The Influence of the Underlying Land Surface on the Water Exchange between Earth and Atmosphere

W O R K I N G P A P E R

1 ^THE INFLUENCE OF THE UNDERLYING lAND SURFACE

ON

THE WATER EXCHANGE

1 ^{BEMEEN EARTH AND} ATMOSPHERE.

M.Ya.

A n t o n o u s k y P.A. Kolosou A.A. Minin

December 1988 W-88-108

i n t e r n a t i o n a l I n s t i t u t e for Applied Systems Analysis

THE INFLUENCE OF THE

UNDERLYING

LAND SURFACE ON

THE

WATER

EXCHANGE BGlWEEN

EARTH

AND

ATMOSPHERE.

M.Ya. Antonovsky P.A. Kolosov A.A. Minin

December 1988 WP-88-108

W o r k i n g Papers are interim r e p o r t s on work of t h e International Institute f o r Applied Systems Analysis and h a v e r e c e i v e d only limited review. Views o r opinions e x p r e s s e d h e r e i n d o not necessarily r e p r e s e n t t h o s e of t h e Institute o r of i t s National Member Organizations.

INTERNATIONAL INSTITUTE FOR APPLIED SYSTEMS ANALYSIS A-2361 Laxenburg, Austria

Foreword

In t h i s Working P a p e r , t h e a u t h o r s p r o d u c e maps of IWR, a n index of water ex- c h a n g e v a r i a b i l i t y p r o p o s e d by t h e National Environment a n d Climate Monitoring L a b o r a t o r y , Moscow ( s e e Lisseev a n d Minin, 1986). Values of t h e index are comput- e d from measurements of monthly p r e c i p i t a t i o n a n d e s t i m a t e s of monthly evapo- t r a n s p i r a t i o n obtained from a l a r g e number of h e a t budget s t a t i o n s in t h e Soviet Union. Values of IWR c o r r e s p o n d r e m a r k a b l y with ecosystem t y p e s , t h e isopleths being closely p a c k e d along e c o t o n e s ( s e p a r a t i n g f o r e s t a n d t a i g a , f o r example).

Given some f u t u r e climate s c e n a r i o , t h e method could b e used t o estimate c h a n g e s in t h e locations of ecotones. Thus t h e p a p e r is a contribution t o t h e ICSU IGBP p r o g r a m (International Geosphere-Biosphere P r o g r a m ) a n d as s u c h , i s t o b e welcomed.

Bo R . Doos

L e a d e r , Environment P r o g r a m

-

ⁱⁱⁱ

-

THE INFUTENCE OF THE UNDERLYING LAND SURFACE

ON

THE WATER EXCHANGE

BElW?ZN EAK@l AND ATMOSPHERE.

M.Ya

A n t o n o u s b . P.A. Kotosou* a n d A.A. Minin*

1. INTRODUCTION

The

water

exchange between land and atmosphere i s a p r o c e s s of g r e a t impor- t a n c e t o t h e biosphere. In f a c t , t h e hydrologic cycle i s t h e main p r o c e s s through which living organisms are provided with water and nutrients. The r o l e of ecosys- tems in t h e regulation of this water exchange i s not as y e t clear. The local hydro- logic cycle is, in p a r t i c u l a r , as follows: precipitation falls on t h e land, i s transformed by t h e ecosystem, and r e t u r n s t o t h e atmosphere by evapotranspira- tion. The t y p e of ecosystem influences t h e input-value (precipitation) only

to

a small d e g r e e . Such influences have been explored by Konstanitov (1963). Fedorov (1977), Rakhmanov (1984). etc. But o u r knowledge of a n ecosystem's ability

to

in- fluence t h e output (evapotranspiration) i s not sufficient. This p a p e r i s devoted t o a new method of investigating t h i s important problem.

2. YETBODOLOGY

An ecosystem i s a unit of t h e biosphere in which different p a r t s

-

vegetation, soil, t h e atmospheric boundary l a y e r , animals

- ^are

connected by

fluxes

of m a t t e r and energy. Problems arise when r e s e a r c h e r s attempt

to

estimate

an

ecosystem's

*

Natural Environment and Climate Monitoring Laboratory COSKOMCIDROMET and USSR Academy of Sciences, Moscow.

behavior, as t h e r e are no e x a c t methods of observation and measurement. There- f o r e , a new method t o r e v e a l and estimate t h e influence of a n ecosystem on ex- change p r o c e s s e s i s proposed. This method used a comparison of ecosystem input and output fluxes, and i s based on a statistical analysis of a long-term s e r i e s of ob- servations, yielding climatic values.

