Water is the prerequisite for human adaptation to climate change and is the key link among climatic conditions, humans, and the environment. Human behavior can mitigate the impacts of climate change. The present study aimed to evaluate rural people's readiness for sustainable management of water resources. To achieve this goal, the Theory of Planned Behavior (TPB) and Health Belief Model (HBM) were used as the research framework. The research instrument was a closed-end questionnaire developed on the basis of TPB and HBM. The face and content validity of the questionnaire was confirmed by a panel of experts in sustainable agriculture. Its reliability was also checked in a pilot study by calculating Cronbach's alpha, the average variance extracted (AVE), R2, and composite reliability (CR). The research sample was composed of 480 villagers from Hamadan province, Iran, who were familiar with sustainable water resources management in the context of the rooftop rainwater harvesting project. The results showed that in TPB, the variables of moral norms, attitude, and self-identity could account for 61 percent of the variance in rural people's intention to adopt the practices of sustainable water resources management. Based on HBM, the variables of perceived benefits, perceived susceptibility, and perceived severity could capture 49 percent of this variance. The results revealed that both theories had the potential to predict rural people's intention to engage in the sustainable management of water resources, but TPB proved to provide a more robust prediction than HBM.

  • Moral norms, attitude, and self-identity had significant effect on rural people's intention to adopt the practices of sustainable water resources management.

  • Perceived benefits, perceived susceptibility, and perceived severity could capture 49 percent of this variance.

  • TPB proved to provide a more robust prediction than HBM.

In addition to its vital role in the survival of humans, water is the cornerstone of sustainable development and is necessary for socio-economic development and a safe environment. Water is the prerequisite for human adaptation to climate change and is the key link of climatic conditions, human society, and environment. However, water is a finite and irreplaceable source that is renewable if it is well managed (Ataei et al. 2018; Shahid et al. 2018; Izadi et al. 2019; Valizadeh et al. 2019; Veisi et al. 2020). Nonetheless, presently over 1.7 billion people reside around rivers and they use this renewable source extravagantly. In its latest annual report, the World Economic Forum has identified the water crisis as the biggest global threat due to its potential impacts (Mekonnen & Hoekstra 2016). This risk is especially grave in low-water areas because the global water cycle will intensify due to climate change in the near future, and consequently the wet regions will become wetter and the arid regions will be more arid (WWAP 2018). There is no doubt that Iran is experiencing a water crisis. Various scholars and experts have repeatedly voiced their concerns about the water crisis (Motiee et al. 2001; Foltz 2002; Madani Larijani 2005; Karbalaee 2010; Yazdanpanah et al. 2013a, 2013b; Shojaei-Miandoragh et al. 2019). In Iran, more than 90% of water is consumed in rural and agricultural areas (Yazdanpanah et al. 2014). Water conservation and management is the most important strategy for planning and managing water in the future and represents one of the most important environmentalist activities (Gilbertson et al. 2011; Saurí 2013; Adams 2014).

In the last decade, sustainable water management has become a serious concern in the world and in Iran (Yazdanpanah et al. 2015). In this regard, a wide range of solutions has been put forth which can broadly be divided into two categories of supply-oriented management solutions and demand-oriented management solutions (Yazdanpanah et al. 2016). Traditional management has generally been supply-oriented, and many researchers argue that this approach is not appropriate given the current water conditions (Hurlimann et al. 2009). This has led to a shift in paradigm towards a demand-oriented approach globally (Jorgensen et al. 2009; Russell & Fielding 2010; Beal et al. 2013). Demand-oriented management is a useful solution that can have a significant impact, especially on the conservation of limited water resources (Brooks 2006; Russell & Fielding 2010). This management approach offers a variety of sustainable and environmentally, socially and economically friendly solutions to water conservation (White et al. 2007). They include initiatives such as efficiency enhancement, price increases, economic motives, and non-price options such as promoting voluntary conservation of water (Cary 2008; Hurlimann et al. 2009; Beal et al. 2013; Adams 2014; Yazdanpanah et al. 2016). This management strategy can be viable and effective if it has been voluntarily adopted and implemented by villagers and farmers, so these policies rely heavily on the behavior of consumers and society (Bayard & Jolly 2007).

In general, the current policies to encourage people to ‘change their behavior’ can be either economic or psychosocial (Jackson 2005; Bayard & Jolly 2007; Hassell & Cary 2007; Collier et al. 2010; Siebert et al. 2010; Bamberg 2013). Economic policies, such as economic incentives (tax and subsidy), may change behavior without changing underlying attitudes and motivations. Thus, if these policies are abandoned or modified, the behavior change may not be sustained and it may revert to its initial state (Collier et al. 2010). On the other hand, psychosocial policies can achieve sustainable changes by changing people's priorities, reinforcing social norms, and/or influencing their attitudes. These policies play two primary roles in understanding what causes behavior change. In the first place, they provide an exploratory framework to examine and conceptualize consumer behavior. In the second place, these models can be used as a framework for empirically testing the power of various relationships (e.g., between values and behavior) under different conditions (Jackson 2005). In this kind of policymaking for behavior change, it is commonplace to use psychological methods and psychosocial models in the initial examination of behavior. Numerous models and theories have been developed to induce changes in human behavior. Since in the context of sustainable water resource management, villagers are crucial decision-makers in implementing policies, it is imperative to analyze their behaviors and the factors that influence their intention (Siebert et al. 2010). So far, various forms of behavioral models, such as the Theory of Reasoned Action (TRA) and its developed form, Theory of Planned Behavior (TPB), have been used in social psychology. TPB is a very functional and comprehensive model to study behavioral change. Also, the Health Belief Model (HBM) is an accepted model to explain why people do not engage in preventive activities, or why there is no interest in preventive activities in society (Strecher & Rosenstock 1997).

Another theory of behavior is the health belief model. This theory focuses on changes in people's beliefs and argues that changes in beliefs lead to changes in behaviors (Glanz et al. 2008; Namdar et al. 2012). HBM has been used in various studies on sustainable agriculture and conservation. For example, it has been applied in research on the willingness to use biofuels in agriculture (Bakhtiyari et al. 2017), environmental issues such as well water testing (Straub & Leahy 2014), the use of pesticides (Khan 2010; Bay & Heshmati 2016; Yazdanpanah et al. 2016), and farmers' intention to undertake food safety measures at farms (Rezaei & Mianaji 2019).

