Evaporation and Climate Change

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Evaporation and Climate Change

Theo Brandsma January 25, 1993

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Communication no. 45

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Eva

poration

and Climate Change

Theo Brandsma

Faculty of Civil Engineering Delft University of Technology

January 25, 1993

Abstract

In this artic1e the infiuence of c1imatechange on evaporation is discussed. The emphasis is on open water evaporation. Three meth-ods for calculating evaporation are compared considering only changes in temperature and factors directly dependent on temperature. The Penman-method is used to investigate the present relationship between temperature and open water evaporation forDe Bilt. Using the data for De Bilt the sensitivity of the open water evaporation to changes in all the input variables is examined. Two methods are proposed to construct evaporation scenarios, the c1imate analog method and artifi-cial elimate scenarios. FinaUy,a short discussion is given on the erop factor method.

1 In

t ro duction

Climate change due to the green house effect and natural elimate variations may significantly alter the amount of evaporation. Evaporation is an impor-tant factor in many hydrological studies. Therefore,in the present article, the calculation of evaporationvaluesfor changedelimate conditionswill be addressed.

1.1 Defini

tions

Evaporation can be defined as the energy consuming phase transition from liquid to vapor, while in the reverse process, condensation,the same amount of energy is set free. In this process evaporation is the connect ing link between the water budget and the energy budget. Therefore,evaporation is important both in climatological and in hydrological studies.

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2 1 INTRODUCTION

Evaporation from water saturated surfaces is determined mainly by en-ergy supply, to evaporate the water, and by the ability of the atmosphere to transport the vapor away from the surface.

For evaporation from water saturated surfaces often a distinction is made between evaporation from the soil and transpiration by plants, together denoted as evapotranspiration. In many cases this distinction is artificial. Therefore, in this article, the term evaporation is used for both processes.

Potentlal evaporation is the evaporation occurring when there are no limitations in water supply, i.e., the soil moisture content does not restriet plant growth. The actual evaporation is the evaporation experienced in re-ality, and is always a fraction of the potential evaporation. One other term is often used, namely the open water evaporation. The open water evapo-ration is the evapoevapo-ration from a lake with a limited water depth. However, it would be better to speak of a reference evaporation because for the com-putation of this evaporation: 1) no lake parameters are used; and 2) the meteorological input variables are measured above land surfaces. For clar-ity, however, the term open water evaporation is used in this article. Open water evaporation is often used in combination with the so-called erop factor method (section 5).

1.2 Description of the problem

Future elimate change may significantly alter the amount of evaporation in certain areas, especially in those areas where water is abundantly available. Nevertheless, the socioeconomie impact willlikely be largest in those areas where water is already scarce. It is obvious that it is important to assess the magnitude of the changes in evaporation as a result of elimate change.

To assess the impact of elimate change on evaporation it is necessary to obtain information on those variables that determine evaporation. Among those variables are temperature, net radiation, relative humidity, and wind-speed. However the input from elimate change studies is minimal. There is only some confidence in the globally or zonal averaged temperature changes. Therefore, the problem addressed in this artiele is to find an alternative method(s) to estimate the impact of climate change on evaporation.

1.3 Scope and objectives

The research in this artiele is restricted to the influence of elimate change on the open water evaporation. As said before, the open water evaporation can

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3

be used to calculate the potential evaporation using the erop factor method (section 5).

Geographically the research is restricted to De Bilt. De Bilt is regarded to be representative for the average conditions in the Netherlands.

The objectives of this artiele are: 1) to give a first order approximation of the influence of elimate change on evaporation; 2) to obtain open water evaporation scenarios; and 3)to examine the relationships betweenelimate and evaporation.

2 Comparison of evaporation equations

2.1 Theory and method

Three weIl known temperature-basedmethods for computing the evapora-tion are compared: the Thornthwaite-method, the Makkink-method, and the Penman-method. The methods are mentioned in the order of an in-creasing number of meteorological variables which are necessary to compute the evaporation. The Thomthwaite-method uses only temperature readings; the Makkink-method uses readings of temperature and incoming short-wave radiation; and the Penman-method uses readings for temperature,humidity, sunshine duration (or doudiness),and windspeed (if measured, the compo-nents of the radiation budget are also be used). The three methods are subsequently described below.

2.1.1 Theory

Thornthwaite-method The Thomthwaite-method (Thomthwaite, 1948)

has been derived for a short cut grass cover with optimum growing condi-tions. The coefficients in the equations are determined from experiments with lysimetersin the U.S.A. between 29 and 43° northem latitude. There-fore. if this method is used to calculate evaporation values for the Nether-lands. the results willlikely be wrong. However, it is suggested that it may still be used to assess the relative changes in evaporation. The equation is as fellows

Et

=

1.62b

[l~T]

a (1) where Etis the monthly potential evaporation in centimeters according to Thornt hwaite, bis an adjustment factor to account for the fact that sunshine is not 12 hours a day and the months are not all30 days in duration,T is

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4 2 COMPARISON OFEVAPORATION EQUATIONS

the mean temperature of a month in degrees Celsius, a is defined by the following equation a= 67.5 x10-8_{[ 3 -} _77.1_X_10-6_{[ 2}

+

_0.0179[

+

_0.492 ₍₂₎ where 12

[t ]

1.51 1=

L ;

m=1

(3)

andtm is the mean temperature in the mth month in degrees Celsius where

the mean temperature is averaged over several years.

Makkink-method Makkink (1957) proposed a simplified method for evap-oration during summer conditions in the Netherlands

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whereEris the so-called reference erop evaporation which is comparable to the concept of potential evaporation,Àis the latent heat of vaporization,I is the psychrometric constant, s is the slope of the saturation vapor pressure versus temperature curve, Cl and C2are constants and Ki is the incoming short-wave radiation, which is observed directly on a routine base at sev-eral stations in the Netherlands. Makkink assumed that the net heat flux into the ground equals zero (good approximation for wet grassland) and that C2 accounted for aerodynamic effects. For summer conditions in the

Netherlands C2~O. For grass cover the constantCl was found to be 0.65. De Bruin (1981a) compared the Makkink-method with several other methods, among others the Penman-method. He found a good agreement between the Penman-method and the Makkink-method for summertime evaporation values. The Makkink-method appeared to have such advan-tages, that the Royal Netherlands Meteorological Institute (KNMI) decided to use this method instead of Penman'5 method, starting from the first of April 1987. The main reason to look for an other method for the determi

-nation of evaporation was the fact that from Penman's method,which was used until April 1987, several versions exists, which caused a tremendous confusion. The main advantages of the method of Makkink are (de Bruin,

1987)

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2.1 Theory and method 5

• Itis remarkablysimple: it requires only air temperature and global radlation as input;both can be measured directly and very accurately; • Under dry conditions Makkink'smethodappearsto haveaneven

bet-ter performance.

