Investigating the effects of climate change, drought, and agricultural sector policies on the trend of the water poverty index in Iran

Water scarcity and water stress have become major global concerns over the past years. Increasing water demand due to population growth, urbanization, industrialization, expansion of agricultural activities, and economic growth are some reasons for water scarcity (Duc et al. 2021; Xiao et al. 2021a, 2021b, 2022; Yang & Usman 2021). In addition to the above-mentioned factors, there are some other parameters, such as climate change, drought, and inefficient water management policies, especially in the agricultural sector (Khadka et al. 2017; Salman et al. 2021; Stenzel et al. 2021) which play a significant role in assessing water stress accurately, determining the areas with water shortage, and developing effective management policies. Examining the current water resource situation and its future changes to identify the depth of the water crisis in each region and provide proper management plans requires the use of appropriate scientific multi-criteria indicators (Ray & Shaw 2019).

In Iran, water is mainly used in the agricultural sector (Nouri et al. 2019). The agricultural sector accounts for 92% of water consumption in Iran, which is much higher than the global average (62%) (Mohammad Jani & Yazdan 2014). Therefore, water resources management policies in the agricultural sector can effectively reduce water scarcity and its consequences. Climate change in Iran has shown itself in the form of increasing droughts and a shortage of water resources (Nazari et al. 2018). Therefore, it is vitally important to study the scarcity of water resources (i.e., water stress) and its future changes and evaluate the consequence of climatic variables and drought with and without appropriate management policies in the agricultural sector of Iran.

To achieve this goal, it is necessary to define climatic, drought, and water scarcity indicators. In the study of climate, the United Nations Environmental Program (UNEP) index has been one of the most widely used indicators in different parts of the world (Kimura & Moriyama 2019; Zarei et al. 2019a, 2019b). It has been adopted to determine the climatic situation in various studies (Meslier & DiRuggiero 2019; Moghimi & Zarei 2021; Yang et al. 2019; Bahrami et al. 2020; Zarei & Mahmoudi 2021c). For example, Zarei et al. (2019b) showed that the UNEP index is more accurate in determining different regions’ climatic conditions than the modified De Martonne index. Nouri & Bannayan (2019) examined the trend of changes in the spatial and temporal pattern of the climate index in Iran based on the UNEP index from 1966 to 2012 and found that the index had a downward trend.

Another highly recommended index, which is internationally used in examining droughts and determining their severity and frequency, is the Standardized Precipitation Evapotranspiration Index (SPEI) (Abbasi et al. 2019; Alwan et al. 2019). It has been employed to determine drought conditions in various studies (Polong et al. 2019; Starks et al. 2019; Wang et al. 2019). In the following, some studies are mentioned that have employed this index. For example, Abbasi et al. (2019) have studied and predicted drought in the west of Lake Urmia; Polong et al. (2019) have studied drought's temporal and spatial patterns in Kenya, and Ye et al. (2019) have studied drought's spatial and temporal conditions in Northeast China.

So far, various indicators have been presented to study the scarcity of water resources in different parts of the world, including the Falcon Mark Index, the United Nations Index, the International Water Management Index, the Water Security Index, and the Water Poverty Index (WPI; Ray & Shaw 2019; Shadeed et al. 2019; Wurtz et al. 2019). Many efforts have been made to develop various indicators, methods, and options for quantitative assessment of water stress in the current conditions and its future changes at the regional and national levels (Sullivan et al. 2006). Water resources-related indicators contribute to water adequacy, help ensure food safety and population needs, and are helpful tools for policymakers in water resources management (Koyratty et al. 2021; Ladi et al. 2021; Mishra et al. 2021).

Unlike many indicators, the WPI deals with various aspects affecting the management and development of water resources. It is an effective and comprehensive tool that analyzes the existence of surface water resources and their relationship with human and environmental needs. Due to the unfavorable quantitative and qualitative conditions of water resources, the WPI has been proposed as a multi-criteria and more comprehensive index in the study of water resources (Asiabi Hir et al. 2018).