Factors that influence rural people's behavior towards sustainable management of water resources are much more complex than expected, such as place attachment, environmental attitudes and beliefs (Shojaei-Miandoragh et al. 2019), self-efficacy, psychological needs, and time perspective (Sadeghi et al. 2019), governmental policies, and mass media (Ataei et al. 2019), environmental value attitudes, beliefs, and norms (Veisi et al. 2020), farmers' intention, self-efficacy, and social-structural factors (Valizadeh et al. 2019), moral norms, social pressures, social responsibility, and satisfaction of water resources management (Valizadeh et al. 2018). Therefore, it seems necessary to examine their behaviors as the first and utmost important chain of an economic system. In this regard, the present research aims to shed light on Iranian rural people's intention to engage in the sustainable management of water resources by providing practical and basic information and data. The research will establish knowledge that will lead to public policymaking that will ultimately result in the adoption of a sustainable water resources management plan. It is also crucial to consider different strategies for rural people's decisions regarding sustainable water resources management with an emphasis on rainwater harvesting. These people's intention was evaluated by two theories – TPB and HBM.

TPB started as the Theory of Reasoned Action in 1980 to predict an individual's intention to engage in a behavior at a specific time and place. The theory was intended to explain all behaviors over which people have the ability to exert self-control. The key component to this model is behavioral intent; behavioral intentions are influenced by the attitude toward the likelihood that the behavior will have the expected outcome and the subjective evaluation of the risks and benefits of that outcome. The intention of the individual largely reflects his personal attitudes, or his perception of the extent of favorability of an act. The subjective norms that the individual is exposed or privy to will also have an impact on his intentions. This is in recognition of man being, by nature, a social creature, so that he will no doubt care about what others think or believe. The intentions and the resulting behaviors of the individual are affected by their perceived behavioral control, or what they think and believe to be their ability to actually perform or engage in the said behaviors (Ajzen 2002).

Although TPB has been proven to be predictive of behavior, it has also been shown that the inclusion of some other variables, such as moral norms and self-identity, in the theory can enhance its predictive power (Kaiser 2006; Fielding et al. 2008; Nigbur et al. 2010; Whitmarsh & O'Neill 2010). The limitation of TPB has led scholars to add a new dimension to the TPB itself. In other words, it was necessary to add a new dimension while using TPB as a foundation in the theoretical framework. Most scholars (Ajzen 1991; Sánchez et al. 2018; Tommasetti et al. 2018; Hafaz et al. 2019) accentuated the adding of some other variable which might provide a fuller explanation of the intended behavior of the study. The variables representing TPB are referred to the cognitive determinants that would involve the person's behavior (Rivis et al. 2006). Since it is linked to cognitive characteristics, the construct that could be a moderator for the study must also be linked up to the cognitive component. Therefore, this field would try to use self-identity as a moderator for the study since self-identity is also part of the cognitive ingredients and it considers rural people's needs prior to engaging in sustainable water management. Nigbur et al. (2010), Kaiser (2006), Whitmarsh & O'Neill (2010), and Fielding et al. (2008) confirmed that self-identity has a strong effect on people's behavior. Furthermore, the health belief model is used to overcome the limitations of TPB in this study.

There is ample evidence to include moral norms in TPB (Kaiser & Scheuthle 2003; Burton 2004; Arvola et al. 2008; Moradhaseli et al. 2017). This variable is important for understanding behaviors that are interpreted ethically. Water conservation and management is a kind of moral behavior. Moral norms are one of the fundamental cognitive–social factors that shape behavioral intentions (Bamberg 2013) and influence people's decisions (Bamberg & Schmidt 2003). Similarly, there is evidence to include self-identity as another predictive variable of behavioral intentions in TPB (Sparks & Shepherd 1992; Whitmarsh & O'Neill 2010). According to Stryker's theory, self refers to a set of social roles; that is, the extent to which a person views himself or herself as a criterion for specific social roles (Pelling & White 2009) In fact, self-identity is a label people use to describe themselves and is expected to have a significant impact on behavioral intention (Cook et al. 2002).

In TPB, an individual's behavior is determined by his or her behavioral intention; in other words, behavioral intention predicts an individual's behavior (Kaplan et al. 2015). Based on this theory, behavioral intention is a function of three factors – attitude, subjective norm, and perceived behavioral control (Ajzen 1991). Attitude towards a behavior is a person's overall assessment of the behavior. Subjective norms include a person's belief about whether others (parents or friends) think he or she should display the behavior (Lajunen & Räsänen 2004; Şimşekoğlu & Lajunen 2008). A person's belief in the results of behavior and his or her assessment of these results shape attitude. Subjective norms refer to the perceived pressure by individuals who are important in a person's life to perform or not to perform a particular behavior (Dezham et al. 2015). Perceived behavioral control shows an individual's perception of how easy or difficult it is to perform a behavior (Lajunen & Räsänen 2004). This theory holds that when people evaluate a behavior to be positive and know that important and influential people will approve it, they will decide to perform that behavior (Mohammadi Zeidi et al. 2013). Ajzen (2002) argues that TPB is capable of expanding and incorporating other variables.

Health Belief Model (HBM)

HBM is based on the assumption that a person will accept a health-related action if he or she feels that it will protect him or her against an ailment. In this model the person has a positive expectation – health and prevention of illness by accepting advice; that is, he expects that he will not become infected by accepting the advice and that he believes that by heeding the advice, he will succeed in achieving the goal (Yazdanpanah et al. 2015). In other words, this theory emphasizes how an individual's perception generates motivation and movement and shapes behavior. HBM focuses on two aspects of health behavior, including perceived threat (the problem perceived by the person) and behavioral assessment (the balance between benefits and obstacles) (Vassallo et al. 2009).

HBM is composed of seven constructs pertaining to behavior persistence. They include perceived severity, perceived susceptibility, perceived benefits and barriers, perceived self-efficacy, health motivation, and cues to action. Perceived severity refers to the perception and belief that the problem is serious and that it can lead to death or other serious consequences for the individual. Perceived susceptibility is the individual's perception and belief that he or she is exposed to the risk of an ailment. Perceived benefits are defined as a person's belief in the effectiveness of the recommended activities in mitigating the risk or the severity of the effect. Perceived barriers refer to a person's belief in the objective and mental costs of the recommended activities. Perceived self-efficacy is an individual's perception of his or her ability to pursue a behavior. Cues to action mean that reinforcing forces make one feel the need to do something. Finally, health motivation refers to an individual's desire for health-and-safety activities. Therefore, according to this theory, an individual is very likely to perform the recommended behavior if he or she (i) feels the status of local water resources is in critical condition, (ii) feels that the status of local water resources is a serious issue for him or her, (iii) feels that it is in his or her interest to perform the behaviors of sustainable water resources management, (iv) feels that he or she is faced with few obstacles to perform the behavior, (v) will, in the meantime, receive motives for the behavior, and (vi) has the sense of self-efficacy or ability and self-confidence to perform the behavior.

