Abstract
Floods have significantly affected many regions worldwide, imposing economic, social, and psychological consequences on human societies, in recent decades. Rural communities in Iran are particularly vulnerable to floods, and without effective risk reduction systems, the impact can be exacerbated. In this context, this study aims to investigate the role of social capital in enhancing the resilience of rural households against floods in the southwest of Iran. The statistical population includes all rural households in Shushtar County that have experienced floods at least once. The primary tool for data collection was a questionnaire and obtained data were analyzed using structural equation modeling. In examining the situation of confrontation between different groups of people based on the state of social capital and resilience, it can be said that men, older people and people with higher income had more resilience and social capital to deal with floods. In addition, the results revealed that components of social capital (social networks, social solidarity, social trust, social awareness, participation and collection action) explained 68.1% of the variance in the resilience of rural households against floods. Overall, our findings can provide new insights for policymakers in the area, contributing to the reduction of flood impacts and promoting safer living conditions in flood-prone areas.
1 Introduction
Natural hazards constitute one of the primary factors contributing to the increasing prevalence of malnutrition and food insecurity worldwide, particularly in developing countries where vulnerable agricultural communities face greater challenges in coping with climatic adversities (FAO, IFAD, UNICEF, WFP, WHO, 2018; Pham et al., 2020; Shokati Amghani et al., 2022; Savari et al., 2024a). The rise in temperature and other climate-related changes likely amplifies the frequency and intensity of natural hazards, particularly floods, in many Asian countries (Raghavan Sathyan et al., 2018; Sam et al., 2021; Savari et al., 2024b). Flood risk is a manifestation of climate change that is less predictable than other climatic phenomena (Wasson et al., 2020). Additionally, floods can be triggered by the intensity and duration of rainfall, topographical features, and anthropogenic factors (Mamo et al., 2019). Approximately 40% of all natural disasters worldwide result from floods, accounting for nearly 50% of total casualties, with Asia having the highest flood potential (Noji, 1996; Ohl and Tapsell, 2000; Iqbal and Nazir, 2023). Over the past 20 years, the livelihoods of approximately 400 million people were annually affected by floods, resulting in 28,000 flood-related fatalities in Asia between 1987 and 1997 (United Nations University, WHO, 2001; National Disaster Management Authority NDMA, 2022). Studies documented that floods have widespread adverse effects globally (Alhassan, 2020; Ndue et al., 2023), exacerbating regional inequalities (Mohanty et al., 2020). Floods, a natural phenomenon, can have the most significant impact on the world’s human population (Ahmadi et al., 2022). However, individuals residing in flood-prone areas are more vulnerable, with their property and lives at greater risk of damage (Kovacs et al., 2017). Furthermore, this natural disaster can lead to the destruction of crops, and critical infrastructure, and other social damages (Owusu et al., 2016). Besides, floods have far-reaching adverse effects on human health, food security, economic activities, physical infrastructure, natural resources, and the environment (Eze et al., 2018; Savari, 2023; Savari et al., 2023a,b). In addition to direct impacts, these phenomena create other indirect damages such as social unrest, mental distress, and an imbalanced production and consumption system (Iqbal and Nazir, 2023). Consequently, reducing the damages caused by floods remains a significant concern for human societies (Ahmadi et al., 2022).
The heightened concern among policymakers revolves around identifying factors that can contribute to greater resilience of rural households against floods (Alhassan et al., 2019; Thennakoon et al., 2020). The increasing urgency and intensity of climate change have highlighted the significance of resilience as a vital component in rural planning (Leichenko, 2011; Coaffee and Clarke, 2015; Béné et al., 2018; Mustafa et al., 2018). Consequently, resilience becomes crucial for the sustainability of rural households facing both persistent and unpredictable climate shocks, such as floods (Ali and Rahut, 2019; Thennakoon et al., 2020). However, the resilience of rural households is influenced by a multitude of factors during flood events (Deressa et al., 2009). In the contemporary risk management paradigm of flood management, there is an emphasis on the involvement of private stakeholders such as flood-prone residents in participating in risk reduction activities (Bubeck et al., 2017; Wiering et al., 2017). This approach has evolved into a critical aspect of integrated flood management in many countries (Semnan et al., 2023). In this method, rather than relying solely on public protective measures like constructing levees, individuals are expected to take responsibility for preventing and preparing for flood disasters (Semnan et al., 2023). Through collective efforts to mitigate flood risks, individuals can safeguard their properties and those of other households (AIDR, 2017).
