Measuring the farmers’ vulnerability to climate change in Tashk and Bakhtegan Lakes in Iran

ABSTRACT This study used a descriptive-analytical method to assess how vulnerable farmers in Fars Province's rural regions near the Tashk and Bakhtegan lakes are to the effects of climate change. For this purpose, 17 villages around Tashk and Bakhtegan lakes with 2511 households, who are engaged in agricultural activities, were investigated. To achieve the research goals, a broad range of indexes were determined with the dimensions of exposure, sensitivity, and adaptive capacity to climate change according to the Climate Vulnerability Index (CVI) and were evaluated in the field studies. According to the results, 52.93% of communities were highly vulnerable to climate change. On the other hand, only 23.52% of farmers had very low vulnerability, and 23.52% had moderate vulnerability. The local farmers were aware of the climate change in the studied region with an average of 4.56. Given that more than half of the villagers are highly vulnerable to climate change, the government and relevant institutions need to increase their resilience to vulnerability. Increasing vulnerability requires careful measurement and monitoring of all related variables, increasing adaptation to the generalization of insurance, access to facilities, and reducing climatic sensitivities by increasing livelihood diversification, reducing unemployment, and using drought-resistant plants.


Introduction
Today, millions of people, especially those living in developing countries, suffer from food and water scarcity (Muchuru & Nhamo, 2019), and their health is at risk (Linnér et al., 2012).The global data reveal the fact that over the past two decades, natural disasters have taken place more repeatedly, resulting in many destructive effects (Anees, Shukla, Punia, & Joshi, 2019).Therefore, it is crucial to identify the stages of response to them.
Iran, like many countries, is affected by high climate variability (Jamshidi et al., 2019), and trends of extreme events are increasing (Mansouri et al., 2019).Research on the future effects of climate change indicates that Iran is likely to face longer periods of severe maximum temperatures in the southern part of the world and longer dry periods (Vaghefi et al., 2019).Alongside these problems, Iran has also been faced with shrinkage in a significant number of lakes (Vaghefi et al., 2019).Lakes are natural water resources, which are affected by human activities and climatic, hydrological, and geomorphological changes in their drainage basins (Xiao et al., 2016).The changes in the surface area of lakes result in the destruction of the lands with gentle slopes around them and affect the activities associated with them.Moreover, dramatic changes in the surface of lakes lead to variations in the weather of the drainage basin so that a dried-out lake can totally change the local climate in the drainage basin and even beyond it (Zeinali & Sayyad Asghari-Saraskanrod, 2014).In southwest Iran (Fars Province), there are eight wetlands including those with freshwater, namely Kaftar (in the domain of Eghlid), Haft Barm and Arzhan (in the domain of the city of Shiraz), Parishan (in the domain of Kazerun), and the ones with saltwater, namely Bakhtegan and Tashk (in the domain of Neyriz County), Maharlu (in the domain of the city of Shiraz), and Harm and Hirom (in the domain of Lar County) (Fazelniya & Masoumi Jeshni, 2015).Due to climate change, recent droughts, lack of precipitation, lack of water management, extra exploitation of groundwater, and construction of dams on the Kor and Sivand Rivers as the main sources that feed the Tashk and Bakhtegan lakes, the climatic condition of these lakes has turned them into deserts.Furthermore, based on the output of atmospheric general circulation models, the amount of precipitation and temperature respectively decreases and increases (Ansari et al., 2018).
The dryness of the Tashk and Bakhtegan lakes has received considerable attention in Fars Province and Iran over the past years.The drying process of the lake has produced many economic, social, and environmental outcomes for the areas around it.Over recent years, the growing trend of reduction in water has caused the salt existing in the bed of the Tashk and Bakhtegan lakes to spread through agricultural lands and residential areas (Kiani et al., 2017).In general, the drying of the water of Bakhtegan lake due to the increase of hot and strong winds, especially in summer and autumn, has led to the spread of skin, gastrointestinal, and respiratory diseases in this area.Due to the drying of the water of this lake, the decrease in the fertility of agricultural lands in the region and the salinity of groundwater have caused unemployment among local villagers and reduced their agricultural activities (Mahabadi et al., 2018).Since the basin catchment area of Tashk and Bakhtegan has good agricultural fields, the presence of the lake has been one of the factors of agricultural development in this area.Therefore, the drying up of this lake severely damages agricultural production and productivity.This issue has caused severe problems in the livelihood of farmers in the area.As a result, many of them either abandoned their farms and chose other job opportunities or moved to nearby cities for livelihood (Benhangi et al., 2020).Accordingly, the vulnerability of the residents adjacent to the lake to climate change should be measured and examined since their agricultural economy depends on the lakes and the trend of changes in them.In this context, the results of a study by Shaffril, Krauss, and Samsuddin (2018) revealed the major role of farmers in improving farm adaptation to climate in six key areas such as agriculture, irrigation, water management, farm management, financial governance, and physical and social infrastructure management.Four factors were found to be significant as adaptation measures among farmers in a study by Phuong, Biesbroek, Sen, and Wals (2018): farm workers' number, available information sources, farm income, and the amount of farmable land available during the summer season.The Climate Vulnerability Index (CVI) was used by Jamshidi et al. (2019) to analyze the smallholder farmers' vulnerability to climatic hazards.Their findings revealed that a number of factors, including education, income, infrastructure access, credit, and land size, play a role in the region's vulnerability.However, a lack of vulnerability and understanding of the severity, type, and state of the hazards among the resident population can cause damage (Taherkhani et al., 2012).
One of the first steps in reducing vulnerability is to understand how vulnerable farmers respond to climate change.Overall, it is necessary to look into the factors that influence farmers' ability to adapt to climate change.Meanwhile, this study has a clearer understanding of the factors influencing farmers' decisions to use a particular adaptive practice among the available strategies.Despite recent studies that examine adaptation (e.g.Goli et al., 2020;Karimi et al., 2018), vulnerability (Charrahy et al., 2021;Noorisameleh et al., 2020), and resilience (Biglari et al., 2019;Mehdi et al., 2020) to climate change, especially drought (Nabaei et al., 2019;Sobhani & Zengir, 2020), in Iran, few studies have examined the effects of drought on important lakes such as Tashk and Bakhtegan, agricultural statuses, and livelihoods of farmers.Therefore, the main goal of the present study is to examine the farmers' vulnerability to climate change in the Tashak and Bakhtegan lakes.To achieve the goal, two main research questions will be answered as follows: (1) Are farmers aware of climate change and its consequences?(2) Do farmers have effective vulnerability to the consequences of climate change?