The theory holds that the decision to follow health behaviors is more likely to be made when people want to stay healthy and believe that such behaviors will improve their health (Abbaszadeh et al. 2013). In addition to changing attitude, HBM is effective in keeping or stopping a behavior with the different training pivots that it has (Sadeghi Sedeh et al. 2015). In Iran, no study has ever measured the aspects of HBM and TPB in the context of rural people's conservative behaviors in the sustainable management of water resources. However, studies like Cazacu et al. (2014) have revealed that knowledge, benefits, attitude, and social communications are influential on people's intention. Arvola et al. (2008) found that moral norms played an important role in individuals' intentions. Suprapto & Wijaya (2012) concluded that attitude directly influenced intention. Pino et al. (2012) reported that ethical motivations influenced consumers' intentions whereas the safety and health of products affected occasional consumers' intentions. Numerous studies have supported the role of perceived barriers as a strong predictor of people's protective behavior (Raksanam et al. 2012; Coppens 2016). Raksanam et al. (2012) argue that there is an inverse relationship between perceived barriers and farmers' protective behaviors in the use of pesticides; in other words, the more the people's perceptions are of how to remove barriers, the more likely it would be for them to perform protective behaviors.

The present study aimed to evaluate the constructs of HBM and TPB in adopting protective behaviors for the sustainable management of water resources among rural people in Hamadan province, Iran. In this study, we attempted to analyze the dimensions of the models before planning because understanding these factors will help planners develop more effective plans based on HBM and TPB. By drawing on the research findings and emphasizing the constructs that predict behaviors, they can make more accurate plans to encourage farmers to show sustainable management behaviors when using water resources.

Rooftop rainwater harvesting (RRWH) technologies

RRWH systems are used to collect rainwater from roofs and other areas. The systems employ gutters and pipes to convey water to storage tanks or cisterns. The pipes and gutters are made of wood, bamboo, galvanized iron sheets or PVC. The tanks are usually made of iron sheets. Pipes and all conveying ducts may be blocked by dust, leaves, sand, insects, or bird droppings, so filters are mounted at their entrance on the roof (Figure 1). Water collected in the tank may be extracted by a faucet, manual bucket, or water pump (Lim & Jiang 2013). If constructed soundly, water collection structures will have a favorable impact on the deposition of clay and organic matter in floodplains on rocky, light-textured soils so that they will improve soil physical and chemical properties and vegetation cover. On the other hand, flood control by these structures will increase water penetration into soil and soil moisture retention, thereby enhancing vegetation cover (Abdollahi et al. 2015). It can also provide the water needed for agricultural and livestock applications in times of water scarcity (Rockström et al. 2010). In their study of the effects of rainwater harvesting on water resources in the semi-arid regions of South Africa, Welderufael et al. (2013) concluded that this method had a significant effect on annual water yield and the recharge of water resources. In an attempt to estimate a rainwater harvesting cistern along with reducing costs in the USA, Pelak & Porporato (2016) suggested the use of a rainwater harvesting system to tackle the problem of global water resources scarcity.

Figure 1

A rooftop rainwater harvesting system.

Figure 1

A rooftop rainwater harvesting system.

Close modal

This research was an applied study in terms of purpose and a descriptive study based on structural equations modeling (SEM) in terms of data collection. The research population consisted of 9,856 rural people in Asad Abad and Nahavand cities, Hamadan province, who were trained in sustainable water resources management techniques including rainwater harvesting. The sample size was determined to be 480 people by Bartlett's table, who were taken by a proportionally allocated stratified randomization technique. Data were collected by interviews using a structured questionnaire that was developed after a comprehensive review of the literature. Research variables included attitudes, subjective norms, perceived behavioral control, moral norms, behavioral intention, self-identity, perceived susceptibility, perceived severity, self-efficacy, perceived benefits, perceived barriers, health motivation, and cues to action, which were measured on a six-point Likert scale (none, very low, low, moderate, high, very high). Previous studies (Şimşekoğlu & Lajunen 2008; Vassallo et al. 2009) were also used to measure the constructs of the variables. The face and content validity of the questionnaire was checked by a panel of experts in different disciplines including plant protection, environmental psychology, and agricultural extension and training, for which the average variance extracted (AVE) index was calculated. To assess the reliability of the questionnaire, a pilot study was carried out on farmers who were outside the research population and Cronbach's alpha and composite reliability (CR) were calculated. Data were analyzed in the SPSS22 and Spart PLS software packages.

Hamadan province is located in the west of Iran (Figure 2), where it is prone to be affected by drought. Different research studies anticipated that climatic variables and the occurrence of extreme events in this area have changed in the last decades and will change even more in the future. For example, IMO (2013) indicated that the mean temperature of the area will increase by 0.5–0.8 °C and annual precipitation will drop off about 23 mm in the short period of 2010–2039 in comparison with the base period of 1976–2005. Furthermore, Nazari et al. (2016) illustrated the amount of rainfall decreases for the period 2045–2065 almost from −1.4 to −6.1 percent. The results of Jamshidi et al. (2019) showed that the annual precipitation of the area declined while the value of the Standardized Precipitation Index (SPI) index increased. Also, the drought intensity maps illustrated that intensity regions appear with those stations that have high underground water table deficits. Mohammadian Mosammam et al. (2015) concluded that yields of rainfed wheat would decrease in Hamadan province primarily because of decreasing precipitation and higher temperature. During the ten-year period, 22.9% and 15.6% of Asad Abad and Nahavand counties and 15.4% and 6.2% of their population were affected by drought, respectively (NDWMC 2020).

Figure 2

Location of the study area.

Figure 2

Location of the study area.

Close modal

Demographic characteristics

The demographic characteristics of the respondents indicated that in terms of gender, 86% were male and 14% were female. In terms of educational level, 59% had less than a bachelor's degree, 25% had a bachelor's degree, 12% had a master's degree, and 4% had a PhD degree. In terms of age, 27%, 43%, and 20% were in the age ranges of 30–40, 40–50, and >50 years, respectively. Regarding work experience, 30% had 0–10 years of experience, 46% had 10–20 years of experience, and 24% had 20–26 years of experience. Among the respondents, 64% lived in rural areas and 36% in urban areas.

Prioritization of extended TPB and HBM components

The components of TPB were described by the Friedman test. The results show that rural people differed significantly in their different psychological criteria about sustainable management of water resources so that the first three priorities for the farmers were attitude (3.68), moral norms (3.26) and perceived behavioral control (3.11), respectively (Table 1). This means that sustainable water resources management, including rainwater harvesting, was not a familiar topic for the participants in the general dimension (subjective norms), but it was a familiar topic personally (self-identity).

