mohammad reza yazdani

Drought is one of the natural disasters that has caused a lot of damage in Iran. Considering the importance of the Hable Rood watershed in the development of various activities, especially the agricultural sector, and the adverse effects of drought on this region, in this research, the causes of drought including natural and human factors in the region were investigated and using the Group Analytical Hierarchy Process (GAHP) Factors were ranked. The results obtained from 11 natural factors and 14 selected human factors showed that among natural factors, rainfall reduction is the most important factor and water and wind erosion is the least important factor. Among human factors, the lack of integrated and efficient management in the water sector and agriculture, and regional and national policies have been identified as the most important factors, and piloting the region as the least important factor. The obtained results indicate that the water shortage crisis can be managed better with proper and efficient management and the implementation of correct policies in water management. On the other hand, proper actions should be taken by the authorities in this regard. The obtained results can be used for related organizations to solve the problem of water stress in the studied area.

Groundwater is considered one of the most important sources for agriculture and drinking water supply, and it is significantly affected by environmental and climatic factors. Our limited understanding of hydrological processes, particularly groundwater resource, makes understanding the metrics and patterns affecting groundwater recharge essential for the optimize water resource management. Examining the temporal patterns of groundwater recharge provides a foundation for sustainable management of groundwater resources to mitigate the effects of drought on water supplies.

This study quantifies groundwater recharge from 2008 to 2018 using the SWAT model in the Damghanroud watershed located in Semnan Province. Calibration and validation of the model were performed using SWATCUP and the SUFI2 algorithm. The standardized precipitation index (SPI), the reconnaissance drought index (RDI), and the standardized runoff index (SRI) were used to assess the impacts of drought on aquifer recharge. The trend of aquifer recharge was analyzed using the Mann-Kendall non-parametric test and Sen's slope estimator method.

The analysis of the Nash-Sutcliffe Efficiency (NSE) coefficient during the calibration (0.77) and validation (0.69) periods in the SWAT model showed that the model's performance in simulation groundwater was relatively good. The findings revealed that, on a monthly scale, the effects of drought on aquifer recharge did not show a specific trend; however, in the winter, spring, and summer seasons, there was an increasing trend in the decline of aquifer recharge. Reduced rainfall and runoff, coupled with increased temperature and evapotranspiration during rainy seasons, intensified drought conditions, leading to decreased groundwater recharge.

and suggestionsTemporal analysis of aquifers revealed that in arid and semi-arid regions, climatic variable changes are closely linked with drought phenomena. The results of this study show that the temporal pattern of aquifer recharge changed under the influence of various variable changes in the watershed, and the magnitude of these changes was based on the correlation of the variables. The trend analysis of droughts on aquifer recharge showed an increasing trend during wet periods and a decreasing trend during dry periods. These findings can be used to improve aquifer recharge during wet periods and to mitigate the effects of droughts on aquifer recharge through optimal management and planning of existing water resources. It is recommended to implement comprehensive planning and optimal management of water resources during both wet and dry periods to improve groundwater recharge and mitigate the effects of drought. Additionally, using climate change prediction models and strengthening monitoring of groundwater resources in arid and semi-arid areas is essential to prevent unexpected reductions in aquifer recharge in a timely manner.

Agricultural drainage water, containing inorganic minerals (nitrogen, phosphorus, and metals) and organic pollutants (pesticides and agricultural toxins), is considered a major threat to aquatic ecosystems, leading to eutrophication and damage to downstream water resources. Undredged vegetated ditches can potentially serve as effective beds for removing nutrients and suspended solids from agricultural drainage water. This study investigates the efficiency of non-dredged drainage channels in removing nutrients from drainage water in the paddy fields of Gilan province. For this purpose, two treatments of natural drainage channels, without vegetation (V1) and with vegetation (V2), with lengths of 200 and 105 m respectively, containing specific plant species (Reed, Typha, Sparganium) were examined under high (C1) and low (C2) pollutant concentrations in July and August. The study measured the initial nitrogen and phosphorous content in water, sediment, and plants to compute the mass balance for the V1C1, V1C2, V2C1, and V2C2 treatments. Analysis of variance revealed significant removal of nitrogen and phosphorus, with the highest removal percentages observed in the V2C2 treatment. Phytoextraction was the primary nitrogen and phosphorous removal process in V2C2 at the rate of 37.06% and 61.69%, respectively, while seepage losses dominated in V2C1 treatment at 27.42% and 20.04% per 100 meters, respectively. Sediment absorption was notable, particularly for nitrogen in V2C2 and phosphorus in V1C1 treatments. Thus, our findings suggest that natural un-dredged drainage ditches possess promising capabilities in eliminating typical pollutants discharged from agricultural areas, thereby substantially improving the quality of drainage water that flows into downstream water sources.