Concept of vulnerability
The concept of vulnerability is defined in a variety of ways in the literature, most of which are based on the disciplines from which they originated (Eifert et al., 2018).Based on the findings of Berrouet et al. (2018), definitions of vulnerability should not be conflated with conceptual frameworks.While definitions describe the aspects of vulnerability, conceptual frameworks provide the definitions meaning so that they may be studied in a clear and repeatable manner based on the analytical context (Berrouet et al., 2018).Nevertheless, it is critical to first define and comprehend what is meant when vulnerability is discussed and written about in the context of climate change.Vulnerability to climate change has been defined by the Intergovernmental Panel on Climate Change (IPCC) as "a completely undesirable phenomenon" (IPCC, 2014).According to this definition, vulnerability in the context of climate change is "the inability of a system to deal with adverse and destructive effects, including climate change and extremes".Vulnerability is a function of the character, magnitude, and rate of climate change and variation to which a system is exposed, its sensitivity, and its adaptive capacity (IPCC, 2014).Vulnerability refers to a system or unit's incapability to minimize the effects of a hostile environment.Vulnerability can also have adverse effects on individuals' relationships with their environment, social forces, and institutions, as well as the cultural values that support or oppose them (Chipangura et al., 2017;Paul, 2019).Agricultural vulnerability to climate change can thus be stated in terms of exposure to higher temperatures, crop yield sensitivity to higher temperatures, and farmers' ability to adjust to the impacts of this exposure and sensitivity (Hagenlocher et al., 2019).

Three components of vulnerability
Relevant studies (e.g.Azadi et al., 2018;Caceres, 2021;Uekusa, 2018) that analyzed vulnerability mainly focused on the measurement and assessment of appropriate indicators for various aspects of vulnerability and participatory methods.
Vulnerability has three components: (1) exposure, (2) sensitivity, and (3) adaptive capacity.Weather and climate events, both extreme and non-extreme, have varying degrees of severity based on the level of vulnerability and exposure to these events.Exposure, according to IPCC, is defined as the nature and degree to which a system is "exposed to significant climate variations" (IPCC, 2014).Exposure affects the climate stress level of a specific analysis unit or system.Understanding how weather events and climate change influence the occurrence of disasters, as well as developing effective adaptation and disaster risk management strategies, requires identifying the complex nature of vulnerability and exposure (Gómez-Aíza et al., 2017;Monterroso & Conde, 2015).
The degree to which climate-related stimuli affect a system is known as sensitivity (Ingram, 2018).Adaptive capacity refers to a system's ability to adapt to climate change, including climate variability and extremes, in order to mitigate potential damages, seize opportunities, or cope with the consequences (Abdul-Razak & Kruse, 2017;Alemaw & Chaoka, 2018).When it comes to the vulnerability of socio-ecological systems, the concept of adaptive capacity is frequently used.Vulnerability is often characterized as the combination of a system's exposure and sensitivity to external pressures, as well as the system's adaptive capacity or coping capacity in the face of those stresses (Holland et al., 2017).A system's adaptive capacity is determined by a number of factors that are not mutually exclusive or independent but result from a mixture of them (Stock et al., 2019).It is crucial to understand who is more vulnerable to climate change and who has a lower capacity for adaptation.Identifying the important factors of these capacities is the first step in finding more effective strategies to help farmers in their attempts to preserve their agriculture, increase productivity, and therefore improve their living.Assessing farmers' ability to adapt to climate change, therefore, provides crucial information for the development of climate change adaptation policies.

