沙漠研究 23-4, 173 -177 (2014 )－Special Issue on Sustainable Ecological Technologies－

Journal of Arid Land Studies

Estimating Pan Evaporation in Kabul, Afghanistan
Hayat Khan SHAMS1), Fumio WATANABE*2), Shinji SUZUKI2),
Satoru TAKAHASHI2) and Mitsuru KASHINO2)
Abstract: Pan evaporation has been widely used as an estimate of potential or reference evapotranspiration. It is also an importantvariable in making crop management decisions such as irrigation scheduling for crops. However, Afghanistan has many issues inagricultural development due to two decades of conflict and a prolonged drought, poor irrigation facilities, etc. In particular, the basic
data for irrigation scheduling, such as pan evaporation and meteorological data, are still poor. The objective of this study is to clarify
meteorological properties and to develop an applicable method for estimating pan evaporation in Afghanistan. Finally, we developed
a method for estimating pan evaporation for locations where it is not usually being measured. It is clear that this method is slightly
more accurate than the Penman model. Therefore, the use of this method is recommended for irrigation scheduling in Afghanistan.
Key Words: Conflict, Crop production, Effective water use, Irrigation scheduling, Penman model.

1. Introduction
Afghanistan is a landlocked country that is locatedapproximately in the center of Asia. It is bordered by
Pakistan on the south and east; Iran on the west; Turkmenistan,
Uzbekistan, and Tajikistan on the north; and China on the far
northeast (Fig. 1).
Agriculture employs 80% of the Afghan population andsustains more than half its gross domestic product (Gregory etal., 2010). Afghanistan, with an area of 652,000 km2, is alandlocked mountainous country located between Central andSouth Asia. Afghanistan is divided into 34 administrative
divisions, 40 watersheds, and 5 main river basins (Shobair and
Alim, 2004).
Winter precipitation occurs in the form of snow.
Agricultural production depends on the availability of water,
either as direct rainfall or in the form of snow. However, two
decades of conflict and prolonged drought have destroyed
irrigation systems and vineyards, and livestock numbers havebeen greatly diminished. Afghanistan faced a lack oftechnical guidelines for irrigation planning and a shortage of
irrigation water during the cultivation and growing season,
resulting in low agricultural productivity.
Moreover, demands on the resources have grown, andQureshi (2002) has estimated that long-term water availability
is about 2,500 m3 head per year, enough to irrigate 4 million
hectares, which is significantly higher than the current 2.6
million hectares in the command area.
Otherwise, Afghanistan is an arid to semi-arid country* Corresponding Author: f-nabe@nodai.ac.jp

whose agricultural production depends on the availability ofwater, either as direct rainfall or in the form of irrigation. In
Afghanistan, rainfall data is difficult to access due to the factthat most of the old time-series was stopped in 1977 or, insome cases, in 1992.
Meteorological stations have been damaged and rainfall
data were not collected (except at four agro-meteorologicalstations -Kabul, Jalalabad, Mazare Sharif and Herat- installed
in 1999 under the FAO project).
The Afghan Meteorological Department and Institute ofMeteorology are not functioning. Due to this particularsituation, agro-meteorological observations have become avery important task for the country. Because of the very

Fig.1. Location map of Afghanistan.
（Received, October 1st, 2013; Accepted, January 17th, 2014）

1-1-1 Sakuragaoka, Setagaya, Tokyo 156-8502, JAPAN
1) The Ministry of Agriculture, Irrigation and Livestock, Afghanistan (Graduate student of Agricultural Engineering, Tokyo University of Agriculture)2) Faculty of Regional Environment Science, Tokyo University of Agricultureerratic spatial distribution of rainfall in the mountainous
regions, data from a large network of rain gauges are required.
In addition to rainfall, other parameters are highly importantand needed in Afghanistan. They are snowfall and snow
cover, upon which most of the country’s irrigated sector
depends, frost, and low temperature. Accurate and timely
information on agro-meteorological observations, including all
weather parameters, actual planting times, areas planted,
harvested crops, and crop conditions and pasture, are highly
needed for each agro-ecological zone and each district in
Afghanistan.
In other words, the agro-meteorological approach tohelping agriculture can only be effective if reliable, real-time,
and timely data are available. Rabah et al. (2004) suggested
that the timely collection and proper utilization ofagro-meteorological information could help promote increased
farm profits under favorable weather conditions or decreased
farm losses under unfavorable conditions. It is necessary to
get it on the orbit of sustainable agricultural development forthe stability and the property of this country.

