Techno-Science Research Journal 9(1) (2021) 33-40
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Techno-Science Research Journal
Journal Homepage: www.ric.itc.edu.kh

Urban Flood Modeling in Phnom Penh Using Flo-2D: Consideration of Climate Change EffectSokchhay Heng1, Kimleng Kheav1, Panha Hok1*, Kong Chhuon1, Sarann Ly1, Tsuyoshi Kinouchi2
1

Faculty of Hydrology and Water Resources Engineering, Institute of Technology of Cambodia, Russian Federation Blvd.,
P.O. Box 86, Phnom Penh, Cambodia
2
Department of Transdisciplinary Science and Engineering, Tokyo Institute of Technology, 226-8502 Yokohama-shi Midori-ku
Nagatsuta-cho4259, Japan
Received: 26 October 2020; Accepted: 01 March 2021; Available online: xxxx
Abstract: Phnom Penh, the Capital City of Cambodia, frequently gets flooded when there is heavy precipitation. To this concern, warming
temperature and changing precipitation patterns may intensify the situation. This study aimed at (1) assessing the applicability of the urban
inundation model of Flo-2D and (2) forecasting inundation characteristics in the downtown area of Phnom Penh under climate change
scenario. The selected study area of 12.50 km2 is an independent catchment frequently affected by precipitation-flood events. Also, baseline(2010) and near future (2030s) extreme precipitation events were taken as a case study. The overall model performance was evaluated basedon the JICA survey study and flood photo analysis. The result showed that Flo-2D model is applicable in modeling the complex storm
drainage in this particular area. Based on the ECHAM4 model under SRES A2, the inundation area will be expanded, and the inundation
depth is also expected to increase between 0.20 m and 0.50 m in the near future. This study will provide fruitful information on inundation
conditions in the Phnom Penh city, especially most prone and affected areas under future extreme precipitation to local people, researchers,
and policymakers to formulate any structural and non-structural adaptation options to overcome the current and future challenges.
Keywords: Climate change; Flo-2D; Phnom Penh; urban flood
1.

INTRODUCTION 1

the floodplain areas (Barredo, 2009; Barredo et al., 2012;
Bouwer et al., 2010; Doyle, 2012; Geoffrey, 2009; Jongman
et al., 2012; Jonkman et al., 2008; Kreft, 2011; Kundzewicz
and Takeuchi, 1999; UN and ISDR, 2007; UN and ISDR,
2011). According to Geoffrey (2009), the Greater Mekong is
one of the most vulnerable regions in the world to the impact
of climate change. Doyle (2012) also reported that
Cambodia, particularly Phnom Penh city, will besignificantly susceptible to the change in precipitation
patterns and warmer temperature. Likewise, a recent
mapping assessment identified Cambodia as being
particularly vulnerable to climate change because of climate
impacts such as droughts, floods, and sea-level rise due tothe country’s relatively low adaptive capacity (Christensen,
2013). Notably, aspects of Phnom Penh’s existing
infrastructure much of which are aged and damaged due tothe neglect during the war, struggles to keep up with thisdevelopment, and rapid population growth.
In recent year, heavy sewer flooding and waterlogging
hazards have occurred frequently because of the intensive
precipitation, low flood flow capability of urban drainage
systems, and a large proportion of impervious areas. These
have negatively affected the social-economy in the Phnom
Penh city. So, it is very important to invest in structural andFlooding is a very common environmental hazard
because of the widespread distribution of river floodplains
and low-lying coasts and the importance they had on humansettlement throughout the history of mankind (Vu and Ranzi,2017). The rise of extreme urban flooding/sewer flooding
has been growing rapidly due to rapid urbanization andclimate change, especially in low- and middle-income
countries (IPCC, 2013). Molyvann (2003) also stated thatwhen the city is being developed with little planning orcontrol, there will be results in flooding problems, informal
settlement along with drainage ways, increased landfill, andpoor urban infrastructure. Not only flooding affects thenormal daily life but also flooding has negative effects on
the environment and society as a whole, in terms of tangible
and intangible losses and damage.
Several studies indicated that the increase in the life
expectancy, economy, and the quality of the environment
can be also related to the population and wealth growth in*

Corresponding author: Panha Hok
E-mail: hokpanha8@gmail.com;
Tel: +855-10-288-384/89-575-578
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Heng et al./Techno-Science Research Journal 9(1) (2021) 33-40

non-structural measures for the flood mitigation which areparts of the investment allocated for the socio-economic
development (Kundzewicz and Takeuchi, 1999; UN and
ISDR, 2007). Meanwhile, flood modeling can provide alogical representation of urban drainage systems andessential information for the managerial and technicaldecision making. That is why the quantification ofinundation change in the future is crucial for reducing flood
losses and damage and to raise awareness and preparedness
to people to cope with the current and future flood hazard.
Better preparation is also required among the people and thedecision-makers. Thus, the objective of this study is toestimate inundation characteristics in the downstream area ofPhnom Penh under the climate change scenario using the
Flo-2D model.
2.