Farmers' decision-making under climate change impacts
Numerous studies have examined how climate change affects farmers' decision-making.After the negative impacts of climate change on Iran's water resources, Pakmehr & colleagues (2021) investigated the underlying causes.Based on their findings, farmers' responses to climate change were influenced by demand appraisal and self-efficacy, which were both significant predictors of problem-focused coping.Pakmehr et al. (2020) found how the water sector could be affected by climate change in such a way that harvest and income will be reduced, and poverty and other social issues (e.g.conflicts) will be exacerbated.Their findings revealed that farmers have been dealing with drought and water scarcity for a long time and are well aware of the harmful repercussions of water shortage.According to Delfiyan et al., empirical research reveals that farmers may successfully control the negative consequences of drought by altering and adjusting their present farming techniques (2021).As a result, farmers' vulnerability can be reduced through adaptation.Understanding how farmers react to drought can help expand adaptation options and strengthen the sector's vulnerability.
According to the findings of Fahad and Jing (2018), the severity and frequency of past weather-associated extremes, farm typology, socio-economic settings, and the ability of farming communities to pay should be considered while introducing crop insurance programmes in the region.Moreover, disseminating awareness in farming communities regarding the future changes in climate and the related risks of the existence of extreme weather incidences is important.The government support to subsidize insurance schemes might increase the need for crop insurance among subsistence farmers in and cushion them against adverse effects arising from such extreme weather conditions for the sustenance of livelihoods.Another study by Fahad and Wang (2018) has shown that in the study area, study participants were facing various constraints in the adoption of certain adaptation measures to deal with climate variability.For example, shortage of labour, insecure land tenure system, lack of market access, poverty, lack of governmental support, lack of access to assets, lack of water sources, lack of credit sources, and lack of knowledge and information were the main constraints faced by the farm households.Moreover, Su et al. (2021) indicated that developing local industries and governmental financial support improve the sustainable livelihood of farmers and eradicate absolute poverty.The findings of their study further indicate that there is a positive correlation between poverty alleviation measures and natural and social capital for sustainable livelihood.Fahad et al. (2022) argued that while the influx of capital further boosts technological progress, a benign interaction effect was observed between technological innovation and foreign investment.The findings of their study show that the policy of market borrowing technology is more effective, and the implementation of the new environmental policy will intensify the strategies between managers and enterprises.

Study area
The studied region included villages around the saline Tashk and Bakhtegan lakes, located in Fars Province (Figure 1).For a more accurate explanation, it should be noted that these lakes are located in the west of Neyriz County, which are among the most important aqueous habitats and are considered as the second inland lakes of Iran in terms of area.Their drainage basin has an area of 25000 km 2 (Fazelniya & Masoumi Jeshni, 2015).Pichakan, Ghichakan, Bajeghan, Neyriz, and Chubanan are the other names of Lake Bakhtegan.Lake Tashk is also known as Basfuyeh and Narges.The two lakes extend and join each other in pluvial years.They are located at 29°42'42"N and 53°31'13"E at a distance of 160 km from the east of Shiraz.This marshland is playing a vital role in preserving water for agricultural lands at the marshlands border and is considered to be one of the few wetlands in the world where fresh water is running in the winter in the east and saline water is running in the summer in the west.The agriculture industry consumes almost 90% of the water in this basin, yet the irrigation network in this region is inefficient, resulting in the loss of millions of cubic meters of water each year.If the current trend continues, severe concerns about water availability and the region's agricultural future will inevitably arise (Ghader, 2018).