One of the crucial factors influencing collective efforts in coping with climate-related disasters, such as floods, is social capital (Azad and Pritchard, 2023). The focus on social capital is particularly important and necessary in developing countries, as stronger social capital can compensate for financial, human, natural, or physical resource deficits (Rockenbauch et al., 2019). Previous studies revealed that this factor plays a role in various aspects of the disaster management cycle, including risk reduction, preparedness, response, and recovery (Savari, 2023). Before the hazard initiation, social capital facilitates information gathering and decision-making, including evacuation plans (Wuepper et al., 2018). During the disaster, this factor enables mutual care and assistance, facilitating the provision of physical, financial, and emotional support. In post-disaster conditions, it can be vital for people’s access to information and resources crucial for reconstruction. Generally, a positive relationship has been found between the presence of social capital and resilience to disasters (Hagedoorn et al., 2019; Wang et al., 2021). In other words, social capital can moderate the effects of climate-related hazards and enhance adaptive capacity and recovery pathways (Smith, 1981; Adger, 2010; Aldrich, 2012, 2014; Klinenberg, 2015; Sadri et al., 2018). In this regard, this research followed three general goals: (i) investigating the state of resilience and social capital of rural households during floods (ii) the effect of social capital on resilience and (iii) formulating practical policies and suggestions for the planners of this it was the field.
1.1 Social capital and resilience
Contemporary perspectives and theories related to natural disaster management and sustainable development aim to create resilient communities in the face of various environmental events. In light of these interpretations, numerous researchers contend that resilience stands as one of the paramount subjects in achieving sustainability (Savari et al., 2023c). Psychologists define resilience as a series of actions aiding individuals in overcoming adversities and stressors (Seyed Akhlaghi and Taleshi, 2018). Furthermore, it was asserted that residing in an environment prone to natural hazards does not inherently involve damage and vulnerability. Instead, the absence of resilience and individuals’ awareness and understanding of the degree, type, and nature of risks can lead to harm (Zhou et al., 2010). Given its dynamic nature and adaptability in the face of challenges, resilience is deemed essential for the psychological well-being of individuals, especially in navigating various stressors and potentially traumatic events (Marschke and Berkes, 2006). In the context of disasters, the development of resilience is seen as a process contributing to both the mitigation and recovery from adverse events, as well as the enhancement of individual capacities to cope with and adapt to changing conditions (Seyed Akhlaghi and Taleshi, 2018).
The concept of social capital emerged in the field of sociology and was first introduced by Bourdieu (1986), who claimed that social capital is a relationships network that aids actors to acquire actual and potential resources. Coleman (1988) subsequently defined social capital as a personal asset determined by structural social resources in terms of functional performance. Besides, Putnam et al. (1994) elevated social capital from an individual level to a collective one, asserting that social capital includes specific features of social organizations such as social trust, social networks, and social norms. In this study, we defined social capital as social relationships and the ability of actors (individuals, groups, or societies) to use these relationships to access financial, emotional, physical, or other resources to meet survival and improvement needs (Savari et al., 2015; Panday et al., 2021). The key dimensions of social capital influencing individuals’ behaviors in the environment include social networks, social awareness, collective action, social solidarity, and social trust (Dolnicar and Hurlimann, 2010; Blackburn, 2013; Savari et al., 2013; Allo and Loureiro, 2014; Fielding and Roiko, 2014; Fikret, 2018; Ito et al., 2018). Table 1 illustrates the relationship between social capital and resilience.
