Risk assessment of landslide-induced surge disaster of river type reservoir in mountainous area

Abstract

The landslide-induced surge of river type reservoir in the mountainous area has become one of the most important disasters affecting the waterborne transportation and the safety of human life and property in the reservoir area. Based on the field observation of landslide and landslide-induced surge in the Three Gorges Reservoir (TGR) area and relevant research results, this paper develops the basic principles for selecting the risk factors of landslide-induced surge, analyses the risk factors of landslide-induced surge, and gives the main and secondary risk factors and their characteristics. According to the characteristics of landslide-induced surge disaster, the hierarchical structure, judgment matrix, and risk calculation model suitable for landslide-induced surge disaster are established by using analytic hierarchy process method, and the classification standard of the action index of each main evaluation factor is determined. This well-developed evaluation method is then applied to evaluate the risk of Hongyanzi landslide-induced surge disaster in the TGR area. The evaluation result is high risk, which is consistent with the actual disaster situation.

Full text

SYSTEMS SCIENCE & CONTROL ENGINEERING: AN OPEN ACCESS JOURNAL
2020, VOL. 8, NO. 1, 454–461
https://doi.org/10.1080/21642583.2020.1788469
Risk assessment of landslide-induced surge disaster of river type reservoir in
mountainous area
Meili Wanga, Shengfa Yangb, Jie Zhangband Xiaoling Lic
aCollege of Architecture and Urban Planning, Chongqing Jiaotong University, Chongqing, People’s Republic of China; bCollege of Hehai,
Chongqing Jiaotong University, Chongqing, People’s Republic of China; cSouthwest Water Transportation Engineering Research Institute,
Chongqing Jiaotong University, People’s Republic of China
ABSTRACT
The landslide-induced surge of river type reservoir in the mountainous area has become one of the
most important disasters affecting the waterborne transportation and the safety of human life and
property in the reservoir area. Based on the field observation of landslide and landslide-induced
surge in the Three Gorges Reservoir (TGR) area and relevant research results, this paper develops
the basic principles for selecting the risk factors of landslide-induced surge, analyses the risk factors
of landslide-induced surge, and gives the main and secondary risk factors and their characteristics.
According to the characteristics of landslide-induced surge disaster, the hierarchical structure, judg-
ment matrix, and risk calculation model suitable for landslide-induced surge disaster are established
by using analytic hierarchy process method, and the classification standard of the action index of
each main evaluation factor is determined. This well-developed evaluation method is then applied
to evaluate the risk of Hongyanzi landslide-induced surge disaster in the TGR area. The evaluation
result is high risk, which is consistent with the actual disaster situation.
ARTICLE HISTORY
Received 16 March 2020
Accepted 24 June 2020
KEYWORDS
Three Gorges reservoir;
landslide-induced surge;
disaster assessment; risk
degree; AHP method
1. Preface
As a kind of swell, the landslide-induced surge has a large
energy and spreadability, which makes it very destructive.
The surge will bring great threat to the nearby water area
and the service-life of the ships, channel, wharf auxiliary
facilities, and other structures and local residents in the
spreading area after the landslide enters the water. In seri-
ous cases, it can destroy the ships, wharf, dam and other
structures, or even cut off the river, obstruct the chan-
nel and cause the navigation interruption. It is of great
significance to carry out the risk assessment of landslide-
induced surge disaster, to reasonably determine the risk
level of disaster, and to select the countermeasures and
measures for disaster prevention and mitigation, so as
to ensure the safety of human economic activities and
reduce disaster losses.
At present, there are many studies on the risk assess-
ment of geological disasters such as landslides and col-
lapses (Erener & Düzgün, 2013), including the initial wave
height, wave runup, wave propagation, and energy dis-
sipation, flow field caused by the wave and the impact
of the wave on navigation (Wang et al., 2019;Yuan
et al., 2019). However, there are few studies on the risk
assessment of the landslide-induced wave. Slingerland
CONTACT Meili Wang wml9106@163.com
and VoightPaolo (1982) investigated the phenomenon of
landslide-induced surge disaster assessment, which was
further discussed by Huber (1984). Wieczorek et al. (2003)
pre-assessed the landslide-induced surge disaster at the
tidal estuary of Glacier Bay National Park in the United
States. Gusiakov (2008) studied the catalogue of the sea
surge disaster and risk assessment, and Wang et al. (2014)
took Baishuihe landslide-induced surge as an example.
Lin et al. (2019) established a safety assessment system for
landslide-induced surge of river reservoir based on GIS.
In the existing disaster risk evaluation, the popular or
well-developed evaluation methods mainly include com-
prehensive index method, fuzzy comprehensive evalua-
tion method, and chromatography analysis method (Qi,
2008;Yang,2014). Comprehensive index method is a
method of statistical analysis by using comprehensive
index, which needs a lot of original data. Fuzzy compre-
hensive evaluation method is a method of comprehen-
sive evaluation by using the characteristics of fuzzy rela-
tion synthesis, from multiple indexes to the subordinate
level of the evaluated things, which is a method of simu-
lating some thinking modes of human brain, with certain
uncertainty. Analytic hierarchy process (AHP) is a system-
atic, flexible, concise, and practical multi-factor decision
© 2020 The Author(s). Published by Informa UK Limited, trading as Taylor& Francis Group
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distribution, and reproduction in any medium, provided the original work is properly cited.

