جستجوی مقالات مرتبط با کلیدواژه « تغییر اقلیم » در نشریات گروه « کشاورزی »

Limiting bioclimatic conditions, destructing natural tourist attractions, displacing the tourism calendar, climate change, and global warming may also displace tourism territories to different degrees (Xiu Xia et al., 2023). The findings of various studies assert that due to the increase in temperature, heat stress, and the deterioration of the bioclimatic conditions in the Mediterranean, Malaysia, and America, favorable areas for tourism have been moved to northern latitudes (Jong et al., 2023; Matzarakis & Amelung, 2008). The assessment of the effects of climate change on Iran's tourism also indicates an increase in the locational changes of favorable tourism sites and the shift of tourism classes from excellent or ideal to desirable and suitable due to the increase in temperature and droughts (Sobhani & Esmaeilzadeh, 2020; Moradjani, 2022; Abedi & Sedaghat, 2022; Farajzadeh & Ahmadabadi, 2010).Located in southwestern Iran, Khuzestan Province is regarded as a region with extensive and concentrated tourism capabilities, whose geographical features have led to the formation of mountain, plain, sea, desert, and even desert landscapes. Moreover,Khuzestan plain is known as the cradle of ancient and historical civilizations that continue to the coast of the Persian Gulf, where the cold months of the year (November to April) make the site a suitable place to visit (Borna, 2018, Rahimi et al., 2019). However, the temperature rate has been increasing by one to three degrees from 2017 on (Mohammadi et al., 2024), placing some restrictions on the tourism calendar. Therefore, climate change (2020–2080) may exert an adverse influence on tourism territories in their golden visiting time. Considering the status of tourism in the prospective development of Khuzestan province and the high sensitivity of such potential to climate change, this study sought to investigate the effect of climate change on tourism in Khuzestan province through a temporal-spatial comparative study using the thermal comfort index coefficient.Study Area: Covering an area of approximately 64236 square meters, Khuzestan province is located in southwestern Iran, whose average annual temperature varies from 15 °C in its northern regions to 26 °C in its southern regions. Moreover, more than 85% of the province’s area measures less than 500 square meters, and 15% of the province falls within the north and northeast mountainous regions. As the province possesses great tourism potential, special tourism development plans have been incorporated into the policy documents of the province to prepare the grounds for its sustainable development. However, increasing chances of climate risks such as heat waves, dust, and floods pose a potential threat to the advancement of the tourism industry in the province. In this regard, the current study set out to investigate the change in the thermal comfort index and its territories until 2050.

Method and Data:

 To investigate the effects of climate change on the tourism calendar and its territories in Khuzestan Province, this study examined the thermal comfort index in terms of two periods: the historic period (1985–2020) and the future period (2021–2050). The index considers such climatic elements as air temperature, precipitation, humidity, radiation, and wind. As for the time periods investigated, the study collected the required data regarding the climate variables recorded in the meteorological stations of Ahvaz, Omidiyeh, Aghajari, Abadan, Behbahan, Dezful, Safiabad, Ramhormoz, Mahshahr, and Masjed Suleiman. Moreover, to calculate the thermal comfort index for the future period, the study used downscaled climate data based on CMIP6 scenarios under the SSP 4.5 scenario.

Climate change and global warming have changed climatic comfort conditions and the displaced territories in Khuzestan province. Comparing the maps prepared for the 1985–2020 period with the ones prepared for the future period (2021–2050), the study found that the thermal comfort index territories have been changed in different classes and months of the year. In other words, it could be said that global warming will create a longer summer in Iranian southern regions, leading to the reduction of the geographical territories’ rank from ideal and excellent to lower classes and the movement of tourism territories. In the historical period (1985–2020), March was found to be the most ideal time for tourism. However, the findings revealed that November would be the best time for tourism in the future (2021–2050) when the province would experience the best thermal comfort index conditions. These findings are consistent with the results reported by Matzarakis & Amelung (2008), Xio Xia et al. (2023), Gössling et al. (2023), Rastegar & Ruhanen (2023), Bakhtiari et al. (2018), Shamsipour et al. (2014), Moradjani (2022), Abedi and Sedaqat (2022), and Farajzadeh and Ahmadabadi (2010).

The findings indicated that Khuzestan province will experience great changes in the future in terms of tourism thermal comfort index. In this regard, the province's thermal comfort index rank will, in the future period (2021–2050), decrease in the months of January, February, March, April, and October compared to the one found for the historic period (1985–2020), suggesting that no part of the province will have ideal conditions to attract tourists. Moreover, the conditions will be quite unfavorable in May, June, July, August, and September. However, compared to the historic period, the conditions will improve in November and December of the future period. Furthermore,  the tourism territories of the province will be limited to northern latitudes and mountainous areas in the future.The prospective changes in the monthly tourism calendar and its territories will exert a great influence on the province's tourism economy. Currently, tourism infrastructure such as accommodation, welfare services, transportation networks, and private sector investment have been prepared and developed based on the historical conditions of the climate. Therefore, the relocation of tourism territories, the weakness of facilities in new areas, and the neocolonialization of previously suitable areas will bring about great economic and social losses. Thus, it is recommended that various aspects of tourism development plans be considered based on uncertainties.

