ABSTRACT Flood simulation at basin scale can be enhanced by combining Satellite-Based Precipitation (SBP) with ground rain gauge measurements. The present study attempts to show feasible approaches in terms of time, space and pattern at selected basins in South East Asia. As for temporal downscaling it was possible to detect flood timing and magnitude with high temporal resolution at poorly gauged basins. This approach was tested at the upper part of the Huong in Vietnam and Ping River basins in Thailand respectively. Both catchments are located in steep, humid, and vegetated areas. Two SBPs were employed: the Global Satellite Mapping of Precipitation (GSMaP) MVK version and the Tropical Rainfall Measuring Mission (TRMM) 3B42 Ver. 6product. The results indicate that SBPs products tend to underestimate precipitation intensities, but they seem able to depict the spatial and temporal patterns. The evaluated SBPs at basin scale were found useful and river discharge simulation was enhanced with corrected SBPs. This approach might be applied at other basins not only in Asia region

Kazuki Tanuma

Masahiro Ryo

Oliver C Saavedra Valeriano

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Seventeenth International Water Technology Conference, IWTC17                        Istanbul, 5-7 November 2013  
   
 
 
GROUND VALIDATION OF SATELLITE-BASED PRECIPITATION FOR 
FLOOD SIMULATION IN SOUTH-EAST ASIAN RIVER BASINS 
 
 
Oliver C. Saavedra Valeriano
1
, Masahiro Ryo
2
, and Kazuki Tanuma
 3
 
 
1 
Associate professor, Department of Civil Engineering, Tokyo Institute of Technology,  
E-mail: saavedra.o.aa@m.titech.ac.jp    
2
 Graduate student, Department of Civil Engineering, Tokyo Institute of Technology,  
E-mail: ryo.m.aa@m.titech.ac.jp 
3
 Graduate student, Department of Civil Engineering, Tokyo Institute of Technology,  
E-mail: tanuma.k.aa@m.titech.ac.jp  
 
ABSTRACT 
Flood simulation at basin scale can be enhanced by combining Satellite-Based Precipitation 
(SBP) with ground rain gauge measurements. The present study attempts to show feasible approaches 
in terms of time, space and pattern at selected basins in South East Asia. As for temporal downscaling 
it was possible to detect flood timing and magnitude with high temporal resolution at poorly gauged 
basins. This approach was tested at the upper part of the Huong in Vietnam and Ping River basins in 
Thailand respectively. Both catchments are located in steep, humid, and vegetated areas. Two SBPs 
were employed: the Global Satellite Mapping of Precipitation (GSMaP) MVK version and the 
Tropical Rainfall Measuring Mission (TRMM) 3B42 Ver. 6product. The results indicate that SBPs 
products tend to underestimate precipitation intensities, but they seem able to depict the spatial and 
temporal patterns. The evaluated SBPs at basin scale were found useful and river discharge simulation 
was enhanced with corrected SBPs. This approach might be applied at other basins not only in Asia 
region. 
 
Keywords: ground validation, flood simulation, satellite based precipitation, distributed hydrological 
model 
1 INTRODUCTION 
The water assessment based on hydro-meteorological observations plays a key role not only in 
water resources management, but also in flood damage protection of the society. However, rain gauge 
networks might be sparse in developing countries due to maintenance costs and accessibility. On the 
other hand, as remote sensors installed at satellites can cover large areas over the globe continuously, 
the exploitation of these products in those countries has shown high potential. For example, in poorly 
gauged regions like in Thailand and the Amazon, the availability of a global data set was assessed by 
using error evaluations (Chokngamwong and Chiu, 2008; Su et al., 2007). Nowadays, there is an 
attempt to improve SBP, namely Tropical Rainfall Measuring Mission (TRMM) measurements with 
statistical evaluation in South America (Vila et al., 2009). However, this product is monthly calibrated 
using global hydrology network (e.g. long term variability of rainfall); therefore, it doesn’t have 
enough capability to accurately specify local flood events with short duration (Huffman, 2007). The 
possibility to quantify the biases or tendency at regional and local scales is still under investigation. 
The biases might be associated to the type of rainfall events within the basin and surroundings. The 
correction factor considering the biases could be applied to SBP and increase local precipitation 
measurements’ accuracy. For example, in Bangladesh, the correction factors were extrapolated over 
regions with no in-situ data (Saavedra et al., 2010) 
This study aims to investigate the applicability of Satellite Based Precipitation (SBP) in 
combination with local rain gauge network to improve the spatial and temporal resolution of 
measurements in Asian River basins. The process can be carried out in three steps: 1) evaluation of 
Seventeenth International Water Technology Conference, IWTC17                        Istanbul, 5-7 November 2013  
   
