HYDROLOGICAL PROCESSES
Hydrol. Process. 17, 2929– 2945 (2003)
Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/hyp.1442

Hydrological regime analysis of theSelenge River basin, Mongolia
X. Ma,1 * T. Yasunari,1,2,3 T. Ohata,2,4 L. Natsagdorj,5 G. Davaa5 and D. Oyunbaatar5
1 Frontier Research System for Global Change, 3173-25 Showa-machi, Kanazawa-ku, Yokohama 236-0001, Japan
2 Frontier Observational Research System for Global Change, 3173-25 Showa-machi, Kanazawa-ku, Yokohama 236-0001, Japan
3 Hydrospheric Atmospheric Research Center, Nagoya University, Nagoya 464-8601, Japan
4 Institute of Low Temperature Science, Hokkaido University, Kita-19, Nishi-8, Kita-ku, Sapporo 060-0819, Japan
5 Institute of Meteorology and Hydrology, Khudaldaany Gudamj 5, Ulaanbaatar 46, Mongolia

Abstract:
Arid and semi-arid regions are very vulnerable to environmental changes. Climate change studies indicate that theenvironment in such areas will steadily deteriorate with global warming; inland lakes will shrink and desert areas will
expand. Mongolia is a landlocked country in north-central Asia that contains a unique ecological system consistingof taiga, steppe, and desert from north to south. The Selenge River basin (280 000 km2  in northern Mongolia is asemi-arid region underlain by permafrost, between latitudes 46 and 52° N, and longitudes 96 and 109° E. The issue ofsustainable development of the basin is very important owing to its limited natural resources, including fresh water,
forest, and rangeland. To examine the water cycle processes in the basin, a hydrological analysis was carried out using
a simple scheme for the interaction between the land surface and atmosphere (big-leaf model) coupled to a hydrologicalmodel for the period 1988–92 to estimate the hydrological regime of the basin. Annual precipitation in this period
averaged 298 mm, ranging from 212 to 352 mm at a 1° ð 1° resolution based on data from 10 gauges, and the estimatedannual evapotranspiration averaged 241 mm, ranging between 153 and 300 mm. This indicates that evapotranspirationaccounts for the overwhelming majority of the annual precipitation, averaging 81% and ranging between 64 and 96%.
The annual potential evapotranspiration in the basin averaged 2009 mm; the ratio of evapotranspiration (actual topotential evapotranspiration) was 0Ð12 and the wetness index (annual precipitation to potential evapotranspiration) was
0Ð15. Copyright  2003 John Wiley & Sons, Ltd.
KEY WORDS

semi-arid area; hydrological model; water budget component; Selenge River basin

INTRODUCTION
Arid and semi-arid regions cover one-third of the land on Earth (Verstraete and Schwartz, 1991; Renard et al.,1993). Since these regions are sensitive to environmental changes, studies of the interactions between the land
surface and atmosphere are of increasing importance (e.g. Manabe et al., 1991; Milly, 1992, 1997; Wetherald
and Manabe, 1999, 2003). Arid and semi-arid zones have recently become an important topic of research on
climate change (e.g., McMahon, 1988; Michaud and Sorooshian, 1994a,b; Ye et al., 1997; Lange et al., 1999;
Andersen et al., 2001; Jothityangkoon et al., 2001). IHP-IV (International Hydrological Programme phase IV
from 1990 to 1995) included this issue to give special attention to the hydrological regime changes associatedwith global climate changes in arid and semi-arid regions.
Mongolia, a landlocked country in north-central Asia, lies on a high plateau surrounded by mountain ridges,
in the transition zone between the Siberian taiga and the dry steppes and semi-deserts of central Asia. The
country has a distinctly continental climate, with very cold winters and hot summers. According to records,
the extreme minimum temperature is 52Ð9 ° C in January and the extreme maximum temperature is 43Ð1 ° C* Correspondence to: X. Ma, Frontier Research System for Global Change, 3173-25 Showa-machi, Kanazawa-ku, Yokohama 236-0001,
Japan. E-mail: xyma@jamstec.go.jp

Copyright  2003 John Wiley & Sons, Ltd.

Received 19 June 2002
Accepted 7 April 2003

2930

X. MA ET AL.

Temperature (°C)

3.0
2.0
1.0
0.0
-1.0
-2.0
-3.0
1940

1950

1960

1970
Year

1980

1990

2000

1950

1960

1970
Year

1980

1990

2000

Precipitation (mm)