Drought stands as an inevitable natural disaster with no means of prevention. Its detrimental impacts extend across diverse sectors, including water resources, agriculture, and the environment. Drought is typically defined as a substantial scarcity of natural freshwater resources persisting over an extended period due to shifts in precipitation and temperature patterns. Consequently, periods marked by below-average rainfall often result in temporary drought, particularly in arid and semi-arid regions characterized by relatively high temperatures. Globally, drought events are classified into four categories: meteorological, soil moisture (agricultural), hydrological, and socio-economic. Studying drought becomes imperative for implementing optimal solutions and strategies to manage water resources and ensure food security, among other concerns.  This research utilizes the Pedj Drought Index (PDI), a unique and potent tool, to delve into drought analysis. The PDI, grounded in precipitation and temperature data, offers a more accurate and accessible understanding of drought's spatial and temporal characteristics. Based on yearly averages at stations, this innovative approach provides a fresh perspective on drought analysis. We gathered and scrutinized annual rainfall and temperature data from 20 synoptic stations in Northwestern Iran from 1987 to 2021 to conduct this study. The PDI's accuracy and accessibility make it a reliable choice for drought analysis, providing a comprehensive view of the situation.  From 1991 to 1995, most of the studied stations experienced wet conditions, while from 2013 to 2017, they faced a severe drought. The most extended wet period occurred in the south at the Bijar station (9 years), and the most prolonged drought period happened in the east at the Ardabil station (8 years). The maximum wet period based on the PDI index (9 years) was observed at the Bijar station, and the most prolonged drought period was at the Ardabil station (8 years). In the northwest of the country, the average duration of the most extended wet periods is 5.5 years, and the average duration of the most prolonged drought periods is 7.5 years. Additionally, the central station experienced two 5-year drought periods, and the Tabriz station underwent two 4-year wet periods. Based on the precipitation anomaly index, 60% of the stations (12 stations) showed a decreasing trend in precipitation anomalies, with the Sanandaj and Maragheh stations having a significant 95% decrease. In comparison, only 40% (8 stations) exhibited an insignificant upward trend in precipitation. The temperature anomaly index showed an upward trend in all studied stations, with only Bijar, Takab, Sarab, and Miandoab stations (highlighted in red) having a significant 95% increase. According to the drought index PDI, none of the stations experienced extremely dry (ExD) or moderately dry (MiD) conditions. The highest percentage of severe drought was observed in Zanjan (71.5%), moderate drought in Khalkhal (20%), and mild drought in Tabriz, Maragheh, and Piranshahr (42.85%). Severe dryness was observed in the Bijar station (42.85%), moderate dryness in Maku (17%), severe dryness in Takab, Khormabad, and Miandoab (71.5%), and highly severe dryness (71.5%) in Ardabil Province. These findings underscore the urgent need for effective drought management and water resource planning in the northwest region of Iran. These findings underscore the urgent need for effective drought management and water resources planning in the northwest area of Iran. Discussion and This study investigated the effects of annual mean precipitation and temperature changes on drought and long-term dry events using the PDI index in 20 stations in the northwest region of Iran, spanning five provinces over 35 years (1987-2021). The northwest Iran stations experienced wet periods from 1990 to 1994, dry periods from 1998 to 2001, and from 2013 to 2017. The most extended wet period was approximately 5.5 years, and the longest prolonged drought period was around 7.5 years. On an annual scale, the PDI could describe the spatiotemporal variations of drought and wetness in the study area to a considerable extent. Despite its simplicity, the PDI provided highly accurate results compared to common drought indices such as SPI and SPEI, which rely on statistical assumptions and distribution-related parameters. The stronger correlation of PDI with SPEI, as opposed to SPI, demonstrates the capability of PDI to explain the effects of precipitation and temperature changes on drought and wetness in the northwest region of Iran.

Climate change is one of the biggest challenges that humanity has faced in the 21st century, because it can have severe effects on water resources, agriculture, energy, and even human bioclimate. The purpose of this study is to investigate the changes of climatic parameters in four sites of Plour, Rineh, Kangarchal and Poshtkoh in Mazandaran province using general atmospheric circulation models. For this purpose, the data of IPSL-CM5A-MR and CSIRO-MK36 models under RCP4/5 and RCP8/5 scenarios have been scaled with LARS WG statistical micro-rotator to evaluate the impact of climate change. After carrying out calibration, verification and modeling of data in two stations (Abali and Kiasar), the effectiveness of the models in terms of the amount of compliance of the observed data with the simulated value using the RMSE index, R2, MAE was evaluated. The obtained results showed that IPSL-CM5A-MR and CSIRO-MK36 models obtain acceptable results. Considering that in Abali station, the amount of rainfall in the base period is 542.08 mm under RCP4.5 and RCP8.5 scenarios in both IPSL-CM5A-MR and CSIRO-MK36 models in the future between (2021-2060) will increase by 0.91-0.97 percent. The average maximum temperature will increase by 1.7-2.2 centigrade and minimum temperature by 1.56-1.88 centigrade compared to the base period. Accordingly, the amount of rainfall in the base period in Kiasar station is 528.46 mm, which under the scenarios of RCP4.5 and RCP8.5 in both models in the future between the years (2021-2060) is 96. 0-87% will increase. The average maximum temperature will increase by 1.72-18.2 centigrade and the minimum temperature will increase by 1.62-1.82 centigrade compared to the base period.

Different plants from different climates are collected according to the objectives of botanical gardens. Climate is one of the important ecological factors that has the greatest impact on the longevity of plants. Changing the location of the plant from a dry to a humid climate may cause stress and change in vegetative behavior. Therefore, the selection of plants for each region should be based on climate knowledge. The objectives of this research included investigating the effect of climate and nutritional treatments on the growth of wild almond (Prunus scoparia Schneider).

This research was conducted by two related experimental methods. One of which included investigating the effect of climate on the growth of wild almond in Nowshahr Botanical Garden in Nowshahr county in north of Iran and the other one was the nutritional treatments on the seedlings of the wild almond in the Garden. The investigated factors in the climate effect test included the species of wild almond, environmental indicators and soil. The nutritional treatments were carried out as a completely randomized factorial design in three replications in the nursery section that the test factors were three levels of calcium nitrate as foliar spraying with a concentration of zero (control), 5 and 7.5 mM and two levels of potassium sulfate as foliar spraying with a concentration of zero (control) and 6 mM. The time of conducting this research was from 2017 to 2022. The seeds of the wild almond species were collected from the heights of Ghatour valley from Rahal village to Ghatour district located in Khoy county, Iran with an altitude range of 1492 to 1873 meters above sea level. Some parameters related to soil, plant and climate were evaluated at the same time as the experiment started in Nowshahr and Khoy counties. After the seeds germinated and the seedlings emerged from the soil, nutrition treatments were carried out by spraying potassium sulfate and calcium nitrite.