The method i s based on a comparison of time variabilities of local moisture fluxes. Precipitation (P) i s considered as t h e input value, and evapotranspiration (E) as t h e output value. The growing season and t h e individual months are analyzed.

The purpose i s to study t h e r a n g e of "output" changes (E) t h a t c o r r e s p o n d

to

t h e r a n g e of t h e "input" changes (P) f o r different ecosystems, using a new index IWR.

proposed in Minin (1986; 1988a). The index IWR i s t h e r a t i o of t h e precipitation and evapotranspiration variabilities as follows:

Here, IWR

-

index of water exchange; p

-

probability (%) of any value exceeding some fixed level, i.e., p =p (X

>%);

^Pp, PlO0 *, Ep , EIOO

-

monthly amounts of precipitation (P) and evapotranspiration (E) during t h e growing season f o r proba- bility p o r 1 0 0 p . The index of time-variability i s 6%

= I$ -

XlO0

*.

where X i s any variable. The probability p may b e corinected with a time interval ( f o r exam- ple, p=20X

means

a 5-year period).

%

i s a mean maximal value f o r a s t a t i s t i c a l period determined by probability ( p ), and X1OO-p i s a mean minimal value f o r t h e s a m e period.

Three situations are possible (Figure 1).

IWR

>

1, ecosystem attenuates input signal

-.

Ecos.

iZ/\

^IWR

^<

^1. ecosystem intensifies input signal

/ \ p f ] v

^IwR

⁼

^{1, signal is} not transformed by ecosystem Figure 1: Scheme of ecosystem's influence on the water exchange.

Figure 2: Location of water budget stations.

W e investigated t h e behavior of this index during t h e growing season

at

six water-balance stations in t h e USSR (Figure 2). (The Primorskaya station, situated in a broad-leaved f o r e s t zone n e a r t h e town of Ussuriysk in t h e f a r

east

of t h e USSR, i s not shown in t h e figure.) W e also investigated the time-space distribution of t h e index f o r boreal f o r e s t s and steppe zones in t h e USSR. The investigations

were

based on a l a r g e climatological dataset. The monthly precipitation (meas- ured) and evapotranspiration (estimated using t h e Budyko method) (Budyko, 1984) during t h e investigation

are

included in t h e analysis. The probability curve approximating t h e long-term s e r i e s of meteorological d a t a w a s determined by a method of Kolosov (1972), Kolosov and Lisseyev (1987) and Minin (1988a), based on Pearson three-type curves. The values of Pp,lOOp and Ep

,loo were

taken from t h e s e theoretical curves (Minin, 1988b).

A t t h e regional level t h e d a t a of monthly observed precipitation and estimated evapotranspiration were taken from Shver (1976) and Zubenok (1976) respec- tively. Space resolution

was

2 X 2 degrees.

3.

RESULTS AND

DISCUSSION

3.1. Local Level

A s e r i e s of 124 monthly precipitation and evapotranspiration ranges has been analyzed. The

serles are

successfully approximated by Pearson three-type theoretical curves, leading

to

t h e results shown in Table 1.

W e notice t h a t t h e relation Ca m 2Cv (see Table 1 , p.5) is approximately ful- filled both f o r precipitation and evapotranspiration. Shver (1978) obtained a simi- lar

result

f o r precipitation in h e r analysis of numerous long-term s e r i e s but t h e results f o r evapotranspiration have not previously been obtained. Knowledge of Ca/Cv helps

to

calculate E- and P-value probabilities on a regional level, when t h e r e i s information of mean-values. Cv only.

Table 1: Values of Ca* and Cv**

'

Forest and grass:

Sum Mean

Under forest crown:

Sum Mean

--

Ecosystems

Total:

56.7 33.64 1.7

Mean 1.0 0.61

--- Evapotranspiration

* Ca

-

coefficient of aeymrnetry; ** Cv

-

coefficient of variation.

