Advertisement

Plant and Soil

, Volume 430, Issue 1–2, pp 307–328 | Cite as

Comparison of the partitioning of evapotranspiration – numerical modeling with different isotopic models using various kinetic fractionation coefficients

  • Yonge Zhang
  • Xinxiao Yu
  • Lihua Chen
  • Guodong Jia
Regular Article
  • 62 Downloads

Abstract

Background

In the context of a warming climate and dry conditions, aggravating water shortages, research on partitioning total evapotranspiration (ET) into soil evaporation (E) and plant transpiration (T) is needed.

Methods and aims

Recently, using the oxygen isotope ratio as a tracer has proved to be a valuable way to better partition ET. In this study, we carefully considered the process of heavy water fractionation during the transpiration process, and specifically, we modified the kinetic fractionation coefficient (αk2) of transpiration, based on previous formulations used to estimate it.

Results

Our results show that, for the hourly and daily mean data set, both the isotopic–steady–state (ISS) and non–steady–state (NSS) assumptions for δ18O of leaf water (δL,b) provided a good fit with observed δL,b when using the modified αk2. In contrast, using αk2 values traditionally assigned led to significant deviations from observed δL,b (p < 0.05), potentially influencing ET partitioning results. On diurnal time scales, the percent contribution of T to total ET (FT) is sensitive to different model assumptions and different formulations to estimate αk2. The modeled FT, assuming NSS conditions and using the modified αk2 value, led to the best agreement with observed values. In contrast, on longer time scales (days), using the ISS assumption to partition ET is adequate, as the NSS assumption could introduce more complexities and uncertainties.

Conclusions

Our study demonstrates that the stable isotope technique is a promising utility for quantitatively partitioning ET. To more accurately estimate FT, we also call on a better description of the nature of αk2 of transpiration.

Keywords

Evapotranspiration Non–steady–state Oxygen isotopes Partitioning Transpiration 

Notes

Acknowledgments

This study was supported by the National Natural Science Foundation of China (No.41430747), the National Science Fund for Distinguished Young Scholars (No.41401013), and the Beijing Municipal Education Commission (CEFF–PXM2018_014207_000024).

Author contributions

Yonge Zhang designed and performed the experiment. Yonge Zhang analysed the data and wrote the manuscript. Lihua Chen, Guodong Jia contributed significantly to data analysis, manuscript preparation and practice of experiment. Xinxiao Yu revised the paper and finished the submission.