The results of the experiments showed that Nowshahr's climate had a significant effect on the growth indicators of almond species from temperature, humidity, evaporation, sunny hours and ice days. The highest photosynthesis rate of 2.45 mg/fresh weight and the highest plant transpiration rate of 1.35 mmol/square meter per second were observed in Khoy climate. The lowest root length in Nowshahr Botanical Garden was 63.32 cm with the highest share of leafless branches at 60.98%. Correlation relationships of root length in the soil and the intensity of leaf fall (leafless branches) show a significant positive correlation at the 1% level with the amount of plant transpiration. The results of the test data showed that the use of potassium sulfate compared to the control seedlings, led to an increase in the amount of plant growth and, as a result, expanded the canopy width. In this research, the relationship between calcium absorption and transport in the plant showed that the reduction of calcium in the leaf tissues in the control seedlings decreased the resistance of the plant to maintain the leaves. Calcium foliar application increased the amount of calcium in leaf tissue in almonds. One of the effects of this phenomenon is the increase in the durability of almond seedlings to about 30%.

Foliar treatments of potassium and calcium nutrients, although to some extent increased the durability of almond seedlings during the experiment, but the growth disorders caused by the effect of climatic factors prevailed over the nutritional treatment. Therefore, the seedlings could not successfully adapt to the new environment even with the help of nutritional behavior.

Evapotranspiration variations (ET0) were investigated and analyzed using Minitab16 software for the 2010-2019 period using the Nizab system's data in Yazd province, and then ET0 was predicted until 2027. Based on the results, the increase of ET0 in cities of Yazd province was affected by the enhancement in wind speed and weather temperature, and the decrease in relative humidity from 2010 to 2019. To determine the appropriate model, Ardakan, Abarkooh, and Taft cities were selected as a representative in each climatic group, and ET0 data for the years 2010 to 2015 were considered as the input data of the software and ET0 data for the years from 2016 to 2019 were used to validate the determined model. The prediction of the determined models showed an increasing trend of ET0 for cold seasons in Ardakan and Abarkoh by 2027. Also, the model prediction showed a decreasing trend of ET0 for hot seasons in Taft by 2027. Also, the ET0 will not change significantly in cold seasons. In Abarkoh and Ardakan cities, autumn-spring crops such as wheat and in Taft city, spring-summer crops such as sunflower will be more affected by ET0 variations.

The uneven distribution of rainfall caused by global warming will lead to more irregular and multiple abiotic stresses such as heat, drought, cold stresses or the combination of them. Developing stress-tolerant plants is the purpose of most plant breeders to develop cultivars that are high yielding with yield stability. Plant responses to drought stress have been evaluated in many different species, but the occurrence of stress memory as well as the potential mechanisms for memory regulation have not yet been well described. It has been observed that plants are able to memorize past events in a way that adjusts their response to new challenges without changing their genetic constitution. This ability could enable the plants to face upcoming challenges. A better understanding of the mechanisms associated with the stress memory leading to change in gene expression and how they link to physiological, biochemical, metabolic and morphological changes would initiate diverse opportunities to plant breeders to develop stress-tolerant genotypes through molecular breeding or biotechnological methods. In this perspective, this review discusses different types of stress memory in crop plants and gives an overall view using general examples. Moreover, with focusing on drought stress, we demonstrate coordinated changes in epigenetic and molecular gene expression control mechanisms, the associated transcription memory responses at the genome level and integrated biochemical and physiological responses at cellular level following recurrent drought stress exposures. Indeed, coordinated epigenetic and molecular changes of expression of gene networks link to biochemical and physiological responses that facilitate acclimation and survival of crop plants during repeated drought stress.

In the last three decades, land use in the Minab river basin has undergone significant changes and these changes along with climate change in the basin can affect the trend of hydroclimatic variables. Due to the changes that have occurred in the climate and land use of the Minab River Basin in the past decades until now, the investigation of trends and changes in the threshold indicators of precipitation, temperature and flow rate becomes particularly important. Therefore, the aim of the current research is to investigate the trend of land use changes and hydroclimatic variables in the Minab basin.

In the current research, the data of hydrometric, rain gauge and evapotranspiration stations in the Minab watershed were analyzed to extract threshold indices based on the ETCCDI standard including precipitation, temperature and river flow. Trend analysis was done using a non-parametric Mann-Kendall test. Also, land use changes were extracted using TM series Landsat satellite images in 1989, 2004, and 2020 from TM, ETM+, and OLI sensors, respectively, and the accuracy of the extracted images was confirmed with Kappa statistics.

The finding showed that all the temperature limit indices, including tropical nights, hot days, hot nights and the range of day and night temperature, have an increasing trend. The extreme precipitation indices, heavy precipitation of 10, 20, and 30 mm in some stations has an increasing trend, but the annual average precipitation has an increasing trend. The number of wet days is decreasing and the number of dry days is increasing. The investigation of the changes in the rainfall regime of the region showed that the intensity of the rainfall is increasing in the duration of 15 and 45 minutes. According to the changes that have occurred, the change in the precipitation situation in the region is inevitable. The survey of land use changes over the past three decades showed that 22% of the pasture land area has decreased, and residential and agricultural land has increased by 280 and 220%, respectively.

Conclusion and Suggestion:

The findings of this research showed that despite the increase in the average annual rainfall (16 mm per year), and other rainfall indicators that had no significant trend, the trend of 15 and 45 minute rainfall intensity was increasing and significant. Contrary to the trend of precipitation, which cannot be proven with great certainty, the increasing trend of all temperature indices (on average 0.9°C per year) confirmed the climatic changes in the Minab watershed. On the other hand, the trend of minimum and maximum stream flow and maximum discharge was also increasing in the watershed, and it can be one of the reasons for the changes in rainfall, construction of dams, and changes in land use from pasture and war lands to agriculture and residential. Based on the results of this research, it is suggested to investigate the effect of future climate changes on meteorological and hydrological variables and use its findings in natural resources management.