 
 
SBP products in regions with few gauges by scale difference; 2) validation of SBP correction method; 
3) application of corrected products as input for hydrological model. The improved measurement 
product may allow us to detect the precipitation pattern and to quantify the risk of flooding. 
2 STUDY AREA 
  Due to the diversity in geomorphology, ecological steps, and dominant weather, we would propose 
two test basins: Chao Phraya (Thailand) and Ping (Vietnam) in Asia region. Application of satellite-
based precipitation in combination with rain gauge measurements to simulate hydrological processes 
is proposed.  
Ping River: 
This catchment is located in upper Chao Phraya basin, Thailand (Fig.1). The basin encompasses 
26,200 km
2 
and rainy season extends from May to October. The TRMM products were employed with 
promising results following Tanuma et al (2012). A higher variability of precipitation in the basin in 
the future has been identified based on TRMM analysis (Ogata et al. 2012).  
Huong River: 
Huong River basin in the central Vietnam was chosen (Fig. 1). The basin area is 1,513 km
2
. The 
flood control point called Kim Long is set as the outlet of the basin. The Huong River experiences an 
average of 3.5 floods per year with threat water level. Each flood season begins normally in October. 
The area is dominantly composed by evergreen forest and shrub. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 1. Location of test River basins in South-East Asia region 
 
Target 
domain 
 
 
Huong River in Vietnam 
Ping River in Thailand 
Seventeenth International Water Technology Conference, IWTC17                        Istanbul, 5-7 November 2013  
   
 
 
3 METHODS 
In order to measure precipitation intensities at land surface, data from available local rain gauge 
network systems were used. In this study, TRMM product was launched by the National Aeronautics 
and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) in 1997 
provides 3 hourly rainfall data in tropical areas with quasi-global coverage. The spatial resolution is 
0.25 degrees. Additionally, the Global Satellite Mapping of Precipitation version MVK 
(GSMaP_MVK) was used. This product delivers hourly precipitation data. The different sensor-
algorithms are merged to retrieve intensities: passive microwave radiometers of TRMM/TMI, 
Aqua/AMSR-E, ADEOS-II/AMSR, DMSP/SSMI; and infrared brightness temperature provided by 
NCEP/CPC. The version MVK is re-analyzed with bias retrieval from the near real-time product. The 
spatial resolution is 0.1 degrees. 
 
Once the rain gauge and SBP precipitation data was prepared, river discharge simulation was 
obtained using a Distributed Hydrological Model (DHM).  The DHM employed in this study was  
physically-based semi-distributed hydrological model set-up at each test basin. The model takes into 
account for the spatially distributed hydrological process in the basin and the routing of water in the 
streamline. Geomorphology-based hydrological model (GBHM) developed by Yang (1998) was 
chosen because of its high applicability to a steep mountainous area (e.g. Yang 2002). See Fig. 2. The 
GBHM compounded from two modules to solve the continuity: energy and momentum equations. 
Firstly, a hillslope module calculates entire water budgets including canopy interception, 
evapotranspiration, infiltration, surface flow and exchanges of water between ground and surface. The 
module simulates surface runoff and subsurface flow drift into the main river channel. Water flow 
under the ground divided by several layers is governed by the Richards equation on the unsaturated 
condition. Otherwise, Darcy’s law is applied to the saturated zone. Secondly, the water routing of the 
river is determined by solving one-dimensional kinematic wave equations. The simulation sequence is 
performed at each sub-basin and then water is gathered to the outlet along the direction of the 
streamline.  
 
Then, it was possible to apply of corrected products as input for hydrological model following 
Tanuma et al (2012). The improved measurement product may allow us to detect the precipitation 
pattern and to quantify the risk of flooding. 
 