The WPI has been conceptualized differently in various studies comparing the status of water resources in different regions and countries (Sullivan et al. 2003, 2006; Panthi et al. 2019; Maiolo & Pantusa 2019; Ray & Shaw 2019; Chen et al. 2020; Khadka & Pathak 2021; Koirala et al. 2020). For example, the WPI has been calculated 56 using remote sensing techniques for the environmental component, namely the semi-arid San Luis Potosí region of Mexico, reflecting the strong resource management conflict. Koirala et al. (2020) assessed water stress in 27 areas of the Koshi River Basin in Nepal using the WPI. They selected 12 indicators from the five main components of the poverty index and found that the degree of water poverty in this basin ranged from low to moderate. Chen et al. (2020) argued that water resources on Taiwan's Strait Island are scarce according to the calculated WPI. They also concluded that policies for developing water resources, improving water storage, and controlling groundwater resources could reduce water stress. Khadka & Pathak (2021) examined the correlation between groundwater potential and the WPI in the Midhill region of Nepal and realized that the index is lower than the national level, and the potential of groundwater resources is directly correlated with the WPI.

An international literature review shows that the WPI in the current situation and its trend in the future has not yet been analyzed under climate change, drought, and the application of water resources management policies in the agricultural sector. Therefore, this research has been tried to apply a novel and inventive approach to examine the climate conditions, drought situations, and management policies and their relationship with the WPI. It can be claimed the present study has tried to cover the following objectives: it wants to (a) determine the climatic conditions of the study area during the period under evaluation, (b) evaluate the drought situation of the study region from 2008 to 2018, (c) calculate the WPI in the Fasa plain based on five weight components including resources, accessibility, capacity, use, and environment, and (d) assess the correlation between the WPI and climatic conditions and drought situation (with and without the application of water resources management policies) from 2008 to 2018.

The study area consists of the Fasa plain in Fars province, which is located at east longitude of 53°28′–53°54′ and north latitude of 28° 48′–29° 07′ with an area of 840.21 km² (Figure 1). It is one of the large plains of Fars province located 100 km away from the south of Shiraz. This plain is also situated at an average of 2,040 meters above sea level and has a dry climate with an average rainfall of 289.01 mm/year and an average temperature of 19.42 °C. It is mountainous in the east and is covered with forests and rangeland areas in the east and west. The agricultural and urban lands are mainly located in the central regions of the plain. The Fasa plain does not have a permanent river, and water is mainly extracted from groundwater for various sectors such as agriculture and drinking. The bedrocks in the mountainous regions are mainly comprised of dolomite and calcite, while the surface of the plain consists of Quaternary deposits (i.e., mainly gravel, sand, sandy loam, and clay). In the bed of this plain, agricultural and livestock activities are the axis of the livelihood economy of the local people; in other words, over 80% of the rural population and about 20% of the urban population of Fasa are engaged in agricultural activities and animal husbandry. The dependence of these activities on water resources, the lack of proper management of water abstraction in farms, and the impact of climate change and drought on water resources in this plain have caused the focus on water resources management. Accordingly, this study tries to calculate the WPI in the Fasa plain.

In the above equation, the Penman–Monteith FAO equation was used to calculate the potential evapotranspiration (Allen et al. 1998). Based on the UNEP method, climatic condition classes are presented in Table 1.

Then, the water consumption reduction scenarios in the agricultural sector were presented as a policy approach of policymakers in water resources management to examine the different water resources management policies on the WPI. These scenarios can be played by improving irrigation efficiency through new irrigation technologies and appropriate water transfer systems, cultivating crops that require less water, increasing the use of varieties of drought-resistant crops, and applying low irrigation. Therefore, the impact of water consumption reduction scenarios as the output of appropriate water resources management policies on the WPI is measured using Equation (20).

In this study, the required meteorological data was prepared by the Iran Meteorological Organization. Information about the total volume of water reservoirs of dams, information on water resources (surface and groundwater), incoming and outgoing water, and water consumption in different sectors were provided by the Fasa Water Organization. Statistics of the population and their accessibility to safe drinking water were prepared by the urban and rural water supply department and the central health department of Fasa. Information on agricultural parameters and fertilizers was obtained from the Agricultural Jihad Organization of Fasa.