400
300
200
100
0
1940

Figure 1. Variation in annual temperature and precipitation in Mongolia over the last 60 years (from Dagvadorj (2000))(Dagvadorj, 2000). The average temperature in Mongolia has increased approximately 1Ð56 ° C over the last
60 years (Figure 1). This temperature increase has been more prominent in the winter months and in themountain areas of western and northern Mongolia than it has in the Gobi and steppe areas. An impact
assessment was implemented using the IPCC-recommended climate change scenarios for 2039 and 2069 to
predict the effects of climate change in Mongolia. This suggested that the desert and steppe zones will expand
northwards; the Gobi desert will significantly increase in size by 2039 and 2069, and the area of desert
steppe will also increase by 2069 (Dagvadorj and Batjargal, 1999). It is also very possible that the currently
permanent snow and glaciers will melt, and that after a period of warming many of the small rivers that are
fed by snow, permafrost, and glaciers will disappear. Permafrost occurs in about 63% of Mongolia; according
to these climate change scenarios, the area of permafrost will drop to 24–28% by 2040 and 16–25% by 2070.
The Selenge River basin (280 000 km2 ) is a semi-arid region located in northern Mongolia between latitudes
46 and 52° N, and longitudes 96 and 109 ° E. Most of the basin is covered by forest or grassland and isunderlain by permafrost. This densely populated area is the major source of fresh water in Mongolia. The
demand for water is increasing annually because of population growth, industrialization, and lifestyle changes.
Consequently, much attention is being paid to the hydrological regime changes associated with development
and the probable environmental changes in the basin in the near future. No quantitative hydrological analysisof the basin has ever been conducted.
This study examined the hydrological processes of the Selenge River basin using a model comprised of asoil–vegetation–atmosphere transfer (SVAT) scheme combined with a hydrological model (Ma et al., 2000).
The next section describes the basin and provides information regarding its location and the datasets used inthis study. The third section explains the model, and the fourth section describes the results of the model.
The hydrological regime of the basin is analysed in the fifth section. Finally, conclusions are drawn in thesixth section.
Copyright  2003 John Wiley & Sons, Ltd.

Hydrol. Process. 17, 2929– 2945 (2003)

2931

HYDROLOGICAL REGIME ANALYSISBASIN AND HYDROMETEOROLOGICAL DATA
Basin description
The Selenge River basin is located in northern Mongolia, between latitudes 46 and 52° N and longitudes
96 and 109° E, and has an area of 280 000 km2 . It is the source region for the Lake Baikal basin (area600 000 km2 ). It contains two main rivers: the Selenge and Orhon (Figure 2). The basin covers sevenprovinces (Zavkhan, Khubsgul, Bulgan, Arkhangai, Uvurkhangai, Selenge, and Tuv), and contains the capitalcity, Ulaanbaatar. The population of the basin is about 1 450 000, which is approximately 70% of the total
population of Mongolia (Adyabadam, 1999). The average annual temperature is below freezing. The annual
precipitation is about 300 mm (Oyunbaatar, 1999), but the temporal and spatial distribution over the basin
is very uneven; during the period 1980–92, it ranged from 147 mm at Murun (no. 231 in Figure 2) in 1980
to 598 mm at Erdenet-Ovoo (no. 236 in Figure 2) in 1985. Although there are no detailed reports of thevegetation distribution for the basin, the World Resources Institute (http://www.wri.org) has reported the land
cover for the Lake Baikal basin as 33% forest and 52% grassland.
The basin is shown on a digital map based on the NOAA–GLOBE (global land one-kilometre base elevation) dataset (http://www.ngdc.noaa.gov/seg/topo/globe.shtml). Figure 3 shows the distribution of elevationin the Selenge River basin. The lowest elevation, near the outlet, exceeds 600 m, and the highest, in the
Hangyan Mountains, exceeds 3000 m. The elevation is between 1000 and 2000 m in about 72% of the basin.
To simulate the water flow in channels, a 0Ð1° grid map of the river network was derived and, to run themodel, meteorological data were interpolated for the whole basin on a 1° ð 1° grid.

Taig
a
Fore
st

Zone

Step

M

Taig
pe Z
a Zo
H
one
ne
L
an
U TA MO g a y NT
G
O
L
I
A
N I
a
ig
T
n
a Zo
For A
n
e
est I
N u
Step
Ste N
r
p
u
e
u
Zone
ppe S
Zo
ne
Dese
rt S
tepp
e Zo
ne

A
O

Dese

rt Zo

ne

96°E

100°E

104°E

108°E

50°N

112°E

4
14
207

iver
nge R

3

Sele

1
231
232

48°N

236

iver

on R

Orh
272

292 290

Meteorological station

282

Hydrological station
285

Lake
River

46°N

Basin divide

287

96°E

100°E

104°E

108°E

Figure 2. Natural zones in Mongolia and map of the Selenge River basin

Copyright  2003 John Wiley & Sons, Ltd.

Hydrol. Process. 17, 2929– 2945 (2003)

2932

X. MA ET AL.

25

Percent (%)

20

15

10

5

0
≥3
Z

27

50

≤Z

00

00
<

27
<
≤Z
00
25

≤Z
50
22

30

50

00
25
<

<
≤Z
00
20

≤Z

<

22

20

50

00

50
50
17

00
15

≤Z
50
12

≤Z

<

<

15

17

00

50
12
≤Z
00

10

75

0≤

Z

<

<

75

10

0>

00

Z

0

Altitude (m, a.s.l.)
Figure 3. Elevation distribution of the Selenge River basin

Hydrometeorological data
Data for 1988 to 1992 are available from four hydrological stations. Two are located midstream anddownstream on the Selenge River, one is located downstream, on the Orhon River, and the fourth is at theoutlet. The locations of the gauges are shown in Figure 2. The discharge data were based on measured waterlevels according to the calibrated relationship between the water level and discharge at a section. The basin
outlet is at Sukhbaatar (no. 4 in Figure 2). The study also used data from 10 meteorological gauges: twooutside and eight inside the basin. Table I lists information for all of the gauges, and Table II shows themeteorological variables used in the study. Meteorological data were interpolated onto a 1° ð 1° grid with thedata for the nearest three stations weighted using the inverse of the distance between each grid point and thethree gauge locations (Ma et al., 2000).