References

  1. Baldocchi DD, Ryu Y (2011) A synthesis of forest evaporation fluxes – from days to years – as measured with eddy covariance. In: Forest Hydrology and Biogeochemistry: Synthesis of Past Research and Future Directions, Ecological Studies 216. Springer, Netherlands, Dordrecht, pp. 101–116Google Scholar
  2. Cappa CD, Hendrichs MB, De Paolo DJ, Cohen RC (2003) Isotopic fractionation of water during evaporation. J Geophys Res 108:1–13CrossRefGoogle Scholar
  3. Cernusak LA, Barbour MM, Arndt SK, Cheesman AW, English NB, Field TS, Helliker BR, Phillips MMH, Holtum JAM, Kahmen AF, McInerney A, Munksgaard NC, Simonin KA, Song X, Williams HS, West JB, Farquhar GD (2016) Stable isotopes in leaf water of terrestrial plants. Plant Cell Environ 39:1087–1102CrossRefPubMedGoogle Scholar
  4. Dubbert M, Cuntz M, Piayda A, Maguás C, Werner C (2013) Partitioning evapotranspiration – Testing the Craig and Gordon model with field measurements of oxygen isotope ratios of evaporative fluxes. J Hydrol 496(14):142–153CrossRefGoogle Scholar
  5. Dubbert M, Cuntz M, Piayda A, Werner C (2014) Oxygen isotope signatures of transpired water vapor, the role of isotopic non–steady–state transpiration under natural conditions. New Phytol 203:1242–1252CrossRefPubMedGoogle Scholar
  6. Fan SJ, Lin WS, Su XH, Chen XY, Ma SQ (1999) Study on the application of Richardson number’s stability classifying schemes of the surface layer over coastal reign. J Trop Meteorol 15:370–375Google Scholar
  7. Farquhar GD, Cernusak LA (2005) On the isotopic composition of leaf water in the non–steady state. Funct Plant Biol 32:293–303CrossRefGoogle Scholar
  8. Farquhar GD, Cernusak LA, Barnes B (2007) Heavy water fractionation during transpiration. Plant Physiol 143:11–18CrossRefPubMedPubMedCentralGoogle Scholar
  9. Ferrio JP, Pou A, Florez–Sarasa I, Gessler A, Kodama N, Flexas J, Ribas–Carbo M (2012) The Peclet effect on leaf water enrichment correlates with leaf hydraulic conductance and mesophyll conductance for CO2. Plant Cell Environ 35:611–625CrossRefPubMedGoogle Scholar
  10. Good SP, Soderberg K, Wang L, Caylor KK (2012) Uncertainties in the assessment of the isotopic composition of surface fluxes, A direct comparison of techniques using laser–based water vapor isotope analyzers. J Geophys Res Atmos 117:1–22CrossRefGoogle Scholar
  11. Jasechko S, Sharp ZD, Gibson JJ, Birks SJ, Yi Y, Peter JF (2013) Terrestrial water fluxes dominated by transpiration. Nature 496:347–351CrossRefPubMedGoogle Scholar
  12. Jia JB (2016) Eco-hydrological process and mechanism analysis on forests in Beijing mountainous area. Thesis for doctor degree, Beijing Forestry UniversityGoogle Scholar
  13. Jiang X, Kang S, Li F, Du T, Tong L, Comas L (2016) Evapotranspiration partitioning and variation of sap flow in female and male parents of maize for hybrid seed production in arid region. Agric Water Manag 176:132–141CrossRefGoogle Scholar
  14. Kahmen K, Simonin KP, Tu KP, Merchant A, Callister A, Siegwolf R, Dawson TE, Arndt SK (2008) Effects of environmental parameters, leaf physiological properties and leaf water relations on leaf water delta 18O enrichment in different Eucalyptus species. Plant Cell Environ 31:738–751CrossRefPubMedGoogle Scholar
  15. Keeling CD (1958) The concentration and isotopic abundances of atmospheric carbon dioxide in rural areas. Geochim Cosmochim Acta 13:322–334CrossRefGoogle Scholar
  16. Kool D, Agam N, Lazarovitch N, Heitman JL, Sauer TJ, Ben–Ga A (2014) A review of approaches for evapotranspiration partitioning. Agric For Meteorol 184:56–70CrossRefGoogle Scholar
  17. Kumagai T, Tateishi M, Miyazawa Y, Kobayashi M, Yoshifuji N, Komatsuf H, Shimizu T (2014) Estimation of annual forest evapotranspiration from a coniferous plantation watershed in Japan (1), Water use components in Japanese cedar stands. J Hydrol 508:66–76CrossRefGoogle Scholar