2. Previous Studies
Pan evaporation is an important weather variable that canbe applied to decision making in agriculture, forestry ecology,hydrology, and other fields. Many studies on estimating
evapotranspiration and evaporation in various countries havebeen conducted (Sheffield et al., 2009; Coulomb et al., 2001;
Hedayat et al., 2012; Kisi, 2010). Abdollahzadeh et al.
(2011) studied soil erosion in Tanakami, Japan, using an
artificial neural network. It has also been used for agriculture
and for estimating evaporation and transpiration. Hedayat etal. (2012) examined evaluating the artificial neural network for
estimating the reference evapotranspiration with the least
meteorological data. Kisi (2010) developed generalized
regression neural networks (GRNN) based on evapotranspiration (ET) estimation. The potential of GRNN
models for estimating ET using climatic variables has been
illustrated. Kisi’s study demonstrated that the modelling ofdaily reference evapotranspiration is possible by using the
GRNN technique. The GRNN model, whose inputs are windspeed, solar radiation, relative humidity, and air temperature,
performs the best of the input combinations tried in the study.
This indicates that all of these variables are needed for better
evapotranspiration modelling. For the correct estimation ofET, many studies have been conducted on different underlying
conditions to promote the effective use of water resources andto introduce this management into long-term rainfall runoff
models. Many approaches regarding different climatic or
underlying conditions for estimating actual ET have been

A

B

C

D

Fig. 2. (A) Sunshine hours, (B) Air temperature and relative
humidity, (C) Rain gauge and (D) Wind speed.

proposed (Wanchang et al., 1999). A comparison of 20
different methods for estimating ET has shown that Morton'scomplementary equation provides the most accurate estimateof monthly ET from well-watered grassland under varied
climatic conditions.
However, the applicability of the equations on different
time and space scales has not yet been clearly understood.
Only a few studies of estimating evaporation have been
conducted in cold alpine regions, owing to the difficulties inmeasuring the necessary meteorological parameters, especially
evaporation observation, in such regions. Three decades ofconflict in Afghanistan have brought destruction, and weather
stations and weather data are not registered. Thus, morestudies are needed. It is very important for the efficient use ofwater and the development of agriculture in Afghanistan.
The purposes of this study are to clarify meteorologicalproperties in Kabul and to introduce a method for estimating
pan evaporation.

3. Materials and Methods
Meteorological data were collected in the Qargha
experimental research center in Kabul Afghanistan, which ismanaged by the Research Institute, the Ministry of Agriculture,
Irrigation and Livestock. The station is located 10 km west of
the city center of Kabul, latitude: 34º53’N, longitude: 69º8’E
and altitude: 1,834 m. The data were collected during athree-year period from January, 2010, through December, 2012.
These data consist of the air temperature, relative humidity,
wind speed, sunshine hours and rainfall (Fig. 2).
Daily pan evaporation data were also observed at thisresearch station. Pan evaporation data have been measured

60

21.8

51.9

50

15

40

Temperature (℃)

20

10

30

31.5

5

20
Temp(℃
)

0

-5

-2.0

R.H (%)

25

10
0Fig. 3. Changes of monthly air temperature and relative humidity in
Kabul.