Climate is one of the environmental factors whose changes cause extensive alterations in different parts of the ecosystem and pose a significant threat to sustainable development. Temperature, a main element of climate, can affect the climate structure of any region through sudden, short-term, and long-term changes. In recent decades, the Earth has faced global warming, evidenced by climatic changes worldwide. One important consequence of global warming is the increase in extreme weather phenomena, such as sudden temperature changes, excessive heat, abnormal cold, heavy rains and floods, drought, and dust storms caused by the drying of wetlands. Climate extreme indices not only play an important role in investigating climate events on regional and global scales but also assist in climate modeling and decision-making for various sectors.

In this research, temperature data from the MRI-ESM-2 model under three scenarios—optimistic (SSP1-2.6), average (SSP2-4.5), and pessimistic (SSP5-8.5)—for two periods, the near future (2021-2060) and the distant future (2061-2100), were used. First, historical data for the base period and scenario data for the future period (until 2100) for the studied climate model were obtained from the ESGF database. Then, using the R programming language, the time series of historical data and scenarios were extracted from the model for each desired station, and the statistical downscaling of the data was performed using the bilinear interpolation method at the level of the studied stations. The data were grouped based on the three scenarios in all studied stations, and RClimDex software was used to extract indices based on minimum and maximum daily temperatures. In this research, 16 extreme temperature indices for the studied area were calculated on annual and monthly scales, and trends and breakpoints in these indices were investigated using the Mann-Kendall trend detection test, Sen’s Slope test, and Pettitt mutation detection test.

The results show a decrease in extreme hot events based on the SSP1-2.6 scenario, a decrease in indices related to cold and freezing days, and an increase in extreme warm indices based on the SSP5-8.5 scenario, observed in most areas of the province. Generally, the indices for the number of summer days (with a slope of 40-70%), tropical nights (45-65%), the length of the heat period (30-50%), and the length of the growing season (40-60%) showed significant increases. Conversely, the indices for the number of frost days (-20 to -80), ice days (-10 to -40), and the length of the cold period (-10 to -70) significantly decreased. The results of Pettitt's test indicated change points for increasing and decreasing trends in hot and cold extreme indices, respectively, in the 2040s (near future) and 2080s (far future). Therefore, to control extreme temperatures and their adverse effects on various aspects of human life, especially agriculture and water resources, strategies should be developed and implemented according to the needs of each region.

The results indicated more frequent sudden changes in temperature indices under the pessimistic scenario compared to the other two scenarios, affecting broader areas of Mazandaran province. There is a likelihood of sudden increases in hot extreme indices and decreases in cold and freezing days both in the near future (2030s, 2040s, and 2050s) and far future (2070s and 2080s). Overall, significant changes in temperature extreme indices were observed during the future statistical periods studied, with Mazandaran province expected to experience higher air temperatures and more frequent extreme heat events. These findings align with regional and global studies. The rise in temperature, particularly during hot months when precipitation decreases naturally, significantly impacts agriculture in this region, which is a major area for rice production in the country. These changes also affect the hydrological cycle downstream of the Haraz basin. Additionally, temperature fluctuations during winter and cold months can influence the timing of snow melting in the basin, thereby affecting peak flood flows downstream. Given these factors and the necessity of such research in understanding human activities, water resource management, food security, and human health, it is crucial to investigate the impacts of extreme climate events driven by temperature in future policy-making. Human societies must adapt and adjust based on these anticipated conditions. Therefore, studying the intensity, frequency, and timing of extreme events and raising awareness about them can effectively address environmental challenges and enable rational planning to mitigate and reduce these events.

Nowadays, the world has different features than in the past, including intense and competitive changes, low adaptability, complexities, and uncertainties. The agricultural sector, as a major food producer worldwide, is not exempt from these traits, and, according to scientific reports and predictions, these changes are expected to become more prominent and challenging by 2050. In addition to the instability and restriction of main agriculture resources (water and soil), which can be seen in most parts of the world, other issues such as population growth and aging, rural-to-urban migration, declining willingness to work in agriculture, paradigm shift in food supply and demand, and most importantly climate change, have create serious obstacles in agriculture and food security governance of human societies. On the other hand, the technical and hidden aspects of these factors, as well as their entanglements and interactions, have made it more difficult to investigation. It is quite obvious that to overcome this complex and competitive environment, it is essential for countries to utilize efficient tools and methods, taking into account their own developmental conditions, by adopting an interactive approach at national and international levels, they must prioritize the formulation and implementation of strategic programs to enhance resilience and adaptability within their sustainable development policies. One such method that has gained attention in recent decades is futures studies based on the analysis of megatrends, which, through logical data analysis, provide a clearer picture of future priorities, strengths, and weaknesses for policymakers and statesmen. Given that Iran is also among the vulnerable countries against climate change impacts, the changing trend and predictions of the most significant factors affecting water, soil, and food have been evaluated, and while comparing Iran's situation globally, the necessity of serious attention and national resolve to confront these conditions has been emphasized.Studying of the effective trends in the agricultural, especially "climate changes" and "competition for production resources", shows that the emergence and intensification of conditions are quite evident, and despite of the expected unknown progress in the future, planning and implementation of actions based on "Mitigation" and "Adaptation" approaches are undeniable. Since Iran is located in the arid and semi-arid region of the world, it has always faced the negative effects of climate change, especially in terms of quantitative and qualitative characteristics of water resources, and considering that more than 93% of food production in Iran is dependent on irrigated croplands, this issue becomes even more important. Although in the country's Seventh Development Plan, the climate change issue is not considered enough, it is necessary to develop a comprehensive plan compatible with country conditions as a national agenda at the parliament and government level, as well as formation of a national working group consisting of responsible bodies, to implementation of appropriate action based on priorities. Of course, it is necessary that for each topic, the relevant government body should be adopt effective policies, for example, in population and urbanization issues, can be relatively managed through the implementation of incentive programs. Of course, the implementation of large-scale projects like this, will definitely not be realized without the participation and presence of the people, and therefore, one of the important priorities in the current conditions is focusing and preparing comprehensive plan in order to educate and improve public awareness, especially among the young generation, farmers, experts and Even managers. Also, in order to move on the path of sustainable development of the country in the field of water and soil, it is suggested that the following programs and approaches be emphasized and paid attention to:• Conducting of water resources management, especially underground water resources, by implementing watershed plans, flood control, optimal use of green water and water recycling projects.• Improving the productivity and efficiency of irrigation by using modern irrigation methods and using smart irrigation technologies and precision agriculture.• Modifying croping patterns according to the climatic conditions and reducing dependence on climate-sensitive products through plant biotechnology approaches.• Emphasis on the government's support policies for the agricultural sector with the priority of mechanized agricultural projects with high levels and productivity, such as agricultural settlements and revitalization of production hubs.• Development of international cooperation and exchange of experiences with specialized organizations and other countries that work in the field of agriculture and climate change.Fortunately, after establishment of the Global Soil Partnership Program or GSP, in the FAO, valuable actions and activities related to various aspects of sustainable soil management began with the cooperation of countries. Iran joined this program in 2016 and has had several joint programs in the fields of training, soil governance, awareness raising, managing salt affected soils, organizing soil laboratories network, increasing soil organic matter, soil studies, etc. with this international institution. And it is necessary to consider more arrangements for the maximum use of significant capacities with this global program.