Itshould be noted that the Makkink-method must be used with the erop fac-tor method to obtain potential evaporation. As compared with the Penman method different erop factors must be used.

Penman method Penman(1948) derived the foIlowing equation for evap-oration and he verified it for open water,bare soil and grass

>-'E

o= sQ"

_s+,

+

,>-'Ea (5) where Eois the open water evaporation according to Penman,

Q

"

is net radiation, >-'Ea= f(u)[e.(Ta) - eaj is the drying power of the air, f(u) is a wind function, e.(Ta ) is the saturation water vapor pressure at Ta(air

temperature)and ea is the water vapor pressure at screen height.

The net radiation,Q",can be calculated directlyusing the short-wave and long-wave components of the radiation budget. However,often these data are not available. Therefore,Q"is estimated using empirical relation-ships and measurements for temperature, relative sunshine duration and humidity. In this artiele these relationships are also used. In de Bruin (1981b) these relationships are explicitly stated.

Measurements are now needed for temperature, humidity,sunshine du-ration (or cloudiness), and windspeed. They are needed at only one height (usually 2 m). Although the Penman-method is adequate for many condi-tions, in many cases the necessary input data are lacking.Then one can use simplified versions of which the Priestley and Taylor-method and Makkink-method are weIl known examples.

2.1.2 Method

Meteorological data Evaporation will be computed with the three meth-ods using meteorological data of De Bilt in the Netherlands. These data consist of time series of daily data for temperature, relative humidity, rel-ative sunshine duration,and windspeed for the period 1970-1990. For the Thornthwaite-method the daily data are transferred into monthly data. For the Makkink and Penman-method daily evaporation values are calculated

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6 2 COMPARlSON OFEVAPORATION EQUATIONS

Figure 1: Penman open water evaporation(Eo) for the Netherlands: (a) mean annual evaporation computed for the period1951-1980;(b) mean evaporation corn-puted for the summer half year (April-September) for the period1951-1980(from Cultuurtechnische vereniging,1988).

which are subsequently summed to obtain monthly evaporation values. As noted before, several versions of the Penman-method are being used in prae-tiee. In this artiele the Penman evaporation is calculated according to the method described by de Bruin (1981b).

lt should be kept in mind that evaporation in the Netherlands varies in spaee and time as can be noted from figure 1.Itappears that the Penman open water evaparation decreases inland. This is caused by the fact that windspeed and sunshine duration decrease inland which predominates the effeetof higher temperatures inland (in the summer). It also appears that the evaporation for De Bilt is representative for the average conditions in the Netherlands.

Assumptions The main assumption made in this sectien is that only tem-perature changes are considered together with changes in those factors that are directly dependent upon temperature,like upward and downward long-wave radiation and the saturation water vapor pressure. All other factors are fixed. Inthe present climate,factors like relative humidity and sunshine durationdo vary along with temperature. Therefore, if the assumption of

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2.1 Theory and method 7

only temperature change is correct, evaporation equations which are more physically based willlikely produce more reliable results for a changed cli-mate than equations which are less physically based.

Net radiation is determined by the surface energy balance.Publications of Manabe and Wetherhald (1987) and Gutowski et al. (1991) show that it is not clear how the surface energy balance will change due to the greenhouse effect. Especially on a regional scale there is much uncertainty.

Gutowski et al.compared the surface energy balances simulated by three general circulation models for current climatic boundary conditions and for an atmosphere with twice the current levels of CO2 • In the global average

balance the downward long-wave fluxes, absorbed solar radiation, and sensi-bie and latent heat fluxes have intermodel discrepancies that are larger than respective flux changes associated with doubling CO2 • However, global

av-erages for the surface flux changes associated with CO2doubling are qualita

-tively consistent from model to model. The following changes are predicted: 1) the net long-wave radiation (downward minus upward) increases by 4 to 5 Wm-2_; _{2) the net short-wave radiation (downward minus upward)}

in-creases by 1 to 3 Wm-2

;3) the latent heat flux increases by 7 to 10 Wm-2; and 4) the sensible heat flux decreases by 1 to 3 Wm-2_• _{The actual values}

dep end on the model used for the simulation.

Gutowski et al. present the above-mentioned results also as a function of latitude. However,these results show large intermodel discrepancies and are, therefore, not reliable.

For the Penman-method and the Makkink method information is needed on the changes in short-wave radiation. Considering the above mentioned results for short-wave radiation, also as a function of latitude, it will be assumed that net short-wave radiation remains the same. Additionally, for the Penman-method, it will be assumed that for the computation of the net radiation only those variables have to be changed which depend directly upon temperature, namely incoming and outgoing long-wave radiation, LI and LT,respectively.

With respect to relative humidity, RH=

1;,

it seems reasonable to as-sume that the values for this variabie remain the same (Manabe and Wether-hald, 1975; Bultot et al. 1988). A direct consequence of this assumption is that the drying power of the air(~e), ~e

=

e, - e,increases with increasing temperature. The drying power of the air ean be expressed as a funetion of

RH and e,(T) as follows

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8 2 COMPARISONOFEVAPORATION EQUATIONS

Increasing temperature increases e.(T) according to the weil known satu-ration vapor pressure - temperature curve, thus increasing the satusatu-ration deficit.

The relatively small changes in net short-wave radlation suggest that changes in cloud cover are modest (Gutowski et al.,1991). This impliesthat, as a first approximation, it seems reasonable to assume that cloud cover, and thus sunshine duration, remain at the same level as in the present elimate. With respect to windspeed it isalso assumed that no changes occur with respect to the present situation,

Temperature change The temperature changest::..Tthat will be used are uniformly added or subtracted from the existing temperature series. The considered temperature changes are: t::..T E [-3,.. . ,+3] where t::..T is in degrees Celsius andis of the integer type. It may seem strange to examine the infiuence of a negative change in temperature, however, for example a small change in the course of the gulf stream may prove such a scenario to be rea1istic.

Sealing of the equations In this section three methods for calculating evaporation are exarnined. In fact all three methods give a measure for the potentialevaporation. To be able to compare the three methods with respect to elimate change the evaporation values are scaled in such a way that the averages. over 21 years,of the mean monthly evaporation values are the same for all three methods. For this purpose the Penman method is taken as the base method.

To illustrate this principle consider the mean monthly evaporation ac-cording to Penman

1 21 ..

aj

=

21

"f-

E~J

(7)

.=1

whereaj is the mean open water evaporation according to Penman in the

ph

month for the presentelimate. Let bj be the mean reference erop evaporation for monthj according to Makkink. then the sealing factor can be computed as

<pj

=

aj (8)

bj

where <pjis the sealing factor for the

ph

month. To make the methods comparable for monthj allMakkink evaporation values for month

i

,

in the period 1970-1990, are multiplied by <Pj. The same principle is also applied

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2.2 Results 9

to the Thornthwaite-methodto obtain the scaled Thornthwaite evaporation.