The resource component is obtained from the total weight of the two indicators of accessibility and variability, considering the same weight for both indicators. The results showed that the value of the calculated resources component ranged from 0.165 to 0.361, and the average value of this component was 0.230 during the years under study (Table 2; Figure 2). The highest and lowest values of the resource component belong to 2011 and 2018, respectively. The value of the resource component for different areas was estimated at 0.61 in Lopez-Alvarez et al. (2020), 0.40 in Koirala et al. (2020), and more than 0.60 in Chen et al. (2020). Comparing the value of the resource component of the study area with other areas shows that the Fasa plain is not in a good position in terms of available water resources.

Figure 3 shows that accessibility had an ascending trend from 2008 to 2018 and reached one in 2018. Therefore, it can be understood that access to safe and healthy agricultural water has been facilitated in the Fasa plain from 2008 to 2018. The high value of the accessibility component has also been proven in other studies, showing the improvement of facilities and technological advances in transportation and health infrastructure around the world (Maiolo & Pantusa 2019; Ray & Shaw 2019; Chen et al. 2020; Khadka & Pathak 2021; Koirala et al. 2020).

Unlike the accessibility, there was a descending trend in the capacity from 2008 to 2018 (Figure 4), indicating that the Fasa plain's residents’ ability to manage water resources has decreased over time. A review of various studies shows that the capacity value is estimated to be higher than 0.50 (Hawrami & Shareef 2020; Koirala et al. 2020; Lopez-Alvarez et al. 2020) in some studies and less than 0.50 in others.

The use component had a downward trend until 2014 and then had an upward trend (Figure 5). The average value of this component was obtained to be 0.73 for the Fasa plain during the studied years (Table 2). Its normalized value varies from 0 to 1. A comparison of the calculated value of the use in this study with the value of this component in other studies (Maiolo & Pantusa 2019; Panthi et al. 2019; Ray & Shaw 2019; Chen et al. 2020; Khadka & Pathak 2021; Koirala et al. 2020) shows that the level of water consumption is high in the Fasa plain.

The results showed the environment is almost declining and fluctuates wildly during the years under study (Figure 6). The average value of this component is 0.60 during the years under study (Table 3). This component is estimated between 0.20 and 0.60 for different regions of the Strait Island in Taiwan (Chen et al. 2020). The value of this component proved that the use of chemical fertilizers is high in the Fasa plain.

The weight of importance of different components was calculated using the entropy model to measure the WPI, which was obtained from the weight composition of the components. Table 3 shows that the highest and lowest weights of importance are related to the use and capacity, respectively. The results of the WPI calculated in Table 4 show that the WPI fluctuated between 0.678 in 2011 and 0.273 in 2015 (Table 4). Therefore, it can be understood that the shortage of water resources (i.e., water stress) has reached its minimum in 2011 and its maximum in 2015. The average WPI of the Fasa plain is equal to 0.562 during the study years. A review of the literature shows that the WPI in most arid and semi-arid regions is between 0.4 and 0.7 (Maiolo & Pantusa 2019; Ray & Shaw 2019; Chen et al. 2020; Hawrami & Shareef 2020; Khadka & Pathak 2021; Koirala et al. 2020).

The study of changes in the WPI and its components in the Fasa plain was presented using different statistical methods, as shown in Table 5. According to all statistical methods, namely, Spearman, Mann–Kendall, and linear regression, the results showed that the accessibility component has a significant upward trend, which can be due to the improvement of people's living standards, higher access levels to health, more arable lands as a result of the destruction of pastures and their conversion into agricultural land, and the ease of supplying the required water as a result of technological progress (Table 5). In addition, the capacity has a significant downward trend based on all the methods indicating the reduced effectiveness of residents’ ability to manage water resources over time. The changes in the WPI is descending and meaningless; however, despite its statistical insignificance, this decline is an alarm regarding the critical situation of water resources available for drinking and agricultural use in the coming years. Naturally, this issue highlights the need for the scientific and appropriate management and control of water resources in the study area.

Based on the UNEP climate index results, the best and worst years were 2016 and 2017, with index values of 0.279 and 0.027, respectively, in terms of climatic conditions (Figure 7). Studies have shown that this index has an insignificant upward trend in the period under review.