Table 1

Prioritization of the psychological components of rural people concerning sustainable water resources management

ComponentsMdfChi-squareSig
Attitude 3.68 228.88 0.000 
Moral norms 3.26 
Perceived behavioral control 3.11 
Self-identity 3.04 
Subjective norms 1.86 
Perceived susceptibility 3.88 301.18 0.001 
Perceived benefits 3.48 
Perceived severity 3.36 
Health motivation 3.24 
Perceived barriers 2.18 
Cues to action 2.11 
Perceived self-efficacy 2.01 
ComponentsMdfChi-squareSig
Attitude 3.68 228.88 0.000 
Moral norms 3.26 
Perceived behavioral control 3.11 
Self-identity 3.04 
Subjective norms 1.86 
Perceived susceptibility 3.88 301.18 0.001 
Perceived benefits 3.48 
Perceived severity 3.36 
Health motivation 3.24 
Perceived barriers 2.18 
Cues to action 2.11 
Perceived self-efficacy 2.01 

The components of HBM were also examined by the Friedman test. According to the results, there were significant differences among HBM components in terms of sustainable water resources management so that the first four priorities for farmers were perceived susceptibility (3.88), perceived benefits (3.48), perceived severity (3.36), and health motivation (3.24), respectively. These findings imply that rural people are highly sensitive to the use of sustainable water resources management and tend to use such solutions and most villagers are influenced by the benefits of using rainwater.

Structural equation modeling of rural people's intention to manage water resources sustainably

The estimation of the measurement model

We used composite reliability (CR) to measure the reliability of the questionnaire and the average variance extracted (AVE) to measure its diagnostic validity. For CR, a value of above 0.7 indicates acceptable reliability (Raykov 1998). The acceptable level of the AVE is 0.5 (Iglesias 2004). Also, factor loads are calculated by measuring the correlation value of the indices of a variable with that variable. If this value is equal to or greater than 0.4, it confirms that the reliability of the measurement model is acceptable (Raykov 1998). R2 values also indicate the extent to which the endogenous constructs of the research model are predictive. It is worth noting that its value is calculated only for the endogenous variables of the model (Table 2). Divergent validity examines the relationship of a latent variable or aspect with its own questions in the comparison of the relationship of that variable with other latent variables.

Table 2

Measurement coefficients, validity, and reliability of latent traits

ComponentsαAVEFactor loadingCRR2
Attitude 0.81 0.621 0.82 0.712 0.76 
Subjective norms 0.82 0.662 0.81 0.822 0.73 
Perceived behavioral control 0.77 0.612 0.73 0.762 0.70 
Self-identity 0.74 0.711 0.79 0.719 0.37 
Moral norms 0.83 0.732 0.88 0.825 0.48 
Intention 0.77 0.821 0.91 0.721 0.53 
Perceived susceptibility 0.84 0.631 0.89 0.821 0.56 
Perceived severity 0.88 0.745 0.91 0.752 0.48 
Perceived benefits 0.81 0.611 0.84 0.711 0.75 
Perceived self-efficacy 0.83 0.614 0.81 0.814 0.73 
Perceived barriers 0.73 0.615 0.77 0.743 0.72 
Cues to action 0.71 0.711 0.83 0.689 0.37 
Health motivation 0.81 0.717 0.86 0.789 0.48 
Intention 0.76 0.812 0.81 0.825 0.69 
ComponentsαAVEFactor loadingCRR2
Attitude 0.81 0.621 0.82 0.712 0.76 
Subjective norms 0.82 0.662 0.81 0.822 0.73 
Perceived behavioral control 0.77 0.612 0.73 0.762 0.70 
Self-identity 0.74 0.711 0.79 0.719 0.37 
Moral norms 0.83 0.732 0.88 0.825 0.48 
Intention 0.77 0.821 0.91 0.721 0.53 
Perceived susceptibility 0.84 0.631 0.89 0.821 0.56 
Perceived severity 0.88 0.745 0.91 0.752 0.48 
Perceived benefits 0.81 0.611 0.84 0.711 0.75 
Perceived self-efficacy 0.83 0.614 0.81 0.814 0.73 
Perceived barriers 0.73 0.615 0.77 0.743 0.72 
Cues to action 0.71 0.711 0.83 0.689 0.37 
Health motivation 0.81 0.717 0.86 0.789 0.48 
Intention 0.76 0.812 0.81 0.825 0.69 

Correlations of the components of TPB and HBM with rural people's intention

The Pearson correlation test was used to gain a better insight into the relationship between different variables of the model (Table 3). According to the correlation matrix, intention was positively and significantly related to attitude, moral norms, and self-identity. But, subjective norms and perceived behavioral control were not significantly related to intention. Accordingly, only three variables of attitude, moral norms, and self-identity were included in the structural model of the research in SEM.

Table 3

Correlation matrix of TPB variables

Components123456
1. Attitude      
2. Subjective norms 0.015     
3. Perceived behavioral control 0.008 0.034    
4. Moral norms 0.39** 0.031 −0.017   
5. Self-identity 0.27* 0.41** 0.24** 0.33**  
6. Intention 0.51** 0.04 −0.013 0.42** 0.39** 
Components123456
1. Attitude      
2. Subjective norms 0.015     
3. Perceived behavioral control 0.008 0.034    
4. Moral norms 0.39** 0.031 −0.017   
5. Self-identity 0.27* 0.41** 0.24** 0.33**  
6. Intention 0.51** 0.04 −0.013 0.42** 0.39** 

**p < 0.01; *p < 0.05.

Correlation analysis between HBM components and rural people's intention to manage water resources sustainably showed a positive and significant relationship of intention with perceived susceptibility, perceived severity, perceived benefits, perceived self-efficacy, and health motivation. But, it did not significantly relate to cues to actions and perceived barriers (Table 4). Thus, the five components of perceived susceptibility, perceived severity, perceived benefits, perceived self-efficacy, and health motivation were included in the structural model of the study.

Table 4

Correlation matrix for the variables of HBM

Components12345678
1. Perceived susceptibility        
2. Perceived severity 0.44**       
3. Perceived benefits 0.32** 0.49**      
4. Perceived self-efficacy 0.01 0.01 0.19**     
5. Perceived barriers 0.04 0.01 0.01 0.18**    
6. Cues to action 0.02 0.01 0.13 0.01 0.04   
7. Health motivation 0.29** 0.23** 0.26** 0.14* 0.31** 0.37**  
8. Intention 0.29** 0.32** 0.42** 0.19* −0.06 −0.002 0.24** 
Components12345678
1. Perceived susceptibility        
2. Perceived severity 0.44**       
3. Perceived benefits 0.32** 0.49**      
4. Perceived self-efficacy 0.01 0.01 0.19**     
5. Perceived barriers 0.04 0.01 0.01 0.18**    
6. Cues to action 0.02 0.01 0.13 0.01 0.04   
7. Health motivation 0.29** 0.23** 0.26** 0.14* 0.31** 0.37**  
8. Intention 0.29** 0.32** 0.42** 0.19* −0.06 −0.002 0.24** 

**p < 0.01; *p < 0.05.

The estimation of the structural model

After estimating the measurement model, the second step was to estimate the structural model of the research, in which the significance of the path coefficients assumed for the research model was checked. Before calculating the path coefficients, the fitness indices were first examined for both HBM and TPB. To determine the extent to which the models were consistent with the data used, the overall fit of the model was evaluated by fit indices. The results revealed that the reported indices for TPB and HBM had the acceptable values for the overall fit of the models (Table 5). It can, therefore, be stated that in general, TPB and HBM were compatible with the data used.

