







































F. Estelaji et al. /Future Technology                                                                                                May 2024| Volume 03 | Issue 02 | Pages 
11-21 

11 

 

 

 

Article 

Earthquake, flood and resilience management 

through spatial planning, decision and information 

system 
Faraz Estelaji1, Niloofar Moniri2, Mohammad Hossein Yari3, Reza Omidifar4*, Rahim Zahedi5, 

Hossein Yousefi5, Mansour Keshavarzzadeh6 

 1Department of Construction Engineering and Management, Faculty of Civil Engineering, Khajeh Nasir Toosi University, 

Tehran, Iran 
2Department of Structures and Earthquake Engineering, Faculty of Civil Engineering , Khajeh Nasir Toosi University, 

Tehran, Iran 
3Department of Structures and Earthquake Engineering, Faculty of Civil Engineering, Sharif University of Technology, 

Tehran, Iran 
4Faculty of Governance, University of Tehran, Tehran, Iran 
5Department of Renewable Energy and Environmental Engineering, University of Tehran, Tehran, Iran 
6Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa 

A R T I C L E   I N F O 
 

Article history: 
Received 16 July 2023  
Received in revised form 
18 August 2023 
Accepted 26 August 2023 
 
Keywords:  
Flood zoning, Earthquake zoning, Resilience 
 
*Corresponding author 
Email address: 
m.omidi93@ut.ac.ir 
 
 
DOI: 10.55670/fpll.futech.3.2.2 
 

A B S T R A C T 
 

Assessment and planning of crisis management with the natural disasters 
approach include many components. In this regard, floods and earthquakes are 
some of the fundamental pillars in this field. With this view, paying attention to 
the current and future planning and research priorities of the world shows that 
crisis management in flood-prone and earthquake-prone areas and increasing 
resilience are the most important priorities for sustainable development 
studies and planning in the world. The western region of Iran (Lorestan 
province) has a special place due to the prominent features of flood and 
seismicity. This study aims to investigate the current situation regarding floods 
and earthquakes and increase the resilience of settlements with emphasis on 
the study area. After studying the current structure of flood and earthquake 
zoning according to multi-factor criteria, zoning was performed based on the 
integration of GIS and AHP information systems, and at the output of the work, 
high-risk settlements were determined separately for rural and urban areas 
with geographical coordinates, and then areas with low, very low, medium, 
high, and very high resilience were presented separately for rural and urban 
settlements. Also, after analyzing the SWOT model, strategies to increase the 
resilience of settlements to floods and earthquakes were presented. The study 
method of this research and the results, strategies, and operational options 
presented while being used in the study area are also applicable in other areas. 

1. Introduction 

Evaluation and planning of crisis management with the 
approach of natural earthquake disasters include many 
components. In this regard, one of the fundamental pillars of 
construction management is based on resilience [1]. With this 
view, paying attention to the world’s current and future 
planning and research priorities shows that construction 
management in earthquake-prone areas is one of the most 
critical priorities for sustainable development studies and 
planning in the world. According to the studies, Iran is one of 

the earthquake-prone areas, and according to the 
earthquakes that have occurred, a lot of casualties and 
infrastructure have been witnessed in Lorestan province [2]. 
The study of residential constructions in the study area shows 
that with the construction management approach, many 
buildings have been built and are being built in this area, 
which has many challenges from the crisis management 
approach [3]. In this regard, the main direction of earthquake 
zoning research in the Lorestan region is to develop strategies 
to increase resilience. Earthquake is one of the most 

 

 

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F. Estelaji et al. /Future Technology                                                                                                May 2024| Volume 03 | Issue 02 | Pages 11-21 

12 

 

