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Incorporating Stable Water Isotopes in the Community Land Model

Incorporating Stable Water Isotopes in the Community Land Model. Xinping Zhang 1 Guoyue Niu 2 Zongliang Yang 2 1 College of Resources and Environmental Sciences Hunan Normal University, Changsha, China 2 Department of Geological Sciences, the University of Texas at Austin, Texas, USA.

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Incorporating Stable Water Isotopes in the Community Land Model

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  1. Incorporating Stable Water Isotopes in the Community Land Model Xinping Zhang 1 Guoyue Niu 2 Zongliang Yang 2 1 College of Resources and Environmental Sciences Hunan Normal University, Changsha, China 2 Department of Geological Sciences, the University of Texas at Austin, Texas, USA

  2. 1. Introduction

  3. The main objective conducting the global survey program: ☞ Determination of the atmospheric circulation patterns and global or local water cycle mechanisms ☞ Recovery of paleoclimatic records in mid-high latitudes: the index as temperature in monsoon regions: the index as strength of monsoon or precipitation amount ☞ Investigations for water or vapor resources inventory

  4. iPILPS: Isotops in Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) iPILPS is a new type of PILPS experiment in which the process of international intercomparison will inform, illuminate and educate the land-surface scheme (LSS) parameterization community while new aspects of LSS are being developed.

  5. The iPILPS Phase 1 experiment aims to 1. identify and test ILSSs (isotopically enabled land-surface schemes) which incorporate SWIs (stable water isotope) 2. appraise SWI data applicable to hydro-climatic and water resource aspects of ILSSs; 3. identify observational data gaps required for evaluating ILSSs; 4. apply SWI data to specific predictions of well-understood locations simulated by available ILSSs.

  6. In the study, stable water isotopes are added to the Community Land Model (CLM) as a diagnostic tool for an in-depth understanding of the hydrologic and thermal processes; and the diurnally and monthly variations of stable water isotopes in different reservoirs at Manaus, Brazil, are simulated and intercompared in a given year, using the CLM.

  7. Baisic equations On the monthly time scale: water mass balance: Prj-Evapj-Roj-ΔSj=0 isotope mass balance: δPrj×Prj-δEvapj×Evapj-δRoj×Roj- δΔSj×ΔSj=0 δPrj monthly isotopic δ value of precipitation Prj δEvapj monthly isotopic δ value of evaporation Evapj δRoj monthly isotopic δ value of surface plus subsurface runoff Roj δΔSj monthly isotopic δ value of the change in the total storage water Evapj

  8. Basic fractionation equations 1. Rayleigh evaporation fractionation equation: Rl: stable isotopic ratio in water; f: residual proportion of evaporating water body α: α=Rl/Rv(>1) stable isotopic fractionation factor between liquid and vapor. α= α(T) on the equilibrium fractionation α = αk(T, h, V, D) on the kinetic fractionation

  9. 2. Rayleigh condensation fractionation equation: Rv: stable isotopic ratio in vapor; f: residual proportion of condensing vapor

  10. 3. Results 3.1 Seasonal variations of daily-averaged 18O and precipitation

  11. The seasonal variations of daily precipitation and daily-averaged 18O in vapor and in precipitation at Manaus, Brazil

  12. The seasonal variations of daily canopy dew, canopy reservoir and canopy evaporation, and their daily-averaged 18O at Manaus, Brazil

  13. The seasonal variations of daily surface dew and surface runoff, and their daily-averaged 18O at Manaus, Brazil

  14. 3.2 Simulation of monthly-averaged 18O and waters (moisture)

  15. The seasonal variations of monthly canopy dew, canopy reservoir and canopy evaporation, and their monthly-averaged 18O at Manaus, Brazil

  16. Comparisons between actual survey and simulation on month time scale at Manaus

  17. 3.3 Simulation of monthly-averaged 18O and waters (moisture)

  18. (a) (b) time (hours) The diurnal variation of 18O in canopy dew, canopy reservoir and canopy evaporation for January (a) and July (b) at Manaus

  19. (a) (b) time (hours) The diurnal variation of 18O in surface dew and surface runoff for January (a) and July (b) at Manaus

  20. 3.4 Simulation of Meteoric Water Line (MWL)

  21. simulated Comparisons between actual and simulated MWLs in precipitation

  22. Simulated MWL in surface runoff

  23. 3.5 Sensitivity test scheme 1:fpi = 1. - exp(-0.5*(clm%elai + clm%esai)) scheme 2:fpi = min(0.1,1. - exp(-0.5*(clm%elai + clm%esai))) scheme 3:fpi = min(0.2,1. - exp(-0.5*(clm%elai + clm%esai)))

  24. Variations of 18O in surface soil reservoir for different scheme

  25. Variations of 18O in sub-surface soil reservoir for different schemes

  26. Variations of 18O in transpiration for different schemes

  27. 4. conclusions 1. Simulations show reasonable features in the seasonal and diurnal variations of δ18O in canopy and surface reservoirs; 2. Owing to originating mainly from atmospheric precipitation, the stable water isotopes in these reservoirs change as the stable isotopes in precipitation; 3. On the diurnally time scale, the stable isotopes in precipitation display the typical isotopic signature in evergreen tropical forest: the heavy rains are usually depleted in stable isotopes, but the light ones are usually enriched; 4. On the monthly time scale, δ18O in reservoirs have distinct seasonal variation with two peaks. The feature called as amount effect is consistent with the actual survey at Manaus, from 1965 to 1990, set up by IAEA/WMO; 5. Different hydrological process cause very different isotopic responses.

  28. Thank You! End of Presentation

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