Table 5

The fit indices of the structural model

TestRecommended valueHBMTPB
Relative Fit Index RFI > 0.90 0.94 0.92 
Adiusted Goodness-of-Fit Index AGFI > 0.90 0.92 0.91 
Root Mean Squared Error RMSEA < 0.08 0.06 0.06 
Goodness-of-Fit Index GFI > 0.90 0.94 0.94 
Comparative Fit Index CFI > 0.90 0.96 0.94 
Normed Fit Index NFI > 0.90 0.95 0.95 
TestRecommended valueHBMTPB
Relative Fit Index RFI > 0.90 0.94 0.92 
Adiusted Goodness-of-Fit Index AGFI > 0.90 0.92 0.91 
Root Mean Squared Error RMSEA < 0.08 0.06 0.06 
Goodness-of-Fit Index GFI > 0.90 0.94 0.94 
Comparative Fit Index CFI > 0.90 0.96 0.94 
Normed Fit Index NFI > 0.90 0.95 0.95 
The results of the analysis of the structural part of TPB showed a positive and significant effect of moral norms on rural people's intention to engage in sustainable management of water resources (β = 0.16). Also, the effect of attitude on intention was significant at the 1% level (β = 0.31). It was also found that self-identity affected rural people's intention to engage in sustainable management of water resources significantly at the 1% level (β = 0.21; Figure 3). Therefore, the results reveal that an individual will tend to engage in sustainable management of water resources instead of general and unsustainable approaches if he or she has a positive attitude towards it, feels obliged to adopt this approach, gains a better feeling by adopting it, and perceives sustainable management of water resources as an indicator of his or her identity. However, the results did not show any significant impacts of perceived behavioral control or subjective norms on their intention. This means that force by others and families will not be effective in their intention to manage water resources sustainably. Also, since the R2 value is 0.61, overall the variables of ethical norms, attitude, and self-identity account for 61% of the variance in rural people's intentions to engage in sustainable water resources management. In most studies that used TPB (Chen 2016; van Dijk et al. 2016; Gao et al. 2017), attitude has played the most important role in determining behavioral intentions, which confirms our findings. Also in many studies (e.g. Olsen et al. 2010; Menozzi et al. 2015; Shin & Hancer 2016), after attitude, moral norms have been the second most important variable predicting behavioral intention to engage in water conservation. A similar result was obtained in the present work for moral norms. Previous studies on the influence of moral norms on people's intentions have yielded different results. For example, Arvola et al. (2008) and Kaiser (2006) have shown that moral norms have a significant effect on people's intentions. With regard to the variable of self-identity, it can be said that people who feel more self-confidence for sustainable management of water resources are more likely to engage in water conservation behaviors. In other words, rural people who perceive the role of conservation and sustainable management of water resources to be an important part of their identity have a greater incentive to participate in sustainable behaviors. Other studies in different contexts have shown that self-identity has a significant effect on people's intentions (Sparks & Shepherd 1992; Cook et al. 2002; Burton 2004; Pelling & White 2009; Nigbur et al. 2010; Whitmarsh & O'Neill 2010). Finally, the Goodness-of-Fit (GOF) criterion was used as per the procedure provided by Tenenhaus et al. (2004) to evaluate the general fit of TPB:
Figure 3

Structural model of TPB.

Figure 3

Structural model of TPB.

Close modal
The overall fit of the model is calculated as below:

The test result for the model fit index is 0.718. Since the minimum acceptable value for this index is 0.36, it can be claimed that the research model has a good fit.

According to the analysis of the structural part of HBM, perceived benefits had a positive significant effect on rural people's intention to sustainably manage water resources (β = 0.24). This implies that rural people's beliefs about the effectiveness of the recommended practices are effective in their intention to adopt the practices of sustainable water resources management. Also, the effect of perceived severity was significant (p < 0.01) on intention (β = 0.11). In other words, if rural people perceive that drought and water scarcity are serious problems that can create a crisis or other serious consequences for them, their intention to use sustainable water resources management practices will be strengthened. The effect of perceived susceptibility was significant (p < 0.01) on rural people's intention to manage water resources sustainably (β = 0.16; Figure 4). However, we observed no significant effect of cues to action, perceived barriers, and self-efficacy on rural people's intention. Furthermore, as the R2 value of 0.49 shows, the variables of perceived benefits, perceived severity, and perceived susceptibility could altogether capture 49 percent of the variance in rural people's intention to use sustainable water resource management practices. Similarly, Yazdanpanah et al. (2015) and Yazdanpanah et al. (2016) have reported the significant role of perceived benefits, attention to health, perceived severity, and perceived benefits in people's behavior. Vassallo et al. (2009) reported that perceived benefits and barriers and health motivation were good predictors of people's intention. Wier & Calverly (2002) stated that health benefits were the main motivation for behavior in individuals. Finally, GOF was used to evaluate the overall fit of HBM:
Figure 4

Structural model of HBM.

Figure 4

Structural model of HBM.

Close modal
The overall fit of the model is calculated as follows:

The result is 0.697, showing the strong fit of the research model since the minimum acceptable value for this index is 0.36.

Inattention to the sustainability of water resources and the challenges of sustainable development have reached critical points in Iran, and the lack of suitable access to water resources for various uses such as drinking, agriculture, and industry has become one of the most important obstacles to sustainable development. Despite acute problems in the water sector due to inattention to the sustainable development paradigm in water use, local governments have not yet seriously attempted to tackle these problems and reform behaviors based on this paradigm. If the current trend persists, water scarcity will be only a part of the problems in Iran and the decline in the quality of life and political, social and economic crises will all be likely to happen too. Changing the utilization system is not possible only through the use of administrative and legal levers; rather, the participation of farmers in planning and implementation is a must too. In general, given future developments and challenges, water management will be rendered impossible without public participation from the policymaking stage to the utilization stage. In the meantime, the participation of rural people should lead to the development of environmentally friendly behaviors and reinforce their intention to implement sustainable water resource management strategies and technologies. Therefore, this study was conducted to investigate the behavior of rural people in sustainable water resources management using the Theory of Planned Behavior (TPB) and the Health Belief Model (HBM).