Based on the SPEI calculated in the statistical period under review, the most severe drought occurred in 2017 (with the SPEI equal to −3.29), while the most severe wet year (with the SPEI equal to 3.483) occurred in 2016. Studies showed that this index had an insignificant downward trend in the period under study (Figure 8).

The correlation coefficient between the WPI and UNEP and SPEI in Table 6 showed that the correlation with drought is more significant than the correlation with climate. The correlation coefficient between the WPI and UNEP and SPEI is 0.039 and 0.414, respectively, affected by the short-term effects of drought on water resources. However, climate is a long-term phenomenon and its effects in the short term (11-year period under study) are not very tangible. Therefore, drought is a factor affecting the WPI; however, the effect of climate change on the WPI is not proven in the period under review (i.e., a short period).

Agricultural policymakers can reduce water consumption in agriculture by applying appropriate policies to encourage farmers to improve irrigation efficiency through new irrigation technologies and water transfer systems, cultivating crops that require less water, using more varieties of drought-resistant crops, and poor irrigation. In the present study, three water consumption reduction scenarios (10, 15, and 20%) were applied in the agricultural sector of the Fasa plain with the help of policies such as improving irrigation efficiency through the use of new irrigation technologies, and their effects on the WPI were investigated (Table 7). The results showed that the application of irrigation efficiency improvement policies in the agricultural sector of the Fasa plain could increase the average WPI during the years under study. Therefore, the WPI was 0.594, 0.622, and 0.659 with applying water consumption reduction scenarios of 10, 15, and 20%, respectively. The percentage change of the WPI for scenarios of 10, 15, and 20% of water resources consumption reduction compared to the case without using scenarios is equal to 5.69, 10.68, and 17.26%, respectively. This finding shows that as the decrease in water consumption intensifies, the rate of increase in the WPI has become close to the rate of decrease in water consumption. Therefore, further water resources reduction can significantly increase the WPI and solve the water crisis in the Fasa plain.

Finally, the results showed that water consumption management is the most critical measure for reducing water poverty in the Fasa plain, especially in the agricultural sector. As water consumption is in the field of demand in terms of the economic approach, so it is necessary instead of using grammatical tools, demand management in the Fasa plain should be on the agenda to adjust water consumption. According to the results, the WPI quickly depends on drought than climate change. Therefore, it can be understood that drought, despite climate change, will have adverse effects on the water crisis in the Fasa plain in a short time. To this end, it is necessary to use water management policies in the agricultural sector to reduce water consumption and mitigate the unfavorable situation of the water crisis under drought conditions. The results showed that policies of water consumption reduction in the agricultural sector could significantly improve the WPI. Therefore, it is necessary to reduce farmers’ water consumption and solve the water crisis of the drought conditions by teaching agricultural ways such as using new irrigation technologies and proper water transfer systems to farms to increase farmers’ water consumption efficiency and effectiveness.

This study investigated the effects of climate change, drought, and water resources management policies in the WPI and found that the WPI varied from 0.297 to 0.678 in the study area from 2008 to 2018, while its average was 0.562. Therefore, it can be concluded that the region has a moderate water crisis. The trend of different WPI components from 2008 to 2018 showed that the accessibility had a significant upward trend (at the 5% level), and the capacity had a significant downward trend (at the 5% level). The upward trend of accessibility is due to the ease of access to the required water due to the advancement of technology, high level of access to health, and more arable lands due to the destruction of pastures, turning them into farmland over time. The declining trend of capacity also shows that residents’ ability to manage water resources has decreased over time. On the other hand, the downward trend of the WPI, despite its insignificance, showed that the situation of water resources management has been in a more unfavorable situation over time. The results showed that the use has played a more significant role in the occurrence of this challenge than other components.

The authors thank the Iranian Meteorological Organization, the Water Organization of Fars, and the Agriculture Jahad Fars Organization for their cooperation in providing the necessary data.

The participation of authors includes the data collection, analyzing the results, and writing the article.

The authors confirm that this article is original research and has not been published or presented previously.

No funds, grants, or other support were received.

The authors have no conflict of interest. Also, the authors certify that they are not affiliated with or involved with any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this paper.

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