The Alzheimer's disease, a progressive brain disorder, necessitates timely detection for effective management due to the current diagnostic methods' limitations. The study presents an efficient convolutional neural network (CNN) designed for classifying brain magnetic resonance imaging (MRI) images into four categories related to Alzheimer's disease. To enhance diagnosis, this study proposes two distinct approaches at different stages: (1) using optimized data pre-processing; and (2) designing a lightweight CNN architecture with low complexity and fewer parameters that simultaneously possesses good accuracy, computational efficiency, and excellent performance. The proposed method achieved outstanding results, with a final accuracy of 99.22%, a macro average F1 score of 0.99, an MCC of 0.9870, and a Cohen kappa score (CKS) of 0.9870. In addition to accuracy, the complexity of the proposed model, including the comparison of model size, time elapsed, the number of FLOPs, and the trainable and non-trainable parameters of the proposed method were also thoroughly investigated. This model, with the advantages of high accuracy, reduced FLOPs, faster execution time, and lower memory requirements outperforms other deep learning methods used in recent studies.

Diagnosing and controlling the level of stress in order to reduce the risks is so important. In this study, a system for detecting five levels of stress, i.e. physical stress, semi-emotional stress, emotional stress, cognitive stress, and resting state in people based on physiological signals, is presented. In the proposed method, the Non-EEG Dataset for Assessment of Neurological Status database, which is available on the Physionet website, is used. This database contains physiological signals from twenty people. These data were collected using non-invasive wrist biosensors. A set of statistical and frequency and wavelet features are calculated for electrodermal (EDA), temperature, acceleration, heart rate (HR) and arterial oxygen level (SpO2) signals. The determined features are applied as input to the classification units to detect the stress levels. Support vector machine (SVM), k nearest neighbor (kNN), decision tree (DT), ensemble learning and neural networks are evaluated as classification methods. Experimental results show that neural networks can separate different neural states of 5 classes with 97% accuracy.

In this era, cognitive warfare is the main tool to achieve the developmental goals of arrogant powers without military conflict. Cognitive warfare is a hybrid approach of cyberspace non-mobile combat capabilities to win a war without physical confrontation. In 1401, after the death of Mahsa Amini, the enemy used media tools to use cognitive warfare against the Islamic Republic of Iran. So; The present research tries to identify the war science and media flow of the BBC Farsi news agency with the Vandyke critical discourse analysis method and using the statistical community of news published by the Farsi-language media BBC Farsi in the period from September 1401 to December 1401. slow The results of the research indicate that: BBC Persian news texts in terms of lexical style, people and institutions mentioned in the text, neutralization, citations, presuppositions and associations and insinuations, are trying to launch a cognitive war through media tools; form discourses; Discourse analysis of news texts of BBC Farsi media showed that: the main discourse of BBC Farsi website regarding the news coverage of the protests after Mahsa Amini's death was "mandatory hijab", "police violence", "lack of freedom and justice". ", "violation of human rights", and "public dissatisfaction".

Using magnetic water may be one of the ways to improve the effects of water quality/quantity in agriculture. The water shortage in the country and the continuation of droughts are considered as the most important factors limiting crop growth. In this research, effect of magnetic water on the growth and yield of two plants, namely, corn (Zea mays) and roselle tea (Hibiscus sabdariffa), was investigated. The study included three treatments of magnetic water (EC=2 dS/m (  including magnetic water (T1), electromagnetic with high frequency range (T2), and electromagnetic with low frequency range (T3), and a control, in the Educational and Research Field of Semnan University, Iran. In order to investigate the effect of different magnetic water treatments on the morphological characteristics of corn/maize and roselle tea, an experiment was conducted in the form of a completely randomized block design (four blocks and three replications). Results revealed that corn yield in treatment T3 was 1663 gram and outweighed the control by 147 gram. Yield of roselle tea plant for treatments of T1, T2 and T3 was 259, 268 and 235, respectively. However, the results of this study showed that the effects of three magnetic water treatments on the growth performance of maize and roselle tea are not statistically significant at the 95% confidence level. In general, the results show that magnetic water can greatly increase the yield of maize, but the irrigation of roselle tea with magnetized water increased growth, and yield was better during the growing season.

Evaporation is one of the important phenomena of the hydrological cycle and its prediction is essential in water management, planning and conservation. Since chaos theory deals with the study of dynamic systems, therefore, in this research, the prediction of the evaporation process was carried out using the combination of chaos theory and intelligent models, including support vector machine, decision tree, group learning, and Gaussian process.Data of the Semnan synoptic station was selected during the period of 1995-2019. The optimal values of delay and mutual information were obtained using false nearest neighbor methods in order to reconstruct the variable phase space of evaporation, equal to 18 and 9, respectively. According to different combinations of variables, the most optimal response of all models was determined for the combination of all parameters, and the two factors of evaporation and temperature had the greatest impact on the prediction. In general, the support vector machine model with R2 = 85.5 and MAE = 1.4 had the best performance, and then the methods of Gaussian process, group learning and decision tree method performed well. The combined use of chaos theory along with intelligent algorithms has a good ability to estimate evaporation.