Critical to human survival, water resources, including groundwater and particularly rivers, are under threat from anthropogenic pollution. The major Kashafrud River, located in northeastern Iran, is a seasonal watercourse currently encountering numerous challenges. At present, a stretch of this historic river (Parkandabad to the basin's exit) carries wastewater, comprising industrial, urban, agricultural, and even livestock effluents, transforming it into a conduit for sewage. This study reviews existing research on the challenges faced by the Kashafrud River, including pollution, climate change, and its impacts, as well as reduced runoff and drought. It outlines the crisis afflicting the river and then explores solutions to mitigate the current conditions. This research process involved reviewing previous studies on the challenges of Kashafrud, conducting field visits, engaging in discussions with local residents, and validating these findings through consultation with regional water experts responsible for overseeing this water course. Research indicates that there has been a limited focus on the pollution issue in Kashafrud, underscoring the evident necessity for comprehensive scientific inquiry aimed at presenting suitable solutions to tackle river contamination. In conclusion, through analyzing solutions proposed in previous studies and summarizing their strengths and weaknesses, 13 practical solutions were presented to provide the most effective strategies for addressing the challenges of this significant river.

Watersheds are socio-ecological systems that can be significantly affected by climate change. Changes in the pattern and amount of precipitation and increase in temperature can increase the vulnerability potential of watersheds. Understanding the impacts of climate change on hydrological processes and other aspects at the watershed level is crucial for developing approaches to mitigate or adapt to these effects. Therefore, this research aims to assess the impact of climate change on the health of the Radkan watershed in Razavi Khorasan province. In this study, the health of the watershed was initially evaluated for the historical period of 1990-2014 using the Pressure-State-Response (PSR) framework. Sixteen natural and human criteria were selected and classified into three indices: pressure, state, and response. After calculating the criteria for the 14 studied sub-watersheds, they were standardized and weighted using the Analytic Hierarchy Process (AHP). Finally, the health of the studied watershed was determined using the PSR framework for the 14 sub-watersheds and classified into five categories: healthy, relatively healthy, moderately healthy, relatively unhealthy, and unhealthy. To investigate the impact of climate change on the health of the watershed, data from the climate model MPI-ESM1.2-HR were used under two scenarios: SSP2-4.5 and SSP5-8.5. The predicted climate data in three future time periods of 2026-2050, 2051-2075, and 2076-2100 were investigated. The results indicated that during the historical period, one sub-watershed was classified as healthy, two sub-watersheds were relatively unhealthy, and the remaining sub-watersheds were moderately healthy. Comparing the health index in the future time periods with the historical period revealed a decrease in health under both scenarios. The average decrease in the time periods of 2026-2050, 2051-2075, and 2076-2100 under the SSP2-4.5 scenario was 8.84, 8.49, and 11.11%, respectively. Under the SSP5-8.5 scenario, the average decrease was 7.33, 13.04, and 9.85% for the same time periods.

Analysis of the spatial and temporal trends of precipitation is pertinent for the future sustainable management of water resources. Urbanization and climate change affected local rainfall and intensity. As rainfall characteristics are often used to design urban drainage systems, so watershed modeling, and estimate of the flood properties, updating and reviewing rainfall characteristics is necessary. The Intensity-Duration-Frequency (IDF) curves are a suitable tool to estimate the threshold values of precipitation in different return periods. IDF curves should be prepared based on the long-term rainfall statistics in each region and can change under the influence of climate change. These curves which indicate the frequency and maximum intensity of annual rainfall in the different return periods are suitable tools for planning and managing the water resources. IDF curves are broadly used for different purposes, such as the design of flood control and diversion structures in the cities. The main purpose of this research is to investigate the effect of climate change on temperature, precipitation, and IDF curves in the different return periods in an arid environment.

In this research, the effect of climate change on IDF curves was investigated in Kashan City as a dry region. Kashan city with an area of 9647 km2 is located in the northern part of the Isfahan Province. In this study, RCP8.5, RCP4.5, and RCP2.6 scenarios (which are introduced as optimistic, intermediate, and pessimistic scenarios) reported in the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC), were used to predict the impacts of climate change on temperature and precipitation changes. Then, IDF curves were calculated evaluated, and compared for the basic (1993-2017) and future periods (2011-2070). To examine the impact of climate change on the rainfall intensity patterns, it is necessary to extract IDF curves in different climate conditions. Bell's method is a usual method for extraction of the IDF curves, which was promoted by Gharehman-Abkhezr in Iran. In this study, the latest promoted relationships developed were for the desert and southern regions (e.g;Nizar-Salfachgan, Kuhpayeh, Herat, and Jiroft basins in the central Provinces, Qom, Isfahan, Kerman, and Yazd) have been presented and used to extract IDF curves. To investigate the effects of climate change on IDF curves, first, the base period curves were extracted via rainfall data measured at the Kashan synoptic station. Then, using the new climate scenarios (RCP8.5, RCP4.5, and RCP2.6) and the output data of the LARS exponential microscale model, the IDF curves were extracted for different climate scenarios in the future (2011-2030), (2031-2050), and (2051-2070). Finally, the results of these curves were compared with the base period.