SYSTEMS SCIENCE & CONTROL ENGINEERING: AN OPEN ACCESS JOURNAL 455
analysis method combining qualitative and quantitative
analysis, which was put forward by Professor T.L. Saaty,
an American operational research scientist, in the early
1970s (Yi, 2000). It is an effective system analysis method
for the combination of qualitative and quantitative prob-
lems in system engineering (Wang, 2011;Xu,1988). This
paper takes Hongyanzi landslide-induced surge in the
Three Gorges Reservoir (TGR) area as an example and
uses the AHP technology to establish a hierarchical struc-
ture model suitable for landslide-induced surge disasters
according to the characteristics of the problem to be
solved. The main factors of the surge wave are quanti-
tatively evaluated, and the impact of various factors is
comprehensively considered to evaluate the risk of the
landslide-induced surge disaster.
2. Selection of risk assessment factors of
landslide-induced surge
2.1. Principles for selection of evaluation factors
The risk assessment of landslide-induced surge should
combine the hazard range of landslide-induced surge
with the factors of human engineering economic activi
ties and carry out a general and comprehensive risk
assessment. Because there are many factors affecting the
generation and propagation of landslide and its induced
surge, and the influence degree of each factor on its risk is
different. In the case of not fully considering all factors and
their interrelations, the main factors should be selected
and the influence of secondary factors should be ignored.
The risk assessment of landslide-induced surge should
adopt the combination of qualitative and quantitative
methods, select quantitative analysis as the mathematical
expression of qualitative analysis, and take the results of
qualitative analysis as the framework of constraint quan-
titative evaluation.
The evaluation index system is composed of several
single evaluation indexes (factors). It should reflect the
objectives and requirements of the risk prediction of
landslide-induced surge disaster, being comprehensive,
reasonable, scientific, and practical, and being accepted
by relevant personnel and departments. However, due
to various reasons, such as the depth of research, the
requirements of various industries and different priorities,
China has not yet established a unified and standardized
evaluation system of landslide-induced surge disaster
indicators, and there are many evaluation systems com-
posed of a single or a few indicators. Although all kinds of
evaluation index systems are designed to establish a gen-
erally applicable evaluation index system, some focus on
the selection of indicators, some focus on the quantitative
methods of indicators because of the different focuses (Ali
et al, 2014). Based on the characteristics of landslide-
induced surge in the TGR area, this paper discusses the
establishment principle of the index system. It no longer
takes universality as the first principle of constructing the
evaluation index system, but emphasizes the basic crite-
ria of specific analysis of specific problems, and empha-
sizes that the specific situation of the evaluation research
area should be fully considered under the framework
of general adaptability. Therefore, the comprehensive
and systematic consideration of the trigger and disaster-
causing factors that control and influence the occurrence
of landslide-induced surge disasters should be included
in the determination of the evaluation index system. The
evaluation index strives to be concise, operable, and tar-
geted while making every factor as simple as possible.
Meanwhile, they are independent of each other, and the
basic principles such as major and minor factors should be
distinguished.
2.2. Selection of evaluation factors
Based on the field investigation, field data analysis, phys-
ical model test, and numerical simulation of the research
object, the main factors affecting the height of landslide-
induced surge are landslide volume, slope of sliding sur-
face, initial position of landslide, state of water body and
exchange degree (Han et al., 2019). Among them, the vol-
ume and initial position of the landslide reflect the total
potential energy of the landslide, the angle of the slid-
ing surface controls the sliding speed before the landslide
enters the water, and the operation level of the reser-
voir (water depth of the reservoir) controls the state and
exchange degree of the water body. Therefore, the main
factors that affect the generation and height of the surge
are the volume of the landslide, the slope of the slid-
ing surface, the initial position of the landslide, and the
operating water level of the reservoir (the water depth
of the reservoir), which are called as the disaster trigger
environment. After the formation of the surge, the prop-
agation along the reservoir and the wave runup along
the bank will affect the safety of various disaster-bearing
bodies (such as residential areas, ports and docks, roads
and bridges, water conservancy facilities, waterway facil-
ities, municipal facilities, and passing ships), resulting in
disaster losses (Zhiyou et al., 2018). Therefore, the char-
acteristics of propagation wave height and surge runup
are the important factors leading to surge disaster. Other
factors, such as landslide structure, rock and soil prop-
erties, reservoir water velocity, can be used as reference
factors.