The results showed that rural people's attitude was one of the important determinants of their intention to engage in sustainable management of water resources. Therefore, to reinforce conservation and sustainable behavior towards water resources, it is important to understand what attitude they have about water resources conservation and sustainable management. In Iran, it seems that policies towards more sustainable water conservation and management will not be viable unless a positive attitude is created among rural people towards sustainable water resources management practices. The attitude of the rural people is most affected by the community, so their communication and interactions with family members, experienced farmers, and agricultural extension and service centers can influence their attitude and behavior towards sustainable management of water resources. In addition, social media, especially radio and television, and social networks are important factors in changing the attitude of the rural people and can change their attitude by stimulating people's mentality and creating a sense of empathy.

Moral norms are another factor that influences the intention of sustainable management of water resources. Positive moral emotions about water resources management can be developed among rural people by religious and cultural aspects. The results showed that self-identity can also influence rural people's intentions. Therefore, it can be concluded that an individual's perception of himself or herself affects his or her intention to adopt managerial and conservative behaviors towards water resources. In other words, if one sees himself or herself as a person who is intrinsically an agricultural water saver and as a strict person who is compatible with agricultural water saving, his or her intention and behavior towards sustainable water resources management will be affected. This will make them conducive to saving water use during irrigation automatically. It is also suggested that strategies aimed at enhancing sustainable water management emphasize that sustainable activities are an important part of rural people's character. In other words, targeting rural people's self-identity may be an opportunity to change their behavior. As well, society should send signals to rural people that sustainable management and conservation of water is a social responsibility. To provoke the sense of social responsibility in people in dealing with sustainable management of water resources, social responsibility and self-identity can be integrated with moral commitments, personal norms, and local subcultures.

The results showed that perceived benefits influenced rural people's intention. Therefore, it can be concluded that more attention and focus on the advantages and benefits of sustainable water resources management and creating motivation in rural people will reinforce the use of water management strategies by them. In fact, rural people's information and awareness of the benefits of sustainable water management can be effective in their intention to adopt its practices. It can be stated that when deciding on sustainable water resources management, villagers think about its potential benefits. In other words, they are interested in health-related issues, so perceived benefits lead to a greater desire for sustainable water resources management. According to the results, the reasons why rural people choose sustainable water management are concern over the sensitivity of water management, human health, and environmental impacts. Therefore, it is suggested to familiarize rural people with the benefits of sustainable water management and encourage them to use modern technologies, and this can be accomplished by organizing exhibitions on sustainable water resources management, publishing educational packages and brochures and distributing them among rural people, and convening conferences on the technologies of sustainable water management.