According to the results, for the base period, the precipitation and temperature data were predicated with an acceptable accuracy by the LARS model. The accuracy of the model has been higher in estimating the minimum and maximum temperature. the Nash and explanation coefficients for the maximum and minimum temperatures were 0.99 and 0.99, respectively. While, the explanatory and Nash coefficients for precipitation data were 0.95 and 0.93, respectively. Based on the results, the rainfall intensity will have fewer changes compared to the base period for long-term duration rainfall compared to short-duration rainfall (less than four hr. The maximum changes are related to rainfalls with a duration of less than one hour, whereas the minimum changes are predicted for 24- hr rainfalls. For all studied scenarios, a significant difference (P<0.05) was predicted between the average rainfall intensity of 0.17 to 24 hr in the region. As in the two-year return period and under the 2.6 scenario, rainfall intensity was increased from 10.75 to 30.54 mm hr-1 for the duration time of 0.17 hr.

An increase in air temperature, decrease in rainfall, change in the rainfall pattern, decrease in river discharge, and increase in sudden floods, followed by an increase in soil erosion, and a decrease in the amount of agricultural products are the results of climate change. Therefore, the long-term analysis and monitoring of climatic conditions can be very effective for crisis management caused by climate changes such as floods and droughts. Based on the results, the effect of climate change on the intensity of short-term rainfall is greater than long-term duration rainfall, as the intensity of short-term rainfall will increase more than long-term rainfalls.

Climate change is one of the greatest challenges of our time to achieve sustainable development. The dangers of global warming and climate change can be recognised and planned for, so efforts should be made to identify the consequences and methods of adaptation to reduce their impact, as trees and plants are sensitive to climate change, heat and moisture stress, and forest ecosystems are affected by these changes. Climate change is one of the greatest challenges of our time to achieve sustainable development. The threats of global warming and climate change can be identified and planned for, so efforts should be made to identify the consequences and methods of adaptation and reduce their impacts because the sensitivity of trees and plants to climate change, heat and moisture stress, forest ecosystems are affected by these changes. Forest degradation due to climate change is a global phenomenon affecting many tree species. One of the major challenges to Iran's natural resources is the degradation of oak forests. The increase in temperature in recent years has lengthened the growing season of Iranian oak, and due to the lack of rainfall, the intensity of water stress on this forest species has increased. Understanding the extent of climate change in the Zagros ecosystem based on standard indicators that show climate change can help managers and planners take action to adapt to conservation and restoration conditions.

In this study, based on the standard indicators established and updated by the World Meteorological Organization, the occurrence of climate change in six sites monitoring the decline of oak trees in Ilam Province, including Sarabeleh, Mala Siah and Dalab Strait, was detected in both north and south directions. The trend slope line, trend slope error and trend significance of the indices in the statistical range P value=0.05 were calculated using ClimPACT software in R program environment. The characteristics of heat, cold, combined, and precipitation indices such as day, number of occurrences, and continuity of the index in the nearest synoptic station to each site were identified, and daily data of minimum temperature, maximum temperature, and precipitation parameters were used between 1987 and 2019. The variations of each index were plotted and analyzed as graphs in the R software environment. Accordingly, the trend slope and significant indices affecting heat stress (hot temperature indices and cold-temperature indices) and water stress were calculated with the software ClimPACT in the R programme environment.

The results of the trend and significance of thermal indicators for climate change detection showed that of the 16 heat indices studied, in Ivan station, 11 indicators showed a significant trend of about 70% and in Ilam 9 indicators showed a significant trend of about 56%.The heat-based temperature indices, especially those based on maximum temperatures, showed a significant change towards warming, while those based on minimum temperatures showed no significant trend. The study of heat waves showed that the northern and northwestern regions of the province were subjected to several periods of heat waves, which occurred with greater frequency and continuity in the northwestern part of the province (Malah Siah and Dolab Strait sites) than in the northern part (Sarab sites) of the province, confirming the emergence of high mountain regions as a result of climate change. Cold-based temperature indices of 8 studied indices in Ivan-e-Sorchrove station, 7 indices were above 87% and Ilam 3 was about 38% the trend was significantThe cold-based temperature indices in Ivan West station show a significant change in the direction of a decrease of frost and cold and their persistence and warming, and in Ilam station the decrease of cold and warming of air after 2008 indicates a decrease of cold and warming. The results of the trend and significance of the combined indices for climate change detection in Ivan West station were 100% and in Ilam station 50% showed significant trend. The combined indices confirm climate change in terms of increase in air temperature due to increase in growing season and increase in trend of change in maximum temperature. The study of the trend and significance of ten precipitation indices related to the frequency and intensity of heavy rainfall and the length of dry and wet periods showed only one index in Ivan-e-West station, which was about 10%. The station Ilam did not show significant changes in the precipitation index.

It can be concluded that zagros vegetative region in Ilam province has experienced severe thermal changes during 1987-2019 and climate change in the north of Zagros vegetative region is a type of temperature increase that has been extended to the northwestern regions of this region since 2008. The results show that in deterioration sites, in addition to increasing temperature, some precipitation has increased. Therefore, it can be said that the occurrence of climate change phenomenon causes increasing temperature, occurrence of floods, emergence of droughts and creating dust phenomenon, especially from neighboring countries and intensifying it in the country, all of these factors are the starting factors of the decline of Oak Trees in Ilam province. What seems to be important is to take necessary measures to prevent and mitigate the effects of climate change. These two measures can be effective and useful in reducing the effects of flood severity and risk. Therefore, managers and planners of forest ecosystems should have adaptive strategies to climate change in order to maintain and revive their executive plans so that Zagros can survive as a forest ecosystem. Although the occurrence of climate change phenomenon is one of the most important factors of drought and deterioration of Zagros forests, conservation and restoration of oak forest ecosystems can help reduce greenhouse gas emissions and climate change.