The scaled Thornthwaite evaporation and scaled Makkink reference erop evaporation will further be denoted as

E;

and

E;

,

respectively.

In fact this method was also used in the Netherlands to obtain the new erop factors when one shifted from the Penman open evaporation to the Makkink reference erop evaporation (CHO-TNO,1988).

2.2 Results

The results in this section apply to the Penman open water evaporation according to equation5and the scaled Thornthwaite and Makkink evapo-ration. All computations are carriedout with the meteorological time series data for De Bilt (1970-1990). For the Thornthwaite-methodthe daily tem-perature readings were averaged to obtain monthly values. For the Penman-method and the Makkink-Penman-method evaporation is ca!culated for each day in a month. Subsequently, the daily evaporationvalnes are summed up to obtain monthlyevaporation va!ues.

Comparison of simulations under present climate conditions It

appeared, as expected, that the difference between the Penman evaporation values andthe sca!ed Makkink va!ues is negligible. On the other hand,the

difference between the Penman evaporation values and the sca!ed Thorn

-thwaite va!ues may become rat her large in the summer months. This is illustrated in figure2. A difference of40 mm in tota! summer evaporation is not exceptiona!. The fact that Thornthwaite considered only temperature as input variabie seems to be animportantcausefor the observed differences.

Changes in mean annual evaporation The percentage changes inmean

annual evaporation (averaged over21years) as a function of temperature change are given in figure3. The percentage changes are definedas follows

PC =

Eann

(~T)

- 613.7lOOrt

613.7 0 (9)

where PC is the percentage change in evaporation,613.7is the mean annual evaporation ,averaged over 21years,under present elimate conditions,and

Eann(~T) is the mean annual evaporation for a specified ~T. It can be noted that the Thornthwaite-methodis most sensible to changes in temper-ature followed by the Penman-method and the Makkink-method.

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150 120 .--. .J:

-

C 0 90 E <, E &0 E

....

30 1\ I

~

t\

I

M

~

f\

À

I

II

J

\J

\1

J

I

\Ij

\~

\u.

}

,

2 COMPARlSONOFEVAPORATION EQUATIONS

EO (Pen man)

Et

(scaled Thornthwaite)

o 1970 1971 1972 1973 1974 1975 197& 1977 1978 1979 1980 .10

~

~\ ~~

~

\

,I

~

.

~

L~ 11. ~

J

~' I lt,

t

IJ,

\

11 o 11180 1981 11182 11183 U8. 11185 1986 11187 11188 111811 1lI110 111111 150 120 .--.

;:

c 0 90 E <, E &0 E

....

₃₀ Time (years)

Figure 2: Comparison of the Penman open water evaporation,Eo,and the scaled

Thornthwaite evaporation,

E;

I for De Bilt in the Netherlands (values are per

month).

Changes in mean monthly evaporation The mean monthly values for

the Penman open water evaporation, the scaled Thornthwaite evaporation, and scaled Makkink evaporation (for the period 1970-1990) for the present

elimate conditions are given in table1.

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abso-2.2 Results

20

15 _{E; (.caled lotakklnk)}Eo (Penman) 10 " E; (.caled Thornlhwalte) ... 5 t'e ... 0 o a.. -5 -10 -15 -20 11

Figure 3: Percentage changes in the mean annual evaporation (using the mete-orological time series data of DE Bilt for theperiod 1970-1990)as a function of the change in temperature,for the Penman-method(Eo),the scaled Thomthwaite-method (E;), and the scaled Makkink-method (E;). Besides temperature only those variables are changed that depend directlyon temperature, like long-wave radiation and saturation vapor pressure.

month Jan Feb Mar Apr E (mm) 4.9 13.1 34.1 60.9 month May Jun Jul Aug E (mm) 98.3 107.0 112.0 94.7 month Sep Oct Nov Dec E (mm) 53.0 25.2 7.8 2.9

Table 1: The mean monthly open water evaporation (for the period 1970-1990) according to the Penman-method for present c1imate conditions in De Bilt.

lute changes in mean monthly evaporation are given in figure 4. Ifone is interested in evaporation changes for values of !::l..Tin between !::l..T

=

-3 and !::l..T= +3

oe,

the results can be interpolated linearly to the results for !::l..T= 0

oe

,

for which the changes are zero. The changes in monthly evapo-ration are largest for the Penman and Thornthwaite-method and smallest for the Makkink-method. Only in autumn the increase in Penman-evaporation values is larger than the Thornthwaite evaporation values.

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12

...

E E

...

2 COMPARlSON OFEVAPORATION EQUATIONS

...

E E w .!::

..

'"

c o s: u

o

-2 -4 -6 -8 -10 -12 -14 J F A J J A

s

o

N D t.!onth

Figure 4: Absolute changes in mean monthly evaporation (using the meteorologi-cal time series data of De Bilt for the period 1970-1990) for the smeteorologi-caled Thornthwaite-method (1:;), the scaled Makkink-method (17;), and the Penman-metbod (Eo):

(a) for an increase in temperature oft::.T

=

+3 ·C; and (b) for an decrease in temperature oft::.T=-3·C. Besides temperature only those variables are changed that depend directlyon temperature, like long-wave radiation and saturation vapor pressure.

2.3 Discussion of the results

The fact that the Penman and scaled Thornthwaite evaporation values in figure 2 do not coincide, espedally in the summer months, is probably caused

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2.3 Discussion ofthe results 13

by the fact that the Thornthwaite-method does not explicitly account for sunshine duration. Also the fact that the Thornthwaite-method is derived for conditions in the U.S.A.may still be a cause for the discrepancy,although it was hoped to remove this effect by sealing the Thornthwaite evaporation values. On the other hand,the agreement between the Penman evaporation values and the scaled Makkink evaporation values (not shown) is probably caused by the fact th at besides temperature both methods take into account incoming short-waveradiation (or sunshine duration).

The infl. uence of relative humidity is implicitly accounted for in the Makkink-method for in the present elimate relative humidity is linearly re-lated to incoming shortwave radiation. Apparently the infl.uence of wind-speed is of minor importance for°a fixed location.

The results in figure 3 give a first order approximation of the relative changes in mean annual evaporation as a function of temperature changes. The Makkink-method serves as a lower boundary and the Thornthwaite-method as an upper boundary. Itis expected that the Penman-method gives the best results because it is the most physically based method among the three methods examined. Itcan also be noted that the increase and decrease in evaporation values for the Makkink-method are much smaller than for the Penman-method, This is caused by the fact that for the Makkink-method changes in temperature only affect the slope of the saturation vapor pressure-temperature curve (and slightlythe parameters A and j). On the other hand, for the Penman-method, temperature changes affect also the radiation balance, while for the Thornthwaite-method the evaporation is fully governed by temperature alone.