inundation information carried out by the JICA team of thesurvey and the flood photo analysis (Heng et al., 2016).
Once the model performance was successfully calibrated andvalidated with acceptable results, the future inundation
condition in the Phnom Penh city can be estimated from thefuture bias-corrected climate data. The future precipitationhydrograph was established from the future AM
precipitation downscaled by PRECISE GCM of ECGAM4
under SRES A2. This GCM was also employed in previous
studies (Heng et al., 2017; Sreymom et al., 2015) andavailable and ready for use at the time of conducting thisresearch.
2.2 Study area
Phnom Penh is the capital city of Cambodia and thecenter of economic, tourism, cultural heritage, anddiplomacy with a population of about 2.2 million. The
coverage area is 678 km2 (Fig. 2).

METHODOLOGY

2.3 Model framework
The overall study framework is illustrated in Fig. 1. So,
to build the inundation model, a balance should be sought
between the grid element size, resolution of the desired Flo2D result, and the model computer runtime. The gridelement size should reflect the topographic data resolution
and result in an acceptable number of total grid elements.

Fig. 1. Methodological framework of the study area
In this selected area, the grid system was created withthe cell size of 10 m (square grid), and a satellite image(resolution 2 m × 2 m) was used to visualize thecomputational domain. The grid elevation was obtained fromthe interpolation of surveyed DTM data points, which used
only along the road. Different types of land use within the
study area were classified using ArcGIS based on a satellite
image from MRC and observed building data in Phnom
Penh. The baseline hydrograph was selected from the annual
maximum (AM) precipitation within the period of 20092016 from Institute of Technology of Cambodia (ITC)
station. Flo-2D model was calibrated with the observed

Fig. 2. Location map of the study area
Also, it is remarkably noticeable that there has been
rapid urbanization in the capital city. In the Mekong region,
Phnom Penh is located at the confluence of the MekongRivers, Tonle Sap, and Bassac. This intersection has been
known as the “Four Faces”. These rivers provide potential
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Heng et al./Techno-Science Research Journal 9(1) (2021) 33-40

freshwater and river ecosystems as vital resources forsustainable environmental conditions, nature’s beauty, andprosperous culture for Cambodians since the past. The city
center is at an elevation of around 10 m above the mean sea
level. Urban drainage systems in the Phnom Penh capital
city are combined sewer systems which have functions ofdraining stormwater and domestic wastewater.
In Phnom Penh, the average precipitation isapproximately 1,500 mm. However, the range of annual
precipitation is wide (E.g., 1,912 mm in 2008 and 1,171 mm
in 2004). Besides, the annual average of the maximum andminimum monthly temperature is 32°C and 22°C,
respectively. In this study, only 12.5 km2 regularly
inundation downstream area of the Phnom Penh city
covering was selected. Based on the storm drainage masterplan of Phnom Penh Capital Hall, the flow direction is fromthe north to south (Beoung Trabeck station, P1). The study
area is an independent catchment consisting of opened
channels, closed conduits, and groundwater storages. There
are four pumping stations at outfall (Fig. 2). The study area
is surrounded by the Tonle Sap River on the east, other busy
roads, and several municipal administrations, namely Royal
Palace, Olympic Stadium, and embassies. The land use wasclassified into impermeable type including building andasphalt road surface, in which the surface runoff will be fastand generate a large volume.

an exchange between overland flow and storm drain
conveyance. The Green-Ampt method was applied tosimulate the infiltration in this study over the Soil
Conservation Service curve number because of the soil
suitability and data availability.
2.4 Bias correction method
Because either General Circulation Models (GCMs) or
Regional Climate Models (RCMs) exist with their own bias,
so these models are not ready to be used in any decision
support tool. They are not perfect and different from theobserved climatic data (Sharma et al., 2007). So, thehistorical and future climate models are required to performbias correction to reduce some degree of uncertainties, so theresult of any assessment study can be reliable enough.
However, Teutschbein and Seibert (2012) conferred that thequality of adjusted RCM temperature and precipitationstrongly depend on the choice of the correction algorithm,
both for current and future climate conditions. In this study,
a linear correction method proposed by Leander andBuishand (2007) was used. In this method, precipitation
amounts, P, are transformed into P* such that P* = aP,using a scaling factor, a = O/P, where O and P are themonthly mean observed and RCM precipitation,
respectively. Here, the monthly scaling factor is applied toeach uncorrected daily observation of that month, generating
the corrected daily time series.