456 M. WANG ET AL.
(1) Disaster trigger environment
It mainly includes the scale of the landslide, the slope
of the landslide, the initial position of the landslide, and
the operating water level of the reservoir.
The impact of the scale of the landslide on the
landslide-induced surge is obvious. As the scale of the
landslide increases, the potential danger or harm of the
landslide increases rapidly. Generally speaking, the vol-
ume of landslides indicates the scale of landslides, and
there is no uniform division standard so far. The com-
monly used grade standards generally follow the techni-
cal standards of the China Geological Survey: small land-
slide volume is less than 1 ×104 m3; medium landslide
volume is 1 ×104 m3to 10 ×104 m3; large landslide vol-
ume is 10 ×104 m3to 100 ×104 m3; extra large landslide
volume is 100 ×104 m3to 1000 ×104 m3; the volume
of giant landslide is more than 100 million m3. According
to the statistics of the geometric shape and characteris-
tics of rock mass landslides in the TGR area, the volume of
rock mass landslides in the reservoir area is mainly large-
or medium-sized. Because the scale of landslide is directly
proportional to the risk degree of surge and its induced
disaster loss, this paper selects the landslide scale with the
volume of 1 ×104 m3and 10 ×104 m3as the evaluation
criteria.
The slope of the sliding surface determines the move-
ment form of the landslide and the sliding speed before
entering the water. Different from rock landslides, col-
lapse (dangerous rock mass) and steep rock mass land-
slides are sudden and sharp fall movements of rock and
soil mass on steep hillsides under the action of gravity,
which usually occur on mountain with a slope larger than
60° to 70° and mostly occur in rock sections with hard
lithology. Due to the high hardness of rock mass, the scale
of landslides is smaller than that of earth rock landslides,
and the rock mass still remains in the process of falling
with a better integrity. However, the material composi-
tion of rock landslides is mainly composed of mudstone
and sandstone with small hardness, which are widely dis-
tributed in the TGR. The scale is usually large or medium-
sized (10 to 1000 ×104 m3). Due to the fracture develop-
ment and geological structure, they are nearly scattered
in the process of sliding and entering the water. Based
on the statistical analysis of the slope of sliding surface of
typical rock landslides in the TGR area, it is found that the
slope of the sliding surface of rock landslides is between
16° and 64° (average value: 38.5°). Therefore, this paper
focuses on the selection of 20° and 40° rock landslide
slope level as the evaluation criteria.
In addition to the landslide volume and slope angle,
the mechanism of surge also depends on the initial posi-
tion of the landslide relative to the surface of still water,
that is, the water state of the landslide. According to the
different initial position, it can be divided into an over-
water landslide, partially submerged landslide and under-
water landslide. The initial surge generated by overwater
landslide includes solid, liquid, and gas, which is mainly
formed on the surface of water body, and its local ampli-
tude is larger than that of partially submerged landslide
and underwater landslide. Compared with the overwa-
ter landslide, the sliding speed of the partially submerged
landslide is slower, but the initial surge generated by the
landslide still belongs to the mixed flow of solid, liquid,
and gas. One part of the initial surge is formed on the
surface of the water body, the other part is formed under-
water, and the local wave amplitude is between the over-
water landslide and the underwater landslide. However,
the local surge generated by the underwater landslide is
far less than the type of landslide and partially submerged
landslide, and the sliding speed is also slower. The ini-
tial surge only contains solid and liquid phases, and all
of them are formed underwater. Therefore, according to
the initial position of the landslide relative to the static
water surface of the reservoir, this paper takes overwater
landslide, partially submerged landslide and underwater
landslide as the evaluation criteria.
The operating water level of the reservoir affects the
initial wave height when the surge occurs. According to
the existing wave height test of the initial wave height
of rock mass landslide under three operating water levels
of the TGR, it is concluded that the initial wave height of
the same volume landslide decreases with the increase of
water depth in the reservoir when the water inflow angle
is the same. With the rise of water level, the water body
is more and more abundant. In the process of energy
exchange between landslide and water body, the energy
lost is enhanced. Therefore, the greater the water depth
is, the greater the energy consumption of the initial wave
height is, and the smaller the initial wave height is. In
this paper, the three-stage water level (145, 155, 175 m)
in the operation of the TGR is used as the criterion of low,
medium, and high water level.
(2) Surge characteristics
It mainly includes propagation wave height and surge
wave runup.
The initial surge of landslide-induced surge is a com-
plex wave combining progressive wave and oscillating
wave. In the process of propagation, surge is affected
by friction resistance, leading to a reduction of wave
height and energy loss. In practice, the scope of water traf-
fic control and various facilities protection for landslide-
induced surge disaster can be determined according to
the initial and propagation wave height. Among the

