THA 2019 International Conference on“Water Management and Climate Change towards Asia’s Water-Energy-Food Nexus and SDGs”
23– 25 January 2019, Bangkok, Thailand.

Characteristics of River Discharge Simulation Using NHRCM 5km
Output by a Distributed Hydrologic Model in Thailand
AuliaFebianda Anwar Tinumbang1, Kazuaki Yorozu1, Yutaka Ichikawa1 and YasutoTachikawa1
Abstract A river discharge estimation using a detailed
projection of climate data and hydrologic model isimportant to make a basin-level assessment including
climate change impact. Recently, a result of a firstversion of NHRCM 5km-spatial resolution is available
for Thailand area, provided by JMA/MRI. The
objective of this research is to evaluate river discharge
simulated by using the NHRCM 5km output. Before
the river discharge simulation is performed, a 20years-mean NHRCM 5km rainfall was verified withAPRHODITE observation data. It was found thatNHRCM 5km rainfall was underestimated in the mostof Thailand region. However, some area in thenorthern region, which almost corresponds to
Bhumibol dam catchment, was overestimated,particularly in the rainy season. Hence, it showed abetter accuracy. After that, the river discharge wassimulated using NHRCM 5km output as forcing databy a coupled of a land surface model SiBUC and aflow routing model 1K-FRM. The simulated riverdischarge was evaluated with the observed inflow
data. The 20-years-mean monthly river discharge
showed an overestimated result during rainy season.
This is consistent with the rainfall analysis, but only
the total amount of rainfall could not explain thereason of overestimation. The analysis of heavy
rainfall day (more than 20 mm/day) showed a large
number of events during rainy season, which might be
the reason of overestimated river discharge.

Introduction

Keywords NHRCM 5km, distributed hydrologicmodel, river discharge

Methodology

The impact of global warming for the futurewater resources is attracting widespread interests forscientists, policymakers, engineers, etc. In order topredict the changes and impact of global warming,
particularly for regional level assessment, the output ofhigh-resolution global climate model (GCM) isgenerally used. In the recent years, many researchers
already developed regional climate model (RCM) witha fine grid-spacing. For example, Sasaki et al. [1]developed a Non-hydrostatic Regional Climate Model(NHRCM) with 5km spatial resolution. This model
performance was tested in Japan applying multiple
nesting method. The outer boundary was an output
from Atmospheric General Circulation Model 20km
and the inner boundary was created by NHRCM15km.
It showed the annual mean surface temperature andprecipitation had a good agreement with observed
data. This fine resolution model also had a better
reproducibility of the local features, such as it could
reproduce a heavy precipitation events which could
not be obtained from the results of GCM. In this study,
we utilized the output of NHRCM 5km which wasapplied for Thailand region and conducted a riverdischarge simulation by using a distributed hydrologicmodel. The objective of this research is to evaluate theNHRCM 5km output data from river discharge view
point.

A. NHRCM 5km output data
1

Department of Civil and Earth ResourcesEngineering
Graduate school of Engineering, Kyoto University
Kyoto, JapanThe Non-hydrostatic Regional Climate Model(NHRCM) with 5km spatial-resolution is developed inJapan Meteorological
Agency MeteorologicalResearch Institute by Sasaki et al. [1]. The outerboundary condition for NHRCM 5km for Thailand
region is obtained from the result of the NHRCM with25km spatial resolution nested within present climate
simulation using MRI-AGCM version 3.2H with grid
spacing of 60km [2]. The product of NHRCM 5km
consists of 20 years data for the current climate (1980– 1999) and future climate (2080 – 2099) under SRES
A1B. However, only the result of current climate data
is used in this study. For each year, the simulation
starts from April to May in the following year (in total
14 months). The first two months data are discarded
because it is assumed as model spin up simulation.

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THA 2019 International Conference on“Water Management and Climate Change towards Asia’s Water-Energy-Food Nexus and SDGs”
23– 25 January 2019, Bangkok, Thailand.

Fig. 1. 20-years-mean (1980 – 1999) annual rainfall (unit: mm) of (a) NHRCM 5km, (b) APHRODITE, and(c) bias (unit: %) of NHRCM 5km
rainfall relative to APHRODITE. Red color represents underestimated value of NHRCM 5km while blue color isoverestimated result.
B. Observed rainfall and inflow discharge dataand temporal resolution of 1-hour. 1K-FRM is utilizedwith 1-km spatial resolution and the output with 1hour temporal resolution. The runoff output fromSiBUC model is given to 1K-FRM to conduct a riverdischarge simulation. This model was tested for 2011
Thailand big flood and showed good performance forsimulating river discharge [7].