Table 1
| Definition | Relationship to resilience | |
|---|---|---|
| Bonding capital | Bonding capital refers to the communication and interactions between members of a homogeneous society such as neighbors and family members. In this area, there are certain forms of trust and reciprocity (Woolcock, 2001) | During moments of crisis, family members, friends, and neighbors often serve as the initial respondents, disseminating preliminary warning signals (Gawith et al., 2016). They are frequently present on the scene before the arrival of specialists and rescue organizations (Aguirre et al., 1995; Zhao, 2013). These robust connections are crucial for offering temporary shelter, aiding in preliminary reconstruction efforts (e.g., through labor exchange), and contributing to livelihood recovery (e.g., sharing production tools, maintaining livestock in neighboring farms, etc.) (MacGillivray, 2018) |
| Bridging capital | The term “bridging capital” refers to relationships between individuals or groups that are socially and demographically different (e.g., ethnicity, culture, age) and at the same time have a similar social or economic status (Putnam, 1993; Van Deth and Zmerli, 2010) | Access to a diversity of resources, skills, and knowledge that may not be attainable solely through bonding capital is facilitated by bridging capital (Easterly et al., 2006). This capital may represent a crucial prerequisite for adaptation in the face of evolving hazards |
| Linking capital | Linking capital describes relationships that traverse power differentials and authority gradients, such as connections between communities and non-governmental organizations or governmental entities (MacGillivray, 2018) | Linking capital can provide communities with access to a broad spectrum of financial, technical, informational, and logistical support that cannot be internally sourced (Pelling and High, 2005). It can play a crucial role in securing the long-term investments necessary for the reconstruction of social, economic, and physical infrastructures of communities following a disaster (Marin et al., 2015) |
The relationship between social capital and resilience.
2 Materials and methods
2.1 Study area
Shushtar is situated in the northern region of Khuzestan Province and holds significant value due to its abundant water resources (Figure 1). It is a significant agricultural center in Iran, producing crops such as wheat, corn, legumes, and vegetables. Animal husbandry also holds great importance in this country. Over the past years, Shushtar has been repeatedly affected by floods, leading to the inundation of many villages, particularly due to its geographical location within Khuzestan Province.
Figure 1
Case study.
2.2 Study type
This research is quantitative, utilizing field research methods for data collection and adopting a cross-sectional approach in terms of time horizon.
2.3 Statistical population and sampling method
The statistical population of the study includes all rural households exposed to floods in Shushtar County. To estimate the sample size, Krejcie and Morgan (1970) table was used. Accordingly, 400 rural household heads were selected for the study, using a proportional allocation for a stratified sample. Shushtar city has three sector: “Shoaibieh,” “Central” and “Mianab.” At first, it was tried to select two rural district from each sector, and finally, two villages from each rural district were selected for study. In this section, the respondents were classified into two sections. (1) The respondents had sufficient education and were able to read the questionnaire items easily. (2) There were respondents who lacked education and did not have enough power to read the questions. For this group of participants, the interview method was usually used and the items of the questionnaire were read to them and the questionnaire was completed based on their answers (Tables 2, 3).
Table 2
| Components of social capital | Items |
|---|---|
| Social Networks | Agricultural production cooperatives, financial credit funds, and savings (such as rural microcredit funds, family funds, etc.), public welfare organizations, and non-governmental organizations (NGOs) |
| Social solidarity | The social solidarity of the villagers during the floods, the increased cooperation and collaboration, the low level of social differences in the village, the cordial relationship with neighbors and other villagers |
| Social trust | Lending money to friends and acquaintances during floods, lending necessary equipment to friends and acquaintances, accepting guarantees from friends and acquaintances to obtain loans, trusting the words of government officials such as experts and meteorological information experts |
| Social awareness | Exchange of meteorological information on floods, information on adaptation strategies and flood management, more information on habitability through formal and informal mechanisms, and exchange of information on increasing the adaptive capacity of households A village in the face of floods |
| Participation and collection action | Participating in projects to build capacity and strengthen community resilience in dealing with floods, consulting with other villagers in implementing solutions to improve living conditions in the floodplain, providing intellectual advice and opinions in planning and implementing flood management plans, mobilizing local communities to apply flood coping strategies |
Components and items used in measuring social capital variable.