devastating natural disasters due to its unpredictability. In 
the last thirty years (1990-2020), seven hundred and six 
earthquakes have occurred worldwide, killing 380,000 
people and causing significant material damage [4]. 
Approximately, 77% of these casualties were in China, Iran, 
Pakistan, Russia, India, and Turkey [5]. Evaluation is one of 
the most effective solutions to reduce the effects of 
earthquakes. Assessing the vulnerability of existing buildings 
is a kind of prediction of their damage in the face of possible 
earthquakes. Seismic hazard assessment is related to four 
elements: seismic hazards, hazards, location, and 
vulnerability. A flood is a combination of short currents in a 
particular place with a steep slope that usually occurs in 
impermeable and low-strength rocks and formations and 
consists of three main parts: catchment area, waterway, and 
alluvial fan [6]. All rainfall in the catchment area is combined 
into small streams to provide considerable flow in a large 
stream that is narrow and somewhat long [7]. The basis of the 
formation of irregular discharges due to sudden and heavy 
rains is often in the form of showers that occur in feeble and 
intermittent currents [8]. Floods are characterized by solid 
detection currents that arise after each storm on bare and 
unstable ground and in waterways that have been previously 
dug by water currents and often on steep mountain slopes 
and are often highly destructive in terms of severity [9]. 
Therefore, most villages and towns located at the foot of the 
mountains are constantly at risk of this phenomenon [10].  
There are two major natural disaster risk reduction types: 
Structural and non-structural risk reduction, often referred to 
as hard and soft risk reduction [11]. Structural risk reduction 
(hard); This type of risk reduction involves the strengthening 
of buildings and infrastructure at risk in various ways 
(building codes, design, advanced engineering, advanced 
construction technology, etc.). Non-structural risk mitigation 
(soft); This type of risk mitigation includes directing 
development away from known hazardous areas or high-risk 
sites, moving existing product that is likely to be frequently 
damaged to safer areas, and maintaining more protective 
environmental features normal. For example, dunes, forests, 
and vegetated areas can absorb and reduce the effects of 
hazards through land use plans and regulations. Non-
structural risk reduction also includes addressing the specific 
needs of at-risk populations. This category includes housing 
needs as well as other quality-of-life issues. While it is often 
more difficult to implement non-structural risk mitigation, 
this type of hazard mitigation has tremendous value in 
reducing risk and costs [12]. 

The application of the concept of resilience to natural 
hazards was initially considered a legal argument in assessing 
natural hazards.  While Eiser et al. suggested resilience to a 
community's ability to recover using its resources [13], Cox et 
al. [14] also focused on community resilience, describing it as 
a process of linking adaptive capacities (such as social capital 
and economic development) to responses and changes after 
adverse events. In this regard, resilience is a set of capacities 
that can be developed through interventions and policies, 
which help build and increase society's ability to respond and 
recover, and achieve improvement from risks. One very 
different concept is risk engineering resilience, emphasizing 
buildings and critical infrastructure resilience. Shakou et al. 
[15] proposed a resilience framework with an emphasis on 
structural modification, in particular, the concepts of 
engineering systems that include robustness, excessive 
frequency, resourcefulness, and speed of action. Recent 
research has focused on flexibility and resilience from a 
national security perspective, primarily on protecting critical 

infrastructure from terrorism and resilience on critical 
infrastructure. Assuming that resilience is the result of 
measuring an ultimate goal of limiting damage to 
infrastructure [16]. Disaster resilience is important to 
understand and reduce the damage caused by natural hazards 
[17]. Due to different types of hazards and different spatial 
characteristics, it isn't easy to get a general and uniform 
understanding of the resilience of other geographical areas. 
But disaster resilience must be constantly considered, and the 
resilience of vulnerable areas must be improved. Disaster 
resilience analysis requires physical, socio-economic 
information of many places, each of which has a unique 
geographical location. While there are currently three 
problems for researchers in the field of resilience studies: 
• At the conceptual or perceptual level, resilience from a 

geographical point of view lacks a clear explanation. 
• At the operational level, modeling the resilience of 

individual, group, and community behavior in a single 
framework is difficult. 

• At the application level, resilience can hardly be 
transferred at different spatial scales. 

The resilience models used so far are shown in Table 1. The 
components of resilience in infrastructure used by previous 
research are listed in Table 2. 
In this research, Lorestan earthquake and flood zoning is 
done in the GIS system, and strategies to increase resilience 
are presented. Compared to other studies, the innovation in 
this study is the use of new approaches and the integration 
of quantitative and qualitative models in evaluating and 
presenting resilience strategies against floods and 
earthquakes. 

2. Methodology 

The type of research is applied in terms of purpose and 
descriptive-analytical, and exploratory in terms of method 
and nature. Descriptive-analytical research is divided into 
two categories in-depth and expansive research [38]. This 
type of research is also called survey research. 