The results in figure 4 indicate that the Penman and Thornthwaite-method compare fairlyweIl for mean monthly changes in evaporation. How-ever, as mentioned before,for individual years the differences may become much larger. The rather strange shape of the curve for the Thornthwaite values in figure 4b,can probably be explained by the course of the sealing factors over the year,which shows a peak in the months March and April. The values for the Makkink-method are again smaller than for the other two methods for reasons mentioned befere.

In the remaining part of this artiele the discussion wil! be restricted to the Penman-method as this method is the most physicallybased method among the three methods discussed in this section. Furthermore, the Penman-method provides a means to evaluate independently the influence of changes in the several different meteorological variables as will be shown in the fol-lowing section.

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14 3 SENSITIVITYOFTHE PENMAN EQUATION

In the remaining part of the artiele the Penman open water evaporation will be calculated using the mean of the daily meteorological variables for each month. Itappeared that there is only a negligible difference between Penman monthly open water evaporation calculated with daily values for the meteorological input values and with monthly averages.

3 Sensitivity of the Penman equation

3.1 Introduetion

Inthe foregoing section the infiuence of temperature on the evaporationwas examined using three different methods for calculating evaporation. In this section only the Penman-method is considered. The present relationship between temperature and evaporation is examined. Further,the sensitivity of the Penman equation to changes in the various meteorological factors is calculated.

3.2 Present relationship temperature - open water evapora-tion

It may be argued that the present relationship between temperature and evaporation provides the key to future evaporation values. However,it may also be argued that this is not true,because a certain temperature in the present elimate is aresult from a different physical process than the same temperature in agreenhouse influenced world (e.g.2XC02 conditions).

In this section the present relationship between temperature and open water evaporation for De Bilt is examined and compared with the results from the foregoing section.

The relationship is given in figure 5. For each month 21(1970-1990) values are given for mean montWy temperature and the monthly Penman open water evaporation. A linear regression line is drawn through the data and the correlation coefficients are given. All correlation coefficients are significant at the 0.05 level. This means, that the probability that a cor-relation coefficient of at least the given value is obtained when there is no linear association in the population between temperature and open water evaporation is less than 0.05.

From figure 5 it follows that there is a relationship between temperature and open water evaporation values for each month of the year. Using the

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3.2 Present relationship temperature - open water evaporation

15

JAN ('''0.63) O'-'--'---'----J'-'--'--'---' -4 -2 0 2 4 MAR ( ... 0.15) 40 3 5 ; ,

.~

30

X: .

...

45 FEB 20 25

::~

5 25 '-.1--'-...1....-'--'--'--' -4 - 2 0 2 4 6 8 10 2 3 4 5 6 7 8 9

..

,

2 •

.

12 ,.-r-...,.-,.--r--::r--, 10 8 o

...

80 . ...,,...,,.._.--..., 160 ,--r-...,...,.---,--r--,

...

JUN (raO.I5 ) • •

..

.

••

80 140 100 120 MAY 120

~/"O"qj

. ..

.

100

.

•

,

.

80

••

.:

. .

~

:

.

APR (r.0.15)·• • 60 70 50 Ê

!.

8 160 . ...,...,...,,....,...,.--, 65,--r--,---.-"""""'" AUG 120 (r.O.I5). Ê

!.

140 120 100 JUL (r.O.II)

• ..

100

.

• • #

· ..

80 •

.

•

..

_•

60 55 50 45 SEP

....

.

80 60 40 '----''--l._..J..._"'----' 15 16 17 18 19 20 21 15 16 17 18 19 20 21 11 12 13 14 15 16 35,--.---.---r----, NOV·

..

_.

..

....

.

DEC (raO,'I)

•

o -2

.

(r zO. " 4 )

/

. .

..

· ..

,.

.

...

14 ~~_r_~~~~_ 12 10 8

....

• ..

v ;

,.

aCT (r.O.87)

•

30 20 25 o

...

Ê

!.

8 2 '-J-..l...L...1....--I...L-l -4 '--'-_J--'-_...L..-' 2 3 4 5 7 8 9 -2 0 12 14 10 15 ' - - ' - - - ' - _..._ - ' 6

T.mp.ratur. T.mp.ratur. T.mp.rature

Figure 5: Present relationship for each month between mean monthly temperature

and monthly Penman open water evaporation; data are for de Bilt in the period

1970-1990.

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temper-16 3 SENSITIVITYOFTHE PENMAN EQUATION

ature equals the slopeof the regression line. For the months May, June,and July, e.g., this implies a change of 9.7, 13.0,and 10.4 mm per

oe,

respec-tively. Examination of the results in figure 4 of the foregoingsection shows that changes as indicated in that figure are much smaller than the changes as indicated by the regression equations. For instance,it appears for the months May, June, and July that a temperature change ofT

=

+3

oe

in figure 4 has about the same effect as a temperature change ofT

=

+

1

oe

using the regression lines.

The large discrepancy between the two methods originates from the as -sumptions made in section 2. The two most important as-sumptions in this respect are: 1) relative sunshine duration remains the same when elimate changes;and 2)relativehumidity remains the same when elimate changes. In the present climate, in the summer months, sunshine duration is posi -tively correlated with temperature. This means,that an increase or decrease in the Penman open water evaporation due to an increase or decreasein tem-perature is enlarged by the change in relative sunshine duration. This effect is absent in section 2.

About the same is true for relative humidity. For the summermonths relative humidity is negatively correlated with temperature (thesmaller the relative humidity the larger the Penman open water evaporation). Thus again,an increase or decrease in the Penman open water evaporationdue to an increase or decrease in temperature is enlarged by the changein relative humidity. Also this effect is absent in section 2.

At present there are no reasons to question the assumptionsof section 2, therefore,itmust be concluded that the key for future changes in open water evaporation values is not in the present relationship between temperature and evaporation. Itis expected that this conclusion is not restricted to De Bilt but is valid for other regions aswell,

3.3 Variation of some variables

As mentioned before the input variables for the Penman equationare tem -perature,humidity,relative sunshine duration (cloudiness),and windspeed. In this part of the section the sensitivity of

Eo

to changes in these variables is examined.

An important decision that must be made concerns the boundarieswithin which to vary the variables. It is decided to compute the standard deviation for the monthly values of all variables and relate the imposedchange in the variables to their standard deviation. The standard deviation is computed

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3.3 Variation of some variables 17 15 10 5 ... ~ "..J ₀ U Q. -5 -10 -15 • Temp.ratur. V Wlndsp •• d .. Relatl .... humldlty D SUft.hl". duraflon -0.6 -0.4 -0.2 0.4 0.6

Figure 6: Percentage changes in themean annual evaporation (averaged for the period 1970-1990) as a function of relative changes in the input variables for the Penman-method.

from 252 values for each variabIe (21 years and 12 months in a year). Itis decided to vary each variabIe between the fol1owing boundaries

.ó.x·

- 0.6

< -

'

<

0.6 (10)

- Sj

-where .ó.Xjis the change in variabIe i, for instanee windspeed,and s, is the sample standard deviation of the monthly values of variabIe i.