Table 3
| Resilience components | Items |
|---|---|
| Preparation | Use of information from meteorological experts to make the necessary preparations in the event of flooding, use of information from trained forces and local leaders in the event of flooding, and use of local government measures to deal with flooding |
| Response | Using resistant materials in the construction of rural houses, building strong walls and fences against floods, ensuring assets and products in the region, and observing safety points when building houses |
| Rehabilitation and recovery | Participation in the reconstruction and repair of damage after the floods, participation in the relief and rescue of victims during the floods, cooperation in setting up emergency shelters during and after the floods, obtaining public and state aid, both in cash and in kind, and passing it on to the population. Injured people, use the help of doctors and psychologists to treat and restore the morale of the injured |
| Prevention | New plans to reduce flooding in the region, building dams before the floods, moving residential houses in the floodplain, using dams water, and rivers before the rainy season for agriculture |
Components and items used in measuring resilience variable.
2.3.1 Participants
The findings showed that the average age of the respondents was 46.88 with a standard deviation of 11.88 years and the age range of 18 to 71 years. In addition, in terms of gender, 58% were male and 42% female. The average annual income of the examined household was 205.77 million Rials per year with a standard deviation of 85.36 million Rials. Also, the results of the average number of family members showed that it was 4.78 with a standard deviation of 1.63 people.
2.4 Survey instrument
The primary instrument for this research was a questionnaire, comprising two main sections. The first section (i) covered the demographic characteristics of rural households. While the second section (ii) included 27 items related to the measurement of social capital components. These components were based on a theoretical literature review, encompassing social networks (Hillig and Connell, 2018; Kawamoto and Kim, 2019; Panday et al., 2021; Savari and Khaleghi, 2023; Savari et al., 2023d), social solidarity and Participation and collection action (Hillig and Connell, 2018; El Zahed and Habib, 2020; Nugraha et al., 2021; Savari and Amghani, 2022), social trust (Harpham and Dawson, 2006; Savari, 2023), and social awareness (King et al., 2012; Lu et al., 2013; Chen et al., 2014; Martini et al., 2014).
Section (iii) comprised 15 items designed to measure the resilience component based on the Disaster Management Cycle model (Queensland Reconstruction Authority, 2011). This factor assessed preparation, response, Rehabilitation and recovery, and prevention components. The Likert scale (1-very low to 5-very high) was used to measure these components.
2.5 Reliability and validity
Prior to commencing the interviews with farmers, the survey draft and questions underwent a comprehensive evaluation by a panel of experts. This expert panel consisted of professors specializing in agricultural extension and education, environment, psychology, social sciences, and agricultural sciences. Their input was taken into consideration, and necessary revisions were implemented until final approval was obtained. Furthermore, to ensure the reliability of the research instrument, Cronbach’s alpha and composite reliability coefficients were utilized, yielding satisfactory results.
2.6 Data analysis
Following data collection, the gathered information underwent analysis using SPSS and Smart Pls software. Structural Equation Modeling (SEM) is a statistical analysis method for examining structural relationships. It combines factor analysis and multiple regression analysis and is employed to analyze the interconnections between observed variables and underlying constructs (Khoshmaram et al., 2020). One of the most important reasons for researchers to use SEM is to test the theoretical framework of the research along with determining the amount of measurement error (Hoyle, 2012). Smart Pls software is a software that is used to solve problems with the partial least squares method. In this technique and software, unlike other software where sample size and normality of data are important, there is not much sensitivity (Harrington, 2009).
