Incorporating Stable Water Isotopes in the Community Land Model
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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

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



The main objective conducting the global survey program: Model

☞ 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


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.


The ipilps phase 1 experiment aims to
The iPILPS Phase 1 experiment aims to Land-surface Parameterization Schemes (PILPS)

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.


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.


Baisic equations
Baisic equations 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.

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


Basic fractionation equations 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.

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


2. 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. Rayleigh condensation fractionation equation:

Rv: stable isotopic ratio in vapor;

f: residual proportion of condensing vapor


3. Results 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.

3.1 Seasonal variations of daily-averaged 18O and precipitation


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


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


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


3.2 Simulation of monthly-averaged runoff, and their daily-averaged 18O and waters (moisture)


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


Comparisons between actual survey and simulation reservoir and canopy evaporation, and their monthly-averaged

on month time scale at Manaus


3.3 Simulation of monthly-averaged reservoir and canopy evaporation, and their monthly-averaged 18O and waters (moisture)


(a) reservoir and canopy evaporation, and their monthly-averaged

(b)

time (hours)

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


(a) reservoir and canopy evaporation, and their monthly-averaged

(b)

time (hours)

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


3.4 Simulation of Meteoric Water Line (MWL) reservoir and canopy evaporation, and their monthly-averaged


simulated reservoir and canopy evaporation, and their monthly-averaged

Comparisons between actual and simulated MWLs in precipitation


Simulated MWL in surface runoff reservoir and canopy evaporation, and their monthly-averaged


3.5 Sensitivity test reservoir and canopy evaporation, and their monthly-averaged

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)))


Variations of reservoir and canopy evaporation, and their monthly-averaged 18O in surface soil reservoir for different scheme


Variations of reservoir and canopy evaporation, and their monthly-averaged 18O in sub-surface soil reservoir for different schemes


Variations of reservoir and canopy evaporation, and their monthly-averaged 18O in transpiration for different schemes


4 conclusions
4. conclusions reservoir and canopy evaporation, and their monthly-averaged

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.


Thank You! reservoir and canopy evaporation, and their monthly-averaged

End of Presentation


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