SYSTEMS SCIENCE & CONTROL ENGINEERING: AN OPEN ACCESS JOURNAL 457
landslide-induced surge disasters that have occurred, the
frequency of the hazards to ships is the most promi-
nent. Therefore, special attention needs to be given to
the impact of the surge height on the safety of the ship.
In other words, the degree of impact of the surge height
on ship safety in case of the ship being fully loaded can
be adopted. According to the data statistics of inland
river ship type parameters and design draught, it can be
found that the maximum wave height of Navigable Ship
is generally 0.4–0.6 m, which is basically consistent with
the range of 0.5–0.6 m of lock discharge limit standard
(Haiyong et al., 2015). Considering the adverse effects, the
upper limit of surge height is 0.4 m.
The determination of the local wave runup is a very
important parameter in the hazard prediction and dis-
aster reduction design of the bank slope, buildings and
local residents. It directly affects the stability of the bank
slope, buildings (such as residential areas, ports, roads
and bridges, water conservancy facilities, waterway facili-
ties, and municipal facilities) and the life safety of the res-
idents. As many human engineering economic activities
fail to fully realize the danger of landslide-induced surge,
it often causes casualties and various property losses. In
the risk assessment of landslide-induced surge, people-
oriented should be taken into account, and the impact of
surge runup on the people on the shore should be con-
sidered. Generally, it can be discriminated and analysed
according to the children of 0.5–1 m height. In this paper,
0.5 and 1 m surge heights are selected as the evaluation
criteria.
In summary, six factors that have a greater impact
on landslide-induced surge disasters are selected for this
evaluation as landslide scale, landslide slope, initial posi-
tion of the landslide body, reservoir operating water level,
spread wave height, and surge climb. The main evalua-
tion factor is to establish the hierarchical structure model
to evaluate the danger of landslide-induced surge.
3. Risk assessment model of landslide-induced
surge disaster
3.1. Establishment of hierarchy model for risk
assessment of landslide-induced surge
The idea of AHP is to firstl decompose the complex prob-
lem into several levels and its related dominating factors,
then calculate and compare each factor, so as to obtain
the weight value of different dominating factors, and
finally provide decision-making basis for the analysis and
solution of the problem. When applying AHP to analyse
multi-factor decision-making problems, we need firstly
establish a hierarchical level and construct a hierarchical
structural model, which can generally be divided into the
highest level (target level), middle level (criteria level), and
bottom level (indicator level). The elements of the previ-
ous level dominate the elements of the next level. Each
element in each level generally contains no more than
nine elements. After various data and information of land-
slide are analysed and processed, six factors related to the
formation of landslide are extracted: propagation wave
height (C1), surge runup (C2), landslide scale (C3), slope
of sliding surface (C4), initial position of landslide body
(C5), operating water level of reservoir (C6) as index layer
(second layer), together with the disaster-causing factors
(B1), and trigger of criterion layer (first layer) hazard fac-
tor (B2), establishing the hierarchical structure model, and
evaluating the risk of landslide-induced surge hazard (A).
The hierarchy of landslide risk assessment is shown in
Figure 1.
3.2. Construction of judgment matrix
The judgment matrix represents the comparison of the
relative importance between the relevant factors in this
level compared with a certain factor in the previous level.
The analytic hierarchy process uses the 1–9 scale method
to give the quantitative scale for the evaluation of differ-
ent situations. That is, any two evaluation indicators are
compared item by item, while referring to expert opin-
ions to determine their relative importance and assigning
corresponding scores to construct a judgment matrix.
Therefore, it is necessary to start from the second layer
of the hierarchical structure model, and use the numbers
1–9 and its reciprocal as the scale to construct a pair of
judgment matrices for each factor of the same layer that
belongs to each factor of the upper layer, until the lowest
layer. Its form is shown in Tables 1–4.
Then, the feature vector w is solved by hierarchical
single sorting. Hierarchical single ranking refers to calcu-
lating the weight of the importance order of each factor
related to the previous level according to the judgment
matrix (Gu et al., 2009). Its purpose is to calculate the max-
imum eigenvalue and the corresponding eigenvector for
each pair of judgment matrix by the summation method.
According to the square root method, the calculation
steps are as follows:
1
Calculate the product Miof each row element of
judgment matrix B:
Mi=n