Abbaszadeh
A.
Borhani
F.
Asadi
N.
2013
Effects of face-to-face health-belief oriented education about risk factors on knowledge and attitude of myocardial infarction patients after discharge
.
Iranian Journal of Medical Education
12
(
9
),
638
646
.
Abdollahi
V.
Zolfaghari
F.
Jabbari
M.
Dehghan
M.
Rafie
M.
2015
Investigating the effect of crescent construction on some parameters of vegetation and soil in Saravan rangelands (Sistan and Baluchestan Province)
.
Iranian Range and Desert Research
22
(
4
),
675
667
.
Adams
E. A.
2014
Behavioral attitudes towards water conservation and re-use among the United States public
.
Resources and Environment
4
(
3
),
162
167
.
Ajzen
I.
1991
The theory of planned behavior
.
Organizational Behavior and Human Decision Processes
50
(
2
),
179
211
.
Arvola
A.
Vassallo
M.
Dean
M.
Lampila
P.
Saba
A.
Lähteenmäki
L.
Shepherd
R.
2008
Predicting intentions to purchase organic food: the role of affective and moral attitudes in the theory of planned behaviour
.
Appetite
50
(
2–3
),
443
454
.
Ataei
P.
Khatir
A.
Izadi
N.
Frost
K. J.
2018
Environmental impact assessment of artificial feeding plans: the Hammami plain in Iran
.
International Journal of Environmental Quality
27
,
19
38
.
Ataei
P.
Aliabadi
V.
Norouzi
A.
Sadighi
H.
2019
Measuring the employees’ environmental attitude of agricultural knowledge-based companies based on sociocultural components: a case study from Iran
.
Environment, Development and Sustainability
21
(
5
),
2341
2354
.
Bakhtiyari
Z.
Yazdanpanah
M.
Forouzani
M.
Kazemi
N.
2017
Intention of agricultural professionals toward biofuels in Iran: implications for energy security, society, and policy
.
Renewable and Sustainable Energy Reviews
69
,
341
349
.
Bay
A.
Heshmati
H.
2016
Factors associated with pesticide use behaviors among farmworkers based on health belief model
.
Iranian Journal of Public Health
45
(
2
),
276
277
.
Brooks
D. B.
2006
An operational definition of water demand management
.
International Journal of Water Resources Development
22
(
4
),
521
528
.
Cary
J. W.
2008
Influencing attitudes and changing consumers’ household water consumption behaviour
.
Water Science and Technology: Water Supply
8
(
3
),
325
330
.
Collier
A.
Cotterill
A.
Everett
T.
Muckle
R.
Pike
T.
Vanstone
A.
2010
Understanding and Influencing Behaviours: A Review of Social Research, Economics and Policy Making in Defra
.
Department for Environment, Food & Rural Affairs (DEFRA)
,
London, UK
.
Cook
A. J.
Kerr
G. N.
Moore
K.
2002
Attitudes and intentions towards purchasing GM food
.
Journal of Economic Psychology
23
(
5
),
557
572
.
Coppens
M.
2016
Understanding Limited Glove Use among Pesticide Applicators: A Qualitative Study on Java Island, Indonesia
.
Knowledge, Technology and Innovation, Wageningen University
,
Wageningen, The Netherlands
.
Dezham
S.
Rouzbahani
N.
Khorsandi
M.
2015
Application of theory of planned behavior in predicting screening mammography in housewives over 40 years
.
Daneshvar Medicine
22
(
5
),
33
40
.
Fielding
K. S.
McDonald
R.
Louis
W. R.
2008
Theory of planned behavior, identity and intentions to engage in environmental activism
.
Journal of Environmental Psychology
28
(
4
),
318
326
.
Foltz
R. C.
2002
Iran's water crisis: cultural, political and ethical dimensions
.
Journal of Agriculture and Environmental Ethics
15
,
357
380
.
Gao
L.
Wang
S.
Li
J.
Li
H.
2017
Application of the extended theory of planned behavior to understand individual's energy saving behavior in workplaces
.
Resources, Conservation and Recycling
127
,
107
113
.
Gilbertson
M.
Hurlimann
A.
Dolnicar
S.
2011
Does water context influence behavior and attitudes to water conservation?
Australasian Journal of Environmental Management
18
(
1
),
47
60
.
Glanz
K.
Rimer
B. K.
Viswanath
K.
2008
Health Behavior and Health Education: Theory, Research, and Practice
, 4th edn.
Jossey-Bass
,
San Francisco, CA, USA
, pp.
45
51
.
Hafaz
N. A.
Jeevan
J.
Mohd Salleh
N. H.
Tae Hwee Lee
T.
Mhd Ruslan
S. M.
2019
Willingness to pay for halal transportation cost: the moderating effect of knowledge on the theory of planned behavior
.
International Journal of Engineering and Advanced Technology
8
(
6S3
),
479
488
.
Hassell
T.
Cary
J.
2007
Promoting Behavioural Change in Household Water Consumption: Literature Review
.
Smart Water, Heatherton, Victoria, Australia
.
Iglesias
V.
2004
Preconceptions about service: how much do they influence quality evaluations?
Journal of Service Research
7
(
1
),
90
103
.
Iran Meteorological Organization (IMO)
2013
Statistical Center of Iran
.
Available from: https://www.amar.org.ir
.
Izadi
N.
Ataei
P.
Karimi
H.
Norouzi
A.
2019
Environmental impact assessment of construction of water pumping station in Bacheh Bazar Plain: a case from Iran
.
International Journal of Environmental Quality
35
,
13
32
.
Jackson
T.
2005
Motivating Sustainable Consumption
.
Centre for Environmental Strategy, University of Surrey
,
Guildford, Surrey, UK
.
Jamshidi
O.
Asadi
A.
Kalantari
K.
Azadi
H.
Scheffran
J.
2019
Vulnerability to climate change of smallholder farmers in the Hamadan province, Iran
.
Climate Risk Management
23
,
146
159
.
Jorgensen
B.
Graymore
M.
O'Toole
K.
2009
Household water use behavior: an integrated model
.
Journal of Environmental Management
91
(
1
),
227
236
.
Kaiser
F. G.
2006
A moral extension of the theory of planned behavior: norms and anticipated feelings of regret in conservationism
.
Journal of Personality and Individual Differences
41
(
1
),
71
81
.
Kaiser
F. G.
Scheuthle
H.
2003
Two challenges to a moral extension of the theory of planned behavior: moral norms and just world beliefs in conservationism
.
Journal of Personality and Individual Differences
35
,
1033
1048
.
Kaplan
S.
Manca
F.
Nielsen
T. A. S.
Prato
C. G.
2015
Intentions to use bike-sharing for holiday cycling: an application of the theory of planned behavior
.
Tourism Management
47
,
34
46
.
Karbalaee
F.
2010
Water crisis in Iran
. In:
Paper Presented at the Proceedings of the International Conference on Chemistry and Chemical Engineering (ICCCE)
,
1–3 August
,
Kyoto, Japan
.
Khan
M.
2010
Using the health belief model to understand pesticide use decisions
.
The Pakistan Development Review
49
(
4
),
941
956
.
Madani Larijani
K.
2005
Iran's water crisis: inducers, challenges and counter-measures
. In:
Proceedings of the 45th Congress of the European Regional Science Association
.
Vrije University
,
Amsterdam
,
The Netherlands
.
Mekonnen
M. M.
Hoekstra
A. Y.
2016
Four billion people facing severe water scarcity
.
Science Advances
2
(
2
), e1500323.
Menozzi
D.
Fioravanzi
M.
Donati
M.
2015
Farmer's motivation to adopt sustainable agricultural practices
.
Bio-based and Applied Economics
4
(
2
),
125
147
.
Mohammadi Zeidi
I.
Pakpour Hajiaghaye
A.
Mohammadi Zeidi
B.
2013
Investigating the effect of education based on the theory of planned behavior on employee safety behaviors
.
Knowledge & Health
8
(
3
),
105
111
.
Mohammadian Mosammam
H.
Mohammadian Mosammam
A.
Sarrafi
M.
Nia
J. T.
Esmaeilzadeh
H.
2015
Analyzing the potential impacts of climate change on rainfed wheat production in Hamedan Province, Iran, via generalized additive models
.
Journal of Water and Climate Change
7
(
1
),
212
223
.
Moradhaseli
S.
Ataei
P.
Norouzi
A.
2017
Analysis of students’ environmental behavior in the agriculture college of Tarbiat Modares University, Iran (application of planned behavior theory)
.
Journal of Human Behavior in the Social Environment
27
(
7
),
733
742
.
Motiee