Puddling process is a part of land preparation in rice cultivation. In other words, puddling is an important method of soil management, which is done to disturb the structure of the surface layer of the soil and prepare the field for rice transplanting. Usually, in this process, the soil is flooded and tillage is done on it. The soil texture and the soil moisture conditions before flooding are factors that affect the process of the puddling. Therefore, this study was conducted to determine the effect of initial soil moisture and soil texture on some properties of paddy soils puddling process in Guilan province.

The experiment was conducted as a factorial based on a randomized complete block design in three replications. Three textures (silt, silty clay, and clay) of paddy soils were prepared under four initial soil moisture treatments (85, 90, 95, and 100% degrees of saturation). After preparing the soil samples, they were puddled using a laboratory panel. During and after the puddling process, the amount of net water consumed, the depth of water collected on the soil 2 and 6 days after puddling, the soil swelling at the end of the operation, the depth of soil settlement after 2, 4 and 6 days and the final depth of the soil were measured. Statistical analysis of the effect of the experimental treatments on the measured properties and their mean comparison was done with LSD test using SPSS 23 software. Calculations and graphs were done using EXCEL software.

The results showed that the independent effects of initial soil moisture and soil texture on all of the measured properties except the depth of soil after 6 days were statistically significant at 1%. With increasing initial soil moisture, the amount of net water consumption and the final depth of soil decreased and other measured parameters increased. On the other hand, the effect of soil texture on net water consumption, water collected on the soil 2 and 6 days after puddling, soil amass at the end of the operation, depth of soil after 2 and 4 days, and the final depth of the soil were statistically significant at 1%. The interaction effect of initial soil moisture and soil texture on soil amass at the end of the operation and final soil depth was statistically significant at 1%, and for the depth of water accumulated on the soil 2 days after puddling and the depth of soil after 2 days was statistically significant at 5%. By increasing the initial soil moisture content from 85 to 100% of saturation degree, the amount of water used for the puddling process decreased by 61%.

According to the results, the features of the puddling process are affected by the initial moisture and soil texture. Therefore, the results of this research can be used in the agricultural management of paddy fields in Guilan province. With increasing soil clay content, the measured parameters include the amount of net water consumed, the depth of water collected on the soil 2 and 6 days after puddling, the soil swelling at the end of the operation, the depth of soil settlement after 2, 4 and 6 days and the final depth of the soil were increased. The range of net water consumed in the puddling process for experimental treatments varied between 31 and 114 mm, and the lowest was obtained in silty soil texture with 20% clay and initial moisture treatment of 100% degree of saturation. Estimating water consumption in the puddling process and its correlation with initial soil moisture and clay percentage can inform the management of the agricultural calendar and water allocation program in the Sefidroud irrigation network for paddy fields. This information can help optimize water usage, especially in light of rainfall events at the start of the irrigation season, with the goal of reducing overall water consumption.

Selection and accuracy of appropriate zoning methods and preparation of maps corresponding to variation of groundwater qualitative characteristics depend upon the region's condition and the available statistics and data. The goal of this research is to determine the most appropriate method of interpolation and spatial analysis of qualitative components such as Cl, EC, SO4, SAR, TDS and TH of groundwater in Mashhad Plain. In this research, at first, the data of 177 wells were selected with respect to their dispersion and accuracy for two consecutive years (1392-1393); then controlling and reconstruction of data were performed. Kolmogorov-Smirnov test showed that the data were not normal and to normalize them their logarithm was obtained. Then using GS+software, the best variogram model was fitted to the spatial structure of data. The results show that for qualitative parameters, the exponential, Semi-variogram and linear models are the best semi variogram models. The precision of groundwater qualitative parameters in the three methods of Kriging, Cokriging and Inverse Distance Weighting (IDW) was assessed and the precision rate results showed that Cokriging method has a higher precision and lower error. The spatial structure of studied characteristics follows the exponential, spHerical and linear model with an influence range of 9656 to 71100001m and the threshold range of 0.965 to 5.65, and the spatial dependency class was in the range of 0-0.87. Finally, the zoning maps of water qualitative parameters were prepared using GIS software. Due to population concentration in the southern parts and overuse of wells and recent droughts, the highest values of qualitative components belong to the south of the study area. According to the geological formations and the type of rocks in the northwest and southeast, the concentration of calcium, potassium, sodium, chlorine, as well as the percentage of evaporation and transpiration and temperature are more evident.

In this research, three methods of interpolation, namely, Weighted distance image, Kriging and Co-kriging are used to predict some quality indicators such as Na, TH, EC, SAR, CL, CA, Mg, and SO4 in 2013-2014. Data have been collected from 177 piezometric wells in the Mashhad Plain. In this study, after data normalization, parameters were interpolated using three geostatistical methods (ordinary kriging, co-kriging, and IDW). In order to evaluate the methods of interpolation, the mutual evaluation test was used. Then, based on the best method of mediation and the use of geographic information system, a map of some parameters and plain zoning maps were prepared.

