ID:330

THAILAND FLOOD 2011 AND
DEVELOPING OF FLOOD PREDICTION TOOL
Supattana Wichakul1 And Yasuto Tachikawa2
1,2Hydrology and Water Resources Research Laboratory, Department of Civil and Earth Resources

Engineering, Kyoto University, Japan
E-mail: 1 supattana@hywr.kuciv.kyoto-u.ac.jp,

2tachikawa@hywr.kuciv.kyoto-u.ac.jp

The Chao Phraya River basin, the heart of Thailand, is the center of rice production andeconomic center. Due to the worst flood occurring in the basin on last year, there are many
losses in term of human loss, social loss, and economic loss. Therefore, the flood 2011 is not
only effected to local people but also all Thai people. This study is to analyses a main result ofthe flood and to develop a tool (distributed hydrological model) that can reproduce thephenomena of flood in year 2011 based on a concept of infiltration variable capacity andkinematic wave model; and the tool will be used for flood prediction in the future

Keywords: Thailand Flood 2011, Flood Prediction, Chao Phraya River Basin

Introduction
Due to the worst flood occurred in Thailand from July 2011 until the end of year
2011, this study concentrates on studying of the flood and develop the tool for looking
forward to the future under the condition of climate change whether the huge floodwill occur.
The Chao Phraya River originates in the north region of Thailand and flow
direction is from north to south. There are two parts of the Chao Phraya River basin,
upper and lower part with an area of 157,925 km2. The upper part of the basin consistsof four main sub-basins, Ping River, Wang River, Yom River and Nan River basin.
The confluence of Ping and Nan River at Nakorn Sawan province in the central ofThailand is the beginning of the Chao Phraya River. For the purposes of irrigation andpower generation, the Bhumibol Dam was built in 1964 on the Ping River with thereservoir capacity of 13.5 MCM, and the Sirikit Dam was built in 1974 on the Nan
River with the reservoir capacity of 9.5 MCM.
This study is to analyses a main result of the flood and to develop a distributedhydrological model based on a concept of infiltration variable capacity to reproduce
the flood 2011.

ID:330

Figure 1: Diagram of The Chao Phraya River basin of Thailand
Methodology
Rainfall analysis
The rainfall data of 26 stations over the Chao Phraya River basin were obtained
for analysing an origin of the amount of the runoff, which is the cause of inundation in
the Lower Chao Phraya River basin in 2011. Rainfall data analysis was conducted byconsidering the accumulated rainfall data of year 2011 with the accumulated average
rainfall of year 1980 - 2009 (30 years) and year 2010. The 2-Dimesions rainfall dataover the area of latitude 98E-103E and longitude 13N-20N was created to be the inputof the hydrologic model.
Developing of Distributed Hydrological modelFrom the above process, it can be summarized that whether the flood situation in
the lower of Chao Phraya basin mainly depends on a volume of the runoff generated
by the precipitation in the upper part of the Chao Phraya basin. The distributedhydrological model consists of a hydrologic model and a flow routing model, whichID:330

will be explained in more detail as follows.
- Hydrologic Model
A simple water balance model for the catchment, which was developed by
Nirupama et al. (1996) using the concept of the Variable Infiltration Capacity(VIC) Model, is utilized in this study. Originally, the VIC model is thesimplification of the concept of Xinanjiang (XNJ) Model developed by Zhao et al.
(1980). Main feature of the XNJ model is the concept of runoff formation on
repletion of storage, which means that runoff is not produced until the soil
moisture content of the aeration zone reaches field capacity. The concept ofinfiltration variable capacity with respect to the soil tension water capacity(STWC) and the portion of pervious and impervious areas are introduced in aparticular grid for the surface runoff generation. Quantitatively, the model definesthat infiltration capacity as:

where A = the fraction of the pervious area; AI = the fraction of theimpervious area; b = the empirical parameter that represents the shape of theSTWC curve, and im = maximum infiltration capacity. The runoff will not be
produced until soil moisture content of the aeration zone reaches the field capacity
which follows the equation (1). And some part of the generated runoff by theSTWC will infiltrate the deep aquifer system and go to the sub-surface.
The base flow (sub-surface flow) is estimated by a simple tank model.
Hereafter, we would call the model we have developed that “the simplifiedXinanjiang Model” (SXNJ Model). The output of the SXNJ model will be runoff
at the particular grid with unit of millimetre per hr. This output will be input to theflow routing model.
-Flow Routing Model
Initially, Tachikawa Y. et al (2010) initiated and developed the flow routing
model, 1 km distributer flow routiing model (1K-FRM), based on combination of
the watershed model and the flow model. The spatial resolution 3 arc-second(about 100 m) of a digital elevation model (DEM) was used in the watershed
model. The flow direction was developed follow the 8-direction method. The
kinematic wave model was also applied for the watershed model to rout the water
through the river according to the flow direction information.