Data collection and analysis
This research employs a descriptive-analytical approach to evaluate farmers' climate change vulnerability and examine the factors that determine their vulnerability.For this purpose, several data have been used.Part of its data was acquired from documentary and library methods like the theoretical framework of the research, and the remaining was collected from field studies using surveys.The statistical population of the research included all farmers' households who live in the villages and who are directly associated with the Tashk and Bakhtegan lakes.For this purpose, considering a radius of 3 km, 17 villages with 2511 households directly related to the lakes were identified.Then, using the Cochran formula with a margin of error of 0.5%, 333 households were chosen as the sample population.Within the village, households were selected using a simple random method so that the distribution of households is scattered throughout the village.Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants (households in this study) from a community (all households in the village).In this study, 333 farmer households were selected based on Cochran's formula.In order to have a proper distribution in all the villages, this study first considered the population of each village, then the percentage of the population of that village was estimated in relation to the total population.This topic was a suitable guide for distributing the number of questionnaires in each village according to the population of that village.After estimating the number of questionnaires for each village, the following steps were taken.First, each household was assigned an individual number.Then, randomly, a subset of the population was selected according to the required number of questionnaires.This subset represents the households that should complete the questionnaire.
It should be noted that data were collected by completing the questionnaire after confirming its validity at both expert and pre-test stages.In this regard, 35 questionnaires were distributed among farmers in the studied villages.The selected villages were located around the lakes (Figure 1).Cronbach's alpha test was also used to evaluate the reliability of the research items (the closer the Cronbach's alpha value is to 1, the more reliable the indicators are).Table S-1 shows the Cronbach's alpha level for each research dimension.It is worth noting that three additional questionnaires were added during the sampling process to achieve sampling accuracy.As a result, 336 samples were obtained in total (Table S-2  and Figure S1).
It is necessry to explain part of the study comes back to trust and it is ethical data that should be trusted.However, the study method will help reduce errors due to randomness.In addition, the questionnaires are completed by students from the same regions who have sufficient knowledge about the region.Furthermore, after completing the statistics, it can be reviewed and followed up by regional organizations such as the health centre and sometimes the governor's office.So, the data is reliable.However, the following entries are intended to clarify ethical aspects: . Research participants (farmers) took part voluntarily, free from any coercion. .The confidentiality of the information provided by the survey participants and the anonymity of the respondents were respected. .Research participants were fully aware of the purpose and method of the research. .The research tool was designed based on the research objectives with complete accuracy and the data were collected by the graduates in complete accuracy.It is noteworthy that the population of children, adolescents, and young people under 25 years in the study areas has decreased significantly compared to the past.This has happened for various reasons such as drought and water shortage, climate change, lack of resources, lack of proper production inputs, weakness in health and welfare infrastructure, and migration, all of which are somehow dependent on economic and livelihood factors.To achieve the research goal, i.e. investigating the vulnerability of the farmers to climate change, a wide range of indexes were evaluated based on the Climate Vulnerability Index (CVI).This index has three dimensions: exposure, sensitivity, and adaptive capacity (Sullivan & Huntingford, 2009;Sullivan & Meigh, 2005).Each of these components has several variables.For example, the variables related to the adaptation component are net income earned from agriculture, product insurance, number of livestock, rainfed land, agricultural income, non-agricultural income, cultivation under pressurized irrigation, share of land ownership, members engaged in agriculture, technical counseling level, land area, number of family members involved in social assemblies, number of adult members, parents' (mother's) level of education, parents' (father's) level of education, level of education of the head of household, the highest number of years of education in the household, etc. (Table 1 illustrates all variables separately, along with their effects).
Given the different scales each data has, in order to compare them, they should be standardized before taking any measures.Various methods have been suggested for the standardization of the values of the indexes.Equation ( 1) was used in this study (Leiserwitz, 2007).
Here the lowest and highest a and b are combined in Dimension Index which is normalized between 0 and 1, with specific values for each respondent.It is necessary to explain that some variables have a negative relationship with the degree of vulnerability.That is, their amount will lead to a reduction in vulnerability.Therefore, before calculating the value of the CVI index, they were reversed based on their relationship, which is specified in Table 1; as an example, the use of drought-resistant plant species will lead to a decrease in the household's sensitivity to the effects of climate change.Therefore, to equalize its value in the sensitivity factor, its value was considered reversed.After normalizing the data and calculating the indexes of exposure (EX), sensitivity (CS), and adaptive capacity (AC) for each of the studied villages, Equation (2) was used to estimate the vulnerability of each of them in the final step (Hejazizadeh et al., 2015;Pandey et al., 2015).
The index for the three dimensions of vulnerability is the sum of all indicators considered for the dimension.The indicators signs are reported in Table 1: The Climate Vulnerability Index (CVI) (Sullivan & Huntingford, 2009;Sullivan & Meigh, 2005) is a comprehensive and interdisciplinary tool designed to provide a clearer understanding of how climate and other global impacts affect human populations.Specially created for farmers.Many researchers have used this index, which is referred to in the Introduction and Method section.For example, Mbakahya and Ndiema (2015), Jamshidi et al. (2019), andHejazizadeh et al. (2015) used four collective (Perch-Nielsen, 2010), multiplicative (Ferrier & Haque, 2003), cumulative-exponential, and multiplicative-exponential models to calculate the vulnerability index.Despite the fact that the factors are different, the output of the index was the same in the first three cases.In fact, they concluded that based on the multiplicative model, the index score changes very little.Finally, they suggested that the multiplicative-exponential model is vulnerable to distinguish between indicators.Therefore, this index was used multiplicative-exponential in this study.CVI = LOG((AC * CS) EX ) (5) Here, EX is the exposure component, CS is the sensitivity component, and AC is the adaptive capacity component, each of them has its own sub-components (Table 1).We engage a quintile level for the classification of people with very high, high, low, and very low vulnerabilities (Table 2).
It should be noted that in addition to the mentioned methods, in order to investigate the climatic behaviour and evaluate the attitude of farmers toward the changes in meteorological variables based on their experiences, SPI (McKee & Richards, 1996) was used for analysing dry and wet years.Moreover, the recommended methods (Nairn & Fawcett, 2013;Perkins & Alexander, 2013) using ClimPACT2 software were used to count the heat and cold waves (Alexander & Herold, 2016).Figure 2 schematically shows the steps of conducting the research.

Results and discussion
In this research, the farmers' beliefs in and experiences of climate change were investigated prior to calculating the vulnerability index.In fact, before calculating any dimensions of CVI, the attitude of the people toward climate change was studied using surveys.Afterward, three extreme phenomena, including drought, heat waves, and cold waves, were evaluated in the region using the stations adjacent to the lakes.Eventually, the components of CVI were calculated according to the designed surveys.