2.1 Seismic zonation of Lorestan 
Different layers of information and sources were 

examined. According to the factors affecting the occurrence 
of the earthquake and based on the characteristics of 
Lorestan province, the following factors were selected as 
effective factors. 
• Fault: This layer includes all faults in the area that are 

separated from active and inactive fault maps. According 
to the regulations approved by the Ministry of Housing 
and Urban Development, the boundaries of the main faults 
are 1000 meters, and sub-faults are 300 meters on each 
side. Therefore, in these borders, the creation of any 
building and any activity accompanied by crowds should 
be prevented. 

• Earthquake centers: This layer is based on the epicenter 
of earthquakes that have occurred in the past. If we draw 
a vertical line from the epicenter of the earthquake that is 
inside the earth to the surface of the earth, the place where 
this line collides with the earth's surface is called the 
center of the earthquake. 

2.2 Flood zonation of Lorestan 
In general, the steps of the current zoning were done in 

the form of two main steps; Collecting the required data and 
preparing information layers. At this stage, by reviewing the 
previous data, the necessary data and information have been 
collected from various sources, and adequate information 
layers on flooding have been prepared.  



F. Estelaji et al. /Future Technology                                                                                                May 2024| Volume 03 | Issue 02 | Pages 11-21 

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Table 1. Disaster resilience models 

 

 

 

 

 

 

 
 
 
 
 
 
 
 
 
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Geological maps of Lorestan province, digital elevation model 
of Lorestan province (DEM), land use map, hydrometric 
information and waterways of the region, and rainfall data 
have been collected. The collected information has been 
analyzed using the GIS system, and the decision tree diagram 
has been compiled as criteria and sub-criteria. The effective 
boundaries of each criterion are identified in flood potential 
and weighted and standardized by the analytic hierarchy 
process (AHP) method. The degree of importance of the 
criteria is estimated, and a flood zoning map is prepared by 
combining all criteria. Different layers of information and 
sources were examined. According to the factors affecting the 
occurrence of floods, based on the characteristics of Lorestan 
province, the following factors were selected as influential 
factors: 
• Slope: This layer is the topographic slope of the area. Land 

use: This layer includes various natural and unnatural 
benefits. 

• Rainfall: This layer includes the average annual rainfall in 
different areas of the province 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

• Waterway density: This layer includes the main and 
secondary waterways of Lorestan province.  

• Soil erosion: This layer contains geological information 
and soil formations. 

2.3 Resilience zonation of Lorestan 
Different layers of information and sources were 

examined. According to the factors affecting resilience and 
based on the characteristics of Lorestan province, the 
following factors were examined as effective factors for 
zoning resilience in Lorestan province. 
• Distance from flood areas: This factor was considered so 

that according to the results obtained in flood-prone 
zoning, the closer it is to the areas that had a very high and 
high potential for flooding, the less its resilience and the 
less to areas with less risk. In terms of flooding, the closer 
it gets, the more its resilience increases. 

• Distance from seismic areas: This factor was considered 
so that according to the results obtained in the seismic 
zoning of the region, the closer it is to the areas that had 
very high and high seismic potential, the less resilience 

Model Property 

Tobin model [18] 

This model has been proposed to study and evaluate the resilience of communities located in high-risk 

areas, the framework of which is more ecological. To show how the society is stable and resilient, three 

models: risk reduction to study risk reduction plans, recovery model to recover physical capital structure, 

public and private attitudes, and strategies, and finally, structural-demographic model to study the factors of 

structural and material changes. Culturally and economically used. These are interrelated and affect 

sustainability goals; Finally, in this model, the characteristics of a stable and resilient society are introduced. 

The ultimate goal of this framework is to achieve the degree of sustainability and resilience of communities 

to technological and natural hazards. The focus of this model is on risk reduction in such a way that 

sustainable and resilient societies are societies that structurally reduce the consequences of disasters and 

rapid recovery by rebuilding vital socio-economic factors of society. 

Linear-temporal 

Davis model [19] 

According to the definition of resilient society, it shows that a country or a large urban area in the form of a 

timeline in specific circumstances following development can improve its vulnerability over time. This 

model has three stages: Absorption and tolerance of stress and impact before the accident Return to balance 

after a disaster means the ability and capacity to go back during and after disasters changes in societies to 

make them safe and resilient. 