In this research, the observed rainfall datathat is used for evaluation of NHRCM 5km rainfall
output data is obtained from Asian Precipitation –Highly-Resolved Observation Data Integration
towards Evaluation of water resources(APHRODITE)[3] with 0.25q spatial-resolution. In addition, theobserved inflow data with daily records in Bhumibol
Dam is acquired from the Electricity Generating
Authority of Thailand (EGAT).

Result and Discussion
A. Characteristics of NHRCM 5km rainfall output
data

C. Distributed hydrologic model

The reproducibility of NHRCM 5km rainfall
for Thailand region was analyzed by comparing withAPHRODITE observation data. First, the NHRCM
5km rainfall was aggregated from the original
resolution to 0.25q resolution, which corresponds toAPHRODITE grid spacing.
The 20-years-meanannual rainfall was calculated for both NHRCM 5kmand APHRODITE data.
The calculated result of 20-years-meanannual rainfall of NHRCM 5km and APRHODITE areshown in Figure 1(a) and 1(b), respectively. The resultof NHRCM 5km rainfall shows that the amount ofrainfall in the central part of Thailand is lower thannorthern part, and the southern part of Thailand is thehighest. The APHRODITE observed rainfall also
shows the similar trend. Therefore, it can be said thatA distributed hydrologic model, which is a
coupled of land surface model SiBUC (Simple
Biosphere including Urban Canopy) and a flowrouting model 1K-FRM [4] is used for conducting ariver discharge simulation. SiBUC [5] is a land surface
model which implements a mosaic scheme that canconsider a mixture of land use, paddy field, andirrigation system in the model. 1K-FRM [6] is a
distributed flow routing model, developed based on
one-dimensional kinematic wave theory to conduct ariver discharge simulation. The forcing data used for
SiBUC model is obtained from NHRCM 5km output
rainfall, surface pressure, humidity, short-wave
radiation and long-wave radiation in downward
direction, wind speed, and air temperature. The SiBUC
model is used with a spatial resolution of 3 minutes
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THA 2019 International Conference on“Water Management and Climate Change towards Asia’s Water-Energy-Food Nexus and SDGs”
23– 25 January 2019, Bangkok, Thailand.

the NHRCM5km rainfall output could catch the spatial
distribution of the observed rainfall.

there is an overestimation result in some region in theupper part (shown in black circle) and in the easternpart of Thailand. The bias in these regions iscomparatively smaller than other regions. Based on
this result, the upper region in Thailand, which almostcorresponds to Bhumibol Dam catchment, wasselected for river discharge simulation.
Bhumibol Dam catchment is located in 98–99.5qE, 17–19.9qS. It is located in the upper part ofPing River Basin (Fig. 2), with the area is about
26,400 km2. The result of 20-years-mean basin
average rainfall for NHRCM 5km and APHRODITEin the upper part of Bhumibol Dam catchment isshown in Fig. 3. From this result, the total amount ofrainfall is overall underestimated and thatin June, July,and August (JJA) shows a better accuracy compared toother months. And then, the NHRCM 5km rainfall
produces the peak of rainy season on July, while theobserved peak rainy season is on September.
B. Characteristics of NHRCM 5km river discharge
To conduct a river discharge simulation, first,
the forcing data from the NHRCM 5km output wasaggregated from the original grid spacing into 0.05q(or3-minute resolution) grid size. Then, the forcing data
was given into SiBUC model to calculate the runoff.
After that, the river discharge was calculated by 1KFRM using the runoff output.

Fig. 2. Ping River Basin. Red circle shows Bhumibol
Dam location.

Fig. 4. Flow Duration Curve of 20-years-mean riverdischarge. Black dots show the observed inflow inBhumibol Dam and blue line shows the simulated
result using NHRCM 5km forcing data.

Fig. 3. 20-years-mean basin average rainfall in theBhumibol Dam catchment. Black color shows
APHRODITE rainfall and blue color shows NHRCM
5km rainfall.