3 Results
3.1 The status of social capital and resilience in the studied groups
In examining the situation of confrontation between different groups of people based on the state of social capital and resilience, it can be said that men, older people and people with higher income had more resilience and social capital to deal with flood (Table 4).
Table 4
| Variables | Category | Social capital (%) | Resilience (%) | ||||
|---|---|---|---|---|---|---|---|
| Low | Medium | High | Low | Medium | High | ||
| Age | Lowest than 20 years | 22 | 38 | 40 | 31 | 43 | 26 |
| 20–40 | 16 | 43 | 41 | 23 | 39 | 38 | |
| More than 40 years | 13 | 37 | 150 | 16 | 42 | 52 | |
| Gender | Men | 17 | 39 | 44 | 13 | 44 | 43 |
| Female | 12 | 51 | 37 | 15 | 49 | 36 | |
| Annual income (tomans) | Lowest than 150 million | 22 | 34 | 46 | 24 | 43 | 33 |
| 100–150 | 19 | 37 | 44 | 13 | 46 | 41 | |
| More than 150 million | 20 | 39 | 41 | 8 | 37 | 55 | |
| Number of family members | Lowest than 3 people | 14 | 23 | 63 | 18 | 38 | 44 |
| 3–5 | 13 | 27 | 60 | 15 | 42 | 43 | |
| More than 3 people | 19 | 25 | 57 | 22 | 39 | 39 | |
The status of social capital and resilience in the studied groups.
3.2 Measurement models
To evaluate the research measurement model, unidimensionality, validity and reliability, and discriminant validity were investigated.
3.2.1 Unidimensionality
Given that the standardized factor loading value (ƛ) for the chosen indicators was statistically significant (above 0.5) at a significance level of 1 % (p < 0.01), it can be concluded that the selected markers exhibit unidimensionality. This finding confirms that the selected indicators accurately measure the research constructs and possess adequate precision (Table 4).
3.2.2 Validity and reliability
Regarding the validity and reliability assessment of the research instrument, the findings indicated that all constructs within the proposed research model exhibited composite reliability (CR) values exceeding 0.60 and Cronbach’s alpha coefficients surpassing 0.70. Furthermore, the average extracted variance (AVE) for all constructs in the proposed research model exceeded 0.50. Consequently, all latent variables within the proposed research model demonstrated favorable reliability and validity (Table 5).
Table 5
| Constructs | Measurement item | Ć› | t | Reliability and validity |
|---|---|---|---|---|
| Social networks | SN1 | 0.752 | 23.587 | AVE: 0.621 CR:0.841 α: 0.758 |
| SN2 | 0.698 | 12.360 | ||
| SN3 | 0.845 | 45.042 | ||
| SN4 | 0.827 | 38.521 | ||
| Social solidarity | SS1 | 0.627 | 32.520 | AVE: 0.607 CR: 0.862 α: 0.790 |
| SS2 | 0.866 | 66.361 | ||
| SS3 | 0.805 | 54.287 | ||
| SS4 | 0.744 | 48.699 | ||
| Social trust | ST1 | 0.784 | 88.631 | AVE: 0.611 CR: 0.901 α:0.840 |
| ST3 | 0.746 | 74.635 | ||
| ST3 | 0.805 | 95.362 | ||
| Social awareness | SA1 | 0.822 | 74.632 | AVE: 0.680 CR: 0.942 α:0.854 |
| SA2 | 0.652 | 33. 250 | ||
| SA3 | 0.761 | 51.249 | ||
| SA4 | 0.808 | 66.523 | ||
| Participation and collection action | PCA1 | 0.755 | 67.635 | AVE: 0.771 CR: 0.958 α: 0.877 |
| PAC2 | 0.882 | 88.360 | ||
| PCA3 | 0.869 | 77.586 | ||
| PCA4 | 0.878 | 84.685 | ||
| Preparation | PR1 | 0.638 | 29.687 | AVE: 0.590 CR:0.866 α:0.746 |
| PR2 | 0.758 | 35.690 | ||
| PR3 | 0.837 | 49.663 | ||
| Response | RE1 | 0.608 | 41.680 | AVE: 0.635 CR: 0.885 α: 0.812 |
| RE2 | 0.855 | 74.157 | ||
| RE3 | 0.890 | 89.249 | ||
| RE4 | 0.628 | 24.453 | ||
| Rehabilitation and recovery | RR1 | 0.844 | 86.630 | AVE: 0.605 CR: 0.856 α: 0.786 |
| RR2 | 0.758 | 45.781 | ||
| RR3 | 0.885 | 102.63 | ||
| RR4 | 0.863 | 98.672 | ||
| RR5 | 0.784 | 74.625 | ||
| Prevention | PRE1 | 0.793 | 56.871 | AVE: 0.572 CR: 0.803 α: 0.755 |
| PRE2 | 0.803 | 87.658 | ||
| PRE3 | 0.673 | 41.875 | ||
| PRE4 | 0.759 | 50.693 |
The results of fitting the research measurement model.