Fol1owing this procedure a variabIe is now varied between, more or less, realistic boundaries while other values are kept constant.

Points of departure are again the meteorological time series data for De Bilt (1970-1990). The change in a variable, .ó.Xj, is uniformly added to all monthly values for this specific variabie in the series for De Bilt, and the corresponding mean annual evaporation is calculated. The percentage change of the evaporation values is again calculated according to equation 9. The results are given in figure 6 and apply to the percentage changes in mean annual evaporation values. From this figure it can be noted that the Penman open water evaporationis most sensitive to changes in temperature fol1owed by changes in relative humidity and sunshine duration, and least sensitive to changes in windspeed.

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18 4 EVAPORATlON SCENARlOS

3.4 Discussion

Itthis section it appeared that the present relationship between open water evaporation and temperature suggests a much larger increase or decrease in evaporation values than computed with the models in section 2. As the assumptions made in that section were considered reliable, it must be con-cluded that the present relationship between evaporation and temperature values cannot be used for climate change studies.

From the results in figure 6 it appeared that temperature is by far the most important variabIe in the Penman equation. Thus for climate change studies it is most important to obtain reliable information on temperature changes. Information on relative humidity and relative sunshine duration is also important, espeeially because it is known that in the present cli-mate these variables are mutually negatively correlated, thus enhaneing any increase or decrease in evaporation.

lt seems that the role of windspeed is of minor importance. However, considering the spatial variability of windspeed in the Netherlands, it might be of interest to know how windspeed will be affected by the greenhouse effect and natural climate variations.

4 Evaporation

scenarios

For studies involving the impact of elimate change on water resources and hydrology evaporation scenarios are needed. In this section two types of evaporation scenarios are constructed. The first type is named analog cli-malescenarios. These scenarios are based on climate data from stations in otber countries in Western Europe. The second type is narned artificial scenarios. These are scenarios based on the method proposed in section 2.

4.1 Analog c1imate scenarios

The climate analog method involves the use of temperature and precipita-tion series of existing climates, different from the climate in the Netherlands. The assumptionis that in a changed climate, due to the greenhouse effect and natural elimate variations, elimate in the Netherlands may be repre-sented by the analog climates. For this study this is further restricted to the elimate of De Bilt, which is considered to be representative for the average conditiorisin the Netherlands. The location of the eities for which climate data are available are given in figure 7. The data have been obtained from

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4.1 Analogdimatescenarios 19

Figure 7: Cities in Europe for which daily precipitation depth data have been obtained for the period 1970-1990.

De Bilt Bordeaux Cdarisk Göteborg Lisboa Nantes Plymouth Porto Southampton Stockholm Temp.(OC) 9.6 0.7 12.9 0.7 7.4 1.1 7.3 1.0 16.9 0.6 12.1 0.7 10.8 0.5 14.5 0.5 10.9 0.6 6.4 1.0 Pree. (mm) 792 141 918 138 553 102 788 123 708 168 783 123 967 129 1233 233 734 107 525 96

Tab1e 2: Mean and standard deviation of the average annual temperature and annuaJ precipitation depth for the stations in figure 7.

the meteorologicaJ services in the relevant countries and concern the period 1970-1990. Some of the c1imate characteristics for the stations in figure 7 are given in table 2. In this table the mean (x) and the standard

devia-tion (S,,)of the annual temperature and the annuaJ precipitation depth are

given, respectively.

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20 4 EVAPORATION SCENARIOS

1970-1990 using the available temperature and precipitation readings. Of course it would be possible to use the Thornthwaite method, which uses only temperature readings. However, this method is considered to coarse for reasons mentioned above. Therefore it is decided to use the Penman

-method with some modifications.

It is assumed that the input data,relative humidity, relative sunshine duration and windspeed may be derived making use of the data for De Bilt.

Starting with windspeed it is assumed that windspeed data of De Bilt can be used. For daily evaporation values this may not be realistic. However,

here monthly averages of windspeed are used producing monthly totals of evaporation thus canceling day to day differences.

For re1ative humidity and re1ative sunshine duration another approach is used. To obtain more or less realistie values for those two variables both analog c1imate data and data from De Bilt are used. For De Bilt there ap-pears to be a good relationship between the two variables relative humidity and relative sunshine duration on the one hand, and the number of wet days on the other hand. A wet dayis defined as a day with precipitation depth

>

0.3 mmo The number of wet days in a month is further denoted as wet-days. The relationship between relative humidity and wetdays is illustrated in figure 8, and the re1at ionship between reÎativesunshine duration and wet-days is illustrated in figure 9. For each month the linear regression line is drawn and the correlation coefficient is given. In figure 8 only the corre1ation coefficients for the months January,February, November,and December are not significant at the 0.05 level. In figure 9 only the correlation eoefficients

for January and December are not significant at the 0.05 level.

It is now assumed that the above-mentioned relationships will remain approximately the same in case of elimate change. Using the number of wet days (wetdays) computed for the analog climates, the relative humidity and relative sunshine duration can be approximated using the above-mentioned relationships. For those months where the correlation coefficient is not sig

-nificant at the 0.05 level the 21 year mean monthly value is used for each month. Fortunately, the re1ationships are strongest in the months with largest evaporation.

The monthly Penman open water evaporation for De Bilt is compared with the Penman open water evaporation eomputed using the regression equations,denoted

Eo'

The results are given in figure 10.Itappears that the results for both methods are about the same, strengthening our confidenee in the method.

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4.1 Analog climate scenarios 21 100 r--'---r-~--r----' 1 00 ,---,-...,.--,--..,

E

%

'"

90 JAN (r.-O.,,>

..

.

. .

.

-.

90 80 fEB (r.O

.

.U)

.

..

.

~

_.

· . .

80 MAR • (~,

...

.

· .

)

.

• Ia. •

·.

· .

80 70 ' - - - - ' ' - - - ' - - - ' - - - ' 70 '---'---'----'--...--' 5 10 15 20 25 30 0 10 15 20 5 10 15 20 25 30 90 r--r--,---,,---r--,----, 90 r--r--,----,--r-,--. 90 r--,---r---.--r----, 5 la 15 20 25 JUN (':.'71).~

Á

-.

_·

70 80 60 '---'---'----'--...--' o MAY (rao.70) •

-.

..

...

_...

70 80 5 1 0 15 20 25 30 APR (r.0.75)

/

· _·

...

.

.-

..

80

E

% '" 90 r--r--,----,,---r--,----, 90 r--,.--,---r----, 100 r--,---,--,---,---, AUG (r.O.II)

E

% '" 80 70 JUL (....: ..l~

~.