The local farmers' beliefs in climate change
Eight questions were considered to evaluate the local farmers' beliefs about climate change (Table 3).According to Table 2, almost 97% of the farmers and residents of the villages believed that a reduction had occurred in temperature and precipitation.Furthermore, more than 97% agreed that the drought periods have been extended, and about 95% approved warmer (hotter) winters (summers).
Moreover, a one-sample t-test was used to determine how aware the farmers were of climate change in the studied region.For this purpose, "3" was chosen as a theoretical average (Joseph & Rosemary, 2003) for assessing farmers' beliefs in climate change in the studied region.Generally speaking, in questionnaire studies, the Likert scale is usually based on 5, 7, or 9 points.In this study, we used a 5-point Likert scale.A scale can be constructed by taking the simple average of questionnaire responses across a set of individual items (questions).A 5-point Likert scale has a mean of 3 (Likert, 1931).As a result, it is possible to conclude that the majority of people agree with our hypothesis (awareness of climate change) that it is higher than average.Indeed, this issue has been evaluated quantitatively using the t-test (with a significant level of 95%).The results obtained from the analysis of the test are presented in Table 4.According to the test results, the local farmers had the highest beliefs in climate change in the studied region, with an average of 4.56% and a significance level of 99%.In other words, the farmers' beliefs in climate change were more than the theoretical average of three.
As shown in Tables 3 and 4, in the farmers' and beneficiaries' views, the climate was changing, and these changes were reflected in their perceptions and experiences.In order to verify this issue, an effort was made to investigate the changes in drought, heat waves, and cold waves using the stations of the studied region.In this regard, the statistical data on the precipitation, maximum temperature, and minimum temperature in a period of 31 years were used to examine the climate in the studied region.Finally, the conditions of the studied domain were prepared using remote sensing and false colour composition (FCC).The monthly SPI on 3-month and 6-month scales was used to obtain the number of wet and dry years in the studied period.The results obtained from 3-month SPI in all stations revealed that the number of months with severe drought was much more than those with extreme wetness.According to the available frequencies, drought was a natural phenomenon with an almost definite cycle in the region.Moreover, the drought had become more severe over time.The study area is located in the centre of Fars Province.Based on the findings of Moradi et al. (2011), the severity of drought in the south and central regions of the province is more.
The trend of drought severity on the 3-month and 6month scales for all stations is evaluated (Figures not shown).Fluctuations are considered natural in the severity of the drought and wetness.However, the worsening trend of drought on both scales deserves special attention.The severity of this index shows a decreasing trend on both scales in all three stations, which indicates the worsening of the droughts in the stations.The results of this study were consistent with the results of previous research studies.Modarres et al. (2016) showed that extreme droughts in Iran are increasing, and more precisely, the station used in this study showed an increase.Simultaneously, they have warned of a critical situation in Iran due to extreme climate change and the growing risk of environmental changes in the twenty-first century.
According to the results of the report of IPCC, the global average temperature is increasing.One of the most important consequences of these changes is a change in the pattern of extreme climatic phenomena and an increase in their occurrence, including heat and cold waves (IPCC, 2014).In fact, if the average daily temperature of a given threshold (for example, 95th percentile for heatwaves and 5th percentile for cold waves) is for several days more (less), it is called a heat wave (cold).That could have dire consequences for ecosystems, agriculture, and socioeconomic systems (Parmeson et al., 2013).Figure 3 illustrates the frequency results of the heat (Figure 3(A)) and cold waves (Figure 3(B)).According to these figures, it can be found that the number of heat waves (Figure 2(A)) has increased while the number of cold waves (Figure 3(B)) has decreased over time.The coloured dotted lines in both figures show the trend.As can be seen, the frequency of these extreme phenomena changes with relatively strong trends in all three stations.
Due to population growth and industrialization in the twenty-first century, humans consume more natural resources, so they have to solve the related issues, including those concerning water supply.Consequently, humans are continuously changing their environments through water control and storage, resulting in changes in the water level of lakes (Gao  et al., 2020;Kiani et al., 2017).Figure 3 shows the changes in the water level of the Tashk and Bakhtegan lakes.Since 2007, their water level has enormously varied.However, the reduction in the water level is not only attributed to natural issues, and the construction of a dam upstream of the basin is another effective factor worsening the situation.
The components of the vulnerability index were calculated after recognizing the climatic behaviour of the region, considering the experiences of the farmers and evaluating three extreme phenomena.

Exposure
The exposure dimension includes 12 indexes.According to Figure 4, the results reveal that in the farmers' view, the salinity of drinking and agricultural water, reduction in vegetation, reduction in the region's water, and increase in the migration have respectively caused the most damage to the studied region.An important aspect associated with the indexes of exposure dimension was that the respondents believed that the drinking and agricultural water had become saline in the villages of the studied region.The main reasons for this phenomenon are longer periods of drought in the region, the lower level of water income to the lakes, and the extra usage of groundwater.Consequently, the area of agricultural lands under cultivation, as well as the fertility of their soil, had reduced, leading to the migration of most of the villagers to the close and far cities.This issue made the villagers more vulnerable.In other words, it reduced their vulnerability (Figure 5).