The purpose of this research was to determine the most appropriate interpolation method in order to investigate and spatially analyze the changes in some quality characteristics of underground water in Mashhad plain. After the appropriate model was fitted, according to CO/(CO+C) observations, the strength of the spatial structure in the quality components of the studied water is not very strong. For the zoning of the quality components, the Co-kriging method was introduced as a suitable method, and considering that correlation between different variables is used in this method. It can be said that there is a significant relationship between the components of groundwater (Zahtabian et al., 2019). The results of zoning the quality of the parameters showed two inappropriate ranges in the northwest and east of the region, which about 70% of the exploitation wells are located in these areas. Also, due to the recent droughts, the process of desertification will be accelerated in this region; therefore, more attention should be paid to the proper management of underground water in this region.

 According to the obtained results, the best fitted model for CA and MG parameters is linear model; EC parameters are exponential model and NA parameters are Semi-variogram model. Regarding the spatial structure, parameters MG and TH have strong location continuity (less than 0.25) and parameters MG, NA, EC have weak continuity (more than 0.75). According to the obtained results, was used to estimate TH from anion, CL from TDS, anion from cation, CL from anion and vice versa and estimate CL from SAR.The results show that the concentration of calcium, potassium, sodium, chlorine, SAR, TH, PH is higher in the northwest and southeast, and as a result, the quality of water for various uses is lower, which is one of the possible reasons, in addition to the different formations of the earth. The geology and type of rocks (that is, the presence of gypsum materials and stones in the northwest and southeast parts or smaller amounts of these materials in the north, central and south parts (Owaisi, 2000)) can lead to higher temperature and drier environment which is the result of the higher rate of evaporation and transpiration as well as the type and density of land use (Laleh-Zari, 2019)

In order to analyze the temporal and spatial changes in the amount of water required for puddling in rice fields of the Sapidroud Network, daily soil moisture data from the SMAP satellite was obtained and used in a seven-year period (2015 to 2021). The puddling stage (from April 20 to June 10) was analyzed after grouping based on different probability of occurrence (1%, 10%, 25%, 50%, 75%, 90% and 99%) and using raster calculations. In addition, in order to validate the calculations, the predicted values were compared with the saturated soil moisture values of 321 soil samples with specific geographic coordinates that had been measured by the Rice Research Institute of Iran. The comparison was conducted by using the mean absolute error (MAE), mean bias error (MBE), and normalized root mean square error (NRMSE). The results showed that in all moisture scenarios (from the wettest to driest), the foothills had less moisture than the plain and, especially, the low lands, and the soil moisture showed a decreasing trend during the growing period. The rate of this reduction increased gradually and in some areas it reached 2% per day at the end of the puddling period (May 22 to 31). The amount of gross water required for puddling increased from the wettest to the driest year and in the middle of the season (May 3 to 5) it was from 1693 to 2983 square meters per hectare and at the end of the season from 2496 to 3602 m3/ha, respectively. The validation results showed that the calculated MAE, MBE, and NRMSE values were 4.26%, 1.59%, and 15%, respectively, indicating that the accuracy is acceptable. The findings showed that the delay in the start of the puddling operation increases the water required for puddling operation (1.34 m3/ha for each day delay in a normal year). Therefore, in the lands of this network, in all circumstances, especially in dry years, to save water, it is better to release/supply water required for puddling from local reservoirs, wells, or from the Sepidroud Dam in early May.

Teleconnection patterns can affect climate parameters in different regions of the world. Investigating their effects, especially on the climatic extreme values, can provide appropriate information for optimal management of weather processes as well as terrestrial ecosystems, including vegetation. Temperature is one of the important elements of the atmosphere and is involved in climate changes on a regional and global scale, which quantitatively leads to tremendous events affecting the environment, including increased evaporation and transpiration and plant water needs, increased frequency of droughts, and lack of water resources. The effects of extreme events are often large at the local scale and can severely affect certain sectors and regions. The everincreasing emission of greenhouse gases will cause global warming and cause damages and losses to the water, agriculture, environment, and economy sectors and will have a significant impact on the lives of humans and animals. One of the most important effects of this phenomenon will be the influence on extreme events of atmospheric and climatic elements such as drought, flood, and storm. On the other hand, atmospheric circulations are very variable. These changes lead to the emergence of air patterns and forms of atmospheric currents that occur in different time scales. The teleconnection patterns indicate large-scale changes that occur in the pattern of atmospheric waves and winds and affect the temperature pattern, precipitation, direction of clouds, and position and intensity of the winds in many regions. The effectiveness of these indicators has attracted the attention of researchers in various parts of the world, indicating the importance of these interactions on the atmosphere and surrounding environment. The purpose of present research was to investigate the effect of teleconnection patterns on temperature extreme values (minimum and maximum) in Chaharmahal and Bakhtiari province.

Chaharmahal and Bakhtiari province is one of the mountainous parts of the central plateau of Iran, which has an area of 16421 km2 and is one of the mountainous and rainy provinces of the country, which are the source of two important rivers of the country, Zayandehroud and Karun. This province has one percent of the total area of Iran, which is located in the Zagrosmountain range and in the path of the humid winds of the Mediterranean systems and causes the rise and discharge of these systems. This province has relatively good rainfall. In this research, 8 synoptic meteorological stations of the province in the statistical period of 30 years (1368-1398) were considered. Ten teleconnection indexes were used during this period to investigate their effect on climatic extreme values using Pearson's correlation coefficient.