3.2.3 Discriminant validity
The findings displayed in Table 6 revealed that the average square root of the variance extracted for the research constructs (0.781 < AVE < 0.878) exceeded the correlation between them (0.352 < r < 0.635). These results indicate that the discriminant validity of the established structures in the proposed research model was substantiated.
Table 6
| Constructs | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|
| Social norms | 0.788 | |||||
| Social solidarity | 0.425 | 0.799 | ||||
| Social trust | 0.352 | 0.634 | 0.781 | |||
| Social awareness | 0.624 | 0.527 | 0.422 | 0.824 | ||
| Participation and collection action | 0.528 | 0.475 | 0.628 | 0.521 | 0.878 | |
| Resilience | 0.635 | 0.526 | 0.471 | 0.421 | 0.536 | 0.860 |
Correlations with square roots of the AVE.
3.3 Evaluation of the research structural model
To check the fit of the structural model, various indicators were used (Table 7). Based on the suggested values of the provided indicators, it can be concluded that the model has a good fit.
Table 7
| Fit index | SRMR | D-G1 | D-G2 | NFI | RMS-Theta |
|---|---|---|---|---|---|
| Suggested value | <0.1 | >0.05 | >0.05 | >0.90 | ≤0.12 |
| Estimated value | 0.08 | 0.425 | 0.635 | 0.99 | 0.08 |
Summary of goodness of fit indices for the measurement model.
Once the research measurement model was validated, the path analysis method (structural model evaluation) was employed in the subsequent phase to examine the research hypotheses within the proposed research model. Figures 2, 3 illustrate the research path model, showcasing standardized factor loadings that are statistically significant.
Figure 2
Structural model with standardized path coefficients.
Figure 3
The model along with the t-values.
3.3.1 Evaluation of effects
At this stage, the results of the final impact of social capital components on the resilience of rural households are presented. Bootstrapping method was used to check the effects. The results showed that all relationships were significant. Also, the results showed that the components of social capital are able to explain 68.1% of the resilience of rural households in dealing with floods (Table 8).
Table 8
| Hypothesis | Ć› | t | Result | R 2 |
|---|---|---|---|---|
| H1: Social networks → Resilience | 0.190 | 3.139 | Confirm | 0.681 |
| H2: Social solidarity → Resilience | 0.198 | 3.206 | Confirm | |
| H3: Social trust → Resilience | 0.190 | 3.242 | Confirm | |
| H4: Social awareness → Resilience | 0.178 | 3.018 | Confirm | |
| H5: Participation and collection action → Resilience | 0.207 | 3.204 | Confirm |
Results of research structural models.