2.1 Flow-2D model

2.5 Temporal downscaling method

Flo-2D is a two-dimensional grid-based physicalprocess flood routing model, which is an effective tool fordelineating flood hazards, regulating floodplain zone ordesigning flood mitigation over unconfined flow surfaces orin the channel using the continuity equation (Eq. 1) andmomentum equation (Eq. 2).

∂h ∂hv+=i∂t ∂x(Eq. 1)S f =S0 −(Eq. 2)∂h v ∂v 1 ∂v
− −−∂x g ∂x g ∂t

The sub-daily precipitation (5 min, 1 h, or 2 h) areneeded to input in the simulation. Since Southeast Asia
START Regional Center provides future climate data at thedaily interval, it is necessary to temporally downscale theprecipitation data. There are different types of downscaling
techniques such as linear regression, stochastic method andartificial neural networks which have been developed over
the years and used so far. These methods are used to develop
the artificial hydrograph for designing storm drain, etc. For
this study, the extreme AM precipitation pattern in the past
was selected to construct the extreme AM precipitation for
the future. This method is described in Eq. 3:

where h is the flow depth, V is the depth-average velocity
and i is the excess precipitation intensity. Sf and S0 represent
the bottom friction and bed slope, respectively.
Flo-2D has several components to simulate street flow,buildings and obstruction, sediment transport, spatial
variable and infiltration, floodways, and many other flooding
details. The Flo-2D also includes a Grid Developer System(GDS), a MAPPER++ program, and two other processor
programs, namely PROFILE and MAXPLOT. Significantly,
the Flo-2D flood routing model integrates with the Storm
Water Management Model (SWMM), which is developed by
the Environmental Protection Agency (EPA). At runtime,Flo-2D is linked to the EPA-SWMM model, so there can be

i f = icf

ip
icp

(Eq. 3)where if and ip rainfall intensity for a specific day in past andfuture (mm/s) and icf and icp are accumulative rainfall
intensity in a specific day of past and future (mm/day). The
extreme precipitation among the AM daily precipitation withthe period of 2009-2016 recorded by ITC station near to thestudy area was chosen to generate precipitation hydrographfor the analysis.
2.6 Observed inundation data35

Heng et al./Techno-Science Research Journal 9(1) (2021) 33-40

Since there is no historical record of inundation
conditions in the study area, the Flo-2D model wascalibrated with observed inundation map extracted from the
JICA survey database and flood photo analysis which is very
crucial when lacking the observed data (Luo et al., 2018;
Sea et al., 2018). According to JICA (2017), the inundation
map was established using data from the interview withcitizens after the completion of some development projects
as shown in Fig. 3. Some 108 respondents corresponding to
83% of the total number of interviewees replied that they
had experienced flooding in front of their houses. The
experienced flooding depth ranged from ankle to waist-deep.
Around 80% of interviewees have experienced flooding
mentioned that the depth was up to the shin (about 20 cm) or
higher. Besides, some flood information was obtained fromphotos posted on Facebook, YouTube, etc. 11 photos werecollected from Facebook including one photo each of flood
event in 2012 and 2017 and the rest are 2015 flood events.
The location of flooding was found on their status based on
the spot in photos like hotels, restaurants, schools, or theirliving locations. Similarly, the specific time of flooding
might be on the information they shared. The inundation
depth could be recorded by estimating flood depth incomparison with any inundated objective such as the humanbody and vehicle (Table 1 and Table 2). The observed
inundation depth in various locations from these sources is
depicted in Fig. 3.

(1985-2012) was used to define a scaling factor. As a result,the bias-corrected precipitation data from ECHAM4 under
SRES A2 pretty improved closeness to the observed data
(Fig. 4). This scaling factor was used to adjust the future
precipitation from ECHAM4 under SRES A2 for the 2030s(2020-2038). Fig. 5 shows the adjustment result of thedownscaled precipitation data using the defined scaling
factor.

Table 1. Average inundation depth at parts of the human bodyParts of body
Averagedepth (cm)

Ankle

Shin

Knee

Thigh

Waist

10

20

40

60

80

Table 2. Average inundation depth at parts of the car
Part of car
Average height (cm)3.