 
 
Figure 2. The concept of hillslope based hydrological model 
 
Seventeenth International Water Technology Conference, IWTC17                        Istanbul, 5-7 November 2013  
   
 
 
4 RESULTS AND DISCUSSIONS 
Flood simulation by using DHM was performed with both satellite based precipitation products: 
GSMaP_MVK and TRMM at the two river basins. The precipitation with MVK was first compared 
against rain gauge at Huong river during monsoon season (Sept-Nov) in 2006-2009 as seen in Fig. 3. 
It can be noticed that at lower intensities better agreement can be expected. Opposite, at higher 
intensities the estimations might be scattered. 
 
 
 
 
 
 
 
 
 
 
 
Figure 3. GSMaP performance at Huong River basin, Vietnam 
 
Then, simulation of stream flow was possible by forcing the hydrological model as seen in Fig. 4 
where results using GSMaP_MVK are able to represent the pattern of flood peaks. However, the 
magnitudes of peaks show underestimations not only for 2008 as in Fig. 4.  
 
 
 
Figure 4. Underestimation of river discharge simulation using GSMaP_MVK (in continuous black) at 
Huong River basin, Vietnam. Dashed line shows the observations. 
 
 
 
Daily acc Gradient: 0.36 
MVK underestimates but seems 
to capture the timing of prec. peak 
 
Seventeenth International Water Technology Conference, IWTC17                        Istanbul, 5-7 November 2013  
   
 
 
Similar procedure was applied for 2006, 2007 and 2009. Then, results are summarized suing simple 
bias, RMSE and NSE as in Table 1 where the pattern of 2008 can also be noticed. 
Table 1.  Three efficiency criterions using GSMaP_MVK at Huong River, Vietnam 
 
On the other hand, at river discharge simulation at Ping River was obtained by comparing the raw 
TRMM and the corrected one. Actually, the correction factors were developed for 2008 and 2009 and 
then validated for 2010 as seen in Fig. 5. The comparison of simulated total volumes indicates that 
corrected TRMM can improve the result. This result indicates the possibility to adjust correcting 
factors of TRMM by using information from the past years for actual flood management. 
 
Figure 5. Enhanced inflow to Bhumipol dam using corrected TRMM at Ping River basin, Thailand 
 
CONCLUSIONS  
In this study two popular satellite based precipitation products called TRMM and GSMaP_MVK 
were used at Ping and Huong Asian rivers respectively. The results indicate that SBPs products tend to 
underestimate precipitation intensities, but they seem able to depict the spatial and temporal patterns. 
The evaluated SBPs at basin scale were found useful and river discharge simulation was enhanced 
with corrected SBPs. This approach might be applied at other basins not only in Asia region. 
 
ACKNOWLEDGMENTS  
The authors appreciate the financial support from 7th Research Announcement (RA) Precipitation 
Measuring Mission (PMM) from Japan Aerospace Exploration Agency (JAXA) and Japan Society of 
Science Promotion (JSPS) Asian core program. We also appreciate data collection support from our 
colleagues at Dpt. of Env Eng, Faculty of Engineering, Kasetsart University in Thailand and the 
Seventeenth International Water Technology Conference, IWTC17                        Istanbul, 5-7 November 2013  
   
 
 
National hydro-meteorological forcasting institute of Vietnam for guiding us in the field and sharing 
the observation data. 
 
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[1]. Chokngamwong R. and L.S. Chiu, (2008) Thailand Daily Rainfall and Comparison with 
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[2]. Huffman, G.J., D.T. Bolvin, E.J. Nelkin, D.B. Wolff, R.F. Adler, G. Gu, Y. Hong, K.P. 
Bowman, E.F. Stocker (2007) “The TRMM Multisatellite Precipitation Analysis: quasi-
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[3]. Ogata, T., Saavedra, O.C., Yoshimura, C., Liengcharernsit, W., Hirabayashi, Y.(2012) Past 
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[8]. Vila, D.A. , L.G. G. De Gongcalves, D.L. Toll and J.R. Rozante, (2009) Statistical Evaluation 
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GROUND VALIDATION OF SATELLITE-BASED PRECIPITATION FOR FLOOD SIMULATION IN SOUTH-EAST ASIAN RIVER BASINS

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GROUND VALIDATION OF SATELLITE-BASED PRECIPITATION FOR FLOOD SIMULATION IN SOUTH-EAST ASIAN RIVER BASINS

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