MODEL DESCRIPTION
A large-scale hydrological model that incorporates land surface processes, including snowmelt, evapotranspiration, and runoff formation, was developed to understand hydrological regimes at the basin scale. The model
contained three submodels, i.e. SVAT, runoff, and river-flow-routing models, to examine interactions between
the atmosphere and land surface and the water flow over the land.
The study used the SVAT model of Ma et al. (1998). The vegetation was described using a single-layer
big-leaf model and the soil layer was modelled as being 6 m thick, which is considered the isothermal depth.
Radiation components were estimated from the daily routine meteorological data set using the method of
Kondo (1994) as follows.
Copyright  2003 John Wiley & Sons, Ltd.

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HYDROLOGICAL REGIME ANALYSIS

Table I. List of meteorological and hydrological stations used in the study
NumberName/River

Meteorological station
207
Khatgal
231
Murun
232
Khutag236
Erdenet-Ovoo272
Uliastai
282
Tsetserleg
285
Khujirt287
Bayankhongor
290
Zuunmod
292
Ulaanbaat
Hydrological station
1
Selenge3
Selenge
4
Selenge
14
Orhon

District/Station

LatitudeLongitude

Elevation (m)Khubsgul
Khubsgul
BulganBulganZavkhan
Arkhangai
Uvurkhangai
Bayankhongor
Tuv
Ulaanbaatar

54° 260
49° 380
49° 230
49° 3047° 45047° 270
46° 54046° 8047° 430
47° 550100° 90
100° 100
102° 420
104° 60
96° 510101° 280
102° 460
100° 410
106° 570
106° 520

1668
1283
933
1300
1751
1693
1650
1859
1529
1306

Ikh-UulZuunburen
Sukhbaatar
Sukhbaatar

49° 140
50° 4050° 9050° 100

101° 210
105° 280
106° 30
106° 50

Catchment area km2 

69 800148 000
281 700
132 000

Table II. Daily routine meteorological data
used in the study
Item

Unit

Maximum air temperature
Minimum air temperature
Vapour pressure
Relative humidity
Average air pressure
Average wind speed
Precipitation amount
Sunshine duration

°C
°C

hPa
%
hPa
m s1
mm
h

Global solar radiation#
Daily extraterrestrial radiation Sod
was calculated using:
#

Sod D

Ioo




dso
ds

2

Ha sin  sin υ C cos  cos υ sin Ha 

1

where Ioo is the solar constant (1365 W m2 ), ds and dso are the distance and average distance from the Earth
to the sun respectively, Ha is the hour angle,  is the latitude, and υ is the declination. The possible durationof sunshine No is written as
2Ha
2
No D
0Ð2618From Equation (2), the amount of global solar radiation Sd# can be estimated using

 # 
N 1
Sod a C b NCN
, 0< N
No
#
o
Sd D
N D0
c,
No
Copyright  2003 John Wiley & Sons, Ltd.

3Hydrol. Process. 17, 2929– 2945 (2003)

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X. MA ET AL.

where N and N are the observed sunshine duration and the corrected value of the sunshine duration (zero)
respectively, and a (0Ð55), b (0Ð179) and c (0Ð114) are constants that depend on the sunshine recorder type.
Using latitude and the day of the year, dso /ds , Ha and υ can be calculated as:
Ha D cos1  tan  tan υdso
D 1Ð000 11 C 0Ð034 221 cos  C 0Ð001 28 sin  C 0Ð000 719 cos 2 C 0Ð000 077 sin 2
ds

4
5

υ D sin1 0Ð398 sin ˛2 

6

˛2 D 4Ð871 C  C 0Ð033 sin 
2
D
IDA
365
IDA D 30Ð36Month  1 C DAY

7
8
9

where Month is the month and DAY is the day of the month.
Upward and downward longwave radiation#

The upward Lu" and downward Ld longwave radiation can be described, using
Lu" D ε T4s

10#/ T4a C]
Ld# D T4a [1  1  Ldf

11

where ε is the emissivity (0Ð97), is the Stefan–Boltzmann constant (5Ð67 ð 108 W m2 K4 ), Ts is the#land surface temperature, Ta is the air temperature measured 2 m above the land surface, Ldf is the downward#
longwave radiation on a clear day, and C is a coefficient related to sunshine ratio. Ldf and C can be describedusing the empirical formula#

Ldf D 0Ð74 C 0Ð91x C 0Ð07x 2  T4a
x D 0Ð0315TDEW  0Ð1836


WVP
237Ð3 log106Ð11TDEW DWVP
7Ð5  log10
6Ð11

12
13

14

Set A D N/No , if 1A > 0 thenC D 0Ð826A3  1Ð23A2 C 1Ð135A C 0Ð298

15

C D 0Ð2235

16

If A D 0 thenwhere WVP is the water vapour pressure and TDEW is the dew point temperature. The net radiation Rn , canbe calculated as##
Rn D 1  refSd  Lu" C Ld
17
where ref is the albedo (0Ð1 for soil) of the land surface.
Copyright  2003 John Wiley & Sons, Ltd.