Ground clearance
16

Type
40

Fig. 3. Observed inundation by JICA survey in 2017 andflood photo analysis
3.2 Temporal downscaling of future precipitation

RESULTS AND DISCUSSION

Based on ECHAM4 under SRES A2, the annual
maximum precipitation is expected to have a decreasing
direction in the near future (Fig. 6). This can be subjected tothe employed climate model and emission scenario, local
climate conditions, especially the bias correction method.
The precipitation intensity will likely vary between 50
mm/year and 1,600 mm/year in the 2030s. However, theextreme precipitation in the 2030s was selected totemporally downscale daily to sub-daily precipitation toquantify the future change in the inundation depth of thedownstream area in the Phnom Penh city. Also, the extreme
event on 11 October 2010 was used to construct the
precipitation pattern of the extreme precipitation in 2010

3.1 Future precipitation scenario
The bias-corrected precipitation data from the
ECHAM4 model under SRES A2 in comparison with theobserved precipitation data recorded at Pochentong station,near the Phnom Penh International Airport, is illustrated inFig. 4. The cumulative density function (CDF) of daily
precipitation from the ECHAM4 model under SRES A2
does not agree well with the CDF of daily precipitation fromthe gauge observation. So, a linear correction method wasused to correct the bias in this study. The precipitation datafrom GCM given by ECHAM4 under SRES A2 simulationand observed precipitation data from Pochentong station
36

Heng et al./Techno-Science Research Journal 9(1) (2021) 33-40(Fig. 7). The precipitation data from the temporal
downscaling to a time interval of 5 min has the peak
precipitation intensity of 70 mm/hr. From JICA data (JICA,
2017), the peak precipitation intensity for 2-year and 5-yearrecurrence interval is 44.8 mm/hr and 63.2 mm/hr
respectively. Precipitation with an intensity of 70 mm/hr
could probably happen even in one year.

market area can be expected between 0.10 m and 0.47 m (CD). However, light inundation is observed at the east, northand west part of the study area, the area around Olympic
National Stadium, and the area along the opened drainage
channel.
Annual maximum daily rainfall (mm)

200

0.9
0.8

Corrected ECHAM4A2
ECHAM4A2
Observed Data

0.7
0.6

160

120

80

40

0

2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038

Non-exceedance probability

1.0

0.5
0.4
0

50

100

150

Fig. 6. Annual maximum daily precipitation from 2020 to
2038

200

Precipitation (mm/day)Fig. 4. Simulated and corrected CDF of daily precipitation in
the baseline (1985-2012)

Non-exceedance probability

1.0
0.9
0.8

ECHAM4A2 (future)
Correction (future)

0.7
0.6

Fig. 7. Extreme precipitation events in 2010 and 2030s

0.5

Under the assumption of no change in infrastructure andpump capacity, the inundation depth in the downstream areaof the Phnom Penh city under climate change scenario canrefer to Fig. 9. The future precipitation with the same pattern
as the extreme event on 11 October 2010 was applied in thisstudy to find the inundation changes. The infrastructure andthe pump capacity were not changed in the simulation. Fig. 9
illustrates the future inundation depth. The area around theRoyal Palace and Beoung Trabeck market still showed theextreme inundation with the water depth over 0.8 m in somearea. The edge of open channel b3-b4 (Fig. 2) has extremelychanged inundation condition with the maximum water
depth of 0.75 m. All areas along the open drainages affectedby inundation likely influenced by backwater effects fromthe overflow of the open channel. Appendix A shows thegraph of the volume of overbank outflow of both baseline
and near future. The volume of overbank flow will increaseby 1.15 of the baseline volumes. Appendix B illustrates theflow depth profile from point A to B and C to D for both

0.4
0

50

100

150

Precipitation (mm/day)Fig. 5. Simulated and corrected CDF of daily precipitation in
the near future (2030s)
3.3 Baseline and future inundation conditions
In the calibration stage, the validity of the model was
confirmed by comparing the simulation result under theobserved precipitation time series on 11 October 2010 andthe observed inundation. Fig. 8 shows the result of flood
depth from Mapper++ (Flo-2D). The established model forthe study area was well-calibrated because the spatial
distributions of the inundation map were pretty matched withthe observed inundation. The result showed that theinundated area around the Royal Palace is the most serious
and vulnerable. The maximum inundation depth can reach
0.57 m (A-B). Also, the inundation at Beoung Trabeck
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Heng et al./Techno-Science Research Journal 9(1) (2021) 33-40

baseline and near future. Overall, the simulation result
showed differences in the extension of submerged areas withthe peak flood depth typically range between 0.03 m to 1.00
m for the near future precipitation. Also, the inundation
depth will be increased from 0.20 m to 0.50 m in thesubmerged area and spread over the study area.

should parallelly pay attention to develop more detention
basin or ground storage along the open drainage channel tominimize the risk of overflow.
ACKNOWLEDGMENTS
The authors would like to express high gratitude to JSPS
Core-to-Core Program, B. Asia-Africa Science Platforms,
for supporting this research study.

Fig. 8. Inundation condition within the study area in the2030s
Fig. 9. Inundation condition within the study area in 2030s
4.

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Heng et al./Techno-Science Research Journal 9(1) (2021) 33-40

APPENDICES

Appendix A. Overbank outflow volume

Appendix B. Baseline and near future flow depth profile, locations (A, B, C, and D) can refer to Fig. 8 and Fig. 9.

40