Sensitivity
The sensitivity dimension has four components, including population sensitivity (3 variables), vulnerable social groups (5 variables), agricultural activity (3 variables), and sensitivity to real estate (5 variables).The presence of the active population is the factor that increases the vulnerability of the villagers.The number of teenagers and young people was very low in the region.This is due to the slowdown in population growth in recent years, which has affected even rural areas.Unlike in the past, when most farming and rural families had more than 5 children, today, in most of these families, the number of children has decreased to 2 or finally 3 children.The most important reason for this is the economic problems that rural communities face.The  usage of different products for agriculture had a rate of 0.5, which means the region was not in bad conditions in terms of the number of products.However, the diversity of products, especially those resistant to dryness and salinity, should become broader to increase vulnerability in the region (Figure 6).

Adaptive capacity
The adaptive capacity dimension has four components of economic capacity (8 variables), social capacity (5 variables), human resources capacity (4 variables), and facilities capacity (5 variables).As the adaption capacity rises, the vulnerability increases, but this component should be comparable with the other two ones.Therefore, the answers of the respondents were aligned with the other two components, so a higher adaptive capacity index would lead to less adaption.In this mode, lower sensitivity and exposure with a lower adaptive capacity mark (after switching to its reciprocal) increase adaptation.
The variables such as insurance, rainfed land, lack of suitable credits, access to adequate healthcare facilities, lack of pressurized cultivation, or, in other words, lack of modern agriculture methods and educational facilities were the reasons responsible for the lower adaption of the residents in the region (Figure 7).To give a more precise insight into the educational facilities, it should be noted that there was no high school in any of the studied villages, and there was only one library in one of them.Moreover, the farmers had not purchased insurance for their agricultural products, which was one of the reasons effective in reducing their adaption to climate change.
They believed that when they purchase insurance for their products, the actuaries do not approve it or determine low payments, which showed a lack of trust among them.Another effective factor reducing the adaptive capacity of farmers for climate change was the lack of pressurized cultivation in the studied region, which could be caused by the salinity of agricultural water and lack of access to financial and credential facilities due to the lack of access to guarantors.

Zoning of rural habitations based on CVI dimensions
The variables were separately investigated in previous sections.
In this section, an effort is made to report the results for each village separately.The results of evaluating exposure, sensitivity, and adaptive capacity of farmers to climate change demonstrated that most farmers living in the villages neighbouring the Tashk and Bakhtegan lakes were relatively or highly vulnerable to climate change.To explain more, the families highly vulnerable to climate change did not have adequate adaptive capacity.For example, according to the evaluations, the farmers of the villages of Bavarkan, Dehzir, Hasan Abad, and Helal Abad had the highest exposure and sensitivity to climate change.Meanwhile, they had a low to medium adaptive capacity for climate change (Figure 8).Furthermore, the results obtained from the evaluation of the vulnerability to climate change indicated that the farmers of the villages of Qaleh Mahmudi, Sang-Karr, Bavarkan, Kazemi, Gheshme Ghavi, Mobarak Abad, Shargh Abad, and Khane Ket had the lowest vulnerability.In contrast, those of Tashk, Jezin, Hasan Abad, and Bastarm-e Cheshmeh Anjir had the highest vulnerability to climate change.As can be seen, most of the farmers living in the villages neighbouring the Tashk and Bakhtegan lakes were relatively or highly vulnerable to climate change (Figure 9).Spatial analysis of the farmers' vulnerability in the studied villages revealed that the villages located in the north and southeast of the lakes had the lowest vulnerability to climate change in the studied region.
The results obtained from the analysis of the above equation are presented in Table 5.They indicate that the farmers of the villages of Bastarm-e Cheshmeh Anjir, Hasan Abad, Tashk, Jazin, Mohammad Abad, Dehuiyeh, Rashid Abad, Helal Abad, and Deh Zir had the lowest vulnerability to climate change.In other words, they have the highest vulnerability.Approximately, 52.93% of the villages have very high and high vulnerabilities.23.52% of the villages have a low vulnerability, and 23.52% of the villages have very low vulnerabilities, too, mainly in the northwest and west of the lake (such as Ghale Mahmoodi, Sangkar, Kazemi, & Bavarkan) (Table 6).
Considering that the variables are adapted to a specific place and time, the natural, economic, social, political, and other conditions are different from each other; therefore, they cannot be accurately compared or applied to other studies (Botero & Salinas, 2013).However, relative comparisons were made to check the results and compatibility of the variables.As mentioned earlier, vulnerability is a function of three variables, including exposure, sensitivity, and adaptations.The reason for the vulnerability of these villages is precisely the lack of diversity of livelihoods, extreme dependence on agriculture, insufficient access to agricultural land in relation to the total number of households, unemployment, as well as insufficient access to education and facilities and lack of insurance products.However, Ellis and Allison (2004) have emphasized the role of livelihood diversification (i.e.rural households' adaption), and infrastructures such as education, roads, facilities, insurance, etc. must be properly developed under the auspices of the government in a way that promotes prosperity and increases the living standards of the people of the region.Hejazizadeh et al. (2015) attribute the sensitivity of their study area to climate change, the high presence of female supervisors, as well as the large number of people working in the agricultural sector.Mbakahya and Ndiema (2015) suggest that 82% of households are vulnerable to climate change's main adverse effects.Their findings also show that farmers with better education, access to loans and markets, better welfare networks, access to extension services for agriculture, and knowledge of precipitation patterns have demonstrated greater vulnerability during and after climate change-induced shocks.Finally, the Bakhtegan basin is one of Iran's most droughtstricken areas, having experienced moderate, severe, and extremely severe drought.According to Iran's National Center for Drought and Crisis Management (2018), the number of places in the Bakhtegan basin impacted by mild, moderate, and severe drought is 19.4%, 31%, and 21.4%, respectively, bringing the total drought percentage to 71.8%.It is also apparent that reducing precipitation and building numerous dams hasten the impact of drought on various sections of the Bakhtegan basin.Considering the impacts of climate changes leading to drought in this region, the percentage of rainfall in the Bakhtegan basin has fluctuated, resulting in a 22.7% annual decline.In addition, in contrast to precipitation, the temperature in the Bakhtegan basin has risen dramatically in the previous three years, exceeding its long-term average.In reality, this basin has been experiencing warmer temperatures, with a cumulative temperature increase of 0.04 °C (Iran's National Center for Drought and Crisis Management, 2018).Furthermore, because of their significant reliance on agriculture for their livelihoods, chronic food insecurity, physical isolation, and lack of access to official safety nets, farmers in the Tashk and Bakhtegan basins are particularly vulnerable to any shocks to their agricultural system.Pest and disease outbreaks, as well as extreme climate events (especially drought), are common occurrences for farmers, resulting in major crop and revenue losses and are exacerbating food poverty.Farmers employ a number of risk-management measures, but they are insufficient to keep them from becoming food insecure.Due to a lack of finances and capacity, few farmers have changed their farming techniques in response to climate change.Farmers' agricultural production and food security, as well as their livelihoods' resilience to climate change, require immediate technical, financial, and institutional help.
This study provides a deeper understanding of the unique context of rural communities.Therefore, the results of this study can still provide significant guidance for future studies on reducing farmers' vulnerability to climate-related risks.According to the results of this study, increasing public welfare is expected to be the most effective method for extremely poor households to lessen exposure to future hazards linked with climate change.This finding may be generalized to other subsistence farming groups since the most fundamental obstacles farmers face amid climate-related hazards are common.It remains to be seen if this finding applies to small-scale farmers.In addition, the results of this study help policymakers and planners to take more effective steps to deal with, adapt to, and reduce the effects of climate change, especially for farmers.The findings of this research provide useful insights to the responsible authorities for policy implementation.

