Observational Studies at the Khuwae Noi River Basin in Thailand and Regional
Water Balance Analyses by using the Distributed Tank Model*Wenfeng Huang1, Kazurou Nakane1, Panya Polsan2, Thada Sukhapunnaphan3(1: National Research Institute for Earth Science and Disaster Prevention, Japan,
2: Hydrology and Water Management Center for Lower Northern Region, RID, Thailand,
3: Hydrology and Water Management Center for Upper Northern Region, RID, Thailand)* National Research Institute for Earth Science and Disaster Prevention, Japan, 305-0006, 3-1, Tennodai,Tsukuba-shi, Ibaraki-ken, Japan. e-mail: huang@bosai.go.jp
Abstract
Observational studies at Khuwae Noi River Basin (Thailand) with catchment area of 4,841km2 were developed from1996. A hydrometric network consisting of five automatic weather stations, an automatic water level station and eightrainfall stations was established in this basin. The observations gave much information about the spatial and temporal
distribution of the rainfall and the evaporation characters in this tropical area. They were compared with those fromGAME reanalysis data-set and also those from TMD observation data. The evaporation data derived from the GAME
data-set are verified to be reliable, but the rainfall data from GAME data-set need to be improved in this area. The study
shows that the TMD rainfall data can be interpolated into grid data for regional water balance analyses and the analyses
results are in good agreement with the observations. The discharge of this basin was simulated by using the Distributed
Tank Model with temporal resolution of one hour and spatial resolution of 0.1 degree. These results confirm that theDistributed Tank Model is suitable for regional water balance analyses.
Keyword: observational studies, regional water balance, distributed tank model1. Introduction
In the majority of cases, hydrological models areemployed to estimate the water balance of a basin
according to the observed data, such as rainfall,evaporation, soil moisture, and so on. But it was known
that the observation data are temporally and somewhere
spatially sparse in tropical regions. This preventshydrological models from facilitating its application totropical areas. In order to study the water balance, andthe variation patterns of discharge, rainfall and theevaporation in a tropical area, a hydrometric network
consisting of five automatic weather stations, one waterlevel station and eight rainfall stations was established in1996 at Khuwae Noi River Basin under a cooperative
project between the National Research Institute for Earth
Science and Disaster Prevention (NIED) of Japan and theRoyal Irrigation Department (RID) of Thailand (Nakane,et. al. 2001). These observations were successfully
analyzed with the Distributed Tank Model of 0.1-degree
resolution in space and an-hour resolution in time.

1.1. Geographical Condition of Khuwae Noi
River Basin
Khuwae Noi River Basin (see Fig.1), which is atributary of the Nan River in the northeast of the ChaoPhraya Basin, is located to the east of Phitsanulok,
Thailand with catchment area of 4,841km2. Some 77
percent of this basin is occupied by forest and the rest
other is cropland and pasture. There are mountains
ranging from 1,400 to 2,100 meters in height in thenorthern area and mountains ranging from 1,500 to 1,750
meters in the east part of the basin (see Fig.2).

1.2 The Distributed Tank Model
The Tank Model, which is a conceptual model and wasdeveloped by Sugawara (1972), has been one of the
popular hydrological models for analyzing the waterbalance in a river basin. It appeared firstly as a lamped
hydrological model, and in recent years has been
generalized to be a distributed one by Nakane (2001) soas to study the regional water balance model in acontinental scale.
The terrains in the considering area are classified into

four types, namely mountainous area, hilly area, diluvial
area and alluvial area. The land-use is classified into tentypes according to the information of USGS (U.S.
Geological Survey). Each grid of the analyzing area isthe combination of two kinds of tank models: field tankand ground water-river tank, which represent the land
surface and the river respectively. All the parameters inthis model need to be calibrated with try-error method
manually or optimization method automatically.

2. Components of the observations
Totally 14 hydrometric stations were established in
Khuwae Noi River Basin. Five automatic weather
stations (W1-W5), an automatic water level station (H1)and eight rainfall stations (R1-R8) are sited in the
different topographic region, namely the mountains, hilly
land, higher alluvial plain and lower alluvial plain. Threeof the five weather stations (W1-W3) had also acted assoil moisture station. The locations of the stations areshown in Fig.2 and the details of observation
components are listed in Table 1. Additionally, three
existing discharge stations of RID, namely N22 (thesame station as H1), N36 and N58 are used forevaluation with Distributed Tank Model. The details ofthe discharge stations are shown in Table 2.
The dense observations had been successfully
carried out from April 1996 (some from May 1997) toMarch 2000. The five automatic weather stations, aswell as the automatic water level station, record data
every 20 minutes continuously, and the rainfall wasmeasured on 10-minute base in the eight rainfallstations.

