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

1. Introduction

* 在海洋中所占的比率(%): 99.77 0.20 0.03 ＜0.001Proportion in ocean (%):

The measured ratio of the stable oxygen or hydrogen isotope in samples (18O/16O or 2H/1H) is expressed as parts per thousand of their deviation relative to the Standard Mean Ocean Water (SMOW):

10001

/

/1618

161818

SMOW

sample

* 自然水中最重要的同位素：1H216O 1H2

18O 1HD16O 1H217OThe most important stable

isotopic species in natural water The most important isotopic species in natural water

☞ 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

The main objective conducting the global survey program:

iPILPS is a new type of PILPS experiment in which the

process of international intercomparison will inform, ill

uminate and educate the land-surface scheme (LSS) par

ameterization community while new aspects of LSS are

being developed.

iPILPS: Isotops in Project for Intercomparison of

Land-surface Parameterization Schemes (PILPS)

The iPILPS Phase 1 experiment aims to

1. identify and test ILSSs (isotopically enabled land-surface sch

emes) which incorporate SWIs (stable water isotope)

2. appraise SWI data applicable to hydro-climatic and water re

source aspects of ILSSs;

3. identify observational data gaps required for evaluating ILS

Ss;

4. apply SWI data to specific predictions of well-understood loc

ations simulated by available ILSSs.

In the study, stable water isotopes are added to the Co

mmunity Land Model (CLM) as a diagnostic tool for

an in-depth understanding of the hydrologic and ther

mal processes; and the diurnally and monthly variatio

ns of stable water isotopes in different reservoirs at M

anaus, Brazil, are simulated and intercompared in a gi

ven year, using the CLM.

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

Rl: stable isotopic ratio in water;

f: residual proportion of evaporating water body

α: α=Rl/Rv （＞ 1) stable isotopic fractionation factor bet

ween liquid and vapor.

α = α(T) on the equilibrium fractionation

α = αk(T, h, V, D) on the kinetic fractionation

Basic fractionation equations

1. Rayleigh evaporation fractionation equation:

11

ll 1)(t(t)

αfRR

2. Rayleigh condensation fractionation equation:

11)(t(t) αvv fRR

Rv: stable isotopic ratio in vapor;

f: residual proportion of condensing vapor

3.1 Seasonal variations of daily-averag

ed 18O and precipitation

3. Results

The seasonal variations of daily precipitation and dail

y-averaged 18O in vapor and in precipitation at Manau

s, Brazil

-25

-20

-15

-10

-5

0

5

time (days)

δ18

O (

‰)

0

10

20

30

40

50

60

70

P (

kg

/m-2

)

O-18 in vapor O-18 in precipitation precipitation

J F M A M J J A S O N D

The seasonal variations of daily canopy dew, canopy reservoir and can

opy evaporation, and their daily-averaged 18O at Manaus, Brazil

-25

-20

-15

-10

-5

0

5

10

15

time (days)

δ18

O (

‰)

O-18 in canopy dew O-18 in canopy evaporation O-18 in canopy reservoir

J F M A M J J A S O N D

0

0.1

0.2

0.3

0.4

0.5

0.6

time (days)

Qca

n-d

(kg

/m-2

)

0

2

4

6

8

10

12

Qca

n-r;

Qca

n-e

(kg

/m-2

)

canopy dew canopy reservoir canopy evaporation

J F M A M J J A S O N D

The seasonal variations of daily surface dew and surface runoff,

and their daily-averaged 18O at Manaus, Brazil

-15

-10

-5

0

5

10

time (days)

δ18

O (

‰)

O-18 in surface dew O-18 in surface runoff

J F M A M J J A S O N D

0

0.02

0.04

0.06

time (days)

Qsu

r-d

(kg

/m-2

)

0

2

4

6

8

10

12

14

16

Qsu

r-r

(kg

/m-2

)

surface dew surface runoff

J F M A M J J A S O N D

3.2 Simulation of monthly-averaged 18

O and waters (moisture)