Spatial model 

(DROP) [20] 

Designed to provide the relationship between resilience and vulnerability, a comparative assessment of 

disaster resilience at the local and community levels. This model defines resilience as a dynamic process 

dependent on previous conditions, the severity of disasters, time between risks, and extroverts' effects. The 

first step of this model is to provide a proposed set of infrastructural, social, economic, and institutional 

variables. The next step in this model is to operate and create a set of indicators and then examine it in the 

real world. 

Baseline index model 

[21] 

This model provides a methodology and a set of indicators for measuring the existing effective conditions for 

disaster recovery in communities. Its method is to use a hybrid index to determine and achieve specific 

variables to create a collective scale of resilience. To determine the indicators from the spatial model of 

resilience (DROP) in which the relationship between vulnerability and resilience is determined and also 

focuses on the previous conditions, and based on the dimensions of resilience, the desired indicators were 

formed from these dimensions and used for analysis; Finally, this model gives the results of a quick 

comparative overview of which methods and dimensions in resilience-based indices are needed more than 

others; It also determines what infrastructural, economic, institutional, and physical interventions 

contribute to the overall well-being of society. 

Community Based 

Disaster 

Management (CBDM) 

[22] 

This model is a bottom-up management approach that focuses on people's participation in solving disasters 

caused by natural disasters, which aims to reduce communities' vulnerability and strengthen people's 

capacity and participation to deal with the risks of natural disasters. 

 

 



F. Estelaji et al. /Future Technology                                                                                                May 2024| Volume 03 | Issue 02 | Pages 11-21 

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and the closer to the areas where the risk is less 
seismically, the higher the resilience. 

• Distance from main roads: Main roads play a significant 
role in resilience during natural disasters such as floods 
and earthquakes. Thus, when faced with a crisis, 
communication channels play a very key role in restoring 
the performance of infrastructure and residential areas to 
their pre-crisis state, and the closer the crisis area is to the 
main roads, the more possibility of providing assistance to 
those areas from other provinces and the other regions 
that are not in crisis are more easily done. In other words, 
the reconstruction of crisis areas and the return to the 
pre-crisis state in these areas take less time. As a result, 
the closer the surveyed areas are to the main roads, the 
more resilient those areas will be. 

• Distance from open spaces and shelters: Distance from 
open spaces and shelters Outdoors plays an important 
role in the aftermath of a crisis, so much so that after a 
crisis, the possibility of transporting the injured and using 
this type of space as an emergency accommodation is one 
of the most important indicators in the study of resilience. 

2.4 Criteria weighting using Analytic Hierarchy Process 
(AHP) technique 
After selecting the effective criteria in zoning to combine 

them in the form of information layers, the weight of each 
criterion should be determined in proportion to their 
importance following one of the weighting methods [39]. 
Given that some of the selected criteria are quantitative and 
some qualitative, we must use a method that can compare and 
quantify quantitative criteria with qualitative, which is one of 
the weighting problems in multi-criteria decision-making. 
The given weight is included in the evaluation as a number, 
which indicates the relative importance of that criterion 
compared to other criteria.  

Table 2. Components of resilience in infrastructure  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

In this research, a hierarchical analysis method has been 
used to weigh the criteria. 

2.5 Combining effective layers 
One of the essential stages of zoning after determining 

the criteria and weighting is that the information layers are 
combined using a suitable method [40]. This operation can be 
a spatial operation that combines several geographical layers, 
and then the information is Slow, defined. In order to produce 
a map of Lorestan's vulnerable zones, the system analyzer 
was entered into the GIS environment. The weights obtained 
in the adequate zoning layers were multiplied, and obtained 
each criterion's coefficient in the Arc map environment using 
the Raster command. The calculation of the coefficients for 
each standard in the scoring map is multiplied by the same 
criterion. Then all these multiplied maps in the coefficients 
get Over Lay and scalarly obtained, and a final map is obtained 
in which each pixel has a specific value. The combination of 
sub-criteria together is such that the weight obtained from 
the AHP method in expert choice software for each sub-
criterion in the relevant layer was performed by the RASTER 
CALCULATE command in ARC GIS software, and the final 
Lorestan earthquake, flood, and resilience maps were 
obtained. According to the weighting done, it is observed that 
the standard weight of an earthquake has the highest weight 
in resilience, as shown in Figure 1, because it is related to 
human lives and also because the financial damage it causes 
is much more than other crises. 

