E3S Web of Conferences 415, 05010 (2023)
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https://doi.org/10.1051/e3sconf/202341505010

A Study on the Comparative Analysis of the FLO-2D ModelAccording to Debris Flow Sediment AmountHang-Il Jo 1, Chang-Deok Jang 2*, Kye-Won Jun 1, Ho-Jin Lee 3 and Bae-Dong Kang 1
1Graduate School of Disaster Prevention, Kangwon National University, S.Korea
2 CND, Samcheok-si, Gangwon-do, S.Korea
3School of Civil Engineering, Chungbuk National University, S.Korea

Abstract. It is very important to predict the extent of the damage in order to reduce or prevent damage bythe debris flow. In the Republic of Korea, various methods are used to understand the characteristics and toestimate the occurrence of the debris flow in an undamaged area, such as simulating disasters using theestimation of debris flow sediment amount based on field survey data. In this study, the runout distance ofdebris flow was analyzed by using different methods for estimating the debris flow sediment amount, at
Wondeok-eup, Samcheok-si, Gangwon-do, where debris flow occurred due to Typhoon Mitak in 2019. Thesimulation results of the damage area were compared with the actual damage area. The result showed thatthe simulations generally corresponded to the actual area of damage caused by the sedimentation of debris
flow. However, the estimation of damage area varied according to the used method of calculating the debris
flow sediment amount.

1 Introduction
In the Republic of Korea, debris flow was classified asa type of landslide in the disaster risk management.
Earnest studies on the damage caused by debris flow
have been carried out in the wake of the landslide atUmyeonsan mountain in 2011, which drew publicattention. A prediction of the area of occurrence andextent/scale of the damage is necessary in order tomitigate the debris flow damage. Therefore, many
researchers have studied the methods of debris flow
sediment amount estimation generated, analyzed(March.
2004; NILIM. 2016)[1,2] debris flow risk by applying
the characteristics of the watershed to the SINMAP(Ohet al. 2013; Kim P.G et al. 2017)[3,4], and analyzed theflow characteristics using the numerical model of debris
flow FLO-2D(Kim et al. 2011; Peng et al. 2013;)[5,6].
The study area of this study is Wondeok-eup,Samcheok-si, Gangwon-do, where debris flow damage
occurred due to Typhoon Mitak [in 2019]. Runout
distance of the debris flow was analyzed by using two
different methods; applying a general field survey on thedebris flow sediment amount generated, and using theuniversal approach to estimate the occurrence of debris
flow to predict the risks of development sites.
Topographical data applied to the FLO-2D model wereconstructed using field survey data and the numericaltopographic map provided by the Korea National
Geographic Information Institute.

2 Study Area

The study area for this study is around Sinnam Village,
located in Wondeok-eup, Samcheok-si, Gangwon-do,
Republic of Korea. Due to the landing of Typhoon
Mitak in October 2019, accumulated rainfall of 487mm(2 – 3 October) and maximum rainfall intensity of110mm/h caused the landslide in the mountainous
upstream area that resulted in the debris flow damage.
The location of the study area and the site of thelandslide are shown in Fig. 1.

Fig. 1. Location of the Study Area

The area of the watershed is 0.84 𝑘𝑚2 , the average
elevation is 163 m, and the average slope is 17 degrees.
Debris flow occurred by the collapse of many areas ofthe mountain slopes at the top of the Sinnamcheon
stream passing through Sinnam Village. It quickly
flowed to the downstream area and caused flooding or
burial damage to 55 out of 101 housing units in Sinnam
Village. The Korean government declared a special
disaster zone for the area, and provided additional
support for damage recovery. Maintenance and repair
were carried out for the upstream perimeter facilities and* Corresponding author: cdjang79@gmail.com© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0(https://creativecommons.org/licenses/by/4.0/).

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the downstream section of Sinnamcheon, and housingsite development was carried out for the buried housingareas.

σρøθ

3 Theory of Numerical Model𝑆𝑓𝑥 = 𝑆𝑎𝑥 −𝑆𝑓𝑦 = 𝑆𝑎𝑦 −𝜕𝑡𝜕ℎ+𝜕𝑥𝜕ℎ𝜕𝑦𝜕(𝑢ℎ)−−𝜕𝑥𝜕𝑢𝑔𝜕𝑡𝜕𝑢𝑔𝜕𝑡+𝜕(𝑣ℎ)−𝑢𝜕𝑦𝜕𝑢𝑔𝜕𝑥−𝑢𝜕𝑢𝑔𝜕𝑥=𝑖−𝑣−𝑣𝜕𝑢𝑔𝜕𝑦𝜕𝑢

The yield stress and viscosity coefficient varydepending on the topography and soil conditions of thewatershed, and O'Brien proposed 16 types(O’Brien.
1988[8]nts α1 , α2 , β1 and β2 of the study area to beused in the equations to calculate the yield stress and theviscous coefficient, the values corresponding to Aspen
Watershed that can be applied in general mountainousareas were applied.