j=1xij(i=1, 2, ···,n)(1)
where xi,xj(i,j=1, 2, ... ,n) for each factor. xij is the
value of the relative importance of xito xj.
2
Calculate the n-th root Wiof Mi:
Wi=n
Mi(2)

458 M. WANG ET AL.
Figure 1. Hierarchy of landslide-induced surge risk assessment.
Tab le 1. Judgment matrix of A-B layer.
AB
1B2W
B1b11 b12 Wb1
B2b21 b22 Wb2
Tab le 2. Judgment matrix of B1-C layer.
B1C1C2W
C1C11 C12 WC1
C2C21 C22 WC2
Tab le 3. Judgment matrix of B2-C layer.
B2C3C4C5C6W
C3C33 C34 C35 C36 WC3
C4C43 C44 C45 C46 WC4
C5C53 C54 C55 C56 WC5
C6C63 C64 C65 C66 WC6
Tab le 4. Judgment matrix of A-C layer.
B
CB
1B2... Bn
CWb
1Wb2... WbnWTotalweight
C1WC10... 0W
1
C20Wc
2... 0W
2
... ... ... ... ... ...
Cn000WC
nWn
3
Normalize the vector Wito get the weight Wi:
Wi=Wi/n

i=1Wi(3)
Then, W=(W1···W2···Wn)Tis the feature vector, that
is, the weight value of each index.
Finally, the consistency test is carried out to judge
whether the above eigenvectors are reasonable. Con-
sistency test is used to test the constructed judgment
matrix. If the test results are within the allowable range,
the ranking results are valid. Otherwise, the judgment
matrix needs to be readjusted until it is reasonable. The
method is as follows:
1
Calculate the maximum eigenvalue λmax of judg-
ment matrix:
λmax =1
n
n

i=1
(BW)i
Wi
(4)
BW =
⎡
⎢
⎢
⎣
x11 x12 ··· x1n
x21 x22 ··· x2n
··· ··· ··· ···
xn1xn2··· xnn
⎤
⎥
⎥
⎦
⎡
⎢
⎢
⎣
W1
W2
···
Wn
⎤
⎥
⎥
⎦
(5)
Among them, λmaxis the maximum eigenvalue of judg-
ment matrix B; n is the number of pairwise comparison
factors; Wiis the component of W, which is the single-
order weight value of the corresponding element; Wis
the normalized eigenvector corresponding to λmax.
2
Calculate the consistency indicator CI and find the
consistency indicator RI:
CI =λmax −n
n−1(6)
In the formula, the greater the CI value, the worse the
consistency of the judgment matrix. When CI =0, the
judgment matrix has full consistency. Then, check the
table to determine the corresponding average random
consistency index RI, and compare CI with RI to check
whether the judgment matrix is consistent. See Table 5
for the index value.
CR =CI
RI (7)
3
Calculate consistency ratio:
When CR <0.10, the consistency of the judgment
matrix is acceptable. When CR >0.10, the judgment
matrix does not meet the consistency requirements, and
it should be appropriately modified until the consistency
is satisfied.
3.3. Classication of evaluation factors
The classification of risk factors is based on the actual sit-
uation of landslide-induced surge disaster in the study
area, to evaluate the risk factors of landslide-induced

