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Uncertainties in transpiration estimates

Author

Listed:
  • A. M. J. Coenders-Gerrits

    (Water Resources Section, Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands)

  • R. J. van der Ent

    (Water Resources Section, Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands)

  • T. A. Bogaard

    (Water Resources Section, Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands)

  • L. Wang-Erlandsson

    (Water Resources Section, Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands
    Stockholm Resilience Centre, Kräftriket 2, SE 10691 Stockholm, Sweden)

  • M. Hrachowitz

    (Water Resources Section, Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands)

  • H. H. G. Savenije

    (Water Resources Section, Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands)

Abstract

arising from S. Jasechko et al. Nature 496, 347–350 (2013) How best to assess the respective importance of plant transpiration over evaporation from open waters, soils and short-term storage such as tree canopies and understories (interception) has long been debated. On the basis of data from lake catchments, Jasechko et al.1 conclude that transpiration accounts for 80–90% of total land evaporation globally (Fig. 1a). However, another choice of input data, together with more conservative accounting of the related uncertainties, reduces and widens the transpiration ratio estimation to 35–80%. Hence, climate models do not necessarily conflict with observations, but more measurements on the catchment scale are needed to reduce the uncertainty range. There is a Reply to this Brief Communications Arising by Jasechko, S. et al. Nature 506, http://dx.doi.org/10.1038/nature12926 (2014). Figure 1 Ratio of transpiration to total evaporation. a–c, Box plots are calculated using a simplified Monte Carlo simulation of equation (4)1 with data from Jasechko et al .1 (a), and with the same data as in a but with Q = 39,600 ± 5,100 km3 per year and xP = 20,100 ± 9,800 km3 per year (b), and with the same data as in b but with dE = 75 ± 60‰ (c). The blue box indicates the 25th and 75th percentiles with the median in red. The error bars indicate the minimum and maximum values. The red crosses indicate outliers (3/2 times the central box). PowerPoint slide

Suggested Citation

  • A. M. J. Coenders-Gerrits & R. J. van der Ent & T. A. Bogaard & L. Wang-Erlandsson & M. Hrachowitz & H. H. G. Savenije, 2014. "Uncertainties in transpiration estimates," Nature, Nature, vol. 506(7487), pages 1-2, February.
  • Handle: RePEc:nat:nature:v:506:y:2014:i:7487:d:10.1038_nature12925
    DOI: 10.1038/nature12925
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    Cited by:

    1. Zhu, Shihua & Fang, Xia & Cao, Liangzhong & Hang, Xin & Xie, Xiaoping & Sun, Liangxiao & Li, Yachun, 2023. "Multivariate drives and their interactive effects on the ratio of transpiration to evapotranspiration over Central Asia ecosystems," Ecological Modelling, Elsevier, vol. 478(C).
    2. Gong, Daozhi & Mei, Xurong & Hao, Weiping & Wang, Hanbo & Caylor, Kelly K., 2017. "Comparison of ET partitioning and crop coefficients between partial plastic mulched and non-mulched maize fields," Agricultural Water Management, Elsevier, vol. 181(C), pages 23-34.

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