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PRELIMINARY RESULTS OF RIVER FLOW SIMULATION FOR
INDOCHINA PENINSULA REGION UNDER CLIMATE CHANGE
Duc Toan Duong1, Yasuto Tachikawa2 and Michiharu Shiiba3
1,2,3

Graduate School of Engineering, Kyoto University, Japan

E-mail: 1 duong@hywr.kuciv.kyoto-u.ac.jp,

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

3

shiiba@hywr.kuciv.kyoto-u.ac.jp

A distributed flow routing model (1K-FRM) was used to project river discharge in Indochina
Peninsula region. Topographic data used for the flow routing model is 5-min spatial
resolution data which was processed from scale-free global stream-flow network dataset
developed by Masutani et al. (2006). Input data for the routing model is the generated runoff
data in the latest 20km general circulation model (GCM) dataset (MRI-AGCM3.2S), which
has been developed by Meteorological Research Institute, Japan Meteorology Agency, forthe present climate (1979-2008), the near future climate (2015 - 2044), and the future climate(2075-2104). The simulated river discharge for the present climate, the near future climate,and future climate experiment was compared to see the changes of flow in Indochina
Peninsula region under climate change.

Keywords: river discharge projection; scale-free stream-flow network; hydrologicalmodeling

Introduction
Global warming has been having serious impacts on the Earth and its residents.
Many studies have shown that even if the emission of greenhouse gases is reduced
drastically, climate change will be irreversible in coming centuries. Frequencies andmagnitudes of water-related disasters such as floods, droughts and water scarcity arepredicted to increase due to changes of precipitation extremes.
To cope with water-related disasters induced by global warming mentioned
above, projection of river discharge is necessary. In this regards, hydrological andflow routing models play an important role in transferring the climate model outputs
into river discharge. Many researchers analyzed changes in future risks of floods anddroughts using different scale and spatial resolution hydrological models: global scalewith 1-degree spatial resolution runoff model (Hirabayashi et al., 2008); regional scalewith 2-minute spatial resolution hydrological model (Kiem et al., 2008); and basin
scale with 1-km spatial resolution runoff model (Hunukumbura et al., 2012).
In this study, a distributed flow routing model (1K-FRM) with kinematic wave

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flow approximation was applied for river discharge projection in Indochina Peninsula
region under climate change. The original version of 1K-FRM was based on 1km
spatial resolution topographic data extracted from USGS HydroSHEDS. With thathigh resolution, the requirement for computational resources is also high, and it takes
a long computational time. For a balance of spatial resolution, computational
resources, and application of hydrological models, 1K-FRM has been developed touse with scale-free stream-flow network dataset which was provided by Masutani etal. (2006).
In the second part, the processing of scale-free topographic data for 1K-FRM isintroduced. The description of distributed flow routing model and future climate
projection data generated by MRI-AGCM3.2S is shown in part 3 and part 4. In part 5,
the changes of simulated river discharge for the near future climate to the present
climate and the future climate to the present climate are discussed. And then, someconclusions will be given in the last part of this paper.
Topographic data processing
For hydrological models which are grid based, topographic parameters (elevation,river length, flow direction, etc.) and simulation processes are determined at every gridcell. So, the data volume and computational resources are proportional to the numberof grid cells which themselves increase quadratically for each doubling of thehorizontal spatial resolution. As a result, finer spatial resolution grids require higher
computational resources and longer computational time.
Therefore, to ensure the balance of spatial resolution, computational resources,and application of hydrological models, several algorithms for generating stream-flow
networks for macro-scale hydrological models have been presented. Masutani et al.
(2006) developed a scale-free global stream-flow network creation method as the basisof basin-wide hydrologic analyses for any integrated river basins. The most important
advantage of this method is to conserve fundamental hydraulic information based on
the finest-resolution stream-flow channel network, on any spatial scale. They provided
a dataset of stream-flow networks with 11 different scales from high resolution (3s ≈90 meters, 6s, 9s, 12s, 15s), medium resolution (30s, 1 min, 2 min, 3 min), to lowresolution (5 min, 10 min ≈ 20 km). And it enables hydrological models independentof spatial resolution.
However, the dataset consists of topographic data of individual river basins. To
run a hydrological model with study area covering many river basins, it is needed tojoin those individual topographic data into a large topographic map that suits the study
area. Hence, required physiographic information for hydrological models such as
catchment area, river length, elevation, slope, and flow direction will be processed andID:329

joined into a large topographic map.
One of the most important things that need to be considered to join individual
river basins data into a large topographic map is how to process the data of overlapped
grid cells at the boundary of those river basins. The proposed solution to process
topographic data of overlapped gridded cells at the boundary of joined river basin is tokeep the topographic information of grid cells that have larger area. Overlapped gridcells with smaller area will be removed but cell area will be added into the neighbour
cells following its flow direction. This will keep catchments area unchanged when
they are joined into a large topographic map. Flow direction of grid cells that flow into
removed cells will be changed to neighbour cells in the same basin. Figure 1 shows anexample of joining flow direction data.

(a)

(b)

Figure 1: An example of flow direction data before (a) and after joining (b)(Arrows: flow direction; gray cells: overlapped cells; bold lines: basin divides)
Flow routing model
Watershed model
The topography of the catchment is modelled using the 8-direction method
which assumes the flow direction one-dimensionally to the steepest gradient direction.
Each slope element determined by the flow direction is represented by a rectangle
formed by the two adjacent nodes of grid cells. The watershed model is developed
using Digital Elevation Models (DEM). Catchment topography is represented by a setof slope units. For each slope unit, its area, length and gradient used for a flow modelare easily calculated. Schematic drawing of a watershed model using the eightID:329

direction method and an example of flow direction information derived from agrid-based DEM are shown in Figure 2.

