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Agricultural sectors worldwide are under direct threat from climate change conditions. In Iran, agricultural production has decreased due to droughts originating in an increase in annual maximum temperatures—with the corresponding increase in crop respiration and evapotranspiration—and a decrease in accumulated precipitation. Based on a static computable general equilibrium approach, this paper reports implication for the Iranian economy from the effects of climate change on agriculture––as modeled through three scenarios relying on assumptions about the magnitude of continued reduction in total agricultural production. Reductions of 6%, 12%, and 18% in total agricultural production reasonably cover the range of impacts that climate change is expected to impose on the Iranian agricultural sector––under the assumption that no behavioral adaptations or policy interventions are in place. Our simulations suggest that effects on the Iranian economy imply a reduction in GDP ranging between 3.7 and 6.3%. In addition, 5–17% of labor moves away from the agriculture sector––this labor relocation occurs due to declining agriculture incomes. Findings illustrate that climate change will reduce households' consumption and income in all economic sectors, particularly among rural households. We suggest that policies in Iran should focus on improving cultivation methods to save water resources and alleviate the expected effects of climate change. The current study's outcomes are helpful for policymakers, especially in countries with water scarcity. [ABSTRACT FROM AUTHOR]

For an effective reservoir operation during drought, the variations of both water supply and water demand which depend on hydrological and meteorological conditions need to be dealt with. This paper aimed to consider these variations in the Aharchay basin (Iran) by coupling a hedging rule (HR)-based reservoir operation model (HRROM) with a climate-based irrigation scheduling model (CBISM) at the farm level. Through the HRROM, optimal long-term decisions for Sattarkhan reservoir were made by considering the probable streamflow scenarios in the system. Given the variable agricultural demands (VAD) in the CBISM, the irrigation water was optimally allocated to the crops using several evapotranspiration (ET) scenarios. The CBISM employs three sub-models including linear programming (LP), nonlinear programming (NLP), and particle swarm optimization (PSO) to maximize the total income of the Aharchay agricultural network as a function of the climate factors and the supplied water. To this end, the daily weather and discharge data from 1990 to 2015 were used in this study. The standardized precipitation-evapotranspiration index (SPEI) and the streamflow drought index (SDI) were used to detect the meteorological and hydrological droughts, respectively. The SPEI was calculated based on the high-resolution-gridded datasets of the Climatic Research Unit (CRU). The findings demonstrated that the HRROM-CBISM generally managed to increase the time-based (αt) and volume-based (αv) reliability indices by 20% and 44%, respectively, compared with the conventional standard operation policy (SOP). For more investigations, the three major droughts of 2000–2002, 2004–2006, and 2008–2014 were separately analyzed. The average values of αt, αv, and vulnerability (V) for SOP were 0.33, 0.51, and 0.48, respectively. With the HRROM-CBISM, these values were about 0.5, 0.55, and 0.45, respectively. Among these indices, αt had the highest variations, while αv had the lowest variations in both the SOP and HRROM-CBISM approaches. The average water shortage for the mentioned droughts was significantly decreased from 89 (SOP) to 75 MCM (HRROM-CBISM). [ABSTRACT FROM AUTHOR]

Water has been the source of life since it was found. In recent years, the false assurance of the permanence of water services in Iran has led to the creation of institutional structures related to water in an inappropriate and incompatible manner with environmental changes, and when water crises occur, such as droughts, floods, and, on a larger scale, climate changes, they do not have the flexibility and resilience to these changes. To this end, recognizing the current water governance system in the country is considered an essential need. The present study examines the regime of water governance and its structural characteristics in the Kor River basin, which is one of the areas facing water shortage challenges. In order to analyze these characteristics and determine the regime of the water governance system, the method of social network analysis (SNA) was used in the network of formal and informal institutions of Kherameh county downstream of the Kor River basin. This research has been done in a period of 9 months and includes designing questionnaires, field visits, completing questionnaires and analyzing the results. The results showed that the water governance network in this region has an unstable and weak structure and as a result, the level of cooperation and coordination between the institutions is low and the level of power centralization is high. As a result, the governing regime is centralized, and therefore, the establishment of a polycentric governance system requires the improvement of horizontal relations between formal and informal institutions and protection and development institutions. [ABSTRACT FROM AUTHOR]