The changes in average minimum temperature shows that Kohrang station has the coldest minimum temperature in the studied area and annual average fluctuation of this variable has changed from -4.71 to -15.61 degrees Celsius during the studied period. On the other hand, Lordegan station has a higher average minimum temperature than other stations and the range of changes of this variable is from -0.16 to -5.8 degrees Celsius. Lordegan station has the highest values of extreme maximum temperature. The range of changes of this variable fluctuated from 32 to 38.5 degrees Celsius, while the range of these changes for Kohrang station was recorded from 28.7 to 32.2 degrees Celsius during the same period. Based on the results in EGheis and Avergan stations, the average maximum temperature correlation with TNH, NINO3, NINO12, NINO4 and PNA indices was significant at 1% level and with EA/WA, NP and NAO indices at 5% level and had no special relationship with AAO and SOI indices. Among these indices, the highest correlation of this variable with TNH index was 0.728 for EGheis station and 0.71 for Avergan station. At PoleZamankhan and Shahrekord stations, the average minimum temperature correlation was significant at 1% level with TNH, NINO12, and NINO4 indices and with NP, PNA, NAO, and SOI (only for PoleZamankhan station) at 5% significance level. There was no significant correlation with NINO3, AAO and SOI (only for Shahrekord station) and EA/WA indices (only for Kohrang station). The average minimum temperature was significant with TNH, NINO3, NINO12 and NINO4 indices at 1% level and with the EA/WA, PNA, NP and NAO indices at 5% level, and there was no significant correlation with the AAO and SOI indices. The highest correlation coefficient was related to TNH index (0.724) in this station. In Shahrekord and Brojen stations, the average maximum temperature correlation was significant with TNH, NINO3, NINO12, NINO4 and NP indices at 1% level and with EA/WA, PNA and NAO indices at 5% level and there was no significant correlation with the AAO and SOI indices. In PoleZamankhan station, the average maximum temperature correlation was significant with EA/WA, TNH, NINO3, NINO12, NINO4, NAO and PNA indices at 1% level and with NP index at 5% level, and there was no special relationship with the AAO and SOI indices. Results showed that correlation of TNH index with the average maximum temperature of the stations had the highest positive value compared to other indices. The NINO12 index was in the next rank, but its correlation was negative, and it is understood that the occurrence of this index has caused maximum temperature in these stations to decrease. Also, AAO and SOI indices have no significant correlation with this variable in the stations. Also, results reveal that correlation of TNH index with average minimum temperature of the stations had the highest positive value compared to other indices, and the lowest correlation was with Lordegan station and the highest was with Kohrang station. The NINO12 index was in the next rank; but its correlation was negative, and it is understood that the occurrence of this index caused the temperature to decrease at least in these stations. The NINO4 index is also in the third place, with the difference that, like the TNH index, it has a positive correlation in the minimum temperature. The AAO and SOI indices have mainly no significant correlation with this variable in the stations. In Lordegan and Avergan stations, the average minimum temperature correlation was significant with TNH, NINO3, NINO12, NINO4, NAO and PNA indices at 1% level and with EA/WA and NP, NINO3 and NAO indices at 5% level and did not have a significant correlation with AAO and SOI. The highest correlation coefficient related to TNH index was 0.726 and 0.702 for Avergan and Lordegan stations.

In this research, Pearson's correlation was used in 8 meteorological stations in Chaharmahal and Bakhtiari province to investigate the effect of teleconnection indices on extreme maximum and minimum temperature values. In general, it can be said that the teleconnection indices have an effect on the extreme temperature values of the studied area (some have an increasing effect and some have a decreasing effect on these variables). These findings can be used in predicting these extreme values and preventing possible damages to agriculture sector and vegetation. Also, considering the role of temperature values on evaporation and water needs of plants, the results can be used in drought crisis management.

Patients with coronavirus disease 2019 (COVID-19) experience symptoms of cognitive impairment. These patients perceive a lot of stress and are required to comply with quarantine conditions. Remote stress management training, in accordance with the principles of quarantine of these patients, can be effective in their recovery process. Therefore, this study was conducted with the aim of investigating the effect of remote stress management training on the cognitive status of patients with COVID-19.

In this randomized clinical trial, the research population was all the patients with COVID-19 referred to Gharazi Hospital in Isfahan City, Iran, in the winter of 2021. Seventy patients were selected by available sampling method and divided into two intervention and control groups (35 people) by limited randomization method. For the intervention group, the remote stress management online training program was implemented in five 60-minute sessions over two weeks. The control group did not receive training. The cognitive status index was measured using Folstein et al.'s brief cognitive status examination questionnaire [Mini-Mental State Examination (MMSE)] before and after the training sessions. The data were analyzed with SPSS software at two levels of descriptive and inferential statistics and by performing chi-square test, independent t-test, paired t-test as well as the analysis of covariance (ANCOVA).