3. Evaluations
3. 1. Spatial Distribution of the Rainfall
The rainfall in this river basin, both monthly one andthe sum of the rainy season varies quite a lot along withthe terrain, as shown in Fig. 3 (the terrain is shown in Fig.
2). Generally, the rainfall in mountainous area is morethan that in plain area.

Fig. 1: Khuwae Noi Basin

Station Longitude
No.
(E)
W1
W2
W3
W4
W5
H1R1
R2
R3
R4R5
R6R7
R8

100°48′09″
100°20′00″
100°50′10″100°45′52″100°22′55″
100°22′32″
101°03′19″
100°52′45″
100°37′05″
100°59′33″
100°56′05″
100°55′09″
100°53′43″
100°40′30″

Fig. 2: Hydrometric Stations in Khuwae Noi Basin

Table 1: Details of stations and observation components
Components
Latitude Elevation
Water Soil
Soil
(N)
(m)
Wind Radiation Temperature Rainfall
Level Moisture Temperature
16°59′28″
290
*
*
*
*
*
*
17°14′10″
90
*
*
*
*
*
*
17°31′58″
340
*
*
*
*
*
*
17°05′12″
200**
*
*
*
*
16°50′01″
44
*
*
*
*
*
*
17°02′07″52**
17°13′46″
180*
17°22′05″
460*
17°15′49″
240*
17°00′15″ 1,105*
17°15′16″989*
17°41′17″515*
17°36′31″
680*
17°25′56″
840*

Table 2: Details of existing discharge stations
StationCatchment
Longitude *(E) Latitude* (N)No.
Area (km2)
N58
100°56′06″
17°08′33″322
N36
100°49′55″
17°04′59″
1,651
N22 (H1) 100°22′32″
17°02′07″
4,841(* The original format provided by RID is in degree)

For the whole basin, because about 60 percent of area
is under the elevation of 450m, it is reasonable tosuppose that the areal rainfall of this basin mainly
depends on the rainfall from the stations below 450m.
The areal rainfall, the average rainfall of all the stations
and the average rainfall of those below 450m (W2, W3,W4 and R3) are shown in Fig. 4. It can be seen in Fig. 4athat the monthly areal rainfall is very close to the average
rainfall of all the 13 stations (station W5 was removed
because of its much absence of observations), and it canbe almost represented by the average value of thestations W2, W3, W4 and R3. i.e. W2, W3, W4 and R3
can be considered as the control stations of the wholebasin.

3.2. Temporal Distribution of the Rainfall

Fig. 3: Spatial Distribution of theRainfall in 1998 (unit: mm)

The monthly distribution pattern of the rainfalls fromGAME (GEWEX Asian Monsoon Experiment)
reanalysis data, which were developed by MeteorologicalResearch Institute, Japan, is shown in Fig. 4b. It is muchdifferent from that of the observed, as shown in Fig. 4a.
Further more, the rainfall at station W3 is studied in Fig.
5. The rainfall of observations, the GAME reanalysis
data and the TMD (Thai Meteorological Department,Thailand) observation data are all used for thecomparisons. All the time steps were converted into
three-hour base, even though the original one of theobservations, GAME reanalysis data and the TMD
observations is one hour, six hours and three hours
respectively. The rainfall values of GAME at station W3
are interpolated from the original GAME data-set withspatial resolution of 1.25 degrees and those of TMD areinterpolated from the TMD observation data with
Angular Distance-weighted method (New, 2000).
Average Rainfall of W2,W3,W4 and R3250

Average Rainfall of All the Stations
Areal Rainfall

Rainfall(mm/month)

200

150

100

500AprMayJunJulAug

SepOcta) Observations
Average Rainfall at the Sites of W2,W3,W4 and R3
250

Average Rainfall at the Sites of All the Stations

It can be seen that even though the amount of different
datasets is almost the same on middle-sized base such asmonthly interval, the distribution pattern become quite
different if they are zoomed into small-sized base, 3-hourinterval in this study. Briefly, the smaller the temporalbase is, the sharper and more uneven the hyetographbecomes. Fig. 5 also shows that the rainfall interpolated
from the TMD observations is relatively close to that of
the observation in the basin.

3.3. Areal Evaporation
As necessary input data for the Distributed Tank
Model, potential evaporation was carefully studied andcalculated by using Priestley-Taylor method (Priestley, et.
al. 1972). In this method, the calculation of theequilibrium evaporation is needed.
Fig. 6 shows the comparisons of the equilibrium
evaporation derived from the observed heat data andGAME reanalysis data in the basin. Both in May and in
September of 1998, the calculated equilibrium
evaporation by using GAME reanalysis data agrees withthat from observations very well. It tells that the GAME
reanalysis data on heat balance analysis is reliable and it
is feasible to compute the grid evaporation from GAME
data in the regional water balance analyses.