2.6 SWOT Matrix 
By Comparison pair of internal strong points, a 

comparison pair of internal weak points, a comparison pair of 
external opportunity points, a comparison pair of external 
threat points, and a pairwise comparison of external threats, 
the SWOT matrix will be reached in Table 3. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 
 

Dimensions  of  resilience 

T
ran

sp
o

rt n
etw

o
rk

 

W
astew

ater 

In
frastru

ctu
re (w

ater 
electricity, gas) 

IT
 in

frastru
ctu

re
 

b
u

ild
in

gs 

b
rid

ges 

E
m

ergen
cy

  service
  cen

ters 
(fire, em

ergen
cy) 

Fleischhauer [23] * * *  *   

Burby et al. [24] * * *     

Mitchell et al. [25]  * *     

Saunders et al. [26] *     *  

Sharifi et al. [27]    * *  * 

Rega et al. [28]     *  * 

Meshkini et al. [29] *       

Nakanishiet al. [30] * *   *   

Pokhrel et al. [31]    * *  * 

Mehmood et al. [32]  * *     

Brugmann [33]  * *     

Lunecke [34] * * *    * 

Johnson [35]   *     

Villagra et al. [36] * * *     

Sharifi et al. [37] * * * *   * 

 

 

 

 

 



F. Estelaji et al. /Future Technology                                                                                                May 2024| Volume 03 | Issue 02 | Pages 11-21 

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Figure 1. Weight of criteria obtained in expert choice software 

 

Table 3. SWOT matrix strategies [41] 

 Strong Points Weak Points 

Opportunities SO Strategy WO Strategy 

Threats ST Strategy WT Strategy 

 

SO strategy: By using internal strengths, external 
opportunities can be exploited, or in other words, the strategy 
is to make maximum use of environmental opportunities by 
using the strengths of the organization or system. 
ST Strategy: Reduce the effects of external environmental 
threats by using strengths or, in other words, usage strategies 
maximum strengths to avoid threats. 
WO strategy: Maximizing the opportunities in the external 
environment to improve internal weaknesses, or in other 
words, the strategy of compensating for the existing 
weaknesses by using the benefits that lie in the opportunities 
to compensate for the weaknesses, is the function of the WO 
strategy. 
WT strategy: Reducing internal weaknesses by avoiding 
external environmental threats or in other words minimizing 
the damage caused by threats and weaknesses with the aim 
of reducing internal weaknesses and avoiding external 
environmental threats is the function of WT strategy. 

3. Results and Discussion 

3.1 Seismic maps of Lorestan 
The earthquake center layer is based on historical 

earthquakes that occurred in Lorestan province. The 
occurrence of a large number of earthquakes in a place that 
has almost no faults indicates the possible presence of hidden 
faults in this part of the region. Therefore, increasing the 
thickness of the crust in these areas is an effective factor in 
hiding faults affecting the seismicity of the province. Figure 2 
shows the map of Lorestan's active and inactive fault layers, 
standardization of the density layer of Lorestan faults, 
Lorestan earthquake centers, and standardization of the 
density layer of earthquake centers. Lorestan seismic 
zonation layer was obtained by combining the standard fault 
density and earthquake center density layers with the 
RASTER CALCULATE command in ARC-GIS software. Figure 3 
shows the final Seismic zonation of Lorestan. 

 
Figure 2. Map of Lorestan active and inactive fault layers, 
standardization of the density layer of Lorestan faults, Lorestan 
earthquake centers, and standardization of the density layer of 
earthquake centers 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 3. Finale seismic zonation map of Lorestan 

 
According to the seismic hazard zoning map, it can be seen 
that the eastern and northeastern regions of Lorestan have 
the highest seismic hazard. The further we go to the 
province's west, the seismic hazard decreases. The cities with 
the highest seismic hazards are: Borujerd, Aligudarz, Durud, 
and Azena. Cities with moderate seismic hazards are: 
Khorramabad, Dore, and Selsele. The cities with the lowest 
seismic hazard are: Delfan, Kohdasht, and Poldokhtar. In 
areas with less seismic risk, it does not mean that these areas 



F. Estelaji et al. /Future Technology                                                                                                May 2024| Volume 03 | Issue 02 | Pages 11-21 

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are completely safe against earthquakes, and this issue is 
expressed compared to other areas of Lorestan. As can be 
seen on the map, most earthquakes occurred in areas with 
active faults, but in addition, areas such as the north of 
Poldakhtar, Bakhtar Kuhdasht, and parts of Khorramabad are 
the focus of earthquakes. Probably, this phenomenon can be 
attributed to the existence of hidden and covered faults under 
sediments, which despite their activity, did not have a surface 
outcrop. 