Considering the special role of freshwater ecosystems and aquatic species on the sustainability of food security and livelihood of local communities, the evaluation and protection of these natural resources is of great importance. In the current study, the distribution of the Roach (Rutilus lacustris) was predicted under two optimistic and pessimistic (RCP 2.6 and RCP 8.5) scenarios of 2050 and 2080 by Maxent model. The set of data collected by the authors and various available scientific sources from a period of 50 years (1970 to 2020 AD) was used. Also, the environmental and climate variables used in the modeling were extracted and prepared from www.worldclim.org. The results showed that the performance of the model in predicting species distribution was excellent (0.910) based on the AUC (Area Under the Curve) criterion. According to the jackknife test, annual temperature range variable had the greatest impact (54.7) on determining the distribution of the studied species among the environmental variables used in modeling. In addition, it is predicted that under climate change the distribution of the species is likely to decrease significantly in years 2050 and 2080, optimistic and pessimistic scenarios. Also, the highest severity is the pessimistic scenario of 2080 (62.05 %). Therefore, control and reduce the effects of climate change in order to prevent the destruction of riverine ecosystems and preserve valuable edible fish is necessary.

Iran and Afghanistan have a long history of facing climate hazards, leading to extensive damages to life, the environment, and economies. This research conducted a comprehensive comparative analysis of their long-term climate conditions on a national scale.Future climate scenarios based on IPCC6AR were projected to understand climatic similarities between the two nations. The results showed that recent years experienced the highest average temperatures in both countries, with significant changes occurring between 1991 and 2020 within the past 80 years. Monthly average temperatures over the last 80, 50, and 30 years exhibited a consistent upward trend, with the last decade being the warmest. Regarding precipitation patterns, the research revealed significant distribution changes in the last 80 years, particularly during 1951-1980 and 1971-2000 in Iran and Afghanistan, respectively. The study also examined natural hazards statistics resulting from climate change, including event frequency and the number of affected individuals over the past 40 years in both countries. The research emphasized preserving and revitalizing wetlands as an effective triple strategy to address climate change impacts in both countries. Given their shared exposure to climate change, conserving and restoration the Hamoun wetlands is crucial. Additionally, involving third parties in international discussions about wetlands or climate change can help resolve disputes.In conclusion, this study highlights the importance of understanding historical climate conditions and potential future scenarios for Iran and Afghanistan.

Due to climate change and human activities, the quality and quantity of water have become the most important concern of most of the countries in the world. In addition, changes in land use and climate are known as two important and influential factors in discharge. In this research, four climate change models including HADGEM2-ES, GISS-E-R, CSIRO-M-K-3-6-0, and CNRM-CM5.0 under two extreme scenarios RCP2.6 and RCP8.5 were used as climate change scenarios in the future period of 2020-2050. The future land use scenario (2050) was prepared using the CA-Markov algorithm in IDRISI software using land use maps in 1983 and 2020. The SWAT model was calibrated to better simulate hydrological processes from 1984 to 2012 and validated from 2013 to 2019 and was used to evaluate the separate and combined effects of climate change and land use on discharge. The prediction of the climate change impact on discharge showed a decrease in most of the models under the two scenarios RCP2.6 and RCP8.5. The average maximum decrease and increase under the RCP2.6 scenario is 60 and 30 percent, respectively. This significant reduction is greater than that predicted under the RCP8.5 scenario. Examining the combined effects of climate and land use change revealed that the average decrease in discharge in the months of October, November, December, and January under two scenarios is 46.2 and 58%, respectively. The average increase in discharge is predicted to be 47% under the RCP8.5 in the months of April and May in the HadGEM2ES.

Considering its pervasive influence on live creatures, climate change is currently considered one of the most crucial challenges facing human societies, the investigation of which is of great significance. Moreover, climate change exerts an adverse influence on biological resources, the natural environment, and water sources, causing various environmental, social, and economic consequences. Therefore, this study sought to investigate and predict the parameters involved in climate change, including maximum temperature, precipitation, and average temperature under the RCP2.6, RCP4.5, and RCP8.5 scenarios. Furthermore, the applicability of the SDSM model was tested on eleven western provinces of Iran. To this end, first, the predictive variables such as temperature and precipitation were downscaled using combined regression techniques and a small-scale stochastic weather generator, and the required data were collected from the site of the monitoring station. Then, variations in maximum temperature, average temperature, and precipitation for the 2021-2036 and 2036-2100 periods were compared to those of the baseline period (1990-2020). The SDSM model was then validated and its accuracy was assessed using metrics such as MSE, MAPE, RMSE, and MAE.

On the other hand, to verify the accuracy, the data collected for the 1990-2020 period were taken as the actual and observed values, followed by the performance of some simulations with the same data to gauge and measure the accuracy of the extracted data for the 2021-2035 and 2036-2100 periods and compare it with the baseline period (1990-2005). Finally, after confirming the collected data against the actual data of the respective years and determining the accuracy of the four validation methods, the verification process was extended to cover the 1990-2020, 2021-2035, and 2036-2100 periods.

The results of the study indicated that the application of the SDSM model led to a reduction in the required accuracy needed for investigating and simulating climate change. Accordingly, the highest MSE, MAPE, RMSE, and MAE values were found under the second scenario (RCP4.5) in Jolfa station (in terms of maximum temperature), Urmia station (in terms of precipitation), Nahavand station (in terms of precipitation), and Zarrineh station (in terms of precipitation), whose reported values were 0.01, 16.90, 0.10, and 0.10, respectively. On the other hand, the lowest values belonged to the second scenario, whose values were reported to be 0.00, 0.41, 0.00, and 0.00, respectively. Moreover, the results obtained from the application of the SDSM downscaling model to the investigation of precipitation under RCP2.6, RCP4.5, and RCP8.5 scenarios revealed that compared to the other two scenarios, the first scenario (RCP2.6) had a higher level of accuracy in predicting precipitation for 2021-2035 and 2036-2100 periods with a small margin of error, simulating precipitation more closely to the observed data in most cases. Furthermore, the model's predictive outcomes suggested that compared to the baseline period, precipitation would undergo changes throughout the 2021-2035 period, ranging from 2.50% to 3.86%. Similarly, it was found that compared to the baseline period the changes would range from 10.02% to 15.73% during the 2036-2100 period. On the other hand, the most significant alterations in precipitation levels were expected to occur in the Iranian Eastern Azerbaijan and Western Azerbaijan provinces. In this regard, the analysis of maximum temperature rates throughout the 2021-2035 period showed that compared to the baseline period, the rise in the maximum temperature across the study region would range from 0.20 to 0.89 degrees. Similarly, the maximum temperature rate would increase from 0.86 to 0.89 degrees during the 2036-2100, compared to that of the baseline data. However, the most substantial changes in the maximum temperature rate were expected to occur in the southern part of the Iranian Fars province and the bordering areas of Kermanshah province.