Hydrol. Process. 17, 2929– 2945 (2003)

2935

HYDROLOGICAL REGIME ANALYSIS

Latent and sensible heat fluxes
To estimate the heat fluxes between the land surface and atmosphere, the Penman–Monteith method(Monteith, 1965) was adopted:
Rn  G C a ca υq/ra C 1 C rs /ra Rn  G 1 C rs /ra   a ca υq/raHD C 1 C rs /ra 
ED

18
19

where G is the heat flux into the soil or snow layer,  is the slope of the saturated vapour pressure curve at
air temperature Ta , is the psychrometric constant, ca is the specific heat of the air, a is the density of air,υq is the specific humidity deficit, ra is the aerodynamic resistance, and rs is the surface resistance. The valueof G is determined using the soil temperature profile. ra can be calculated with the assumption of a neutral
atmosphere.
To determine rs , Blyth and Harding (1995) reported the following simple modification of the method ofJarvis (1976):
rs D rsmin expˇυq
20
where rsmin is the minimum surface resistance and ˇ is a constant (dimensionless number: 0Ð046). Ma et al.
(1999) conducted a detailed study to fit the value of rsmin , and found a linear relationship between rsmin and theradiation dryness index (RDI), the ratio of the annual net radiation to precipitation for a region, and compared
the results derived from different climatic regions with different vegetation communities. Accordingly, rsmin
is given by21
rsmin D  RDI
where  is a coefficient (dimensionless number) related to local vegetation conditions and is between 100
and 490.
In this model, the thermal conductive processes for the soil and snow layers were considered separately
for different material zones. The conduction equation in the snow layer can be written as


∂In
∂Tp
∂Tp
∂
cp p
p

22
D
 fF
∂t
∂z
∂z
∂z
where cp is the specific heat of snow, p is the snow density, Tp is the snow temperature, p is the thermal
conductivity of the snow (0Ð3 W m1 K1 ), In is the flux density of the net solar radiation entering the snow,
5
1
f is the heat of fusion of ice (3Ð34 ð 10 J kg , F is the snowmelt within the snow layer, t is time, and z
is depth. The flux density of solar radiation is written as∂In#
D 1  refs Sd expz
∂z

23

where refs is the albedo of snow and  is the attenuation coefficient of solar radiation, which is kept constant(40 m1  (Fukami et al., 1985). The simple method of Bai and Ohata (1989) is used to determine the snow
albedo as24
refs D 1Ð0118 exp1Ð954 p 
The snow density

p is calculated using a simplified equation of Yamazaki et al. (1991):

W
∂ p
D 0 p
∂t

Copyright  2003 John Wiley & Sons, Ltd.

25Hydrol. Process. 17, 2929– 2945 (2003)

2936

X. MA ET AL.

where W is the weight of snow. 0 can be written as
0 D A0 expK p  ˛s Ts 

26

where 0 is a constant (6Ð9 ð 105 kg s m2 ), K is a constant (2Ð1 ð 102 m3 kg1 ), and ˛s is a constant(9Ð58 ð 102 ° C1 ).
expˇs ωs   exp100ˇs 
27AD
1  exp100ˇs where ωs is the water content of snow and ˇs (18) is a constant.
The basic equation for thermal conduction in the soil layer is as follows (Outcalt et al., 1975):
∂Tg
∂
D
∂t
∂z



 ∂Tg
cg g ∂z28

where Tg is the soil temperature,  is the thermal conductivity of soil, cg is the specific heat of soil, and gis the soil density. Fukuda and Ishizaki (1980) consider that the phase change of soil water with thawing andfreezing, specifically A D /cg g  with a small finite temperature range T can be replaced by
AD

1
cg1 g

T
2

frozen

AD2
1
f M C 2 cg2 g C cg1 g 

if 

AD

2
cg2 g

if Tg  

if Tg ½

T
2

T
T
< Tg <
22

unfrozen29phase transition

30
31

where 1 is the thermal conductivity of frozen soil (1Ð2 W m1 K1 ), 2 is the thermal conductivity of unfrozen
soil (1Ð0 W m1 K1 ), cg1 g is the heat capacity of frozen soil, cg2 g is the heat capacity of unfrozen soil,and M is the soil moisture content. Fukuda and Ishizaki (1980) also assumed that the temperature of theisothermal layer forming the lower boundary of the thermal conductive model, which is set at a depth of 6 m
below the ground surface, equals the annual air temperature 2 m above the land surface. The soil layer andsnowpack are subdivided at 0Ð01 m intervals in the study. An iterative process was used in the calculationand the value of convergence was set to 0Ð001 ° C for the surface temperature difference between the current
and previous result.
The runoff formation for a grid was simulated using a runoff model (Ma et al., 2000) that is a modificationof HYCYMODEL, developed by Fukushima (1988). The model input was effective precipitation Pn , whichis the total amount of precipitation and snowmelt minus the evapotranspiration calculated using the SVATmodel. The total runoff for a grid was calculated using four reservoirs to give surface runoff and base runoff.
The modified HYCYMODEL used to produce each runoff component from the output of the SVAT model isshown in Figure 4 and is briefly summarized as follows:

Copyright  2003 John Wiley & Sons, Ltd.