H.
Monouchehri
G. H.
Tabatabai
M. R. M.
2001
Water crisis in Iran: codification and strategies in urban water
. In:
Frontiers in Urban Water Management: Deadlock or Hope?
(J. A. Tejada-Guibert & Č. Maksimović, eds), Technical Documents in Hydrology No. 45, UNESCO, Paris, France, pp. 55–62
.
Namdar
A.
Bigizadeh
S.
Naghizadeh
M. M.
2012
Measuring health belief model components in adopting preventive behaviors of cervical cancer
.
Journal of Fasa University of Medical Sciences
2
(
1
),
34
44
.
National Drought Warning and Monitoring Center (NDWMC)
2020
The Report of the Percentage of Area and Population under the Influence of 120-Month Drought with SPEI Index in Hamadan Province
.
NDWMC
,
Iran
.
Nazari
P.
Kardavany
H.
Farajirad
P.
Abdolreza
A.
2016
Assessment of runoff changes under climate change scenarios in the dam basin of Ekbatan, Hamedan Iran
.
Journal of Climatology & Weather Forecasting
4
,
172
.
Olsen
N. V.
Sijtsema
S. J.
Hall
G.
2010
Predicting consumers’ intention to consume ready-to-eat meals: the role of moral attitude
.
Appetite
55
(
3
),
534
539
.
Pelak
N.
Porporato
A.
2016
Sizing a rainwater harvesting cistern by minimizing costs
.
Journal of Hydrology
541
,
1340
1347
.
Pelling
E. L.
White
K. M.
2009
The theory of planned behavior applied to young people's use of social networking web sites
.
Journal of CyberPsychology & Behavior
12
(
6
),
755
759
.
Pino
G.
Peluso
A. M.
Guido
G.
2012
Determinants of regular and occasional consumers' intentions to buy organic food
.
Journal of Consumer Affairs
46
(
1
),
157
169
.
Raksanam
B.
Taneepanichskul
S.
Siriwong
W.
Robson
M. G.
2012
Factors associated with pesticide risk behaviors among rice farmers in rural community, Thailand
.
Journal of Environment and Earth Science
2
(
2
),
32
39
.
Raykov
T.
1998
Coefficient alpha and composite reliability with interrelated nonhomogeneous items
.
Applied Psychological Measurement
22
(
4
),
375
385
.
Rezaei
R.
Mianaji
S.
2019
Using the health belief model to understand farmers’ intentions to engage in the on-farm food safety practices in Iran
.
Journal of Agricultural Science and Technology
21
(
3
),
561
574
.
Rockström
J.
Karlberg
L.
Wani
S. P.
Barron
J.
Hatibu
N.
Oweis
T.
Bruggeman
A.
Farahani
J.
Qiang
Z.
2010
Managing water in rainfed agriculture: the need for a paradigm shift
.
Agricultural Water Management
97
(
4
),
543
550
.
Russell
S.
Fielding
K.
2010
Water demand management research: a psychological perspective
.
Water Resources Research
46
(
5
),
W05302
.
Sadeghi Sedeh
B.
Rabiei
Z.
Razavi
H.
2015
Effects of health belief model components in general physicion rational prescribing of Chaharmahal va Bakhtiary province
.
Razi Journal of Medical Sciences
21
(
128
),
37
46
.
Sánchez
M.
López-Mosquera
N.
Lera-López
F.
Faulin
J.
2018
An extended planned behavior model to explain the willingness to pay to reduce noise pollution in road transportation
.
Journal of Cleaner Production
177
,
144
154
.
Saurí
D.
2013
Water conservation: theory and evidence in urban areas of the developed world
.
The Annual Review of Environment and Resources
38
,
227
248
.
Shojaei-Miandoragh
M.
Bijani
M.
Abbasi
E.
2019
Farmers’ resilience behaviour in the face of water scarcity in the eastern part of Lake Urmia, Iran: an environmental psychological analysis
.
Water and Environment Journal
,
doi:10.1111/wej.12489
.
Siebert
R.
Berger
G.
Lorenz
J.
Pfeffer
H.
2010
Assessing German farmers’ attitudes regarding nature conservation set-aside in regions dominated by arable farming
.
Journal for Nature Conservation
18
(
4
),
327
337
.
Şimşekoğlu
Ö.
Lajunen
T.
2008
Social psychology of seat belt use: a comparison of theory of planned behavior and health belief model
.
Transportation Research Part F: Traffic Psychology and Behaviour
11
(
3
),
181
191
.
Straub
C. L.
Leahy
J. E.
2014
Application of a modified health belief model to the pro-environmental behavior of private well water testing
.
JAWRA Journal of the American Water Resources Association
50
(
6
),
1515
1526
.
Strecher
V. J.
Rosenstock
I. M.
1997
The health belief model
. In:
Cambridge Handbook of Psychology, Health and Medicine
(A. Baum, S. Newman, J. Weinman, R. West & C. McManus, eds).
Cambridge University Press
,
Cambridge, UK
, pp.
113
117
.
Suprapto
B.
Wijaya
T.
2012
Model of consumer's buying intention towards organic food: a study among mothers in Indonesia
.
International Proceedings of Economics Development and Research
29
,
173
180
.
Tenenhaus
M.
Amato
S.
Esposito Vinzi
V.
2004
A global goodness-of-fit index for PLS structural equation modeling
. In:
Proceedings of the XLII SIS Scientific Meeting
, pp.
739
742
.
Valizadeh
N.
Bijani
M.
Abbasi
E.
2018
Farmers active participation in water conservation: insights from a survey among farmers in southern regions of West Azerbaijan Province, Iran
.
Journal of Agricultural Science and Technology
20
(
5
),
895
910
.
Valizadeh
N.
Bijani
M.
Hayati
D.
Fallah Haghighi
N.
2019
Social–cognitive conceptualization of Iranian farmers’ water conservation behavior
.
Hydrogeology Journal
27
(
4
),
1131
1142
.
van Dijk
W. F. A.
Lokhorst
A. M.
Berendse
F.
de Snoo
G. R.
2016
Factors underlying farmers’ intentions to perform unsubsidised agri-environmental measures
.
Land Use Policy
59
,
207
216
.
Vassallo
M.
Saba
A.
Arvola
A.
Dean
M.
Messina
F.
Winkelmann
M.
Claupein
E.
Lähteenmäki
L.
Shepherd
R.
2009
Willingness to use functional breads. Applying the health belief model across four European countries
.
Appetite
52
(
2
),
452
460
.
Veisi
K.
Bijani
M.
Abbasi
E.
2020
A human ecological analysis of water conflict in rural areas: evidence from Iran
.
Global Ecology and Conservation
23
, e01050.
Welderufael
W. A.
Woyessa
Y. E.
Edossa
D. S.
2013
Impact of rainwater harvesting on water resources of the Modder River basin, central region of South Africa
.
Journal of Agricultural Water Management.
116
,
218
227
.
White
S.
Turner
A.
Fane
S.
Giurco
D.
2007
Urban water supply–demand planning: a worked example
. In:
4th IWA Specialist Conference on Efficient Use and Management of Urban Water Supply
,
21–23 May
,
South Korea
.
Wier
M.
Calverly
C.
2002
Market penetration for organic foods in Europe
.
British Food Journal
104
(
1
),
45
62
.
WWAP (United Nations World Water Assessment Programme)
2018
The United Nations World Water Development Report 2018: Nature-Based Solutions for Water
.
UNESCO
,
Paris, France
.
Yazdanpanah
M.
Hayati
D.
Zamani
G. H.
Karbalaee
F.
Hochrainer-Stigler
S.
2013a
Water management from tradition to second modernity: an analysis of the water crisis in Iran
.
Environment, Development and Sustainability
15
,
1605
1621
.
Yazdanpanah
M.
Thompson
M.
Hayati
D.
Zamani
G. H.
2013b
A new enemy at the gate: tackling Iran's water super-crisis by way of a transition from government to governance
.
Progress in Development Studies
13
,
177
194
.
Yazdanpanah
M.
Hayati
D.
Hochrainer-Stigler
S.
Zamani
G. H.
2014
Understanding farmers’ intention and behavior regarding water conservation in the Middle-East and North Africa: a case study in Iran
.
Environmental Management
135
,
63
72
.
Yazdanpanah
M.
Komendantova
N.
Shirazi
Z. N.
Linnerooth-Bayer
J.
2015
Green or in between? examining youth perceptions of renewable energy in Iran
.
Energy Research & Social Science
8
,
78
85
.
Yazdanpanah
M.
Tavakoli
K.
Marzban
A.
2016
Investigating factors that influenced framers’ intention regarding safe use of pesticides through health belief model
.
Iran Agricultural Extension and Education Journal
11
(
2
),
21
29
.