The present study aims to examine the economic impact of changing climate variables on two components of food security in Iran: availability and access to food. Wheat and rice, the two most important foods in the country, were considered representatives of food security. A CGE model was developed to achieve the research goals. In this context, a stochastic model based on Monte Carlo simulation was used to provide three scenarios (best, average, and worst) indicating probable changes in climate variables. It is important to model the problem of changing climatic variables for irrigated crops, as groundwater resource depletion and restrictions on extraction from Iranian aquifers reduce planted areas and yields. Therefore, this study applies this model to both rain-fed and irrigated crops, whereas studies in the literature only evaluate rain-fed crops. Food security will face serious challenges as food supplies, and consumption of goods and services are declining in average and worst scenarios, according to findings. Consequently, the negative impact of climate change on food security and people's livelihoods requires a review of the policies implemented within the country. Effective solutions include research and development to introduce drought-tolerant varieties and adopt appropriate strategies to adapt to climate change. Improving the incomes of farmers is one solution to mitigating the impacts of climate change. [ABSTRACT FROM AUTHOR]

The Ardabil plain, with an approximate area of 1097.2 km2 in northwestern Iran, has experienced land subsidence due to intensive groundwater withdrawal and long seasons of drought in recent years. Different techniques have been used to investigate and evaluate subsidence in this region including: Global Positioning Systems (GPS), Levelling, and Geotechnical methods. These methods are typically expensive, time-consuming, and identify only a small fraction of the areas prone to subsidence. This study employs an Interferometric Synthetic Aperture Radar (InSAR) technique to measure the long-term subsidence of the plain. An open-source SAR interferometry time series analysis package, LiCSBAS, that integrates with the automated Sentinel-1 InSAR processor (COMET-LiCSAR) is used to analyze Sentinel-1 satellite images from October 2014 to January 2021. Processing of Sentinel-1 images shows that the Ardabil plain has been facing rapid subsidence due to groundwater pumping and reduced rainfall, especially between May 2018 to January 2019. The maximum subsidence rate was 45 mm/yr, measured at the southeastern part of the plain. While providing significant advantages (less processing time and disk space) over other InSAR processing packages, implementation of the LiCSBAS processing package and its accuracy for land subsidence measurements at different scales needs further evaluation. This study provides a procedure for evaluating its efficiency and accuracy for land subsidence measurements by comparing its measurements with the results of the GMTSAR and geotechnical numerical modeling. The results of geotechnical numerical modeling showed land subsidence with an average annual rate of 38 mm between 2006 and 2020, which was close to measurements using the InSAR technique. Comparison of the subsidence measurements of the Ardabil plain using the LiCSBAS package with results obtained from other techniques shows that LiCSBAS is able to accurately detect land deformation at large scales (~ km). However, they may not be optimized for more local deformations such as infrastructure monitoring. [ABSTRACT FROM AUTHOR]

This study investigated the effect of climate change on future precipitation and temperature from 2021 to 2050. Three general circulation models (GCMs), namely GFDL-ESM2M, HadGEM2-ES, and IPSL-CM5A-LR, and two greenhouse emission scenarios, RCP2.6 and RCP8.5, were analyzed for this purpose. The CCT model, precipitation data, and minimum and maximum daily temperatures (from 1986 to 2019) were used for downscaling and correcting precipitation and daily temperature bias. According to the results, the weighted annual precipitation recorded in rain-gauge stations was ascending in all scenarios, except for RCP8.5 in the IPSL-CM5A-LR model. The mean weighted precipitation rate of rain-gauge stations in winter did not descend under any climate change conditions, but the precipitation rate decreased or increased in other seasons. The highest increase of 23 mm in the weighted mean precipitation in winter was calculated under the RCP2.6 scenario in the GFDL-ESM2M model. The highest decrease of 10.5 mm in the weighted mean precipitation was observed in autumn. No temperature decline occurred in meteorological stations. The highest increase of 3.1 °C in the weighted mean temperature and the highest seasonal temperature rise of 8.5 °C were observed in summer under the RCP8.5 scenario in the HadGEM2-ES model. According to the standardized precipitation index (SPI), almost 70% of the future 30-year period are dry years, and drought occurs in almost all scenarios in all Iranian watersheds from 2030 to 2040. Given severe long droughts (14 years), Iran needs a comprehensive management plan and a long-term vision of managers and authorities for water resources. [ABSTRACT FROM AUTHOR]