_.

_..

.

80

..

· ..

..

.

·.

90 80 SEP (raO.II) 10 15 20 25 60 70 •• 7 0 '-_-'-_...L_-'-_-' o 5 la 1 5 20 25 30 5 10 15 20 25 5 100 ,---,---,,---,----, 100,--,--,.--,--r--, 10 0r--,---,--,---,---,

· ..

.

E

%

'"

90 aCT (,..0... "

.

_...

.

....

~

~;-• ~;-•

90 NOV C,·0.21)

..

.

~

. .

.

90 DEC ('...·0.15)

•

• _••

•

10 15 20 25 80 I. 80 80 ' - - ' - - - ' - - - ' - - - ' 5 10 15 20 25 5 10 15 20 25 30 5 W.tdays

Figure 8: Present relationship between relative humidity and wetdays for each

month for De Bilt (1970--1990).

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-22 4 EVAPORATION SCENARlOS

0.4 0.6 0.6

JAN ₀_.5

FEB

0.5 MAR

0.3 ('--0.01)

•

(

..

-

....

) ('.-0.7')

• .

0.4 0.4

.'.

"

z ... 0.2

.

_{• '-J•.} e ₀_.3 _0.3

..

'

0.1

.

0.2

..

0.2

.

0.0 0.\ 0.1 5 10 15 20 25 30 0 5 10 15 20 5 10 15 20 25 30 0.6 o.a 0.7

..

APR 0.7 _0.6

.

_JUN 0.5

~"

0.6

..

(, __ 0.11) 0.5

~

z 0.5 ... 0 .• 0 .• c 0 ••

.:

.

. '

_0.3 0.3 0.3

.

.'.

· .

0.2 0.2

.

0.2 0.1 0.1 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 0.6 0.7 0.5

• _•

JUL 0.6 AUG

•

SEP

0.5

.

,

.

(r.-O.74 (r--O.70) 0.4

• .

.

(r.-O.7D)

0.5 z ₀_.4

..

₀_.3 ... e

..

.

_•

₀_.4

.

_'

.

0.3

.

..

0.2

•

0.3

..

0.2 0.1 0 5 10 15 20 25 30 10 15 20 25 5 10 15 20 25 0.5 0.5 0.4

•

OCT ₀_._• NOV DEC

0.3 ,J,"-O..,)-(,..-0.57) (r--O.I2) 0.4

~

..

.

·

0.3 • • t t Z •••• 0.2 ...

~

e

..

·

₀_.2 0.3

..

. .

0.1

.

'

..

0.1 0.2 0.0 0.0 5 10 15 20 25 5 10 15 20 25 30 5 10 15 20 25

Welday. Welday. Wolday.

Figure 9: Present relationship between relative sunshine duration and wetdays for each month for De Bilt (1970-1990).

(25)

4.1 Analog c1imatescenarios

23

\

~

\ ,

Á

A

~~

ft

A

\

J

~

_1/

_I

_J

~

;

\

l!

~

_U

Eo (Pen man)

E; (Penman with regression)

o 19701971 1972 19731974197519761977 197819791980 150 120 ,... s: c 0 90 E <, E 60 E w 30

I

1\

.ft.

)

fI

}

~

I

)

l

j

_IJ

)

_I

₁

_/

_IJ

/

IJ o 1980 1981 n82 1983 1984 1985 1986 1987 1988 1981! 1990 lUl 150 120 ,...

::

c: 0 90 E <, E 60 E w ₃₀ Time (years)

Figure 10: Comparison of the monthly Penman open water evaporation(Eo)for De Bilt with the monthly Penman open water evaporation computed using the regression equations(E

_ó)

.

for De Bilt. Together with the monthly temperature series for the analog c1imate data, and the monthly windspeed data for De Bilt,the open water evaporation for the analog climates can now be computed. The difference between mean monthly evaporation for the analog climates and for De Bilt is given in figure 11 (denoted as E( city )-E(De Bilt),

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24 50 40 ... E E ₃₀ ...

-äi <D 20 c

...

_....

I

~

10 u

...

w 0 -10

•

Stockholm v Goteborg ", Gdansk [J Plymouth

•

Southamton A Nantes .... Bordeaux

o

Porto

•

Lisboa 4 EVAPORATION SCENARlOS J F A J J A S

o

N

o

t.lonth

Figure 11: Difference between the mean monthly evaporation computed for the

analog climates and for De Bilt.

4.2 Artificial c1imate scenarios

As said before, artificial evaporation scenarios are scenarios based on the method proposed in section 2. For the purpose of this study the Penman-method is used and only changes in temperature and net radiation are

im-posed on the existing series for De Bilt. It is assumed that for 2XCO2

conditions greenhouse gases may imposean extra change in net radiation of

about +5 Wm-2_• _{This is of the same order of magnitude as the predictions}

given the IPCC-report (lP CC, 1990).

Five scenarios are distinguished characterized by their changes in

tem-perature and net radiation. A change in net radiation,Q",of +5 Wm-2 _is

combined with changes in temperature of +2,0, and -2 °C giving 3

scenar-ios. Further, two scenarios with only temperature change are considered,

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4.2 ArtificiaJc1imatescenarios

25

... E E ' - ' CD o ' - ' w I ... c CD o

..

' - ' w 15 10 5

o

-5 -10 I I I • ET+ 2,Qo+5 o ET+ 2,Q'+o V ET+ O,Q'+5 - - - . ... ET_ 2,Qo+5 / " " • ET-2.Qo+O~ • J F A J J A

s

o

N D Month

Figure 12: Difference between the mean monthlyevaporation computed for the artificial scenarios and for De Bilt.

a temperature change of -2 °C. The scenarios are denoted by E with a subscript giving the change in temperature and the change in net radiation.

For example, Er+2,Q+5 means an evaporation scenario based on the mete-orological data of De Bilt with a change in temperature of +2 °C and a change in net radiation of +5 Wm-2•

The difference between mean monthly evaporation for the artificial cli-mate scenarios and for De Bilt is given in figure 12. Comparison of this figure with figure 11 shows that the scenario with the largest evaporation values still has smaller evaporation values than the evaporation values for Porto, Lisboa, and Bordeaux. On the other hand, the scenario with the smallest evaporation has smaller evaporation values than all eities.

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26 5 THE CROP FACTOR METHaD

5 The

erop

factor method

5.1 Theory

Evaporation as calculated with the methods of Makkink and Penman,or evaporation measured with an evaporation pan, is frequently used in com-bination with erop factors to obtain potential evaporation. For practical computations the erop factor method is often preferred above more compli-cated methods, like the Penman-Montheith-method.

For certain purposes (e.g.irrigation) one wants to know what the evap

-oration would be if there is no moisture shortage, Therefore the potential evaporation is calculated, As stated before, the potential evaporation is the theoretical evaporation occurring when there are no limitations in water supply, i.e.,the amount of soil moisture does not restriet erop growth.