- --

Precipitation

number of observation periods

The dynamics of IWRZgX in different ecosystems during t h e growing season i s shown in Figure 3. In most c a s e s , t h e index i n c r e a s e s during t h e growing season.

However, t h e c u r v e s f o r f o r e s t and meadow (Figure 3a) a r e different; maximum values f o r f o r e s t o c c u r in August and September and f o r meadow in June and July.

This may b e r e l a t e d t o different vegetative dynamics of t h e s e ecosystems. The g r a s s develops more quickly during t h e growing season than t h e f o r e s t in Valdai.

Figure 3d shows t h a t IWRZOX h a s

a

minimum value in July in t h e crop-fields (Figure 3d). This i s due

to

t h e f a c t t h a t harvesting of t h e plant communities leads

to

a reduction of t h e

water

exchange regulatory p r o p e r t i e s , indicating t h e important r o l e of human activity in

water

exchange. A similar e f f e c t i s

also

b e revealed on

a

regional level.

number of observation periods

Ca

.

Ca Cv Cv W

Cv Ca/

a ) Valdai: 1. under the b ) Volhov: 1 ) virgin soil;

crown of spruce forest; 2 ) glade in forest; 3 ) under 2. spruce forest; the crown of mixed forest 3. meadow

o . , ^{C l}

.

^month

V VI HI U 11 v VI V I HI1 11

C ) Podmoskovnaya st.: d ) Prirorskaya st.:

1 ) under the crown of 1 ) virgin soil;

birch forest; 2 ) meadow 2 ) spring wheat;

3 ) Kamennaya Steppe, virgin 3 ) clover;

soil; 4 ) Nizjnedeviskaya, 4 ) soya virgin soil

F i g u r e 3: T h e dynamics of IWRzox in d i f f e r e n t e c o s y s t e m s during: t h e growing seasor..

The mean probability values of IWR f o r all studied ecosystems (excluding

"under t h e crown") are as follows: IWR,,= 2.15; lWR,,

=

2.22; IWR,,

=

2.23.

3.2. Regional level

The r e s u l t s of t h e statistical analysis

at

t h e local level have been used f o r regional level studies. Mean amounts of precipitation and evapotranspiration and i t s Cv were taken from S h v e r (1976) and Zubenok (1976). Then probabilistic amounts of precipitation and evapotranspiration f o r probability p and 100-

in

e a c h cell 2' x 2' g r i d

were

calculated from t h e statistical t a b l e s f o r Pearson's t h i r d t y p e c u r v e s (Klibashev and Goroshov, 1970). The calculation c a r r i e d out allowed us t o c o n s t r u c t c h a r t s of IWR and a l s o of variabilities of precipitation and evapotranspiration f o r monthly and seasonal time-scales. W e chose t h e probability 20% because errors due t o a lack of e x a c t amounts of Ca and Cv in e a c h c e l l are a minimum in t h e calculations, due t o t h e n a t u r e of P e a r s o n ' s three-type c u r v e s (Kolosov and Lisseyev, 1987).

The map of precipitation variability (Figure 4) shows m o r e variability in t h e b o r e a l f o r e s t zone during t h e growing season t h a n t h e s t e p p e o r d e s e r t zones (in absolute sums, h e r e and l a t e r , t h e values are in centimeters). The regions with l a r g e r variability coincide with t h e forest-steppe and s t e p p e of t h e USSR. There are almost homogeneous fields of variability in t h e b o r e a l f o r e s t .

The map of seasonal variability in evapotranspiration (Figure 5 ) i s developed from a p a p e r by Antonovsky and Kolosov (1987) on energetically a c t i v e regions b

o v e r land. One important sign of such regions i s t h e high time-variability of output water-fluxes. Over t h e plains of t h e

USSR, _{t w o}

energetically a c t i v e regions, situated in forest-steppe and s t e p p e zones on t h e European

territory

a n d in

W e s t

Siberia,

were

revealed. These regions

are

v e r y sensitive

to

climatic changes.