  18. Kurpius MR, Panek JA, Nikolov NT, Mckay M, Goldstein AH (2003) Partitioning of water flux in a Sierra Nevada ponderosa pine plantation. Agric For Meteorol 117:173–192CrossRefGoogle Scholar
  19. Lai CT, Ehleringer JR, Bond BJ, Paw KTU (2006) Contributions of evaporation, isotopic non–steady state transpiration and atmospheric mixing on the δ18O of water vapour in Pacific Northwest coniferous forests. Plant Cell Environ 29:77–94CrossRefPubMedGoogle Scholar
  20. Lee X, Sargent S, Smith R, Tanner B (2005) In Situ Measurement of the Water Vapor 18O/16O Isotope Ratio for Atmospheric and Ecological Applications. J Atmos Ocean Technol 22:555–565CrossRefGoogle Scholar
  21. Lee X, Griffis TJ, Baker JM, Billmark KA, Kim K, Welp LR (2009) Canopy-scale kinetic fractionation of atmospheric carbon dioxide and water vapor isotopes. Glob Biogeochem Cycles 23:1–15CrossRefGoogle Scholar
  22. Lou YH (2016) Research of using isotope in partitioning forestry ecosystem evapotranspiration. Thesis for master degree, Beijing Forestry University.Google Scholar
  23. Lu X, Liang LL, Wang L, Jenerette GD, Mccabe MF, Grantz DA (2017) Partitioning of evapotranspiration using a stable isotope technique in an arid and high temperature agricultural production system. Agric Water Manag 179:103–109CrossRefGoogle Scholar
  24. Manuel I, Frances C (2000) Simplifying daily evapotranspiration estimates over short full–canopy crops. Agron J 92:628–632CrossRefGoogle Scholar
  25. Mathieu R, Bariac T (1996) A numerical model for the simulation of stable isotope profiles in drying soils. J Geophys Res Atmos 101:12685–12696CrossRefGoogle Scholar
  26. Merlivat L (1978) Molecular diffusivities of H2 16O, HD16O, and H2 18O in gases. J Chem Phys 69(6):2864–2871CrossRefGoogle Scholar
  27. Oren R, Phillips N, Katul G, Ewers BE, Pataki DE (1998) Scaling xylem sap flux and soil water balance and calculating variance: a method for partitioning water flux in forests. Ann Sci For 55:191–216CrossRefGoogle Scholar
  28. Pape L, Ammann C, Nyfeler–Brunner A, Spirig C, Hens K, Meixner FX (2009) An automated dynamic chamber system for surface exchange measurement of non–reactive and reactive trace gases of grassland ecosystems. Biogeosciences 6:405–429CrossRefGoogle Scholar
  29. Pendall E, Williams DG, Leavitt SW (2005) Comparison of measured and modeled variations in pine on pine leaf water isotopic enrichment across a summer moisture gradient. Oecologia 145:605–618CrossRefPubMedGoogle Scholar
  30. Ringgaard R, Herbst M, Friborg T (2012) Partitioning of forest evapotranspiration, The impact of edge effects and canopy structure. Agric For Meteorol 166–167:86–97CrossRefGoogle Scholar
  31. Rothfuss Y, Braud I, Moine LN, Biron P, Durand JL, Vauclin M, Bariac T (2012) Factors controlling the isotopic partitioning between soil evaporation and plant transpiration: assessment using a multi–objective calibration of Si SPAT–Isotope under controlled conditions. J Hydrol 442:75–88CrossRefGoogle Scholar
  32. Snyder KA, Monnar R, Poulson SR, Hartsough P, Biondi F (2010) Diurnal variations of needle water isotopic ratios in two pine species. Trees 24:585–595CrossRefGoogle Scholar
  33. Song X, Barbour MM, Farquhar GD, Vann DR, Helliker BR (2013) Transpiration rate relates to within– and across–species variations in effective path length in a leaf water model of oxygen isotope enrichment. Plant Cell Environ 36:1338–1351Google Scholar
  34. Song X, Loucos KE, Simonin KA, Farquhar GD, Barbour MM (2015) Measurements of transpiration isotopologues and leaf water to assess enrichment models in cotton. New Phytol 206:637–646CrossRefPubMedGoogle Scholar
  35. Stannard DI, Weltz MA (2006) Partitioning evapotranspiration in sparsely vegetated rangeland using a portable chamber. Water Resour Res 42:1–13CrossRefGoogle Scholar
