and limitations of the datasets are discussed. The EC measurements have limited spatial coverage, making it difficult for model validations at the national scale.Water budget ET has the largest uncertainty because of data quality issues with precipitation in mountainous regions and in the north. MODIS ET shows relatively large uncertainty in cold seasons and sparsely vegetated regions. The LSM products cover the entire landmass and exhibit small differences inETamong them.AnnualET from the LSMs ranges from small negative values to over 600mmacross the landmass, with a countrywide average of 256 ± 15mm. Seasonally, the countrywide average monthly ET varies from a low of about 3mm in four winter months (November- February) to 67 ± 7mm in July. The ET uncertainty is scale dependent. Larger regions tend to have smaller uncertainties because of the offset of positive and negative biases within the region. More observation networks and better quality controls are critical to improving ET estimates. Future techniques should also consider a hybrid approach that integrates strengths of the various ET products to help reduce uncertainties in ET estimation.

Original languageEnglish
Pages (from-to)1540-1560
Number of pages21
JournalJournal of Hydrometeorology
Volume16
Issue number4
DOIs
StatePublished - 2015

Bibliographical note

Publisher Copyright:
© 2015 American Meteorological Society.

Keywords

  • Ecological models
  • Evapotranspiration
  • Model comparison
  • Remote sensing
  • Surface observations

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