Figure 4: Mean variability of precipitation f o r the growing season (bP2-,X)

F i g u r e 5: Mean v a r i a b i l i t y of e v a p o t r a n s p i r a t i o n f o r t h e growing s e a s o n ( 6 E z o x )

Figure 6: IWRPOX May

F i g u r e 7: IWRzox June

Figure 8 : IWRzox July

Figure 9: IWRzM August

Figure 10: IWRzox September

In Figures 6 t o 10, t h e dynamics of IWRZoX during t h e growing season is shown.

Some differences in t h e IWRZm distribution o v e r t h e European T e r r i t o r y (ET) of t h e USSR and in West S i b e r i a (WSb) are observed in May. IWRzo, i n c r e a s e s gradu- ally from south

to

n o r t h o v e r t h e ET while

areas

of IWR

<

1 a p p e a r in t h e middle of WSb. There

are

no differences in

water

regulation between f o r e s t and s t e p p e

at

t h e beginning of t h e growing season when t h e "green machine" does not work inten- sively.

In June, t h e f o r e s t s o v e r t h e ET and WSb show approximately equal values of IWR. The b o r d e r between f o r e s t and s t e p p e begins t o b e revealed by t h e s t r o n g gradients in IWR. In July, t h i s b o r d e r i s much clearer. This i s t h e month when differences in water regulation between f o r e s t and s t e p p e are maximal. A t this time of y e a r in t h e middle latitudes, maximal biomass production and leaf area in- dex o c c u r . However, in t h e s t e p p e zone of t h e ET, t h e r e area areas with IW;R r 1.

These are likely due t o harvesting of grain c r o p s , which t a k e s place o v e r a wide area practically simultaneously, disturbing t h e dynamics of n a t u r a l processes. I t i s interesting t h a t t h e July amounts of IWRZoX o v e r t h e s t e p p e (stations: Bolchov, Niz jnedeviskaya and Kamennaya S t e p p e ) (Figure 3), are 1.2 -1.6, while IWRPOX for a g r i c u l t u r a l areas in t h e s t e p p e zone i s 0.9%. Such a n example shows a way to com- p a r e t h e water r e g u l a t o r y p r o p e r t i e s of n a t u r a l and a g r i c u l t u r a l ecosystems.

The existence of similar areas in WSb in May and June may b e explained by t h e continentality of t h e climate. The large-scale variation of evaporation i s typical f o r WSb, b u t

water

i s always available f o r evaporation in s p r i n g a f t e r t h e snow melt, in bogs, forest-steppes, lakes,

etc.

In August, t h e c o n t r a s t in IWR-values between f o r e s t and s t e p p e i s less t h a n in July. N e w growth slows down, while leaves begin to fall from t h e

trees.

The differ- e n c e in IWR values d i s a p p e a r s in September.

Thus t h e water regulatory behavior of ecosystems during t h e growing season is different; i t i s more variable in t h e s t e p p e and more s t a b l e in t h e f o r e s t . By means of t h e IWR-method, w e a r e a b l e t o identify regions which would b e t h e f i r s t to respond

to

climate changes and o t h e r regions which would b e t h e l a s t in t h e i r response. I t i s quite c l e a r t h a t t h e f o r m e r are c h a r a c t e r i z e d by IWR

<

1 , and t h e latter by IWR

>

1. W e suppose t h a t t h e ecosystem p r o c e s s e s in such homogeneous areas develop in a similar way. This knowledge i s useful in designing a n optimal network of monitoring stations.

A map of mean values of IWRzoX f o r t h e growing season i s shown in Figure 11.

Of i n t e r e s t is t h a t t h e line f o r IWRzox

=

2.0 coincides exactly with t h e b o r d e r between f o r e s t and forest-steppe zones (forest: IWR

=

2.0-3.0; steppe: approxi- mately 1.5). Maximum values of IWR on t h e ET o c c u r between 56 and 64 d e g r e e s N.

They practically coincide with t h e area of coniferous and coniferous broad-leaved forests. The line 2.5 s e p a r a t e s t h e broad-leaved s p r u c e undertaiga f o r e s t s and broad-leaved lime-oak and oak f o r e s t s . S o t h e coniferous ecosystems of t h e ET may a t t e n u a t e t h e variability of moisture conditions t o a f a r g r e a t e r d e g r e e than o t h e r ecosystems. In t h e WSb, t h e l a r g e s t values of IWR a l s o coincide with areas of coniferous f o r e s t s (spruce, Siberian pine, f i r ) and moss moors. Both in t h e ET and t h e WSb, t h e values of IWR are a maximum in t h e middle and south taiga, declining t o t h e north and south of t h i s zone.