The comparison of the average scores of the cognitive status in the pre-test and post-test phases of the two groups showed that the remote stress management training had a significant effect on the cognitive status of the patients with COVID-19 and improved this index in the intervention group (P ≤ 0.05).

Based on the results, remote stress management training can improve the cognitive status of patients with COVID-19. Therefore, this method of training is recommended due to the convenience and possibility of using it in the quarantine conditions of these patients.

Changes in evapotranspiration values of rice plants in non-northern regions of the country were estimated for three different planting dates (early, on time and late planting) and with four different probabilities of 75%, 50%, 25%, and 10% (years with low, medium, high, and very high evapotranspiration, respectively), using the Penman-Monteith Equation and meteorological data of 15 stations with a statistical period of 30 years (1990-2020). The crop coefficient of rice in different stages of growth were calculated as an average in 10-day periods based on the Weibull Model. The results showed that, in all non-northern climatic regions, adopting an early planting strategy leads to a reduction in water requirement in all evapotranspiration scenarios. Adopting early planting strategy in years with very high evapotranspiration reduces the water requirement of rice in hot, cold and temperate regions by 125.9, 113.5, and 115 mm, respectively, during the growing season (on average 0.7 to 9. 0 mm per day) compared to late planting. However, in cold and temperate climates, there was no big difference between early planting and timely planting and even late planting. So, it is better to use late planting to avoid the possibility of late frosts. Comparison of the results of evapotranspiration rate of rice plant in all planting dates and different probability levels in cold, moderate, hot and very hot climate regions showed that the highest evapotranspiration rate is related to the hot region at the rate of 1021, and moderate and cold regions have much lower evapotranspiration rate than hot regions with evaporation rates of 784.8 and 729 mm, respectively. Therefore, considering the lack of water resources and the negative effects of climate change in arid or semi-arid regions such as Iran, it is better to avoid rice cultivation in hot regions, especially in years with high evapotranspiration. Also, it is better that in cold and temperate regions, the type of irrigation management and the design of structures and water systems should be adapted to the calculations of years with high evapotranspiration.

The lack of water resources in arid and semi-arid regions like our country and the high volume of water losses through evaporation have made the importance of appropriate and practical methods to reduce evaporation from water reservoirs to be more and more clear day by day. Water is one of the most essential human needs. Evaporation is one of the climatic phenomenon in lakes and open space water loss. Different types of decreasing evaporation varied according to regional and economic conditions and environmental issues. On the other hand, in Iran the research conducted regarding reducing and controlling evaporation from water reservoirs is limited. Therefore, the current research is carried out with the aim of using new, economic, and appropriate to climatic conditions and accessible methods to reduce evaporation from water reservoirs, especially agricultural water reservoirs, in the Semnan region.

The efficiency of 6 physical covers (white plastic balls, empty bottles, bottles filled with straw and stubble, green canopy net with 50% density, green canopy net with 80% density, and white canopy net with 50% density), after preparation on the sunken Colorado evaporation pans, is evaluated in four periods of about 30 days in fall 2018 and winter of 2019 and spring and summer of 2021. Measuring the amount of evaporation from pans during 4 periods of approximately 30 days in different seasons of the year are done daily at 10:30 in autumn and winter and at 9:30 in spring and summer. It should be noted that the water temperature is also measured using an alcohol thermometer at the same time as the water level reading.

Based on the results of measurements, the rate of evaporation from the treatments of white plastic balls, empty bottles, bottles containing straw and stubble, green canopy net with 50% density, green canopy net with 80% density, canopy net White with a density of 50% and the control is equal to 259, 320, 213, 277, 369, 283 and 754 mm, respectively in four periods, which clearly shows a significant reduction in the evaporation of the applying six covers to the amount of 66, 58, 72, 63, 52 and 61 percent compared to the control treatment.

In general, according to the efficiency of all the treatments in this research and the application of these covers, taking into account the economic, social conditions and the feasibility of implementation, in order to reduce evaporation from open water reservoirs, especially agricultural water storage pools, it is evaluated as efficient and suitable. Generally, among the methods used, the most efficient related to the bottle filled with straw and stubble, followed by plastic ball treatments and green canopy netting with a density of 80 are evaluated as the most appropriate methods.

The purpose of this study is to accurately measure the watershed potential for constructing rainwater harvesting structures. To carry out this research, the DEM digital-elevation model layer was used to prepare slope, hydrological soil groups and land use maps in the Arc GIS 10.3 software. The drainage density map was prepared by combining the DEM layer, topographic map, drainage density and hydrography data. A map of precipitation levels was prepared by using the pluvial method. CN map was prepared by combining land use and vegetation maps with hydrological soil groups. Runoff calculations were used to prepare runoff potential and coefficient maps. By combining them with the maps of drainage density, slope, and using analytical hierarchy process (AHP), a map of potential runoff production was prepared. The underground water fluctuation map was prepared using the base data and the water demand map was produced using (AHP). By combining this map with runoff production potential map, a water demand map was prepared. According to the obtained results, about 72 percent of the area has medium potential for the implementation of water extraction structures. It also shows about 22 percent of the area of low potential and about 6 precent of good potential.