Sc D Kc Qc0Ð6

32

Sh D Kh Qh0Ð6

33

Su D Ku Qu

34

Sb D Kb Qb0Ð1

35
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2937

HYDROLOGICAL REGIME ANALYSIS

Pn(t): effective precipitation from SVAT
Channel area
(ratio: c')Land surface
Pe(t): effective precipitation
over the saturated area

SuI
Qu: infiltration

Sc

IV
Sh

Sb

III

II

Qc: stream flow
Qt :
total
discharge

Qh: surface flow
Qb: base flow

Figure 4. Sketch of the modified HYCYMODEL (from Ma et al. (2000). (Reproduced by permission of John Wiley & Sons Ltd.))

where Sc , Sh , Su , and Sb are the storage in the channel, land surface, top soil layer and deep soil layer
respectively, Qc is the runoff from the channel area, Qh is the runoff from the saturated area, Qu is theinfiltration from the top soil layer to the deep soil layer, and Qb is the base flow from the deep soil layer.
Kc , Kh , Ku , and Kb are constants. The storage change for each reservoir can be calculated as follows:Sc t D Sc t  1 C Pn t  Qc twhen Pn t ½ 0

36

Sh t D Sh t  1 C Pe t  Qh twhen Pn t ½ 0

37

Su t D Su t  1 C Pn t  Pe t  Qu t38

Sb t D Sb t  1 C Qu t  Qb t39

where t is the current time step and t  1 is the previous time step. Pe t is the effective precipitation overthe saturated area and is determined by the mean effective soil depth, D50 (mm), and its deviation Dsig .
Dsig is defined as a constant (dimensionless number equal to 5), whereas D50 varies according to soil type.
From previous studies (Nakashima and Fukushima, 1994; Tanaka et al., 1998), the value of D50 ranges from25 mm for bare land to 120 mm for forested areas. In order to consider permafrost, D50 was defined using
the following relationship with the depth of the active layer:
D50 D ˛Da1

40

where ˛ (500) is a constant representing soil porosity and Da1 is the depth of the active layer. The value ofPe t was calculated using
41
Pe t D mPn twhere m is the saturated area ratio estimated as
 
 
1
2
p
mD
d
exp
2
2
1

42

where  is a parameter for the normal distribution defined as
D

Copyright  2003 John Wiley & Sons, Ltd.

log[Su0 t/D50 ]
Dsig

43

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X. MA ET AL.

and
Su0 t D Su t  1 C Pn t44Note that if Pn t is less than zero, then the value of Pn t is first added to the topsoil storage as theevapotranspiration loss (Equation (34)). When the remaining topsoil storage is insufficient to offset the valueof Pn t, the topsoil storage is set to zero and the remaining amount of Pn t is deducted from the groundwater
storage (Equation (35)). The total discharge Qt , from a grid is then given by
Qt D 1  c0 Qh C Qb  C c0 Qc45

where c0 is the ratio of the impermeable area of the channel surface to the area of the watershed (equal to0Ð05). The discharge enters the river network and then flows downstream.
The St Venant equations within a one-dimensional framework give a rigorous description of the openchannel flow in a river network (Beven and Wood, 1993). The St Venant equations can be solved using afinite-difference method. However, this necessitates specifying both the upstream and downstream boundary
conditions, as well as the lateral inflow (e.g. Ma and Cheng, 1996). So far, this cannot be done on a macrobasin scale. The Muskingum method, a linear flood routing method, is used to estimate the river flow fromupstream to downstream. To obtain the parameters used in the Muskingum model for each fixed river course
requires data from many flood events. To simplify flow estimates for a river network, the velocity of river
flow is set as a constant. This method has been used in Wyss et al. (1990), Naden (1993), Liston et al. (1994),
Kite et al. (1994), Miller et al. (1994), Kanae et al. (1995), and Oki et al. (1996, 1999). Wyss et al. (1990)
and Naden (1993) used a channel velocity of 0Ð6 m s1 for small basins (area less than 10 000 km2 . Kite
et al. (1994) predicted a velocity of 0Ð33 m s1 for an impervious area (10 ð 10 km2 grid) in the Mackenzie
River basin. Since the velocity varies with the grid scale, the value of the velocity in previous studies ranges
from 0Ð2 to 0Ð6 m s1 . Here, we assumed a constant velocity of 0Ð4 m s1 for the Selenge River basin, whichequalled the velocity used in the Lena River (Ma et al., 2000). Moreover, it must be pointed out that the outputof the SVAT and runoff models was for a 1° ð 1° grid, and this was redistributed into a channel network
using a 0Ð1° ð 0Ð1° subgrid.
This model was applied to the Lena River basin in GAME (GEWEX Asian Monsoon Experiment)-Siberia(Ma et al., 2000) and to the Torne–Kalix basin in the Project for the Intercomparison of Land-surface
Parameterization Schemes Phase 2e (PILPS 2e) (Bowling et al., 2003; Nijssen et al., 2003). Ma and Fukushima(2002) described the model in detail and provided the model program codes. Figure 5 shows the model
framework.