Conclusion
Nowadays, climate changes affect desertification in a slow and imperceptible way and can be recognized by observing some symptoms, such as soil erosion and reductions in temperature, precipitation, vegetation, the efficiency of agricultural products, and surface water and groundwater level.By taking such an attitude, the present study evaluated the vulnerability of the farmers to climate change in the rural areas neighbouring the Tashk and Bakhtegan lakes in Fars Province.Vulnerability as an undesirable phenomenon is a function of the three variables of sensitivity, exposure, and adaptation.Rural communities are more vulnerable, so they have less ability to cope, adapt, and be resilient to climate change.The study area has a dry and semi-arid climate.The ecosystem of such areas is very fragile and sensitive.The exposure variable showed that climate fluctuations and changes are a threat to the environment and consequently to farmers.
Due to the sensitivity variable, components such as lack of agricultural land relative to household members, lack of use of plant species resistant to climatic disasters, and lack of livelihood diversification have led to increased sensitivity of farmers to climate change.As a rule, more sensitivity leads to increased vulnerability.The level of exposure and sensitivity alone does not determine the vulnerability of a community.On the other hand, social, economic, and environmental capital play an important role in reducing or increasing vulnerability.Proper infrastructure such as transportation routes, as well as facilities such as training centres and access to financial facilities, can increase the level of adaptability and reduce vulnerability.According to the results of the adaptation section, the most effective factors that have increased vulnerability are the lack of use of new cultivation methods, lack of access to facilities, and lack of insurance for products.The sum of these factors determines the level of vulnerability of farmers.In fact, the weakness of each of these factors increases the level of vulnerability, which requires increasing the role of government and NGOs.For example, the government can consider solutions so that all farmers have equal and appropriate facilities or change the existing insurance rules so that all farmers can insure their crops.At the same time, they should have the necessary confidence in their product insurance.The main basis for suggesting the adaptation strategies (e.g.providing insurance, access to facilities, reducing climatic sensitivities by increasing livelihood diversification, reducing unemployment, and using drought-resistant plants) by this study was farmers' past perceptions and experiences.Risk experience evaluation, trust in national adaptation, social discourse, precise adaptive capacity, and adaptation incentives are all examples of perceptions that contribute to social and environmental factors.Overall, farmers' perceptions of the appropriateness and effectiveness of adaptation strategies can reveal their new and novel adaptive capacity.
Considering the results, we recommend that the government (as Iran's sole intervener) focus on assisting farmers in this regard because farmers recognize the cost of adaptation strategies as a critical factor in adaptation.It will be very advantageous to provide information on existing simple and low-cost adaptation strategies through educational programmes such as agricultural extension services.Another effective policy for the government would be to invest in the main infrastructure (e.g.subsidies and long-term loans).
As revealed by the findings, to decrease the vulnerability in the region, the diversity of the products, especially those resistant to dryness and salinity, should become more.Therefore, it is necessary for the government to consider these issues in using adaptation strategies at local, national, and international levels and to address these challenges to improve the vulnerability of farming communities and improve their adaptation to climate change.If these actions are timely, correct, based on pre-determined principles, and with plans in which all challenges and opportunities are evaluated and taken into account, their success will be inevitable.
To highlight the feasibility of the suggested measures in this study, the farmers are willing to take adaptation strategies depending on one condition, i.e. if they could be able to examine major climatic hazards and the appropriateness of the measures.If maladaptation has already occurred, farmers are less likely to take the suggested measures.Furthermore, if farmers do not have access to educational and extension programmes, they will explore fewer climatic hazards and the effectiveness of adaptation strategies, resulting in maladaptation.As a result, we need to make sure that such educational and extension information has influenced farmers' perceptions of climate hazards and the effectiveness of adaptation strategies.Maladaptation can occur as a result of inaccurate data, which can thwart adaptation strategies.As a result, information accuracy and timeliness are critical.Finally, the data sources are just as critical as the data themselves.