Climate change and global warming are often considered the main reason for water scarcity in Iran. However, there is little evidence showing that the arid/wet regions get drier/wetter due to climate change. Some researchers believe that parts of water challenges in Iran arise from bad governance and mismanagement of water resources. To address the role of climate change on the water scarcity, this study aims to detect the drought trends in the southeast of Iran to investigate drought characteristics changes during 1981–2020. The nonparametric Mann–Kendall test was used for this purpose. CHIRPS product was collected as an alternative source of ground data for trend analysis of drought characteristics. The evaluation metrics show that the CHIRPS product performs better at monthly and annual scales (correlation higher than 0.8) than daily (correlation less than 0.4). The results also illustrate that the duration and severity of short-term droughts (3, 6, and 9 months) have decreased, while their intensity has increased. Conversely, duration, severity, and intensity changes for long-term droughts (12, 18, and 24 months) are insignificant. The trend in the Standardized Precipitation Index (SPI) showed that, in general, the southeast of Iran has not been getting drier during the last four decades. One may conclude that the change in precipitation is not the only reason for water challenges in this area, and both natural and anthropogenic drought might cause water scarcity. Accordingly, it is suggested that the effects of human activities and governmental plans should be considered as well. [ABSTRACT FROM AUTHOR]

Drought is one of the most complex phenomena in the world; so, proper management is very important in monitoring and reducing its damage. For this purpose, Standard Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Reconnaissance Drought Index (RDI) indices were used to analyze the intensity and frequency of drought in the coastal wet, mountain, semi-mountain, semi-desert, desert, and coastal desert climates of Iran in four seasons, separately: autumn, winter, spring, and summer. Forty-three synoptic stations with a common statistical period of 50 years (1969–2019) were selected. The results showed that the trend of drought in winter and summer is increasing in all studied climates. The comparison of the results in the trend analysis of the drought showed the same trend, but the SPEI index compared to the other indicators showed a quicker response to changes in drier climates. The highest correlation (0.80–0.99) between SPI-RDI and SPEI-RDI indices in coastal desert, mountain, and semi-mountain climates and the lowest correlation (0.34) between SPI-SPEI and SPEI-RDI indices in semi-desert, desert, and coastal desert climates were obtained. SPI-RDI variations showed similar values in colder climates. The SPEI is based on precipitation and temperature data, and it has the advantage of combining multi-scalar character with the capacity to include the effects of temperature variability in the drought assessment. Thus, SPEI is recommended as a suitable index for studying and identifying the effect of climate change on drought conditions. [ABSTRACT FROM AUTHOR]

This study evaluates the impact of climate change (CC) on runoff and hydrological drought trends in the Hablehroud river basin in central Iran. We used a daily time series of minimum temperature (Tmin), maximum temperature (Tmax), and precipitation (PCP) for the baseline period (1982–2005) analysis. For future projections, we used the output of 23 CMIP5 GCMs and two scenarios, RCP 4.5 and RCP 8.5; then, PCP, Tmin, and Tmax were projected in the future period (2025–2048). The GCMs were weighed based on the K-nearest neighbors algorithm. The results indicated a rising temperature in all months and increasing PCP in most months throughout the Hablehroud river basin's areas for the future period. The highest increase in the Tmin and Tmax in the south of the river basin under the RCP 8.5 scenario, respectively, was 1.87 °C and 1.80 °C. Furthermore, the highest reduction in the PCP was 54.88% in August under the RCP 4.5 scenario. The river flow was simulated by the IHACRES rainfall-runoff model. The annual runoff under the scenarios RCP 4.5 and RCP 8.5 declined by 11.44% and 13.13%, respectively. The basin runoff had a downward trend at the baseline period; however, it will have a downward trend in the RCP 4.5 scenario and an upward trend in the RCP 8.5 scenario for the future period. This study also analyzed drought by calculating the streamflow drought index for different time scales. Overall, the Hablehroud river basin will face short-term and medium-term hydrological drought in the future period. [ABSTRACT FROM AUTHOR]