SYSTEMS SCIENCE & CONTROL ENGINEERING: AN OPEN ACCESS JOURNAL 459
Tab le 5. Average random consistency index chart.
Order123456789101112
RI 0 0 0.52 0.89 1.12 1.26 1.36 1.41 1.49 1.49 1.52 1.54
Tab le 6. Classification of evaluation factors and determination criteria for different levels.
Risk factor classification
Discriminant High (1) Medium (0.618) Low (0.382)
Landslide scale ≥10 ×104m31×104m3to 10 ×104m3≤1×104m3
Slope angle ≥400200to 400≤200
Initial position of landslide mass Above water Partial submergence Underwater
Reservoir operating level Low Medium High
Wave he ight ≥0.6 m 0.4 to 0.6 m ≤0.4 m
Runup ≥1.0 m 0.5 to 1.0 m ≤0.5 m
surge. The aforementioned six risk factors are divided
into three levels, and the specific classification and the
determination criteria of different levels are shown in
Table 6.
The action index is a physical quantity that repre-
sents the action size or strength of each factor in land-
slide risk identification, which is a relatively comparative
value and a quantitative expression of qualitative analy-
sis. In recent years, many researchers agree that ‘golden
section’ method (Qi, 2008), not only can be widely used
in the long and wide sections of rectangular objects, but
also exists in people’s analytical epistemology. For exam-
ple, there are main and secondary reasons leading to the
formation of a natural phenomenon. The main and sec-
ondary mathematical sections can still be divided by the
proportion coefficient of 0.618. Usually, people use the
golden section method to determine the proportional
relationship between the effects of geological hazard risk
assessment factors, so as to avoid the randomness of the
distribution factor action index. In this study, the principle
of ‘golden section’ is used to determine the classification
standard of the action index of each evaluation factor
for landslide-induced surge. In other words, the action
index with high risk is taken as 1, the action index with
medium risk is taken as 0.618, and the action index with
low risk is taken as 0.382, which is represented by V1,V
2
and V3, where V1corresponds to high risk, V2corresponds
to medium risk, and V3corresponds to low risk V ={V1,
V2,V
3}={high risk, medium risk, low risk}={1, 0.618,
0.382}.
3.4. Evaluation model
Quantitative indicators for risk assessment are obtained
by calculating the risk index. The calculation model for
landslide-induced surge risk is:
DL=n

i=1wi×Ii(8)
Tab le 7. Criteria for risk classification.
Risk level Judgement index (DL) Risk assessment
I≥0.75 High
II 0.50–0.75 Medium
III ≤0.50 Low
In the formula, DLis the landslide risk factor; Wiis the
weight vector of discrimination factor; Iiis the action
index of discrimination factor. Risk classification standard
canbereferredtoTable7.
4. Example of landslide-induced surge disaster
risk assessment
Since the implementation of the 175 m testing impound-
ment in the TGR in September 2008, a large number
of landslides and bank collapses have occurred on both
sides of the reservoir area. For example, at 18:40 on 24
June 2015, a large-scale landslide (Hongyanzi landslide)
broke out on the North Bank of Jiangdongsi, the mouth of
Daning River in Wushan, Chongqing. About 230,000 m3
of rock and soil mass slid into Daning River with a high
speed, generating a huge swell of about 6 m high in the
near field. Although the Wushan Authority had evacuated
residents around the landslide area before the landslide
arrived, and arranged all operating vessels on the Dan-
ing River to dock in the port. Due to inaccurate estimation
of the intensity and danger of the swell wave attenua-
tion, the shore wave unfortunately caused the sinking of
a 14 m-long sea cruiser docked on the opposite side of
the landslide body, the overthrow of nine small fishing
boats and seven self-used ships. In addition, two people
were killed and four injured due to local surge runup.
In this study, the risk degree of Hongyanzi landslide-
induced surge disaster is evaluated by the above evalu-
ation method.
(1) Determination and calculation of judgment matrix