ID:330

Since, Flow of Chao Phraya River Basin is significantly influenced by theoperations of those two main dams in the Ping River basin and Nan River Basin.
Consequently, this study also considers and includes the effect of those reservoirs
in the 1K-FRM model.
The 1K-FRM, a product of Hydrology and Water Resources ResearchLaboratoryofKyoto
University,canbedownloadedthrough(http://hywr.kuciv.kyoto-u.ac.jp/products/1K-DHM/1K-DHM.html).
Identification of Model Parameters
For the model calibration, rainfall data, observed discharge, evapotranspiration,and inflow of the Bhumibol dam and the Sirikit dam were obtained in year 2011.
There three monitoring points for comparing the observed discharge with thesimulated one are at C.2 station, at upstream of the Bhumibol and Sirikit dams. At thisstage the parameter is defined by using the trial-error method and Nash-Sutcliffe
efficiency (NSE), Root Mean Square Error (RMSE), and Coefficient of Determination(R2) are used to indicate the model performance.
Result and discussion
Rainfall Analysis
The results of the rainfall data analysis are shown in Figure 2. The amount of
rainfall of year 2011 in the northern sub-basins is significantly higher than those of theaveraged 30 years (1980-2009), and year 2010 approximately 36% and 32%,
respectively. Whereas, the amount of rainfall of year 2011 in the Lower Chao Phraya
River basin is slightly higher than the average 30 years and year 2010 only 2% and
24% by order.
This rainfall data analysis proves that flood 2011 in Thailand is mainly caused by
the runoff from the upper part of the Chao Phraya River basin. Therefore, our study
area focuses on the runoff occurring in the upper part of the Chao Phraya River Basin,
where the outlet is at Nakorn Sawan, C.2 Station. The big amount of rainfall about
1,700-1,900 millimetres was occurred in the Yom and Nana basins.
Developing of Distributed Hydrological model
The SXNJ model was simplified to reproduce the flood 2011. The model
parameters that is used in the model are as listed in the Table 1. During identifying themodel parameters, we found that only a set of parameter could not reproduce thehydrological phenomena of the entire Chao Phraya River basin. Hence, three sets ofparameters were in proposed in the model.

ID:330(A)

(B)

(C)

(D)

(E)

Figure 2: Accumulated rainfall of the averaged 30 yrs. (1980-2009), 2010 and2011 in mm. for Ping River Basin (A), Wang River Basin (B), Yom River
Basin (C), Nan River Basin (D), Lower Chao Phraya River Basin (E)ID:330

Table 1: The SXNJ model’s parameters
Parameter Definition

Normalgrids

Lower Yom+Nan
River Basin

Ping+Wang
River BasinAI

Fraction ofimpervious area

0.35

00.30

Wm

a max. tension water
storage (mm)

350

1500

400

b

an empiricalparameter

1.5

0.2

1.5

ks

a sub-surface coeff.
(hr)

150

400

200kg

a Groundwater coeff.
(hr)

1500

401500Ps

an empiricalsub-surface parameter

0.6

0.6

0.5

pg

an empiricalgroundwaterparameter

0.6

0.6

0.6

Afterward, 1K-FRM was implemented to rout and generate the river dischargeduring year 2011 in the Chao Phraya River The overall model performances at thefocused points are shown in Table 2. Discharge at C.2 station as shown in the Figure 2.
The volume of the simulated hydrograph is 1.55% higher than the observedhydrograph.
Table 2: The model performance
Calibration
PeriodStatistical criterion

2011

NSE
3Location
Bhumibol Dam

Sirikit Dam

C.2

0.62

0.71

0.87

310.61

265.16498.53

0.63

0.75

0.87

RMSE (m /s)
2RID:330

Figure 2: Comparison of Simulated and Observed Daily Discharge at C.2 StationConclusionOne of the important reasons of flooding in the lower Chao Phraya River basin in2011 is a huge amount of runoff generated by the rainfall occurring in the northernpart of the Chao Phraya River basin. At this stage, the tool, a distributed hydrologicalmodel, for flood prediction is developed and calibrated, but it is not completelyverified and optimized. Finally we expect to acquire the best tool that will be usefulfor prediction the future flood situation including the impact of climate change in theChao Phraya River basin of Thailand.
Acknowledgement
We greatly thank you to the Royal Irrigation Department of Thailand to provide
the relevant data, the rainfall data and Observed discharge.
References
Nirupama, Tachikawa, Y., Shiiba, M., and Takasao, T. (1996) A Simple Water
Balance Model for a Mesoscale Catchment Based on Heterogeneous Soil Water
Storage Capacity, Bull. Disas. Prev. Res. Inst., Kyoto Univ., vol. 45, Part 2, 3 No.
391, 61-83

ID:330

Tachikawa, Y., Hunnukumbura, P. B., Yorozu, K., and Apipattanavus, S. (2010)
Projection of River Discharge in Thailand under Climate Change and its Impact
on Water Resources, Proc. of 2010 AIT-KU Joint Symposium on Human
SecurityEngineering, Bangkok, Thailand, November 25-26, 102-108
Zhao, R. J., Zhuang, Y. L., Fang, L. R., Liu, X. R. and Zhang, Q. S. (1980) The
Xinanjiang model, Hydrological Forecasting Proc., Oxford Symposium,
International Association of Hydrological Sciences (IAHS), 129, 351-356.