Using the potential evaporation refers to a hypothetical situation with sufficient moisture in the root zone and weather conditions unchanged by evaporation.

The erop factor method combined with Penman's method gives the fol-lowing equation for potential evaporation

(11) whereEpis the potential evaporation,f isthe erop factor,and Eo is the open water evaporation according to equation 5. The erop factors are dependent on erop type and time of the year. Crop factors for the Netherlands can be found in, e.g., Cultuurtechnische vereniging (1988).

5.2 Climate change

With respect to elimate change, the use of the concept potential evaporation and the erop factor method may be questioned for two reasons. First, the as-sumption that weather conditions are unchanged by the evaporation process may be questioned,in partienlar under dry conditions. The method refers to a hypothetical situation with sufficient water available in the root zone. However,in reality,if sufficient water is supplied e.g. by means of irrigation, weather conditions will change. Surface and air temperature will decrease and humidity will increase.Thus influencing the net radiation(Q*)and the drying power of the air (Lle),and, consequently,the potential evaporation.

Second, the increase in atmospheric carbon dioxide may alter the be-havior of plant species, like plant growth and stomatal resistance,and thus

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27

influence the erop factor. However, the net result of increased carbon diox-ide levels on plant behavior is very uncertain at present. Itis not yet clear which plants will benefit from increased carbon dioxide levels and to what extend (Goudriaan et al., 1990; Scurlock and Hall, 1991; Bazzaz and Fajer, 1992).

According to some authors the effects on plant growth and stomatal resis-tance might possibly counterbalanee (e.g. Aston, 1984). As a result,in most studies dealing with the impact of elimate change on hydrology and water resources,itis (tacitly) assumed that plant transpiration is not directly af-fected by increased carbon dioxide levels. Moreover, plants and agricultural production seem to be more sensitive to temperature and rainfall perturba-tions than to a carbon dioxide increase (Montheith, 1981; Unsworth, 1990). A longer growing season, in case of a warming, may be particularly favorable for species with a short life cycle, which produce already several cycles per year.

It is not yet clear how erop factors may change as a result of elimate change due to increased carbon dioxide levels. Considering the discussion above it seems reasonable to assume, as a as a first order approximation, that the erop factor remains the same.

6 Summary and Conclusions

From the study in this artiele it appeared that the calculation of evaporation for changed elimate conditions is still a complicated task. Information about several factors influencing evaporation is still not available. Scenarios for evaporation are obtained using elimate analog data and artificial changes in the data for De Bilt. It is argued that the changes in erop factors, due to the greenhouse effect, are rather uncertain. As a first order approximation it seems reasonable to assume that erop factors remain equal.

The fol1owing general conclusions can he drawn:

• Of the three methods studied in this artiele the Penman-method is considered to be the best method to simulate the impact of elimate change on evaporation values because the Penman-method is the most physically-based method; knowledge of changes in variables affecting evaporation can explicitly be taken into account;

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28

6 SUMMARY AND CONCLUSIONS • The relationship between temperature and evaporation for the present

elimate cannot be used as a key for future elimate conditions: • For the Penman-method it is most important to know the changes in

temperatures; also changes in relative humidity and sunshine duration may be important because for the present elimate these last two vari-ables are mutual1y negatively correlated, thus enhancing any increase or decrease in evaporation;

• The infl.uence on evaporation values of an increase of +5 Wm-2in net radiation due to doubling of carbon dioxide is smal1 compared to the infl.uence of a change in temperature;

• At present it is not clear what the net response of plants will be as a result of increased carbon dioxide levels.

References

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Journalof Hydrology, 67, 273-280,1984.

Bazzaz,F.A.,and E.O. Fajer, Plant Life in a C02-llich Worid,Scientific Ameri-can,39-42,January 1992.

Bruin, H.A.R.de, The determination of (reference erop) Evapotranspiration from routine weather data, Evaporation in relation to hydrology, 25-37,Com. Hy-dro!. Research TNO,The Hague,Proceedings and informations 28,1981a.

Bruin, H.A.R. de,Neerslag, openwaterverdampingenpotentieel neerslagoverschot

in Nederland; Frequentieverdelingen in het groeiseizoen,Wetenschappelijk rapport (W.R. 79-4),Royal Netherlands Meteorological Institute, Oe Bilt, 90 pp., 1981b (in Outch).

Bruin, H.A.R. de, From Penman to Makkink,Evaporation and Weather,5-31,

Proceedings and Information TNO Committee on Hydrology,no.39, 1987.

Bultot,F., A. Coppens,G.L.Oupriez,O.Gellens,and F.Meulenberghs, Reper-cussions of a C02 doubling on the water cycle and on the water balance: a case study for Belgium,Journalof Hydrology, 99,319-347,1988.

CHO-TNO, Van Penman naar Makkink, een Nieuwe berekeningswijze voor de Klimatologische Verdampingsgetallen,Com.Hydro!. Research TNO, Reports and Notas No.ï9, The Hague, 1988 (in Outch).

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29

Cultuurtechnische Vereniging, Cultuurtechnisch Vademecum, 1085pp., 1988(in Dutch).

Goudriaan, J.,H. van Keulen,and H.H. van Laar (editors), The Greenhouse

Ef-fect and Primary ProduetivityinEuropean Agro-Systems,Proceedings of the

international workshop on primary productivity of European agriculture and the greenhouse effect, Wageningen, the Netherlands, 5-10 April,90pp.,1990.

Gutowski,W.J.Jr.,D.S.Gutzier,and W.Wang, Surface Energy Balances of Three General Circulation Modeis: Implications for Simulating Regional Climate Change,Journalof Climate,4, 121-134, 1991.

Intergovernmental Panel on Climate Change (IPCC), Climate Change: ihe [PCC

Scientifie Assessment,WMO UNEP,Cambridge University Press,364 pp.,

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Makkink,G.F.,Testing the Penman formula by means of Lysimeters,Journ. Int.

of Water Eng. 11,277-288,1957 .

Manabe, S., and R.T. Wetherhald, The Effects of Doubling the CO2

Concentra-tion on the Climate of a General CirculaConcentra-tion Model,Journalof Atmospherie Sciences, 92,3-15,1975.

Manabe,S., and R.T.Wetherhald,Large-Scale Changes of Soil Wetness Induced by an Increase in Atmospheric Carbon Dioxide,Journalof the Atmospherie

Seiences,44(8),1211-1235, 1987.

Montheith,J.L.,Climate Variation and the Growth of Crops, Q.J. R. Meteorol.

Soc.,107,749-774,1981.

Penman,H.L.,Natural Evaporation from Open Water Bare Soi! and Grass,Proc.

Roy. Soc.London, A199,120-145, 1948.