460 M. WANG ET AL.
Tab le 8. Judgment matrix of layer A-B.
AB
1B2W
B11 2 0.6667
B21/2 1 0.3333
Tab le 9. Judgment matrix of layer B1-C.
B1C1C2W
C11 1/3 0.2500
C23 1 0.7500
Table 10. Judgment matrix of layer B2-C.
B2C3C4C5C6W
C31 3 2 5 0.4717
C41/3 1 2 5 0.2723
C51/2 1/2 1 3 0.1875
C61/5 1/5 1/3 1 0.0685
Table 11. General layer judgment matrix A-C.
BB
1B2
C 0.6667 0.3333 W Total weight
C10.25 0 0.5000
C20.75 0 0.1667
C30 0.4717 0.1572
C40 0.2723 0.0908
C50 0.1875 0.0625
C60 0.0685 0.0228
According to the field survey, the average slope of the
landslide mass is 34°, the total volume of the landslide
mass is 23 ×104m3, the length of the water part of the
landslide mass is 130 m, the water depth in the area near
the landslide is 25 m (the water level of the TGR is in opera-
tion), the initial wave height is 6 m, the runup is 1.3 m, and
the propagation wave height is greater than 0.6 m. On
the basis of the field data and consultancy of the relevant
experts, the judgment matrix of each level is determined
according to the AHP.
1
The evaluation matrix of Hongyanzi surging land-
slide evaluation factor is shown in Tables 8–11.
CR =0<0.1, so the judgment matrix satisfies the
consistency check, and the above feature vector W can be
used as a weight vector.
CR =0<0.1, so the judgment matrix satisfies the
consistency check, and the above feature vector W can be
used as a weight vector.
CR =0.059 <0.1, so the judgment matrix satisfies the
consistency check, and the above-mentioned feature vec-
tor W can be used as a weight vector.
Consistency check of hierarchical total ordering: CR =
0, satisfying the consistency check.
2
Value index of Hongyanzi landslide evaluation fac-
tor
See Table 12 for the action index of each evaluation
factor of Hongyanzi landslide-induced surge.
3
Risk index of Hongyanzi landslide
According to Tables 11 and 12, using formula (9),
DL=0.9327.
(2) Risk assessment results of landslide-induced surge
According to the above calculation results, Hongyanzi
landslide has a high risk of surge (Grade I). This is consis-
tent with the actual disaster situation. It can be seen that
it is feasible to use AHP to evaluate the risk of landslide-
induced surge. Therefore, this method can be used to
evaluate and determine the risk level of other possible
landslide-induced surge disasters, so as to provide refer-
ence for landslide-induced surge prevention and scien-
tific decision-making.
5. Conclusions
(1) The risk assessment of landslide-induced surge
should be based on the combination of qualitative
and quantitative methods and the selection of main
factors. In the process of risk assessment and analysis,
in order to meet the needs of risk analysis, through
the comprehensive comparison of a large number
of prototype observation data and research results,
the main risk factors of landslide-induced surge dis-
aster are selected as landslide scale, slope of sliding
surface, initial position of landslide mass, operation
water level of reservoir, propagation wave height and
surge runup.
(2) According to the characteristics of landslide surge
disaster, the hierarchical structure, judgment matrix
and risk calculation model suitable for landslide
surge disaster are established by using the AHP
method. The ‘golden section’ method is used to
determine the classification standard of the action
index of each main evaluation factor, and the risk
grade and corresponding assignment of landslide
Table 12. Effect factors of evaluation factors of swell waves in Hongyanzi landslide.
Evaluation factor Wave height Runup Landslide scale Slope angle
Initial position of
landslide mass
Reservoir
operating level
Interaction index 1 1 1 0.618 0.618 0.618