3.2 Flood maps of Lorestan 
In addition to the verification performed with field 

evidence and the ongoing floods, the comparison and analysis 
of the prepared map with the previous research of the flow 
statistics of hydrometric stations is another proof of the 
accuracy of the zoning. Among the factors influencing the 
occurrence of floods, slope factors, rainfall intensity, and 
physiographic characteristics are the most critical factors in 
causing floods. According to the final output, these points are 
flood-prone and high-risk areas. Such issues are mainly in the 
eastern parts and parts of the northeast of Lorestan province. 
The map of different layers for flood zoning is shown in Figure 
4. By combining the five flood criteria types, the final flood 
map of Lorestan is achieved, as shown in Figure 5. 

3.3 Resilience maps of Lorestan 
According to the standardized map of the main roads, as 

we move from the green areas to the red areas, due to moving 
away from the main roads, the reduction decreases 
considering this index. The status of the study area in terms 
of outdoor access is shown in Figure 6. The study of the 
geographical location of this index shows that the Lorestan 
region is in a favorable condition in terms of access to open 
spaces, and in general, there are two protected shelters in this 
province, one with an area of 90186.3 hectares in the east of 
the province and the other with an area of 71214.6 hectares 
in West of the province, according to the standardized map, 
the closer the affected areas are to the shelters, the sooner the 
relief operation will be carried out, and the more favorable 
the situation will be in terms of resilience. After weighing 
criteria in GIS with raster calculation, the final resilience map 
of Lorestan is achieved, as shown in Figure 7.  

To prepare an external factors evaluation matrix, it is 
necessary to perform the above steps. The difference is that 
in this matrix, on the one hand, the factors that cause the 
opportunity and situation of development in the future. On 
the other hand, the external factors that threaten this 
development are listed in this matrix. In the next step, after 
coding each of the factors in the internal and external 
matrices with a systemic approach to these factors, as shown 
in Tables 4 to 7, the appropriate strategies are determined as 
a combination of the mentioned factors in the form of SWOT 
4-cell table and based on the frequency of strategies in the 
relevant house, its position is determined in the 4-cell SWOT 
table in terms of determining the general policy in adopting 
an appropriate development strategy. In the inner and outer 
square matrix, the sum of the final scores from 1 to 2.5 
indicates the internal weakness, and the score of 2.5 to 4 
indicates the strength. Similarly, the sum of the final scores of 
the external factors evaluation matrix from 1 to 2.5 indicates 
the level of threat, and the scores of 2.5 to 4 indicate the 
amount of opportunity. Being located in each of the internal 
and external matrix cells has four specific strategic concepts. 

 

 

 

 

 

 

 

 

 

 

 

 
Figure 4. Map of Lorestan for land use, slope, rainfall, waterway 
density, and soil erosion flood criteria 

  

 

 

 

 

 

 

 

 

 

 

Figure 5. Finale flood zonation map of Lorestan 

 



F. Estelaji et al. /Future Technology                                                                                                May 2024| Volume 03 | Issue 02 | Pages 11-21 

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Table 4. Internal weakness SWOT matrix 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 5. Internal powers SWOT matrix 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Internal 
weaknesses (w) 

Description 
Weight 

(AHP) 
Score 

Final score 
(coefficient * 

score) 

w1 Low financial ability to strengthen housing by the people 0.052 3 0.156 

w2 
Low credits of local institutions for the purchase and 
protection of accident-prone lands 

0.057 2 0.114 

w3 
Lack of solid supervision over construction control in flood 
and earthquake-prone areas by the responsible institutions 

0.0585 3 0.1755 

w4 Construction in the river area 0.064 2 0.128 

w5 
Lack of strong supervision over construction control in 
flood and seismic zones by the responsible institutions 

0.0365 3 0.1095 

w6 Lack of dredging rivers 0.0605 2 0.121 

w7 
Increasing the level of soil erosion, especially fertile soil in 
the region by river runoff 

0.0765 2 0.153 

w8 
Degradation of pastures and forests, change of land use 
pattern, and incorrect land reclamation due to low 
knowledge 

0.044 3 0.132 

w9 The location of many villages in the area of faults 0.051 3 0.153 

Total    1.242 

 