(b)(a)

Figure 2: Schematic drawing of a watershed model using the 8-direction method(a) and an example of flow direction information derived from DEM (b)Topographic data used in this study is the 5-min spatial resolution DEM processedfrom scale-free stream-flow network dataset which was provided by Masutani et al.
(2006).
Flow modelA kinematic wave model is applied to all slope units and runoff is routed according tothe flow direction information. The basic form of the kinematic wave flow equation is:∂A ∂Q+= q L ( x, t )∂t ∂xi0 ⎛ 1 ⎞Q = αA , α =⎜ ⎟n ⎝ B⎠m(1)m−1, m=53(2)

where, A(x, t) is the flow cross-sectional area, Q(x, t) is the flow discharge, qL(x, t) is
the lateral inflow per unit length, i0 is the slope, n is the Manning roughness coefficient,and B is the width of the flow. Equation (1) is the continuity equation and is derived
from the principle of mass conservation within a control volume. Equation (2) isderived from Manning's or Chezy's laws which are flow resistance laws of open
channel uniform flow.
GCM data used for river flow projection
River discharge projection used data provided by the latest GCM (MRI-AGCM3.2S)
with resolution of about 20km which has been developed by Meteorological ResearchInstitute, Japan Meteorology Agency. River discharge was calculated using flowrouting model 1K-FRM with input data is GCM daily runoff generation data whichID:329

was projected by MRI-AGCM3.2S.
Results and Discussion
Simulations for Indochina Peninsula region was carried out to investigate thechanges of river discharge under climate change with 30 years simulated time for eachclimate experiment: the present climate experiment (1979-2008), the near futureclimate experiment (2015-2044), and the future climate experiment (2075-2104). Thestudy area cover five big river catchments including Mekong River basin; Irrawaddy
River basin and Salween River basin in Myanmar; Chao Phraya River basin inThailand; and Red River basin in Vietnam (see Figure 3).

Figure 3: Map of the study area, Indochina Peninsula region
The annual average discharge, mean of annual maximum discharge and mean ofannual minimum discharge for each climate experiment were calculated. Then, theratio of discharge values mentioned above for the near future climate to the present
climate and the future climate to the present climate were calculated for comparison tosee the changes of river discharge between the present climate, near future climate andfuture climate.
Comparison of annual average discharge in 30 years between the near futureclimate and the present climate, the future climate and the present climate
Ratio of annual mean discharge for the near future climate to the present climate,
and the future climate to the present climate is shown in Figure 4.

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The changes of annual average discharge between near future climate and the present
climate showed a slightly increasing of average flow with the ratio smaller than 1.5 at
the most upper part of Mekong River basin, Salween River basin and Irrawaddy Riverbasin; from central to lower part of Irrawaddy River basin; western part of Vietnam.
Only eastern part of Chao Phraya River basin shows a trend of decreasing in river flow
with the ratio is between 0.5 and 0.9.

(a)

(b)

Figure 4: Ratio of annual mean discharge for the near future climate to thepresent climate (a), and the future climate to the present climate (b)A same trend with higher intensity can be seen in the figure that shows thecomparison of the future climate and the present climate. We can see that the changes
in area and ratio range become larger, especially at the lower part of Irrawaddy andeastern part of Chao Phraya.
Comparison of mean of annual maximum discharge in 30 years between the near
future climate and the present climate, the future climate and the present climate
In Figure 5, the ratio of mean of annual maximum discharge for the near futureclimate to the present climate was compared with those for the future climate to thepresent climate. For the near future climate, the mean of annual maximum discharge
has significant changes at upper part of Red River basin and lower part of Salween
River basin. It becomes more visible in the future climate experiment. Irrawaddy Riverbasin showed a noticeable increasing of mean of annual maximum discharge in thefuture climate experiment. The ratio at some areas are larger than 2.5. It means the riskof flooding at those areas will increase.

ID:329(a)(b)

Figure 5: Ratio of mean of annual maximum discharge for the near futureclimate to the present climate (a), and the future climate to the present climate (b)Comparison of mean of annual minimum discharge in 30 years between the near
future climate and the present climate, the future climate and the present climate
Figure 6 shows the ratio of mean of annual minimum discharge for the near futureclimate to the present climate, and the future climate to the present climate.

(a)

(b)

Figure 6: Ratio of mean of annual minimum discharge for the near future climate
to the present climate (a), and the future climate to the present climate (b)From Figure 6, it can be seen that there is a decreasing trend in the southeast partof Indochina Peninsula, especially the southern part of Vietnam. And this trend
became more clearly in the future climate experiment. Then, drought risk can beID:329

expected to increase in Indochina Peninsula region in the future.
Conclusion
In this paper, the processing of scale-free topographic data was presented. A
dataset of scale-free stream-flow network dataset for Indochina Peninsula with 5-min
spatial resolution was processed and used for flow routing model 1K-FRM.
The changes of river discharge in Indochina Peninsula region for 3 climate
experiments (present, near future, and future) were also analyzed. The input data wastaken from the latest 20km resolution GCM dataset (MRI-AGCM3.2S). The changes
in the risk of flood and drought in the region can be seen.
Acknowledgement
We acknowledge Dr. Jun Magome (Department of Civil and Environmental
Engineering, University of Yamanashi) for providing free-scale global stream-flow
networks datasets.
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