15
13
11
9
7
5
3
1
-1

0
7.0

20
40

10.4

60

65.5
4.5

80
Monthly
Rainfall(mm)Sun Shine(h)

100
120

Precipitation (mm)Sunshine duration (h)using a “Class A” evaporation pan, which is a cylinder with adiameter of 47.5 inch (120.7 cm) and a depth of 10 inch (25 cm).
However, evaporation is difficult to measure directly, and,
therefore, many theoretical and empirical approaches havebeen developed. Some of the commonly used techniques
include the Penman model (Penman, 1948), the Priestly-Taylor
model (Priestley and Taylor, 1972) and the energy balancemethod. For open water bodies, the Penman combination
approach is often used, and it is recommended as the preferred
method for estimating the rate of evaporation from open water.
Evaporation pans are another common method of
estimating evaporation, although the problems introduced byadopting a suitable pan coefficient lead to doubts about thereliability of the open water body evaporation estimates.
Johnson et al. (2007) suggested that use of evaporation panswith a pan coefficient can give only a “rough estimate of lake
evaporation, mostly on an annual basis”. Despite theinaccuracies of the indirect evaporation estimates, the Penman
model and evaporation pans are commonly used in researchand in practice to predict evaporative losses.
In this study, the Penman model (Penman, 1948) was used
for estimating pan evaporation. The following equation was
used:
Δ
𝚂
𝛾
∙ +
𝑓(𝚞𝟸 ) ∙ (𝑒𝑠𝑠 − 𝑒𝑎 )𝐸𝐸𝑝 =Δ+𝛾 𝛪 Δ+γ
where ∆ is the saturation vapor pressure at air temperature(hPa/ºC), S is the net radiation (MJ/m2day), γ is thepsychometric constant (hPa/ºC), f (u2) is the wind speed at 2
m height (m/s), esa is the saturation vapor pressure at air
temperature (hPa), and ea is the vapor pressure (hPa).
This equation demonstrates that the mass-transfer andenergy-balance approaches could be combined to arrive at anevaporation equation that does not require surface temperaturedata. The first term shows net radiation, and the second termshows mass transfer.

140

Fig. 4. Changes of monthly precipitation and sunshine duration in
Kabul.

elevation. The coolest temperatures usually occur on theheights of the mountains. Temperatures often range greatly
within single day. Temperature variations in a single day may
range from freezing conditions at dawn to the upper 30s°C at
noon. Most of the precipitation falls between October andApril. The deserts receive less than 100 mm of annual rain,
whereas the mountains receive more than 1,000 mm ofprecipitation, mostly as snow.

4. Results and Discussion
4.1. Overview of the climate in Afghanistan
Most of Afghanistan has a subarctic mountain climate withdry and cold winters, except for the lowlands, which have arid
and semi-arid climates. In the mountains and a few of thevalleys bordering Pakistan, a fringe effect of the Indian
monsoon, coming usually from the southeast, brings moist
maritime tropical air in the summer. Afghanistan has clearly
defined seasons; summers are hot and winters can be bitterly
cold. Summer temperatures as high as 49°C have beenrecorded in the northern valleys. Midwinter temperatures as
low as -9°C are common around 2,000 m above sea level inthe Hindu Kush. The climate in the highlands varies with the

4.2. Meteorological properties of Kabul
Kabul is also classified as a semi-arid region. Air
temperatures in the summer are high and hot, but winter is cold.
The maximum average summer temperature is 21.8ºC in July.
The minimum average temperature is -2.8ºC in February.
Otherwise, Afghanistan has an arid to semi-arid climate and a
low humidity, with a maximum relative humidity of 51.9% in
February and a minimum of 31.5% in July (Fig. 3).
The average annual precipitation is approximately 250
mm/years (Fig. 4). The maximum rainfall of 65.5 mm in in
February is in the winter season and is not useful for
agricultural purposes, while June and July receive theminimum rainfall of approximately 7 mm. Most importantly,

654
y = 0.7554x - 1.2662
R² = 0.7131

3

Ep by Penman-method

Evaporation ammount (mm/day)Observed pan evaporation (mm)

6

2
1

5
4

2
1

Fig. 5. Comparison of estimated evaporation using the Penman
model and observed pan evaporation.