(1)𝜏𝑦 = 𝛼1 𝑒 𝛽1 C , 𝜂 = 𝛼2 𝑒 𝛽2C(2)Table 2. Yield Stress and Viscosity (O’Brien, 1988)[8]𝜂 = 𝛼2 𝑒 𝛽2 C
𝜏𝑦 = 𝛼1 𝑒𝛽1 CSource
𝛼1𝛽1
𝛼2
𝛽2
0.181
25.7
0.0360Aspen Pit1
22.1

(3)

𝑔𝜕𝑦

Where 𝑖 is rainfall intensity, ℎ is flow depth, u is x-axis
flow velocity, v is y-axis flow velocity, 𝑆𝑎𝑥 , 𝑆𝑎𝑦 is floor slope, 𝑆𝑓𝑥 , 𝑆𝑓𝑦 is flow direction and orthogonal to flowof friction slope.

Aspen Natural Soil
Aspen Watershed

28.4
27.1The SINMAP model is based on the infinite slope
stability model, and it requires parameters such as thenumerical elevation data (Digital Elevation Model:DEM) representing the topography, the angle of reposeof the soil (Ф), the complex adhesion between the roots
and the soil (C), and the ratio of the saturated
permeability coefficient of the soil and the groundwater
refill rate (R/T). The most distinctive feature of theSINMAP model is that the groundwater saturation
process is simulated hydrologically in consideration ofsurface runoff from mountain slopes due to heavyrainfall. Risk analysis is performed by infinite slope
stability analysis based on the simulated groundwater
saturation process, as well as in consideration of theadhesion between soil and vegetation, the internal
friction angle of the soil, the weight of the soil, thepermeability coefficient and the groundwater filling rate,etc.

4.1.1 Concentration of Debris flow
The soil density calculation method proposed by NILIM
was used to estimate the concentration of debris flow.
(4)

ρ is density of the particle(kg/m3), σ is density of thefluid(kg/m3), ø is internal friction angle(°), θ is riverbedgradient(°). and riverbed gradient θ is applied anaverage riverbed gradation 14.9° of basin
Table 1. Input variable of debris flow density
Input parameter

0.001360.0004951) Estimation of debris flow sediment amount using
SINMAP

4.1 Physical properties of debris flow∅−tan 𝜃)

18.7
19.6

The estimation of debris flow sediment amount throughthe field survey was presented in a precedent study as
61,433m3 . This study also made an estimation throughthe analysis of the slope stability index using theSINMAP, which is generally used for areas where there
no debris flow has occurred. In doing so, areas withcollapse risk grades 4 to 6, where the calculated slope
stability index was less than 1.0, were selected as thecollapse area and included in the estimation of debris
flow sediment amount.

In order to apply the FLO-2D model to the study area,
topography was constructed by using a 1:5,000
numerical map, and the watershed was distinguished.
The physical properties of the generated debris flow
(viscosity, coefficient of yield stress, and concentration)
were calculated for debris flow simulation. In addition,
this study carried out the comparison of the analyzed
results of the flow characteristics by using two methods;
Case1, the method of estimating the debris flow
sediment amount through field surveys that can beapplied in an area where debris flow occurs, and Case2,
the method of estimating through the SINMAP analysis
that is generally used in Korea for areas where there nodebris flow has occurred.

𝜌 tan 𝜃0.152
0.0383(5)

4.1.3 Debris flow sediment amount

4 Application of Numerical Model

𝐶𝑑 = (𝜎−𝜌)(tan2600
1200
35
14.9

4.1.2 Viscosity and yield stress

The FLO-2D(O’Brien et al. 1993)[7], developed at theUniversity of Colorado, USA, is a physical model basedon the finite difference method, which enables thetracking of rainfall-runoff and flood-hydraulic curves inthe surface and river channels. It is a two-dimensional
numerical analysis program that is defined in 8 flow
directions, and the governing equations consist of acontinuity equation and two momentum equations asfollows.
𝜕ℎDensity of the particle [kg/m3]
Density of the fluid [kg/m3]
Internal friction angle [°]Riverbed gradient [°]Value2