The loss of water from reservoirs in the country, especially in the central and southeast regions, due to the dry climate and high temperatures are significant, causing stress on water resources. There is a need to reduce the amount of evaporation from the surface of the reservoirs in order to conserve the country's usable water resources of the. In the present study, the effectiveness of Palma dactylifera L. mats with two coverage levels of 50 and 100% as evaporation reducion coatings- has been studied. To examine the performance of the mentioned methods on reducing water losses, Colorado evaporation pans were used at the Semnan University. The effectiveness of the mentioned coatings was studied with three replicates and in comparison, with the control for 30 days in different seasons of 2018, using the comparison means method. Based on the results of average comparison test using Duncan's method, the 50% and 100% coatings showed a significant 1% difference with the control in terms of evaporation and water temperature. Results indicate in spring, pans covered with 50% and 100% mats reduced evaporation by 9% and 70%, respectively, and by 0 and 72%. in summer. In autumn, it showed a decrease in evaporation of 39% and 72%, and in winter, and a decrease in evaporation of 38% and 78% compared to the control. In general, palm mat Palma dactylifera L. with 100% coverage has shown the best performance on the surfaces of Colorado evaporation pans. Results show that in arid lands and desert regions, palm mat covering are expected to reduce evaporation from water reservoirs and basins.

Covid-19 patients perceive a lot of stress and suffer from psychological symptoms including depression, stress and anxiety. Because these patients are required to comply with quarantine conditions, remote training can be used for these patients. Therefore, this study was conducted with the aim of investigating the effect of remote training of stress management in a cognitive-behavioral way on the psychological symptoms of covid-19 patients. In this randomized clinical trial, the research population was all the patients with Covid-19 referred to the Dr.Garazi hospital in Isfahan city in the winter of 1400. 70 people were selected by available sampling method and divided into two intervention and control groups (35 people) by limited randomization method. For the intervention group, remote training program on stress management was implemented in five sessions of 60 minutes in two weeks. The control group did not receive training. Psychological symptoms were measured before and after the training sessions using the DASS-21 questionnaire. The data were analyzed with SPSS21 software and by performing chi-square tests, analysis of variance, independent and paired t-test, and analysis of covariance. Remote training of stress management in a cognitive-behavioral way had a significant effect on all dimensions of psychological symptoms of covid-19 patients and reduced them in the intervention group (p≤0.05). Based on the results, this method of training can improve the psychological symptoms of covid-19 patients and it is recommended due to the convenience and possibility of use in the quarantine conditions of these patients.

Changes in climatic variables that affecting access to water can play a key role in the sustainable development of agriculture and the environment. Since ET0 is the most important variable affecting access to water resources after rainfall. Therefore, the present study examines temporal and spatial variations of ET0, temporal analysis of trend, sensitivity and relative contribution rate of climatic variables including Sun Duration (SD), Relative Humidity (RH), Wind Speed (WS), air pressure (P), maximum Temperature (Tmax) and minimum Temperature (Tmin) for a period of 30 years (1988-2017) at 7 synoptic stations on the southern shore of the Caspian Sea at different time scales. The spatial distribution of ET0 in the Caspian Sea basin showed that ET0 increases from west to east. The results showed that on the annual and monthly time scale including March, May, June, July, August and September, all stations had upward trend at 5% probability level of Significance. While the results of sensitivity analysis showed that ET0 has the highest sensitivity to variables of RH, Tmax and WS respectively, but results of relative contribution rate showed that variables of RH, WS and Tmin are the main actors on ET0, in the southern shore of the Caspian Sea during the last 30 years, respectively.

Prevention is the most appropriate way to deal with natural hazards. And resilience means maintaining the structure and function of the socio-ecological system in the face of unexpected events, one of the important branches of prevention. Chaharmahal va Bakhtiari province, due to its specific geographical location, faces numerous environmental hazards annually. Therefore, in this study, the status of resilience in the face of environmental hazards in the governing system of this province was investigated. AHP method was used for this purpose. In the AHP process, based on the pairwise comparison of criteria and sub-criteria, the degree of association between both criteria and sub-criteria is compared and scores between 1-9 are assigned. The research data was analyzed based on Delphi method and hierarchical decision making process. The results showed that according to expert’s evaluation of resilience of socio-ecological systems of Chaharmahal va Bakhtiari province against climate change (4.51), drought (2.09) and soil erosion (2.02) were ranked first to third respectively. Because of this, climate change has attracted the attention of experts who have shifted the rainfall to snow ratio over the past two decades. So that from 70% snow and 30% rain, to 70% rain and 30% snow. However, much of the economic activity and livelihoods in the province depend on snow reserves.