it hardly rains from May through November or December.
Additionally, agricultural productivity has declined further
because of the decreasing water resource, the precipitation
deficit, and traditional inefficiency. Therefore, it is essentialthat all crops be irrigated; however, lower relative humidity andhigher temperatures cause more water evaporation.
4.3. Estimating pan evaporation
Pan evaporation is used to estimate crop evapotranspiration(ETcrop), which can be used to estimate water requirement forcrops. There is a correlation between ETcrop and pan
evaporation.
Basically, ETcrop is equal to theevapotranspiration ratio in multiplying pan evaporation.
Therefore, pan evaporation can be estimated easily so that
ETcrop may estimate irrigation scheduling for crops.
Figure 5 shows a comparison of the estimated evaporation
using the Penman model and observed evaporation with a pan.
There is great variation between estimated evaporation andthat observed, due to the changing climate of Afghanistan from
November to April. Temperatures at this time are low,sometimes below the freezing point.
Therefore,
evapotranspiration during this time becomes small, and it isthought that estimates become uneven.
We tried to estimate pan evaporation using othermeteorological parameters, such as air temperature, relative
humidity, sunshine hour, and wind speed. When we
estimated pan evaporation with the relative humidity, there wasa large inequality; because Afghanistan is located in a dry area,
relative humidity values mostly varied from 30 to 35%. We
also tried to estimate pan evaporation with sunshine hours.
There was a good relationship between pan evaporation and airtemperature as compared to pan evaporation’s relationship with

y = 0.2073x - 1.7583
R² = 0.8349

0
-10.0

6

0.0

10.0
20.0
Temperature (℃)

30.0

Fig. 6. Relationship between air temperature and pan estimatedevaporation and observed pan evaporation amount.

6
Observed evaporation (mm)23
45
Estimated evaporation (mm)5y = 0.188x - 1.441
R² = 0.701

4
3
2
1
0

0

10

20

30

Temperature (℃)
Fig. 7. Relationship between 5-day average temperatures andobserved pan evaporation.
6
observed evaporation (mm)1

y = 0.2062x + 0.524
R² = 0.6612

300Class-A Pan

5
y = 0.193x - 1.520
R² = 0.764
σ=±0.5520

4
3
2
1
0
0

5

10
15
20
Temperature (℃)

2530Fig. 8. Relationship between 10-days average temperatures andobserved evaporation.

relative humidity and wind speed. Similarly we estimatedpan evaporation values with air temperature.

Finally, we found that air temperature was a crucial
parameter for estimating pan evaporation values (Fig. 6) anddetermined the appropriate data set for estimating pan
evaporation, which were average air temperatures and pan
evaporation values in 5- and 10- days periods (Figs.7 and 8).
There is a good relationship between 10-day average airtemperature and pan evaporation as compared to 5-day average
air temperature and pan evaporation, as shown in Figure 7.

5. Conclusions
Afghanistan was classified as an arid and semi-arid region
with hot, little precipitation, and low relative humidity in thesummer. In this period, a lot of irrigation water has been used
for agricultural purposes. Winter is from November to March.
Most of the precipitation fell between October and April.
However, farmers could not fully cultivate due to the cold
weather, which resulted in wasting all of the unusable irrigationwater.
Therefore, crop cultivation activities in Afghanistan werelimited in the summertime. Monthly precipitation data
showed that irrigation was required from May to October.
There was good agreement between the observed airtemperature and pan evaporation values. It was concluded
that the relationship (Eq. y = 0.193x - 1.520) could beapplicable as a practical indicator for estimating pan
evaporation.
This simple approach may help to minimize the amount ofirrigation water required for crop cultivation in Kabul,
Afghanistan. It is important to conduct further research in
Kabul and others provinces of Afghanistan to propose the bestpractice for estimating crop water requirements in field tests.
Acknowledgement
Authors are grateful to Mr. Mohammad Amin Bayat,
manager of the Qargha Research Station, and to Mr. Farid
Ahmmad Orya, head of the weather network from the Ministryof Agriculture, Irrigation and Livestock, Afghanistan, for theirkind cooperation in data collection.

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