E3S Web of Conferences 415, 05010 (2023)
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𝐹𝑆 =

https://doi.org/10.1051/e3sconf/202341505010

𝑅 𝑎,1)𝑟]𝑡𝑎𝑛𝜙𝑇 𝑠𝑖𝑛𝜃

𝐶+𝑐𝑜𝑠𝜃[1−min((6)𝑠𝑖𝑛𝜃The SINMAP analysis result is presented in Fig. 2. Theareas with collapse risk grades 4 to 6, with a slope
stability index less than 1.0, were selected as thecollapse risk areas, and the collapse area for each grade
was calculated as shown in Table 3. Using the available
soil depth of the precision soil map (Fig. 3), the debris
flow sediment amount was estimated as 170,525 𝑚3
Table 3. Classes of slope stablity based on value of theStability Index (Pack,2001)[9]Predicted State

Area

Rate

VolumeStable slope zone

15.10ha17.2%

82,575𝑚3

8.20ha9.3%

43,362𝑚3

21.61ha24.5%

108,893𝑚3

5 Simulation Result of Debris Flow

Lower threshold slope

41.20ha46.8%

164,450𝑚3

5.1.1 Flow Velocity

Upper threshold slope

1.95ha2.2%

6,075𝑚3

Defended slope zone000

Flow velocity the maximum flow velocity in thesediment was 9.9m/s of Case 1, and 12.4 m/s of Case 2(a difference of 2.5 m/s occurred).The soil density
calculation method proposed by NILIM was used toestimate the concentration of debris flow.

Moderately stableslope zone
Quasi-stable slopezone

Fig. 3. Soil Information

5.1.2 Flow Depth
It shows a difference of about 1.8m between themaximum flow depths that were calculated Case 1(6.5m), and Case 2(8.3m).
Table 4. Max Velocity and Max Flow Depth

Fig. 2. Stability Index

Max Velocity

Max Flow Depth

Case 1

0.1 ~ 9.9m/s

0.1 ~ 6.5m

Case 20.1 ~ 12.4m/s

0.1 ~ 8.3m

Error

2.5m/s1.8m

5.1.3 Damaged Area
Fig. 4. shows the analyzed results of the damage area,
using the estimated debris flow sediment amountthrough the field survey and through the SINMAP
analysis. The actual damage area of the debris flow area
was 46,775 𝑚2 , and the calculated damage area was
67,825 𝑚2 when the estimated debris flow sedimentamount through the field survey was applied, and 77,450
𝑚2 when the estimated debris flow sediment amountthrough the SINMAP analysis was applied. That is, thedamage area there was a difference of about 45% in thecase of applying the estimated debris flow sediment3

E3S Web of Conferences 415, 05010 (2023)
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amount through the field survey, and about 65% in thecase of applying the debris flow sediment amountestimation through the SINMAP analysis, confirming
the tendency of overestimation (Table 5)survey method showed more similar characteristics tothe actual debris flow damage on site.
A limitation of this study is that it did not reflect the flowrate and the debris flow sediment amount out to thedrainage culvert in the coverage section of Sinnamcheon,
as well as the debris flow sediment amount out to thecoast.
This research was supported by the program of Research
Program to Solve Urgent Safety Issues (2022M3E9A1095664),
through the National Research Foundation of Korea(NRF),
funded by the Korean government. (Ministry of Science andICT(MSIT), Ministry of the Interior and Safety(MOIS)).

References1.
2.

Fig. 4. Result of FLO-2D

3.

Table 5. Damaged Area
Damaged Area

Error

4.

Actual Affected Area

46,775ha-5.

Case 1

67,825ha

45%

Case 277,450ha

65%

6.
7.

6 Conclusions

8.

This study applied and compared two methods forestimating the debris flow sediment amount, through thefield survey and the SINMAP analysis. The result
showed that debris flow sediment amount in the study
area was estimated as 61,433𝑚3 when applying the fieldsurvey estimation and 170,525 𝑚3 when applying theSINMAP analysis, respectively. Considering that themethod using the SINMAP analysis calculated thedebris flow sediment amount to be rather large, caution
would be required when applying the SINMAP analysis
to the FLO-2D model in Korea, to avoid the tendency ofoverestimation.
As a result of applying these values to the FLO-2Dmodel, the damage area was found to be 67,825 𝑚2 inthe case of applying the estimation through the fieldsurvey, while it was overestimated by about 14%(77,450 𝑚2 ) when applying the estimation through theSINMAP analysis. The flow velocity and flow depth
were analyzed as 9.9 m/s and 6.5 m when applying thefield survey estimation, and 12.4 m/s and 8.3 m when
applying the SINMAP analysis, respectively. It
confirmed that the simulation results using the field9.

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