MODEL APPLICATION AND RESULTS
The model was applied to the Selenge River basin. To calibrate the model, the data for the first 2 years (1988
and 1989) were used. From the meteorological data, the amount of precipitation at all gauges was close to
the annual level and no extreme climatic events occurred during the 2 years. The initial value of rsmin was
set at 400 s m1 for each grid and then the model was run for the 2 years. Then, the value of RDI for eachgrid was derived from the heat flux calculated in the initial run. According to Ma et al. (1999), the value ofrsmin can be fixed by adjusting the slope of the linear relationship between rsmin and RDI until a reasonablehydrograph is obtained at the four hydrological gauges. In this study, the value of the slope  was fixed at210. Consequently, the value of RDI for the basin ranged from 1Ð10 to 2Ð71, so rsmin ranged from 231 to
570 s m1 . Table III shows the main parameters calibrated in this study and the corresponding values forother regions.
The model was then run for the verification period, 1990 to 1992. Figure 6 compares the observed andcalculated results of the daily hydrographs at the four hydrological gauges in the basin. The calculatedhydrographs are close to those observed throughout the calibration period (1988–89), except for missing
Copyright  2003 John Wiley & Sons, Ltd.

Hydrol. Process. 17, 2929– 2945 (2003)

2939

HYDROLOGICAL REGIME ANALYSIS

meteological data (grid scale, daily)

Snow
Active layer
Active layer

SVAT (Big-leaf) model

Runoff formation

surfaceflow

infiltrationbase flow
Conceptual runoff modelRiver network(basin scale)

Down stream

Output (hydrograph, heat flux and so on)
Figure 5. Flowchart of the model

Copyright  2003 John Wiley & Sons, Ltd.

Hydrol. Process. 17, 2929– 2945 (2003)

2940

X. MA ET AL.

Table III. Calibrated parameters used in the model and those variation in different regions
Parameter


Kb
Ku
Kh
Ke

Unit

Lena River basin(Ma et al., 2000)

PILPS 2e(Bowling et al., 2003;
Nijssen et al., 2003)

Selenge River basin(this study)—
mm9/10 h1/10
hmm2/5 h3/5
mm2/5 h3/5

135
687
21Ð7
10
2

200
687
10
20
2

210
687
40Ð7
5
2

data for no. 14 in 1989. From 1990 to 1992, the hydrograph at gauge no. 1 was relatively stable. However,
the hydrographs at gauges no. 3 and no. 14 fluctuated over the 3 years, especially in 1990, which waswetter than the other years. Except for gauge no. 4, which was missing data, the flow due to snowmelt far
exceeded the values observed in 1990 at all gauges. The simulated hydrographs for 1991 had a time lag at allgauges compared with the observed hydrographs, whereas for 1990 they overestimated the observed values
at gauges no. 1 and no. 3, and underestimated them at no. 14 during the summer. In contrast, the simulatedhydrographs for 1992 at gauge nos 1, 3, and 4 were underestimates of the observed values. For the water
budget, the annual precipitation throughout the basin was 298 mm and the estimated evapotranspiration was
241 mm; the difference was 57 mm. The calculated annual runoff at gauge no. 4 was 50 mm (the data were
missing for 1990–91).

ANALYSIS AND DISCUSSION
The annual average sunshine in Mongolia is around 3000 h, which is longer than in other countries at thesame latitude. The predicted capacity for evapotranspiration is, therefore, much higher than in other regions.
Using our model, a preliminary water budget was obtained. Table IV shows the distribution of the 5 year
average annual precipitation calculated with the data from the 10 gauges and extrapolated to the 1° ð 1° gridfor the entire basin using distance-related interpolation. The annual precipitation was 298 mm and ranged from
212 to 352 mm. Oyunbaatar (1999, 2001) reported that the geographic conditions in the Selenge River basinvary markedly, as does the amount and spatial distribution of precipitation. The difference in precipitation,
140 mm, is not very large, and may have been smoothed as a result of using interpolation to calculate
1° ð 1° grids from the precipitation at 10 gauges. Table IV also lists the estimated annual evapotranspiration
during the period. The evapotranspiration averaged 241 mm, and ranged from 153 to 300 mm. In addition,
Table IV shows the estimated potential evapotranspiration (with rsmin D 0). The minimum was 1096 mm andthe maximum was 2779 mm. The basin average was 2009 mm. Table V shows the distribution of the ratio of
annual evapotranspiration to precipitation. The basin average was 0Ð81, with a range between 0Ð64 and 0Ð96.
Therefore, about 81% of the precipitation is lost to evapotranspiration. In other words, the runoff ratio (annual
runoff to precipitation) of the basin is 0Ð19, which is far lower than the reported values of 0Ð49–0Ð80 for Japan(Ma et al., 1999), 0Ð26–0Ð58 for major Eurasian rivers (Serreze et al., 2001), and 0Ð58 for the Mackenzie
River (Kite et al., 1994).
These results show that evapotranspiration dominates the hydrological cycle in the basin. The method
used to estimate the amount of evapotranspiration is, therefore, key to increasing the accuracy of thehydrological simulation. Table V also shows the dimensionless ratio of actual evapotranspiration to potential
evapotranspiration; it averaged 0Ð12, with a range from 0Ð07 to 0Ð18. Moreover, Table V shows the value ofthe wetness index (annual precipitation to potential evapotranspiration) for the basin, which averaged 0Ð15
and ranged between 0Ð1 and 0Ð24. This is an important index for classifying climate regions (Kondo and Xu,
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Hydrol. Process. 17, 2929– 2945 (2003)