4 Discussion
This study represents one of the initial efforts in Iran to enhance the resilience of rural households against floods. The previous studies in Iran mainly have focused on assessing the vulnerability of rural households to floods, while limited attempts have been made to strategies for increasing the resilience of rural households. Therefore, the results of this study not only contribute to closing the research gap but also provide new insights for policymakers in this area to improve the resilience of rural households in flood-prone areas. Our findings indicated that social capital can explain 68.1% of the variance in resilience. These results align with those of Hudson et al. (2020), Karunarathne and Lee (2019), Matthews et al. (2020), Rustinsyah et al. (2021), Tammar et al. (2020), Zhang et al. (2020) and emphasize the significance of social capital in mitigating the impacts of climate change. Rural residents are often suddenly exposed to floods, losing their livelihoods without sufficient resources for recovery (Fahad and Wang, 2018; Huong et al., 2019). Therefore, effective strategies to mitigate the effects of climate change, such as social capital, play a crucial role due to its potential to influence economic, social, and psychological aspects (Bourdieu, 1986; Coleman, 1988; Putnam, 1993; Saptutyningsih et al., 2020). Furthermore, social capital can help minimize the damages caused by floods by enabling community members to collaborate and reduce the threats posed by such disasters (Woolcock and Narayan, 2000; Bowles and Gintis, 2002). Hence, social capital emerges as one of the most important solutions for flood reduction. The following section discusses the effectiveness of social capital components on resilience.
The results highlighted that social networks significantly influence the resilience of rural households in facing floods. In other words, social networks, such as friends and family, can influence individuals’ attitudes toward adapting to climate change (Nam et al., 2012), enrich their knowledge (Fankhauser et al., 1999), and facilitate collective actions (Adhikari and Goldey, 2010). These networks play a crucial role in determining the adaptive capacity within communities (Woolcock, 2001). This can be explained by the fact that communities with strong internal and external relationships can mobilize resources and collectively respond to a common goal (Agnitsch et al., 2006; Cinner et al., 2018). Social networks are a vital component in disaster management, linking communities with support agencies, where people can express their needs and provide recovery support (Aldrich, 2012; Carpenter, 2013; Islam and Walkerden, 2015). In addition, the recovery and sustainable management of assets are possible when active social networks are in place (Harrison et al., 2016; Cohen-Salgado et al., 2021). Social networks connect individuals to supportive organizations such as banks, governmental and non-governmental institutions, schools, and housing authorities, contributing to the social and economic development of affected households (Woolcock, 2002).
The second effective component in improving individuals’ resilience against floods is social awareness. Information can be shared through formal mechanisms such as newsletters and informal mechanisms namely oral communication (King et al., 2012; Lu et al., 2013; Chen et al., 2014). Sharing knowledge is considered a significant advantage of perceived social capital, which can create a foundation for enhancing individuals’ resilience (Savari, 2023). Moreover, it can be noted that many rural households are not aware of flood risk reduction methods and coping strategies (Rustinsyah et al., 2021). In this context, social capital can enhance their resilience by facilitating information sharing (Savari, 2023). Additionally, as natural disasters increase in various communities, there is a continuous search for the discovery and invention of solutions to control or minimize the damages caused by unexpected events such as floods. In other words, the main goal is to control these disasters, and social awareness can provide the basis for this management.
The third effective component in enhancing the resilience of rural households is participation and collective action. Social capital, encompassing dimensions such as awareness, trust, solidarity, network contribution, and relationships between members, plays a valuable role in collective action for protection and coping with environmental challenges (Pumcave, 2016). Social capital improves the flow of information among individuals, making activities more visible and serving as a framework for future collaboration (Fikret, 2018). Colmen proposed that social capital encompasses aspects of social structure and facilitates the actions of agents (Vasylchenko et al., 2018). Therefore, it helps beneficiaries collaborate and commit to group obligations, aiding in the execution of protective programs (Bourdieu, 1977; Vadapalli, 2012). Moreover, many flood mitigation activities require social support and collective action, as individuals alone may not be able to undertake activities such as building embankments and protective walls.