-15

-10

-5

0

5

10

J F M A M J J A S O N D

δ18

O (

‰)

O-18 in canopy dew O-18 in canopy reservoir

O-18 in canopy evaporation

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

0

0.1

0.2

0.3

0.4

J F M A M J J A S O N D

month

Q1

(kg

/m-2

)

0

50

100

150

200

Q2

(kg

/m-2

)

canopy dew canopy reservoir

canopy evaporation

0

100

200

300

400

500

600

J F M A M J J A S O N D

month

P (

mm

)

-6

-4

-2

0

2

δ18

O (

‰)

simulated results

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

0

100

200

300

400

J F M A M J J A S O N D

month

P (

mm

)

-10

-8

-6

-4

-2

0

δ18

O (

‰)

precipitation O-18 in precipitation

actual survey

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

The diurnal variation of 18O in canopy dew, canopy reservoir an

d canopy evaporation for January (a) and July (b) at Manaus

-9

-6

-3

0

3

6

9

1 3 5 7 9 11 13 15 17 19 21 23

time

δ18

O (

‰)

O-18 in canopy dew O-18 in canopy reservoirO-18 in canopy evaporation

(a)

time (hours)

-20

-15

-10

-5

0

5

10

15

1 3 5 7 9 11 13 15 17 19 21 23

δ18

O (

‰)

(b)

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

-2

0

2

4

6

8

1 3 5 7 9 11 13 15 17 19 21 23

time

δ18

O (

‰)

O-18 in surface dew O-18 in surface runoff

(a)

-8

-4

0

4

8

1 3 5 7 9 11 13 15 17 19 21 23time

δ18

O (‰

)

O-18 in surface dew O-18 in surface runoff

time (hours)

(b)

3.4 Simulation of Meteoric Water Line (MWL)

simulated MWL in precipitation

δ D = 7.49δ18O + 6.25

r2 = 0.99

-45

-30

-15

0

15

30

-7 -5 -3 -1 1 3

δ18O (‰)

δD

(‰)

simulated

Comparisons between actual and simulated MWLs in precipitation

actual MWL in precipitation at Manaus

δD = 8.14δ18O + 12.96

r2 = 0.97-120

-80

-40

0

40

-15 -10 -5 0 5

δ18O (‰)

δD

(‰

)

actual

actual MWL in precipitation at Manaus

δD = 8.14δ18O + 12.96

r2 = 0.97-120

-80

-40

0

40

-15 -10 -5 0 5

δ18O (‰)

δD

(‰

)

actualGMWL

δD= 8.0δ18O+10.0

δ18O (‰)

simulated MWL in surface runoff

δ D = 3.05δ18O - 5.13

r2 = 0.66

-20

-10

0

10

20

-4 -2 0 2 4 6 8

δ18O (‰)

δD

(‰

)

Simulated MWL in surface runoff

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)))

Variations of 18O in surface soil reservoir for different scheme

-500

-400

-300

-200

-100

0

J F M A M J J A S O N D

month

δ18

O (

‰)

scheme-1 scheme-2 scheme-3

-260

-240

-220

-200

1 3 5 7 9 11 13 15 17 19 21 23

time (hours)

δ18

O (

‰)

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

-250

-225

-200

-175

-150

J F M A M J J A S O N D

month

δ18

O (

‰)

scheme-1 scheme-2 scheme-3

-220

-200

-180

-160

1 3 5 7 9 11 13 15 17 19 21 23

time (hours)

δ18

O (

‰)

Variations of 18O in transpiration for different schemes

-250

-225

-200

-175

-150

J F M A M J J A S O N Dmonth

δ18

O (

‰)

scheme-1 scheme-2 scheme-3

-240

-220

-200

-180

-160

1 3 5 7 9 11 13 15 17 19 21 23

time (hours)

δ18

O (

‰)

4. conclusions1. Simulations show reasonable features in the seasonal and diurnal vari

ations 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.

End of Presentation