Discharge (m3/s)

1989

1991

1992

observation
calculation

1992

1000

1500

2000

2500

3000

3500

0

Year

0
1990

1991

0
1989

Year

1990

500

1000

1500

2000

2500

3000

3500

500

1988

c) No. 14(132,000 km2, 47%)

1988

observation
calculation

500

1000

1500

2000

2500

3000

3500

0

500

1000

1500

2000

2500

3000

a) No. 1(69,800 km2, 24%)

Discharge (m3/s)

1989

1988

1989

d) No. 4(281,700 km2, 100%)1988b) No. 3(148,000 km2, 52%)

Year

1990

Year

1990

1991

1991

1992

observation
calculation

1992

observation
calculation

Figure 6. Comparison of observed and calculated hydrographs at four hydrological stations from 1988 to 1992. The catchment area and its percentage of the whole basin are
indicated in parentheses

Discharge (m3/s)

Copyright  2003 John Wiley & Sons, Ltd.

Discharge (m3/s)

3500

HYDROLOGICAL REGIME ANALYSIS

2941

Hydrol. Process. 17, 2929– 2945 (2003)

2942

X. MA ET AL.

Table IV. Spatial distribution of annual precipitation (mm), evapotranspiration (mm), and potential evapotranspiration (mm)over the basin in 1° ð 1° grids based on data for 10 gauges during the period 1988–92
NnE

96°

97°

98°

Estimated annual precipitation
51°
50°
292
49°
270
268
48°
265
265
262
47°
264
263
265
46°
Estimated evapotranspiration
51°
50°
202
49°
182
205
48°
199
214
204
47°
202
187
180
46°

99°

100°

101°

102°

103°

104°

105°

106°

107°

108°

304
253
264
279

299
306
251
273
320
212

324
300
303
312
341
272

332
330
329
301
273

339
347
326
286
275

343
352
350
309
276

332
336
317
290
275

324
319
300
290

310
298
290

300

194
217
225
211

201
221
227
221
224
153

213
232
245
248
270
210

247
268
257
283
252

249
280
271
276
257

276
295
296
288
256

295
300
273
259
263

289
277
255
250

279
238
240

232

1857
2037
2779
2288
1861
2138

1591
2240
1997
1905
2180
1631

1751
1627
1611
2254
1638

1587
1745
1727
2349
1884

1893
1931
1936
2073
2033

2424
2388
2428
2675
2334

2630
2526
2551
2690

2529
2210
2335

2014

Estimated potential evapotranspiration
51°
50°
1842
1751
49°
1713
2061
2503
48°
1324
1682
1837
2158
47°
1117
1096
1368
1732
46°

1997). According to Kondo and Xu (1997), the value of the index is between 0Ð1 and 0Ð3 for semi-arid areas;
therefore, according to this criterion, the basin is a semi-arid region.
This study estimated evapotranspiration using the Penman–Monteith method (Monteith, 1965) using the heatbalance and assumptions for local conditions. The minimum surface resistance rsmin was calibrated especiallycarefully, although a simple method (Blyth and Harding, 1995) of estimating the surface resistance rs wasused for the basin. Nijssen et al. (1997) and Abdulla and Lettenmaier (1997) indicated that hydrologicalsimulations of arid and semi-arid basins are difficult, even when using the SVAT-coupled model, VIC-2L(Liang et al., 1994). Nijssen et al. (1997) referenced the dataset of minimum surface resistance of Sellers
et al. (1994) for their study area. The dataset of Sellers et al. (1994) is very important global-scale vegetation
information used for general circulation models, but more detail is necessary for a specific region (e.g. Unland
et al., 1996). Based on a hydrological analysis, Ma et al. (1999) reported an average value of 60 s m1 for
a forested mountainous catchment in central Japan and Ma et al. (2000) reported values of 78 to 911 s m1
in the Lena River basin for a 1° ð 1° grid. For the Torne–Kalix basin (an experimental basin for PILPS 2(e)located in northern Scandinavia), values of rsmin were derived that ranged from 57 to 126 s m1 at a spatial
resolution of 0Ð25° .
The accuracy of the extended meteorological data is not discussed, because it is very difficult to obtain
results for the basin using data from only 10 gauges. The density of gauges in Mongolia is low; it equals
1/5080 km2 , which is 2Ð5 times less than the WMO standard for rainfall observations (Oyunbaatar, 1999).
Michaud and Sorooshian (1994b) recommended that the density of rain gauges should be not less than 4 km2
per gauge for semi-arid catchments, because the amount of precipitation directly affects the hydrologicalresponse. In addition, some digital data for the basin should be checked more carefully. Table VI shows the
February precipitation measured at nine rain gauges in the basin over the 5 years (gauge no. 236 has missing
data during this period). The values for 1990 are three times larger than those for other years, except at gauges
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Hydrol. Process. 17, 2929– 2945 (2003)

2943

HYDROLOGICAL REGIME ANALYSIS

Table V. Spatial distribution of ratio of evapotranspiration (annual evapotranspiration to precipitation), dimensionless evapotranspiration (estimated actual evapotranspiration to potential evapotranspiration), and wetness index (annual precipitation
to potential evapotranspiration) for the basin in the period 1988–92
NnE