The fourth effective component in improving the resilience of rural households against floods is social solidarity. This factor, as one of the dimensions of social capital, involves a strong link between people’s participation in protective activities (Niazi, 2011) and establishes a foundation for social unity and solidarity (Savari, 2023). Expanding social capital leads to increased social solidarity, and social convergence, enhanced individual and group social-economic participation, and creates opportunities for the formation of organizations (Blackburn, 2013). The organizations’ establishment can contribute to increased resilience against floods in two ways: (1) Social groups provide a platform for exchanging information and awareness among rural households, fostering discussions on flood mitigation methods, and identifying the most critical solutions collaboratively. (2) Many social groups, such as microcredit funds, have an economic nature and are formed by rural households to assist each other with minimal resources. These funds can be effective in the economic recovery of individuals during natural disasters.
Ultimately, the fifth effective component in improving the resilience of rural households is social trust. Trust is defined as the expectations in a society for consistent, honest, and participatory behaviors based on common norms among its members (Fukuyama, 1996). This factor, as conceptualized by Putnam and Coleman, is one of the social capital components. Coleman believes that in a group where members are trustworthy and have high mutual trust, they will be able to accomplish much more than in a group lacking trust (Colman, 2008). Honesty and trust encourage individuals to engage in cooperative and collaborative activities, fostering an environment for growth and advancement (Savari, 2023). Additionally, during floods, when individuals lose their economic capabilities and require more support, mutual trust allows them to help each other more effectively and obtain essential resources. Savari and Abdeshahi (2019) documented that trust in rural communities leads to increased resilience in rural households. In rural communities, reciprocal activities, exchange of goods, and financial assistance are more effective when relationships are based on trust, helping to mitigate the impacts of natural disasters.
5 Conclusion and limitations
In conclusion, this study aimed to explore the role of social capital in improving the resilience of rural households against floods in the southwest of Iran. The results demonstrated that social capital components (social networks, social solidarity, social trust, social awareness, participation and collection action) can explain 68.1% of the resilience of rural households. Floods have a severe negative impact on the livelihoods of rural households who need emotional, economic, physical, and other forms of support that social capital can provide, making it easier for them to cope with such conditions. Despite the valuable results of the study, it is imperative to recognize three limitations: First, while explaining only 68.1% of the variance is considered acceptable in the context of social research, suggests potential for enhancement through the identification of additional dimensions of social capital. Second, the research only focused on social capital; future studies should consider other variables such as economic, cultural, and psychological factors. Third, caution is warranted in generalizing the results to other areas worldwide, given the variability in the effects of floods across different regions attributable to numerous factors.
Statements
Data availability statement
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
Ethics statement
All interviewees were informed about data protection issues by the enumerators and gave their consent orally at the beginning of each interview. Informed consent was obtained from all individual participants included in the study. All materials and methods are performed in accordance with the instructions and regulations and this research has been approved by a committee at Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Author contributions
MS: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review editing. AJ: Methodology, Software, Writing – original draft. AS: Project administration, Resources, Writing – original draft.
Funding
The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. The current paper is adapted from a research assigned in Agricultural Sciences and Natural Resources University of Khuzestan, with a Grant Number of 1402.01, and financially supported by the university; thereby we declare our appreciation for their help.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
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Summary
Keywords
natural hazards, social participation, capacity building, empowerment of rural households, Iran
Citation
Savari M, Jafari A and Sheheytavi A (2024) The impact of social capital to improve rural households’ resilience against flooding: evidence from Iran. Front. Water 6:1393226. doi: 10.3389/frwa.2024.1393226
Received
05 March 2024
Accepted
29 April 2024
Published
22 May 2024
Volume
6 - 2024
Edited by
Sarva Mangala Praveena, Universiti Putra Malaysia, Malaysia
Reviewed by
Masoud Bijani, Tarbiat Modares University, Iran
Naser Valizadeh, Shiraz University, Iran
Updates
Copyright
© 2024 Savari, Jafari and Sheheytavi.
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*Correspondence: Moslem Savari, Savari@asnrukh.ac.ir
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