Notes on contributors
Javad Masoumi Jashni is a master's graduate in climatology.He received his master's degree from the University of Sistan and Baluchestan, Department of physical Geography.He chose the subject of his master's thesis: The degree of vulnerability of farmers around Tashk and Bakhtegan lakes.
Mohsen Hamidian Pour is an Associate Professor in the Department of Physical Geography at the University of Sistan and Baluchestan.He is interested in researching climate change and environmental changes.He is currently the head of the Department of Physical Geography, Faculty of Geography and Environmental Planning.
Mehdi Ghorbani is the head of the group of environmental social scientists at the University of Tehran.His research focuses on natural resources engineering, resource management, and policy-making.His work addresses the complex interaction between society and the environment, with the aim of balancing the exploitation of natural resources and their preservation for future generations.His expertise extends to studying the impact of human activities on ecosystems and exploring techniques to mitigate environmental degradation.Prof. Dr. Hossein Azadi is Associate professor at Economic and Rural Development, Gembloux Agro-Bio Tech, University of Liège, Belgium.His research focuses mainly on "Land and Food" and policies in which he tries to understand the impacts of land governance, land tenure and property rights on agrarian change and food security using political economy theory and mixed-method (quantitative & qualitative) approach.

Figure 1 .
Figure 1.Location of the study area.

Figure 2 .
Figure 2. Schematic representation of the stages of research.

Figure 3 .
Figure 3. Frequency of cold waves (A) heat waves (B) and based on the studied stations.

Figure 4 .
Figure4.The reduction trend of water level of the Tashk and Bakhtegan lakes during 2007-2019 (https://earthexplorer.usgs.gov/)-It can be seen that the two lakes are located in the right side of the images: Northern Lake is Tashk Lake and Southern Lake is the Bakhtegan Lake.It is necessary to mention that the left side of the images is showing the Maharloo lake as well.

Figure 5 .
Figure 5. Indexes determining the exposure of the farmers to the climate change in the studied region.

Figure 6 .
Figure6.Indexes determining the sensitivity of the farmers to the climate change in the studied region.

Figure 7 .
Figure 7. Indexes determining the adaptive capacity of farmers for climate change in the studied region.
Kumar et al. (2016) calculated the vulnerability of Karnataka region by using 27 environmental and socio-economic indicators.51% of the region has high vulnerability.As a result, they emphasized immediate attention and allocation of funds and resources to reduce vulnerability.According to Chinwendu, Sadiku, and Okhimamhe (2017), the increasing vulnerability to climate change is due to a lack of education; lack of access to jobs, resources, and labour supplies; traditional information; and finally, lack of local institutional services.In light of climate change in relation to limited resources and the low capacity for adjustment in response to disorder, particularly in crop growing areas, Omerkhil, Chand, Valente, Alatalo, and Pandey (2020) recognized the high vulnerability of smallholder farmers in the Yongi Qala District's Hill Zone.

Figure 8 .
Figure 8.The exposure, sensitivity, and adaptive capacity of farmers to the climate change.

Figure 9 .
Figure 9.The vulnerability of the farmers to climate change.
Prof. Dr. Ahsen Işık Özgüven is vice Dean of faculty of agricultural sciences and technologies, head of department of plant production and technologies, Cyprus International University, Haspolat, Nicosia, North Cyprus, Turkey.Prof.Dr. Alishir Kurban is a professor at the Xinjiang Institute of Ecology and Geography, Chinese Academy of Science.His research interests include the application of remote sensing and geographic information technology in the field of arid environment and ecosystem research.He also tested new three dimensional modelling technology for archaeological site erosion research and three-dimensional change detection of arid land surfaces including vegetation above biomass changes.

Table 1 .
Introduction of research variables and indexes.

Table 2 .
Classification level of villages using deciles index.

Table 3 .
Frequency and percentage of the component awareness of climate change.

Table 4 .
The result of one-sample t-test on the local farmers' awareness of the climate change in the studied villages.

Table 5 .
Monthly frequency of dry and wet years based on the studied stations.

Table 6 .
The final results of farmers' vulnerability to climate change in the studied villages.