Scurlock, J.,and D. Hall, The Carbon Cycle,New Seientist, 51, 20-23,1991. Thornthwaite, C.W.,An Approach Toward a Rational Classification,Am. Geogr.

Rec.,38, 55-94,1948.

Lnsworth,M.H.,Hazards to Productivity- the Changing Risksof Crop Losses,

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Eu-ropean agriculture and the greenhouse effect,Wageningen,the Netherlands,

(32)

COMMUNICATION OF THE DEPARTMENT OF SANITARY ENGINEERING AND WATER MANAGEMENT

Inthe series "Communication oCthe Department oCSanitary Engineering and Water Management" are edited:

1. Siebers, H.H.: Pattems and variability of phosphate and heavy metals in sediments of two shallow lakes. 2. Flipse, M..J. en Heide, J. van der:Ontwikkelingen met betrekking tot vaste afvalstoffen exart.4, 17, 25,26

van de Afvalstoffenwet in periode van ca.1980 tot 1985.

3. Kop, J.H.:Planvorming voor de drinkwatervoorziening.(februari 1986)

4. Blanken, J.G.den en Hoogh, M.P.A..J. de: Modellen voor desinfectie van gezuiverd afvalwater met chloor en ozon.

5. Kop, J.H.:Het probleem van de wederzijdse afstemming van de belangen van drinkwatervoorziening en milieubeschenning bij de planning voor de winning vanzoetgrondwater.(augustus 1986)

6. Boekelman, R.H. en Niet, H. de:Het berekenen van modelkrommen voor Geo-elektrische metingen.

7. Vos, W.L ., Donze, M. and Buiteveld, H.:On the reflectanee spectrum of algae in water:the nature of the

peakat 700 nm and its shift with varying aIgal concentration.

8. Smît, D., Mameren, H..J. van en Veldkamp, R.G.:De zuurstolhuishouding van de Utrechtse Vecht. 9. Heide, J. van der: Kinetische modellen voor ontwerp en beheer van actief-slib-installaties deel 1 en 2.

(februari 1987)

10. Boulan, R.P., Donze, M. en Klapwijk Sj.P.: Fosfaatbalans van de polder Reeuwijk en een aantal deelgebieden.

11. Groot, C.P.M. de en Breemen, A.N. van:Ontspanningsûctatie en de bereiding van drinkwater.

12. Blanken, J.G. den en Hoogh, M.P.A..J. de: Modelvorming voor verwijdering van indicatororganismen in het actief-slibproces.

13. Mishra, K.K. and Breemen, A.N. van:Gravel-bed flocculation.

14. Vlis, E. van der: De filtratietheorie. (maart 1988)

15. Koreman, E.A. en Breemen, A.N. van: Toepassing van het vriesdooiproces bij de ontwatering van coagulatieslib.

16. Ganzev1es, P.P.G., Kop, J.H. en Ywema, R.: Materiaalkeuze afvalwaterleidingen.(juni 1988)

17. Nieuwenhuyze, R.F. van, Stokman, G.N.M., Kuijper, R., Gerritsen, J..J. en Donze, M.: Detectie van proceswater met behulp van thermische remote-sensing.

18. Blanken, J.G. den en Hoogh, M.P.A..J. de:Modelvorming voor een goede procesregeling van de desinfectie met chloor c.q,ozon aan de hand van instelbare enlof direct meetbare variabelen.(augustus 1988)

19. Noppeney, R.M.:De invloed van stagnante zones op dispersie.

20. Noppeney, R.M.: Gevoeligheidsonderzoek Alarmmodel Rijn; De invloedslengte van samenvloeiingen bij dispersie.(november 1988)

21. Noppeney, R.M.:Deverspreiding van olie op rivieren benaderd met het Taylor-model. 22. Noppeney, R.M.:De invloed van near-field processen op een far-'fielddispersiebeschrijving.

(33)

24. Blanken, J.G. den: Afscheidssymposium prof.ir. A.C.I.Koot.

25. Hooykaas, Lol., Donze,M. en Klapwijk, Sj.P. : Fosfaathalans van de polder Reeuwijk en de Reeuwijkse

plassen.(januari1989)

26. Verwoerdt, P.enMazijk, A. van: De één-dimensionale dispersievergelijking van Taylor bij een opdeling van

de rivier in vakken.(maart 1989)

27. Mazijk, A. van: GevoeligheidsonderzoekAlarmmodel Rijn;eindrapportage.(mei1989)

28. Blanken, J.G. den en Hoogb, M.P.A.J. de:Desinfectie van behandeld afvalwater met chloor: vergelijking van

eenpunts-entweepuntsdosering;

deel 1: Tekst,bijlage A,Ben C.

deel 2:Bijlage D,E,Fen G.

(mei1989)

29A. Verstappen, G.G.C.: Gedrag van organische micro-verontreinigingen in rivieren.(juli1989)

29B. Mooren, J.J.M. en Heide, J. van der: Leaching of heavy metals from thermally decontaminated soils.

(maart 1989)

30. Nleuwstad, Tb.J., Wortel, N.C., Bout, F.N.van den enAJting, D.J.: Een vergelijking tussen ladingsgewijze

en continue zuivering van afvalwater.(juni1989)

31. Kramer, J.P., Wouters, J.W. en Kop, J.H.: Dynasand Filtratie.(juli1989)

32. NIeuwstad, Tb.J.: Treatment of municipal wastewater in a pilot-scale airlift-loop reactor.(december1989)

33. Ankum, P.: Polders;achtergronden, ontwerp en toekomstige ontwikkelingen.

34. Brandsma, T.: Evaporation in Hydrology and Meteorology.(juli1990)

35. Mooren, J.J.M.: Het uitlooggedrag van kunstmatig samengestelde en verontreinigde grond.(2 delen)

36. SIngb, S.N., Boekelman, R.H., Rienljes, T.H.M. en Dam, J.C. van: Behaviour of groundwater of the polder

Groot-Mijdrecht.

37. Boekelman, R.H. en Rientjes, T.H.M.: Workshop bydrological models.

38. Stamdes, N., Rienljes, T.H.M. en Dam, J.C. van: Network optimization, a simple approach applying GIS

andMLR.

39. Duindam, P., Morales, C. and Heide, J. van der: lnvestigacion sobre los desechos solidos de la ciudad de

Masaya, Nicaragua.

40. Heide, J.van der: Evaluacion hidraulica de plantas potabilizadoras de filtracion rapida en Nicaragua.

41. Heide, J. van'der: Metodologia de potabilizacionde agua superficialenNicaragua.

42. Veldkamp, R.G.: Randvoorzieningen van rioolstelsels kritisch beschouwd.

43. KrWthof, J.C., Schippers, J.C. and Dijk, J.C. van: Abastecimiento de Agua Potable de Agua Superficial en

los aiios Noventa.

(34)

Evaporation and Climate Change