The simulated river discharge is obtained fordaily discharge for 20-years period. The daily riverdischarge for a year is sorted from the highest to thelowest to draw a Flow Duration Curve (FDC). In total,
there are 20-FDCs for river discharge simulation
during 1980 – 1999. Then, 20-years-mean FDC was
calculated for both simulated river discharge and theobserved inflow in Bhumibol Dam. The result isshownin Fig. 4. The first quartile (95th day) represents a highflow discharge, 2nd quartile (185th day) is a normalflow discharge, 3rd quartile (275th day) is a low-flowdischarge, and 4th quartile is a drought-flow discharge.

However, the absolute value of NHRCM 5kmis mostly underestimated in all over the region. Thisresult is clearly shown from the calculation of 20years-mean bias in the Fig. 1(c). The bias of NHRCM
5km is calculated in (1),B  Rn-Ra) / Rawith B is bias, Rn is NHRCM 5km rainfall, and Ra is
APHRODITE rainfall. Although, it can be seen that51

THA 2019 International Conference on“Water Management and Climate Change towards Asia’s Water-Energy-Food Nexus and SDGs”
23– 25 January 2019, Bangkok, Thailand.

The high-flow discharge is about 15% overestimatedby NHRCM 5km, while the normal-flow, low-flow
and drought-flow, the simulated discharge is wellcompared with the observed data.

NHRCM 5km output might be one of the causes of theoverestimated river discharge of NHRCM 5km.
However, the hydrological model itself might also
have some influence on this overestimated result.
Therefore, the parameter settings or the model
structure itself should also be examined to see its
effect on the river discharge estimation.
Conclusions
In this research, the first version of NHRCM
5km output data was evaluated. Before the riverdischarge is simulated, the 20-years-mean NHRCM
5km rainfall was compared with APRHRODITE data,
as a reference data. The bias calculation shows thatmost of NHRCM 5km rainfall was underestimated inmost of Thailand region, except in Bhumibol damcatchment. The basin average rainfall for upper part of
Bhumibol Dam catchment showed a comparatively
smaller bias during JJA period compared to othermonths. While the river discharge simulation showed
an overestimated result particularly during JJA period.
The NHRCM 5km rainfall had more frequent eventsof heavy rainfall days (more than 20mm/day) whichmight be one of the causes to produce extreme
simulated flood discharge.

Fig. 5. 20-years-mean monthly river discharge. Blackcolor shows the observed inflow in Bhumibol Damand blue color shows the simulated result using
NHRCM 5km forcing data.

Acknowledgment
We would like to express our deep gratitude
for Dr. Patama who provided and simulated theNHRCM 5km data used in this research under
supervision of Dr. Hidetaka Sasaki from JMA/MRI.
This study has been supported by TOUGOU Program(Integrated Climate Model Advanced ResearchProgram) 2017-2021 Theme-C supported by MEXT.
ReferencesFig. 6. Number of heavy rainfall days (more than 20mm day-1) during 1980 - 1999. Black color shows
APHRODITE rainfall and blue color shows NHRCM
5km rainfall.

[1] H. Sasaki, A. Murata, M. Hanafusa, M. Oh’izumi,
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monthly river discharge of NHRCM 5km andobserved inflow. The peak discharge simulated fromNHRCM 5km was produced much earlier comparedto the observed inflow. This might be explained byearlier peak of the basin average of NHRCM 5km
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explain the reason of overestimated simulated riverdischarge.
The number of heavy rainfall days (more than20 mm day-1) during 1980 – 1999 is shown in Fig. 6.
In this result, the short-term heavy rainfall of NHRCM
5km shows a larger number of events compared to theobserved APHRODITE rainfall, particularly in JJA
period. From this result, it is thought that more
frequent short-term heavy rainfall events from52

THA 2019 International Conference on“Water Management and Climate Change towards Asia’s Water-Energy-Food Nexus and SDGs”
23– 25 January 2019, Bangkok, Thailand.

routing process,” Proc. IAHS, vol. 369, pp. 81-86,
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[5] K. Tanaka, “Development of the new land surface
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prediction model,” PhD thesis, Kyoto University,
Japan, 2005.
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http://hywr.kuciv.kyoto-u.ac.jp/products/1KDHM/1K-DHM. html, last access 2018/10/27.
[7] K. Yorozu, N. Kurosaki, Y. Ichikawa, S. Kim,and Y. Tachikawa, “Astudy on long-term riverdischarge
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I_127-I_132, 2018 (in Japanese).

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