While the literature on adaptation to drought has increasingly focused on investigating farmers' understanding of drought, no comprehensive study has been conducted on behavior determinants and farmers' adaptation strategies so far. To address this research gap, the current study was performed to investigate the effective factors and determinants on applying adaptation strategies by farmers in Iran. The statistical sample of the study included 430 farmers in East Azerbaijan province (located in northwest of Iran) selected through multistage sampling method. Study results after categorization of adaptation strategies (AS) first indicated that, the farmers under study suffer from a lack of high adaptation but in order to add more accuracy and grouping farmers' strategies in drought condition, exploratory factor analysis was applied in which they were categorized as self-control, active and integrated strategies. Next, structural equation modeling was adopted to study the effective factors on applying AS by farmers confronted with the drought. The results showed that, social, environmental, infrastructure, and economic factors exert a positively significant effect on selecting the AS whereas, human-related factors were proved to have an insignificant effect on adopting the AS. The results associated with structural equations indicated that, effective factors account for 93.3% of variance in application of AS which is a highly considerable rate. Indeed, these results revealed high importance of social factor, environmental factor, infrastructure factor and economic factors in applying the AS among the farmers. Therefore, our findings offered solutions as to how to reduce risks in farmers' activities during drought conditions to improve adaptation behavior of Iranian farmers. [ABSTRACT FROM AUTHOR]

Drought monitoring is very important for water resource planning due to the impact of climate change on the frequency of drought events. The objective of this study was to evaluate the spatiotemporal characteristics of drought in Iran. Spatial and temporal distributions of drought severity were assessed using the well-accepted standardized reconnaissance drought index (RDIst) in seasonal and annual scales in 40 synoptic meteorological stations of Iran during the years 1967–2014. Parametric and nonparametric statistical tests were further used for trend assessments. According to the results of RDIst on an annual time scale, the trends of drought were positive in 87.5% of the stations. The results of seasonal RDIst also indicated that the trends of drought in winter (92.5%), spring (82.5%), summer (37.5%), and fall (67.5%) were upward. In sequence series of all seasons, 90% of all stations had a negative trend in the value of their calculated RDIst over time, which means an upward trend in drought over time. Our findings demonstrated an upward trend in drought over the study period. In 45% of the studied stations, winter had the most significant positive trend at all time scales. The results also showed that a moderate drought covered the highest portion of the study area. Generally, a positive trend was observed in coverage of extreme, severe, and moderate drought. However, a negative trend was evident in the coverage of extreme, severe, and moderate wet conditions during the time. It is suggested that the spatiotemporal distribution of the RDIst trend can be used to identify drought and mitigate its impacts in Iran. [ABSTRACT FROM AUTHOR]

This study evaluates trends in climatic variables, atmospheric evaporative demand (AED) and meteorological drought between 1988 and 2018 over the southwest of Iran, where the Karkheh Basin is located. For this purpose, we used monthly time series of meteorological variables (precipitation, air temperature, wind speed and sunshine duration). The AED was estimated by the FAO-56 Penman-Monteith equation and drought severity by the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). There have been significant changes in the climate over the study domain, including a large increase in air temperature and wind speed and a decrease in relative humidity, which have driven a positive trend in the AED. The SPEI for the region has fallen, with the decrease being larger than the magnitude of change observed with the SPI. This suggests an increase in drought severity mostly associated with the rise in AED. The implications for water availability and climate change processes in the region are discussed. [ABSTRACT FROM AUTHOR]

Drought analysis has gained great importance owning to recent global warming and climate change. Because of the importance of the Khuzestan province in agriculture and economy of Iran, a semi-arid country, this research evaluates its meteorological drought severity. The data from 40 meteorological stations in the period of 1954 to 2016 were collected and used for this purpose. Standard Precipitation Index (SPI) has been used for assessing the 3-, 6-, 9-, and 12-month time scales meteorological droughts. For regional drought analysis, the linear momentum method is used and after selection of the best regional probability distribution, SPI was calculated at each meteorological station for different return periods and time scales. The results indicated that severe and extreme droughts may occur in west, east, and south of the Khuzestan province in the near future. Also, while the severity of drought is less in north of the Khuzestan province, the probability of occurrence of severe and extreme droughts in central zone of the Khuzestan province (e.g., Ahvaz) is less than other regions. [ABSTRACT FROM AUTHOR]