  36. Stewart MK (1975) Stable isotope fractionation due to evaporation and isotopic exchange of falling water drops. Application to atmospheric processes and evaporation of lakes. J Geophys Res 80:1133–1146CrossRefGoogle Scholar
  37. Sullivan PF, Welker JM (2007) Variation in leaf physiology of Salix arctica within and across ecosystems in the High Arctic,test of a dual isotope (Delta 13C and Delta 18O) conceptual model. Oecologia 151:372–386CrossRefPubMedGoogle Scholar
  38. Sulman BN, Roman DT, Scanlon TM, Wang L, Novick KA (2016) Comparing methods for partitioning a decade of carbon dioxide and water vapor fluxes in a temperate forest. Agric For Meteorol 226–227:229–245CrossRefGoogle Scholar
  39. Sun SJ, Meng P, Zhang JS, Wan X, Zheng N, He CX (2014) Partitioning oak woodland evapotranspiration in the rocky mountainous area of North China was disturbed by foreign vapor, as estimated based on non–steady. Agric For Meteorol 184:36–47CrossRefGoogle Scholar
  40. Wang LX, Caylor KK, Villegas JC, Barrongafford GA, Breshears DD, Huxman TE (2010) Partitioning evapotranspiration across gradients of woody plant cover, assessment of a stable isotope technique. Geophys Res Lett 37:232–256Google Scholar
  41. Wang L, Good SP, Caylor KK, Cernusak LA (2012) Direct quantification of leaf transpiration isotopic composition. Agric For Meteorol 154–155:127–135CrossRefGoogle Scholar
  42. Wang P, Yamanaka T, Li XY, Wei Z (2015) Partitioning evapotranspiration in a temperate grassland ecosystem, Numerical modeling with isotopic tracers. Agric For Meteorol 208:16–31CrossRefGoogle Scholar
  43. Welp LR, Kim K, Griffis TJ, Billmark KA, Baker JM (2008) δ18O of water vapour, evapotranspiration and the sites of leaf water evaporation in a soybean canopy. Plant Cell Environ 31:1214–1228CrossRefPubMedGoogle Scholar
  44. Wen XF, Zhang SC, Sun XM, Yu GR (2008) Recent advances in H2O enrichment in leaf water. J Plant Ecol 32:961–966Google Scholar
  45. Xiao Q, Ye WJ, Zhu Z, Chen Y, Zheng HL (2005) A simple non–destructive method to measure leaf area using digital camera and Photoshop software. Chin J Ecol 24:711–714Google Scholar
  46. Yang B, Xie FT, Wen XF, Sun XM, Wang JL (2012) Diurnal variations of soil evaporation δ18O and factors affecting it in cropland in North China. Chinese Journal of Plant Ecology 36(6):539–549CrossRefGoogle Scholar
  47. Yepez EA, Williams DG, Scott RL, Lin G (2003) Partitioning overstory and understory evapotranspiration in a semiarid savanna woodland from the isotopic composition of water vapor. Agric For Meteorol 119:53–68CrossRefGoogle Scholar
  48. Yoshida M, Ohta T, Kotani A, Maximov T (2010) Environmental factors controlling forest evapotranspiration and surface conductance on a multi–temporal scale in growing seasons of a Siberian larch forest. J Hydrol 395:180–189CrossRefGoogle Scholar
  49. Yu GR, Wang QF (2010) Ecophysiology of plant photosynthesis, Transpiration, and Water Use, ed. Li Y, Chen SS, Science press, Beijing.Google Scholar
  50. Zhang Z, Tian F, Hu H, Yang P (2014) A comparison of methods for determining field evapotranspiration: photosynthesis system, sap flow, and eddy covariance. Hydrol Earth Syst Sci 18:1053–1072CrossRefGoogle Scholar
  51. Zhou Y, Grice K, Chikaraishi Y, Stuartwilliams H, Farquhar GD, Ohkouchi N (2011) Temperature effect on leaf water deuterium enrichment and isotopic fractionation during leaf lipid biosynthesis, results from controlled growth of C3 and C4 land plants. Phytochemistry 72:207–213CrossRefPubMedGoogle Scholar
  52. Zou WA, Jiang B, Gu LH (2015) Measurement of Soil Moisture Constants. Journal of China Hydrology 35:62–66Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Key Laboratory of State Forestry Administration on Soil and Water ConservationBeijing Forestry UniversityBeijingChina

Personalised recommendations