 

 

 

 

 

 

 

 

Internal 

powers (S) 
Description 

Weight 

(AHP) 
Score 

Final score 

(coefficient * 

score) 

s1 
Existence of public desire to participate in the transfer of flood-
prone and earthquake-prone lands to the government, subject 
to awareness and support 

0.0555 
1 0.0555 

s2 
The activity of villagers as executive arms in villages to attract 
public participation for land management 

0.0365 2 0.073 

s3 Existence of empty spaces in some of the studied areas 
0.0915 3 0.2745 

s4 Existence of primary ways to access 
0.048 2 0.096 

s5 Planning and prioritizing programs and crisis preparedness 
0.091 3 0.273 

s6 
Efforts to establish and strengthen emergency operations 
centers 

0.0525 1 0.0525 

s7 
Provide the necessary validity, financial resources, and 
structural mechanisms to prepare for the crisis 

0.0325 2 0.065 

s8 
Apply sufficient standards for the construction of buildings and 
urban development plans 

0.0425 3 0.1275 

s9 
Existence of open and empty spaces in the city for the 
construction of parks and public spaces 

0.05 1 0.05 

Total    

1.067 

 

 

 

 

 



F. Estelaji et al. /Future Technology                                                                                                May 2024| Volume 03 | Issue 02 | Pages 11-21 

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Table 6. SWOT matrix of external threats 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 7. External Opportunity SWOT Matrix 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

External 

threats (T) 
Description 

Weight 

(AHP) 
Score 

Final score 

(coefficient * 

score) 

t1 
Lack of planning based on the return period of floods and 
earthquakes and the threat posed by it in the province 

0.053 
3 0.159 

t2 
Weak monitoring of river area and the plan implemented in the 
flood watershed by the responsible institutions 

0.0365 3 0.1095 

t3 Weak construction monitoring in the fault area 
0.063 2 0.126 

t4 
Weakness is having a comprehensive local, regional and national 
flood warning and information system 

0.09 4 0.36 

t5 
Counting style of enforcing the laws related to the privacy of 
rivers and faults and dealing with its aggressors 

0.06 2 0.12 

t6 
Lack of attention to the participation of people and their 
indigenous knowledge in the management of local floods by the 
authorities 

0.0635 2 0.127 

t7 Earthquake history in the region 
0.0455 3 0.1365 

t8 Rapid population growth and density 
0.0385 1 0.0385 

t9 History of floods in the area 
0.05 4 0.2 

Total    
1.3765 

 

 

 

 

 

 

 

 

 

 

External 

Opportunities 

(O) 

Description 
Weight 

(AHP) 
Score 

Final score 

(coefficient * 

score) 

o1 
Provide credit assistance for the reconstruction of flood and 
earthquake damage by the government 

0.045 
2 0.09 

o2 
The willingness of the responsible institutions for education, 
awareness-raising, holding flood and earthquake maneuvers, and 
determining hazardous areas and public awareness 

0.1005 2 0.201 

o3 
Efforts of responsible institutions to plant trees around rivers and 
watershed management, prevent livestock grazing, change land use 
in flood-prone areas for special uses 

0.0535 2 0.107 

o4 
Improving services and infrastructure facilities of the water supply 
network, telecommunications, the electricity company, and surface 
water disposal 

0.029 2 0.058 

o5 Emphasis on regeneration of worn tissues 
0.041 3 0.123 

o6 Existence of regulations 2800 tenet of construction standards 
0.0605 3 0.1815 

o7 
Utilizing the educational potential of the Red Crescent for public 
education 

0.0705 1 0.0705 

o8 Strengthen the culture of crisis preparedness at the provincial level 
0.0565 1 0.0565 

o9 
Raising the attention of the authorities to the earthquake in the 
region, emphasizing the optimal management of information and 
communication in times of crisis 

0.0435 2 0.087 

Total    
0.9745 

 

 

 

 

 



F. Estelaji et al. /Future Technology                                                                                                May 2024| Volume 03 | Issue 02 | Pages 11-21 

19 

 

 

 

 

 

 

 

 

 

 
 
 
 
 

 
Figure 6. Map of the main communication network, standardized 
main road layer, and open spaces layer of Lorestan 

 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Figure 7. Finale resilience zonation map of Lorestan 
 
 
As can be seen, the total score of internal factors is 2.309, 

which is less than 2.5, indicating an internal weakness 
according to our current plan. In the matrix of external 
factors, it can be seen that the total of external scores is equal 
to 2.351, which is less than 2.5, which indicates that the 
conditions of this sector are also unfavorable and more 
external threats threaten the plan. The combination of 
internal and external factors for the SWOT matrix is shown in 
Table 8. According to the results, the most significant number 
obtained is related to WT factors, project weaknesses, and 
threats. In this case, defensive strategies should be adopted, 
and the project position is risky. 