Areal Rainfall

1.0GAME Reanalysis

150100500AprMayJunJulAugSepOctb) GAME reanalysis

Equilibrium Evaporation (mm/hour)

Rainfall(mm/month)200

Observation

0.8
0.6

0.4
0.2
0.0

-0.2

Fig. 4: Comparisons of Areal Rainfall and theAverage Value of Some of the Stations(April-October, 1998)

101112

13

14

15

16

17

18

19

20

2122

September, 1998

Fig. 6: Comparisons of Equilibrium Evaporation
Derived from the GAME Reanalysis and Observations

300
W3

Observation

TMD

GAME Reanalysis

3.4. Water Balance Analyses with Distributed
Tank Model

Rainfall(mm/month)

250
200
150
100500AprMayJunJulAugSepOcta) Monthly Rainfall at W3 (April-November)
20W3Observation

GAME Reanalysis

TMDRainfall (mm/3hour)

151050Jul-1

Jul-2Jul-3Jul-4Jul-5b) 3-hour Rainfall at W3 (Jul.1-5th)
Fig. 5: Comparisons of Temporal Distributionof Different Data-sets in 1998

The Distributed Tank Model with spatial resolution of0.5 degree and temporal resolution of one day had beensuccessfully applied to the regional water balance
analyses for the continental scale hydrology (Nakane,2001). In this study the resolution was improved for thefirst time to 0.1 degree in space and one hour in time inthis hydrological model.
In the water balance analyses, the input potential
evaporation is based on the calculated equilibrium
evaporation from GAME reanalysis data. It has beenverified to be possible in the above. The calculated
discharges of different places in the basin are compared.
And the rainfall data from observations in thishydrometric network, GAME reanalysis dataset and theTMD observations are also evaluated with theDistributed Tank Model.
The observed and estimated discharges are shown inFig. 7. This figure shows that the estimated discharges,
both daily and monthly ones, agree well with theobserved. It confirms that the Distributed Tank Modelhas great ability to analyze the regional water balance.

10Station N22 (4,841km2)

Estimation

Observation

Runoff (mm/day)8
6
42

is much less from June to July and greater in September
than the observations in this hydrometric network. Itleads estimated discharge based on the GAME data to bemuch less than the observed in June and July. However,
the temporal distribution pattern of rainfall from theTMD dataset is roughly follows that from theobservations except June, and the estimated hydrographfrom the TMD observations is a little better than thatfrom the GAME data (Fig .8b).

0Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

4. Conclusions

Month, 1998a) Daily Discharge at N22 (4,841km2)
Areal Rainfall
Calculated Evapotranspiration
Observed Runoff

Water Equivalent, mm/month250

Input Potential Evaporation
Calculated Runoff

Station N22 (4,841km2)200
150100500JAN FEB MAR APR MAY JUNJUL AUG SEP OCT NOV DECMonth, 1998d) Monthly Discharge at N22 (4,841km2)

Fig. 7: Comparisons of estimated and observed
discharge in 1998
Observed

TMD

GAME Reanalysis

Rainfall(mm/month)

250
200
150
100500AprMayJunJulAugSepOcta) Monthly Areal Rainfall of the Whole Basin in 1998
6Observed
Estimated (TMD)
Estimated (GAME)

Run-off Rate, mm/day

542

Station N22 (4,841km )3210Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month, 1998b) Comparisons of Daily Discharge at N22Fig. 8: Evaluation of the Rainfall from theObservations, GAME Reanalysis and TMD
The areal rainfalls of the whole river basin calculated
from observations in this hydrometric network, GAME
reanalysis data and the TMD observation data are shownin Fig. 8a. It can be seen that the rainfall from GAME
reanalysis data in this area is away from the observed. It

Fourteen hydrometric stations were established in
Khuwae Noi River Basin (Thailand) and observational
studies at this river basin were developed from 1996. The
observations were compared with the data from GAME
reanalysis data-set and also those from TMD observation
data. The studies show that the evaporation data derived
from the GAME data-set are reliable, but the rainfall datafrom GAME data-set need to be improved in this area.
The studies also show that the TMD rainfall data can beinterpolated into grid data for regional water balance
analyses. The discharge of this basin was simulated byusing the Distributed Tank Model with temporal
resolution of one hour and spatial resolution of 0.1
degree. The results confirm that the Distributed Tank
Model is a suitable model for regional water balance
analyses.

Acknowledgements
The analyses in this study were supported by theproject of Prediction of Natural Disasters Caused byVariation in the Atmosphere-land-ocean Hydrological
Circulation of East Asia. The observation project in theKhuwae Noi River Basin had also been supported by theproject of GAME-Tropics organized by Prof. K. Musiake,
Institute of Industrial Science, University of Tokyo, ret.
The GAME reanalysis data were provided by GAME
reanalysis project conducted by Meteorological ResearchInstitute, Japan Meteorological Agency and EarthObservation
ResearchCenter/National
Space
Development Agency of Japan.

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