SYSTEMS SCIENCE & CONTROL ENGINEERING: AN OPEN ACCESS JOURNAL 461
surge disaster are given respectively for landslide
scale, slope of sliding surface, initial position of land-
slide mass, operation water level of reservoir, propa-
gation wave height, and surge climbing height.
(3) Using the evaluation method in this study, the risk of
Hongyanzi landslide-induced surge disaster of Dan-
ing River in TGR area is evaluated, and the weight
of evaluation index and the calculation result of risk
degree are given. The risk assessment result of the
landslide-induced surge disaster is high risk (Grade
I), which is consistent with the actual disaster situa-
tion. It can be seen that it is feasible to use AHP to
evaluate the risk of landslide-induced surge, which
provides a reference for the risk assessment and pre-
vention of other possible landslide-induced surge
disasters.
Acknowledgements
This study is supported by the National Natural
Science Foundation of China (No. 51479015), Chongqing
Basic Science and Advanced Technology Program (cstc2017
jcyjBX0070).
Disclosure statement
No potential conflict of interest was reported by the author(s).
Funding
This study is supported by the National Natural Science Foun-
dation of China [grant number 51479015], Chongqing Basic
Research and Frontier Exploration Project (Chongqing Natural
Science Foundation) [grant number cstc2017jcyjBX0070].
References
Ali, A., Huang, J., Lyamin, A. V., Sloan, S. W., Griffiths, D.
V., Cassidy, M. J., & Li, J. H. (2014). Simplified quantita-
tive risk assessment of rainfall-induced landslides mod-
elled by infinite slopes. Engineering Geology,179, 102–116.
https://doi.org/10.1016/j.enggeo.2014.06.024
Erener, A., & Düzgün, H. B. S. (2013). A regional scale quantitative
risk assessment for landslides: Case of Kumluca watershed
in Bartin, Turkey. Landslides,10(1), 55–73. https://doi.org/10.
1007/s10346-012-0317-9
Gu, X. Z., Peng, Y. Q., & Chen, H. K. (2009). Study on landslide risk
of fengjiaba, Wushan, Three Gorges Reservoir Area. Journal
of Chongqing Jiaotong University (NATURAL SCIENCE EDITION),
28(4), 724–727. https://doi.org/CNKI:SUN:CQJT.0.2009-04-022
Gusiakov, V. K. (2008). An integrated tsunami research and infor-
mation system: Application for mapping of tsunami hazard
and risk assessment. Solutions to Coastal Disasters 2008:
Tsunamis Coastal Disasters and Solutions 2008. American
Society of Civil Engineers. pp. 27–38.
Haiyong, X. U., Pingyi, W. A. N. G., & Tao, Y. U. (2015). Exper-
imental studies of safety scope for ships’ anchorage under
landslide generated waves. Yangtze River,46(15), 78–81.
https://doi.org/10.16232/j.cnki.1001-4179.2015.15.019
Han, L. F., Wang, P. Y., Wang, M. L., & Liu, Y. (2019). Motion charac-
teristics of cataclastic rockslides and change rules of impulse
waves in near-field zone. Journal of Zhejiang University (Engi-
neering Science),53(12), 2325–2334. https://doi.org/10.3785/
j.issn.1008-973X.2019.12.009.
Huber, A. (Feb 1984). Discussion of “evaluating hazard of
landslide-induced water waves” by Rudy Slingerland and
Barry Voight (November, 1982). Journal of Waterway, Port,
Coastal, and Ocean Engineering,110(1), 111–113. https://doi.
org/10.1061/(ASCE)0733-950X(1984)110:1(111)
Lin, X. S., Luo, H. J., Wang, P. Y., Wang, M. L, Yu, T., & Gong, Y.
H. (2019). Design and implementation of safety assessment
system for landslide surge in river type reservoir. Journal of
Chongqing Jiaotong University(Natural Science),38(1), 55–61.
https://doi.org/10.3969/j.issn.1674-0696.2019.01.09
Qi, H. L. (2008). Study on the evaluation and prevention of geolog-
ical hazards of Highway Subgrade. Xi’an.
Slingerland, R., & VoightPaolo, B. (1982). Evaluating hazard
of landslide-induced water waves. Journal of the Water-
way Port Coastal and Oeean Division,1089(4), 504–512.
https://doi.org/10.1016/0022-1694(82)90165-2.
Wang, W. (2011). Application of analytic hierarchy process in sys-
tem of evaluation for sustainable transport system. Beifang
Jiaotong,7, 68–70. https://doi.org/10.15996/j.cnki.bfjt.2011.
07.020
Wang, Y., et al. (2014). Study on landslide movement and surge
disaster of reservoir. China University of Geosciences Press.
Wang, P. Y., Wang, D. Y., Yu, T., Yang, C. Y., & Chen, L. (2019). Char-
acteristics of landslide surge in mountainous river type reser-
voir and its influence on navigation and prevention technology.
People’s Communications Press. ISBN: 9787114142789.
Wieczorek, G. F., Jakob, M., Motyka, R. J., Zirnheld, S. L., &
Craw, P. (2003). Preliminary assessment of landslide-induced
Wave hazards: Tidal Inlet, Glacier Bay National Park, Alaska
(U.S. Geological Survey Open-File Report.2003:03-100). U.S.
Department of the Interior and U.S. Geological Survey.
Xu, S. B. (1988). Principle of AHP. Tianjin Publishing House.
Yang, Y. H. (2014). Study on the method and application of land-
slide risk assessment. Chongqing Jiaotong University.
Yi, L. X. (2000). Index system design of urban fire risk assessment.
Disaster Science,15(4), 90–94. https://doi.org/10.3969/j.issn.
1000-811X.2000.04.019
Yuan, P. Y., Wang, P. Y., & Zhao, Y. (2019). Model test research on
the propagation of tsunamis and their interaction with navi-
gating ships. Applied Sciences,9, 475. https://doi.org/10.3390/
app9030475
Zhiyou, C. H. E. N. G., Pingyi, W. A. N. G., Chengyu, Y. A. N. G.,
Shixian, W. A. N. G., Jie, Z. H. E. N. G., & Yaling, L. I. (2018).
Control mode of waterway traffic under dangerous mountain
landslide conditions. Journal of Southwest Jiaotong University,
53(4), 92–99. https://doi.org/10.3969/j.issn.0258-2724.2018.
04.012