 
 

Table 8. Combination of internal and external factors 

 

4. Conclusion 

The required data and information have been collected 
from various sources, and practical information layers in 
earthquakes and floods have been prepared by reviewing the 
previous data. The collected information was analyzed using 
the GIS system, and the decision tree diagram was compiled 
as criteria and sub-criteria. The effective boundaries of each 
criterion in earthquake and flood potential were identified, 
weighed, and standardized by the analytic hierarchy process 
(AHP) method. The degree of importance of the criteria was 
estimated and by combining all the requirements. According 
to the output map of cities with high potential in terms of 
zoning and low resilience are: Khorramabad, Borujerd, Pol-e 
Dokhtar, Azna, Oshtorinan, Noorabad, Aleshtar, Kakareza-ye 
Sofla, Sepiddasht, Qolian, and Chalanchulan. Based on the 
SWOT analysis, it is concluded that the eastern and 
northeastern regions of the province had the highest 
potential in terms of flooding, and the central and northern 
regions of the province had the average potential in terms of 
earthquake. The southern and western regions of the 
province had the lowest earthquake and flood potentials, 
therefore Lorestan should be in a defensive position, WT, 
which is the riskiest position. Therefore, the following 
operational strategies and options can be considered for 
urban and rural areas of Lorestan. Suggestions for increasing 
earthquake resilience are: 
• Increase physical strength in residential buildings to 

reduce damage with proper management and preparation 
of construction criteria with special attention to the 
seismic characteristics of each area. 

• Implementation of resilience, renovation, and 
reconstruction programs in dilapidated and semi-resilient 
areas to increase their resilience and obligation to carry 
out zoning plans and make them operational in areas with 
active faults in the region. 

• Acquisition of fault lands by the public sector and 
prevention of construction strengthens the role and 
efficiency of open spaces. 

• Plan to organize the communication network to connect 
with sensitive uses such as hospitals and fire brigades to 
prepare for crises. 

• Identifying barren lands and their ownership and 
replacing them with the use of green and open space, as 
well as providing urban facilities and equipment and fair 
distribution of urban facilities and services in proportion 
to the population of neighborhoods and the level of 
vulnerability. 

Suggestions for increasing flood resilience include: 
• Flood reduction through basin-level construction 

methods such as the use of dry-stone dams and use of 
diversion channels. 

• Flood reduction through construction methods specific to 
urban and rural lands, such as the use of water gates and 
use of flood block heritage flood guards. 

foreign causes internal factors 

T(threat) 
O 

(opportunity) 

W 

(weakness) 

S 

(strength) 

1.3765 

 

0.9745 

 

1.242 

 

1.067 

 

Total coefficients of composite factors 

WO ST WT SO 

2.2165 

 

2.4435 

 

2.6185 

 

2.0415 

 



F. Estelaji et al. /Future Technology                                                                                                May 2024| Volume 03 | Issue 02 | Pages 11-21 

20 

 

• Flood reduction through ineffective development 
methods for runoff disposal like vegetable swale and 
porous Asphalt. 

• Management strategies to mitigate and mitigate the 
effects of floods like observance of the privacy of canals 
and rivers and zoning of flood plains, continuous flood bed 
control, creating permeable surfaces in the city and not 
converting free lands into urban structures, converting 
the lowlands of large cities into parks and green spaces 
and reduce river slope. 

Ethical issue 
The authors are aware of and comply with best practices in 
publication ethics, specifically with regard to authorship 
(avoidance of guest authorship), dual submission, 
manipulation of figures, competing interests, and compliance 
with policies on research ethics. The authors adhere to 
publication requirements that the submitted work is original 
and has not been published elsewhere. 

Data availability statement 
Datasets analyzed during the current study are available and 

can be given following a reasonable request from the 

corresponding author. 

Conflict of interest 

The authors declare no potential conflict of interest. 

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