Mean values of I'WR,, f o r t h e f o r e s t ecosystems

are

2.5, f o r t h e s t e p p e 1.5, and f o r a g r i c u l t u r a l land at t h e regional level (taking into account t h e r e s u l t s of t h e study

at

t h e local level) 1.2. This means t h a t f o r e s t r e d u c e s t h e variability of t h e climatic signal 2.5 times, s t e p p e 1.5 times and farmland only 1.2 times.

Nowadays, t h e land s u r f a c e i s transformed by human activities of d i f f e r e n t kinds. S o o u r estimates of t h e water regulatory p r o p e r t i e s of different ecosystems give a possibility t o estimate t h e changes in t h e s e p r o p e r t i e s at t h e global level

(Table 2).

Figure 11: Mean values of IWR20X f o r the growing season.

Table 2: Estimates of some consequences of land ecosystem changes by man.

(Lisseev and Minin (1986), with additions by authors).

A

-

albedo; LE

-

f l u x e s of l a t e n t heat; H

-

f l u x e s of e x p l i c i t heat; t o t a l v a l u e s a r e c a l c u l a t e d a s weighted average.

The level of water exchange regulation by ecosystems i s reduced by 1.6, changes taking place in t h e

structure

of t h e heat balance and in albedo. O u r results (especially f o r albedo) correspond to t h e estimates obtained by Ephimova (1983) and Budyko (1984).

- -- . - - .

C h a r a c t e r of e c o s y s t e m 6 t r a n s i o r m a t i o n

N a t u r a l e c o e y s t e m ( f o r e s t , s t e p p e , etc.) i n t o buildings, roads, engineering c o n s t r u c t i o n s i n t o w a s t e l a n d i n t o r e e e r v o i r s F o r e s t s i n t o meadows, p a s t u r e s , s h r u b s , swamp S t e p p e , p r a i r i e i n t o f i e l d s I r r i g a t i o n Land under t h e influence of r e s e r v o i r s on t h e g r o u n d w a t e r s i n t h e U S S R Draining land

T o t a l

-- --.

X of land a r e a AX

3 3 0.3

27

9.6 1.8

0.7

1.3

46.7

r - ^-

Area of influence mln.sq.lPn.

a r e a

4.5 4.5 0.4

40

14.3 2.7

1

2

69.4

- - - -

E s t i m a t e s of some p a r a m e t e r c h a n g e s

L E ( P O ~ / ~ ') ~ ( W r / m ')

+ 5 -20 + 5

+ 5 -15 + l o

-10 +20 0

+ 8 -25 + 5

0 -5 + 5

-7 + 15 -6

-4 + 10 0

+ 5 -5 + 5

+ 5 -17 + 5

. ^-

^-- _-7

Changes of IslII

2.0 4 1.0 2.0 4 1.0

2.5 4 1.5

1.5-1.2

2 . 2 4 1 . 4

General changes in s u r f a c e p r o p e r t i e s are t h e r e s u l t of a c t i v e transformation of land s u r f a c e s by human activities increasing during t h e p a s t 200 y e a r s . This may have had some harmful consequences. For example, 40 droughts o c c u r r e d in Rus- s i a from t h e Xth

to

t h e XIIth c e n t u r i e s

(an

a v e r a g e of one drought p e r 20 years).

In t h e XIXth c e n t u r y , t h e r e were t e n s e v e r e droughts (approximately 1 in 10 years). In t h e XXth century, t h e frequency of droughts increased

to

1 in 3 y e a r s (Shipunov, 1985) The most s e v e r e droughts o c c u r in t h e s t e p p e and forest-steppe zones of t h e USSR. A s a r e s u l t , dust storms become more frequent, causing soil erosion. We must remark t h a t areas where dust storms o c c u r frequently are areas where IWR

<

1 in June and July.