96°

97°

Evapotranspiration ratio
51°
50°
49°
0Ð67
48°
0Ð75
0Ð81
47°
0Ð77
0Ð71
46°

98°

99°

100°

101°

102°

103°

104°

105°

106°

107°

108°

0Ð69
0Ð77
0Ð78
0Ð68

0Ð64
0Ð86
0Ð85
0Ð76

0Ð67
0Ð72
0Ð91
0Ð81
0Ð70
0Ð72

0Ð66
0Ð77
0Ð81
0Ð79
0Ð79
0Ð77

0Ð74
0Ð81
0Ð78
0Ð94
0Ð93

0Ð74
0Ð81
0Ð83
0Ð96
0Ð94

0Ð81
0Ð84
0Ð85
0Ð93
0Ð93

0Ð89
0Ð89
0Ð86
0Ð89
0Ð96

0Ð89
0Ð87
0Ð85
0Ð86

0Ð90
0Ð80
0Ð83

0Ð77

0Ð11
0Ð09
0Ð10
0Ð12

0Ð11
0Ð11
0Ð08
0Ð10
0Ð12
0Ð07

0Ð13
0Ð10
0Ð12
0Ð13
0Ð12
0Ð13

0Ð14
0Ð17
0Ð16
0Ð13
0Ð15

0Ð16
0Ð16
0Ð16
0Ð12
0Ð14

0Ð15
0Ð15
0Ð15
0Ð14
0Ð13

0Ð12
0Ð13
0Ð11
0Ð10
0Ð11

0Ð11
0Ð11
0Ð10
0Ð09

0Ð11
0Ð11
0Ð10

0Ð12

0Ð17
0Ð10
0Ð12
0Ð16

0Ð16
0Ð15
0Ð09
0Ð12
0Ð17
0Ð10

0Ð20
0Ð13
0Ð15
0Ð16
0Ð16
0Ð17

0Ð19
0Ð20
0Ð20
0Ð13
0Ð17

0Ð21
0Ð20
0Ð19
0Ð12
0Ð15

0Ð18
0Ð18
0Ð18
0Ð15
0Ð14

0Ð14
0Ð14
0Ð13
0Ð11
0Ð12

0Ð12
0Ð13
0Ð12
0Ð11

0Ð12
0Ð14
0Ð12

0Ð15

Dimensionless evapotranspiration
51°
50°
0Ð11
49°
0Ð11
0Ð10
48°
0Ð15
0Ð13
0Ð11
47°
0Ð18
0Ð17
0Ð13
46°
Wetness index
51°
50°
49°
48°
0Ð20
47°
0Ð24
46°

0Ð16
0Ð16
0Ð24

0Ð16
0Ð13
0Ð14
0Ð19

Table VI. Comparison of precipitation at various gauges in February for two different period: period A, the 4 year averagefor 1988 to 1992, excluding 1990; period B, amount for 1990
Precipitation (mm)Period

207

231

232

272

282

285

287

290

292

A
B

3Ð2
18Ð0

2Ð4
2Ð0

2Ð5
2Ð0

3Ð2
77Ð0

3Ð5
30Ð0

4Ð1
45Ð0

5Ð1
22Ð0

2Ð2
95Ð0

2Ð9
33Ð0

no. 231 and 232, yet the observed hydrographs indicate that those heavy precipitation events (snowfall) did
not lead to a big spring flood compared with other years.

CONCLUSION
A hydrological study was carried out for the Selenge River basin, the biggest source of freshwater in Mongolia,
using a scheme for the interaction between the land surface and atmosphere coupled with a hydrological model,using data for 1988 to 1992. The results demonstrated that it was possible to model the hydrological processes,
based on comparisons of the observed and calculated hydrographs at four hydrological stations. Using theresults, the basin-scale distribution of the water budget components was examined. The extended annual
precipitation was 298 mm and ranged from 212 to 352 mm, whereas the estimated evapotranspiration averaged
241 mm and ranged from 153 to 300 mm. This is a high-evapotranspiration area; about 81% of precipitation
is lost via evapotranspiration. This study determined that the annual potential evapotranspiration over the
Copyright  2003 John Wiley & Sons, Ltd.

Hydrol. Process. 17, 2929– 2945 (2003)

2944

X. MA ET AL.

basin averaged 2009 mm, and ranged from 1096 to 2779 mm. The dimensionless ratio of evapotranspiration(annual evapotranspiration to potential evapotranspiration) averaged 0Ð12 and ranged between 0Ð07 and 0Ð18.
The wetness index (annual precipitation to potential evapotranspiration) averaged 0Ð15 and ranged between
0Ð1 and 0Ð24, clearly indicating that the basin should be classified as a semi-arid region. By contrast, the valueof rsmin ranged between 231 and 570 s m1 for the basin at a 1° resolution; this information should prove
useful for studies of hydrology and climatology related to climate change in the region.

ACKNOWLEDGMENTS

This work is part of a cooperative research program examining water and energy cycles in Mongolia by the
Frontier Observational Research System, Japan, and the Institute of Meteorology and Hydrology, Mongolia.
We thank Professor Yoshihiro Fukushima, Research Institute for Humanity and Nature, Japan, for his valuablecomments on this paper.

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