As for the average temperature rates, the study found that the temperature would increase from 0.05% to 5.07% during the first time period, and from 4.47% to 5.05% throughout the second period. However, while the least significant alterations in the studied parameters belonged to the RCP2.6 scenario, the most notable changes were found under the RCP8.5 scenario. Moreover, precipitation changes were investigated in forty stations across eleven Iranian provinces throughout the 2021-2035 and 2036-2100 periods, proving a reduction in precipitation rate within both periods, with the decrease being more conspicuous in the second period (2036-2100) under all three severity scenarios. Furthermore, climatic assessments at the station level indicated that the study area would experience a considerable rise in the maximum temperature rate throughout both study periods, with the second period (2036-2100) being expected to witness a more substantial temperature rise. In this regard, all three scenarios showed that the range of increase in the maximum temperature rate would vary from 3.99% to 4.16%, indicating a significant temperature rise in the study area over the coming years. The regions investigated in the current study play a crucial role in supplying water to the central and western Iranian provinces. The regions are also known as significant hubs for agricultural production. Therefore, any changes in weather and climatic parameters in these areas may lead to increased uncertainty in future predictions and planning, requiring the identification of the areas susceptible to risks caused by prospective extreme climate changes. Thus, it is necessary to develop and implement management and operational plans to deal with such changes and to devise the required strategies to mitigate the consequences of those changes and ensure adaptability to the new conditions.

A lack of adaptive capacities for climate change prevents poor farmers from diversifying agricultural production. Climate change adaptation strategies can reduce the production risk relating to unforeseen climatic shocks and increase farmers’ food, income, and livelihood security. This paper investigates date palm farmers’ adaptive capacities to adapt climate change strategies to reduce the date production risk. The study collected 300 farm-level micro-data of date palm farmers with the direct cooperation. The survey was conducted during periods between July and September of 2022. Date palm farmers’ adaptive capacities were estimated quantitatively by categorizing the farmers as high, moderate, and low-level adapters to climate change adaptation strategies. In this study, a Cobb–Douglas production function was used to measure the effects of farmers’ adaptive capacities on date production. The obtained results show that farmers are moderately adaptive in terms of adaptation strategies on climate change and the degree of adaptation capacities. Agronomic practices such as the quantity of fertilizer used, the amount of labor, the farm’s size, and extension contacts have a substantial impact on date production. This study recommends that a farmer more significantly adjusts to adaptation strategies on climate change to reduce date production. These strategies will help farmers to reduce the risk and produce higher quality date fruit. Consequently, date palm farmers should facilitate better extension services and change the present agronomic practice to attain a higher adaptation status. It can be very clearly seen that low adaptability results in lower date yields

Determining the future climate situation by using climate models seems necessary to consider in the field of adaptation or reducing the adverse effects of climate change. In this research, the temporal trend of rainfall, minimum and maximum temperature in the four stations in the Qarasu basin and in addition to, investigated using Thiessen's interpolation method. Among the five models of the CMIP6, three models were selected as the best models and used for MME. Biass Correction was done with CMHyd software for scenarios SSP2-4.5 and SSP5-8.5 in periods 2026-2050, 2051-2075 and 2076-2100. The trend of variables in the base period (1990-2014) and future were investigated with Mann-Kendall test and sens slope. The results of analysis significant trends annual average maximum and minimum temperature of all stations and in catchment area according to SSP2.4-5 scenario in two near and middle future periods and for SSP5-8.5 scenario in all three future periods have a significant trend at the 99% level. In analysis significant trend seasonal rainfall according to SSP2.4-5 scenario in the summer season distant future all stations and in near future of the station area of Gorgan regional water company at the 95% level and for the SSP5-8.5 scenario only in the winter season in the distant future Ghafarhaji station has a significant trend at the 99% level. The future monthly rainfall in the catchment area according to scenario of SSP2.4-5 in August at the 99% probability level and SSP5-8.5 in March at the 95% probability level have a significant trend.

Climate change has the potential to alter the natural distribution of species and reduce biodiversity in forest ecosystems. This study aimed to investigate the effects of climate change on the geographical diversity of Brant's oak (Quercus brantii L.) to identify the suitable area for this species' occurrence and manage its conservation.

The distribution of Quercus brantii was studied under current and future climate conditions (2050, 2070) using two climate change scenarios, RCP2.6 and RCP8.5, HadGEM2-ES General Circulation Model, the Maxent model, and topography data of Fars province.

The results showed that the current potentially suitable areas for Q. brantii constitute 7.8% (9794.5 Km²) of the total area of the province. Under the RCP2.6 scenario, this will decrease to 6.6% in 2050 and increase to 13.3% in 2070. Also, under the RCP8.5 scenario, the suitable area will increase to 8.1% in 2050 and 10.2% in 2070. Areas with moderate, high, and very high suitability, currently at 1.8%, 1.5%, and 1.7% respectively, will decrease to 1.1%, 0.6%, and 0.3% in 2050 according to the RCP2.6 scenario, and then increase to 2.9%, 1.6%, and 1.2% in 2070. According to the RCP8.5 scenario, these values will decrease to 1.6%, 0.6%, and 0.3% in 2050, and finally change to 2.5%, 0.9%, and 0.2% in 2070.

The study demonstrated that the distribution of Quercus brantii is affected by climate change based on both scenarios. Also, the Maximum Entropy model has proven highly effective in predicting the distribution of this species.