4. CONCLUSION

A method of estimating t h e water regulatory p r o p e r t i e s of land ecosystems is suggested, based on t h e comparison of variabilities of t h e input (precipitation) and output (evapotranspiration) water signals. W e have shown quantitatively t h a t f o r e s t ecosystems have s t r o n g e r regulative p r o p e r t i e s than g r a s s e s o r c r o p s . A t t h e regional level, mean values of ZWRzox are: f o r e s t 2.5, s t e p p e 1.5, and farmland 1.2. Human activities have a s t r o n g influence on t h e dynamics of IWR in ecosystems on different time-space scales. Impacts o c c u r

at

regional and global levels.

Charts

are

p r e s e n t e d t h a t show t h e spatial distribution of a n ecosystem's po- tential response

to

climatic variations and fluctuations of d i f f e r e n t time-scales.

Identification of regions responding similarly

to

climatic changes i s v e r y important f o r optimal ~ o c a t i o n of environmental monitoring stations, in modelling of climate o r t h e biosphere, and in t h e exploration of biosphere sustainability.

ACKN(MLEDGMENT

The authors wish

to

thank Prof. R.E. Munn for his valuable support.

BEFEBENCES

Antonovsky

,

M.Ya., P. A. Kolosov (1987) EPL

srgetically rrdtue cltmate-jbnning regtons as revealed from d a t a o n surjtace euaporatton from l a n d a n d ocean.

WP-87-64. International Institute f o r Applied Systems Analysis, Laxen- burg, Austria.

Budyko, M.I. (1984)

Euolutfon of t h e Biosphere.

Leningrad, Gidrometeoizdat.

Ephimova, N.A. (1983) Influence of cutting down f o r e s t on change of global albedo and air temperature.

Meteorology a n d &drology,

5: 20-25.

Fedorov, S.F. (19'77)

Ezploratton of water budget elements tn the jbrest zone of European t e r r i t o r y of t h e m R .

Leningrad, Gidrometeoizdat.

Klibashev, K.P., Goroshov, I.Ph. (1970)

C4ydrological calculations.

Leningrad, Gidrometeoizdat

.

Kolosov, P.A. (1972)

Construction of probability papers

fir

some d i s t r i b u t i o n t y p e s

u s i n g

hydrology.

Vestnik. Moscow S t a t e University (geogr.).

Kolosov, P.A., A.A. Lisseyev (1987)

Assessment method for probabiltty d t s t r i b u - t i o n c u r v e b y short-period cltmatic observations.

Leningrad, Gidrometeoiz- dat.

Konstantinov, A.R. (1963)

Evaporation

i n

Nature.

Leningrad, Gidrometeoizdat.

Kurilova, Yu.V., A.A. Minin (1986) Estimation of t h e regulatory r o l e of landscape by c h a r t s of statistic zoning of humidification. In:

Materialy meteorologt- cheskich tssledouanij.

Moscow. Mezduvedomstvemyi geophisicheskij komitet (Soviet Geoph. Comrn.) 10: 45-51.

Lisseev, A.A., A.A. Minin (1986) Energetic estimation of t h e climatic r o l e of land surface antropogenic changes. In:

Materialy meteorologicheskich issledo- v a n t j .

Moscow. Mezd. geophisich. komitet (Soviet Geoph. Comm.) 10: 69-73.

Minin, A.A. (1988a) The r o l e of vegetation in t h e

water

exchange betwen land sur- face and atmosphere. In

T t u d y

2

kon$erendi molodych u c h j o n y h

LAM.

Mos- cow, Gtdrometeoizdat

fin

press).

Minin, A.A. (1988b) The analysis of long-term s e r i e s of monthly sums of precipita- tion and evaporation in different ecosystems. In

Materially meteorologt- c h e s k i h issledouanij.

Moscow, Mezd. geophisich, komitet (Soviet Geoph.

Corma.) (in press).

R a k h m o v , V.V. (1984)

~ d r o c l t m a t o l o g t c a l role of jbrests.

Moscow. Lesnaya promyshlemost.

Shipunov Ph. (1985) Y a

Dokuchamv "bastions".

N a s h

s o u r e m m n t k

2 136-163.

Shver, S.A.

Precipttatton o n t h e t e r r i t o r y of t h e

USW. Leningrad, Gidrometeoiz- dat.

Zubenok, L .I. (1976)

Euaporatton o n continents.

Leningrad. Gidrometeofidat.