Drought and subsequent water deficit crisis are one of the most important natural disasters, due to their wider scope than other disasters. On the other hand, 90 percent of the population and 81.3 percent of the Chaharmahal and Bakhtiari province were affected by a 7-year period until the end of March 2016. Therefore, in this study, the rate of resilience of the village's socio-ecological system against the crisis of dehydration and the problems in the province in general were evaluated. Guidelines for the evaluation of resilience were used by the Stockholm University of Sweden Resilience Society guidelines. A researcher-made questionnaire, interview, and checklist tailored to the socio-economic conditions of each local community and its ecological ecosystem were used for data collection. UCINET 6 software was used to analyze network relationships. The results showed that in the socio-ecological system of all, the main issue of water level reduction is accessible. One of the main reasons is the decrease in water intake and water loss due to lack of water storage facilities. The results of the historical line and the outline of the adaptation cycle showed that everyone's socio-ecological system is in the omega-phase (Ω) or pressure. Finally, the results showed that the most appropriate strategies for resilience management in socio-ecological systems include maintaining and enhancing the functional status of any village ecosystem, preserving and strengthening the rural structure and nature of any village, completing the village irrigation system, and Enhancing the social learning of the villagers.

One of the practices to improve the agricultural management of paddy fields for sustainable rice production is land equipment, renovation, and integration operations. However, due to some shortcomings, this does not seem to achieve all its goals. Therefore, the purpose of this study was to evaluate the effect of land leveling operations on non-uniformity and severity of changes in soil fertility using fuzzy logic and integrated fertility quality index, in paddy fields of Khosroabad village which is located in fouman city in Guilan province where the land equipment, renovation, and integration operation has been done. In two stages, before and after land leveling operations, 95 and 126 soil samples were prepared from surface horizons, respectively, and then some soil properties related to rice fertility (electrical conductivity, clay, organic carbon, total nitrogen, available phosphorus and available potassium) were measured. In the next step, using fuzzy functions, soil quantitative characteristics were converted into qualitative variables and by using the effect of weight on qualitative variables, the integrated fertility quality index was calculated. The results of measured properties, calculated indices, and the produced maps from them, showed that due to the land leveling operation, the average amount of clay increased (76/9%), and organic carbon, nitrogen, available phosphorus, and available potassium decreased (37, 32%, 41/7 %, and 20/3%, respectively) significantly. One of the main reasons for this is excavation operations and the placement of subsurface soil with more clay and lower concentrations of nutrients in the lower horizon. The integrated fertility quality index also decreased (from an average of 0.31 to 0.18) in most of the studied areas. As a result, it seems that improper implementation of agricultural land equipment, renovation, and integration operations, by reducing the fertility of topsoil, will have long-term negative effects on agricultural land, that elimination of which, will increase the cost of production.

Evaporation acts as an important component and a key control factor in land hydrological processes. In the context of global warming, pan evaporation demand is expected to increase, but the decrease in measured pan evaporation has challenged the hypothesis that climate change would increase evaporation. The main purposes of this study were (1) to investigate the existence of evaporation paradox, (2) to detect the temporal trends of pan evaporation and related climatic variables on annual time scale. In this study the data of 50 synoptic weather stations in half-west and center of Iran were used. Non-parametric tests Mann-Kendall and Sen's slope estimator were used to discover trend through time series. Results showed that pan evaporation in 10% and 28% of stations had significant (p<0.05) decreasing and increasing trend, respectively. But, trend analysis of mean temperature as source of energy required for evaporation, indicated that in 94% of the stations had increasing trend. Despite the increase in temperature in the all stations, evaporation paradox has occurred in 36% of stations and only in 10% of stations evaporation paradox was significant at 5% level (p<0.05). Data analysis in stations that had evaporation paradox ( with negative pan evaporation trend) indicated that decrease in wind speed and sunshine duration and more increasing in the minimum temperature compared to the maximum temperature, were the main climatic parameters that controlling the rate of pan evaporation. Decreasing in pan evaporation in arid and semiarid areas of Iran is important in climatic studies.

The investigation of adaptability and grain yield stability of promising lines is important in dvevelopment and release of new cultivars. Eight rice promising lines developed by crossing local cultivars including; Hashemi, Domsiah, Alikazemi and Deylamani with improved cultivars including; Khazar, Kados and IR60 with optimal yield along with Khazar, Hashemi and Guilaneh as check cultivars were evaluated using randomized complete block design with three replications in six environments (years 2018, 2019 and 2020 and locations Rasht and Chaparsar), Iran. The results of GGE biplot showed that the first component (main effect of genotype) and second component (genotype × environment) explained 61% and 21% (overall 82%) of the total variation in grain yiled, respectively. The results of ranking based on grain yield and yield stability together and in comparison with the ideal genotype indicated that the most superior genotype was G7 (Deylamani/Kados), followed by genotypes G3 (Domsiah/Khazar//Khazar), G8 (Domsiah/Khazar//Domsiah) and G2 (Hashemi/IR60//Hashemi). Therefore, genotypes G7 and G3 were selected as the most adaptable with yield stability for being released as new rice cultivars for target environments. G7 was developed from a cross between Kados, an improved and high-yielding cultivar, and Deylmani, a local and high-quality cultivar, with an average yield of 7.25 ± 0.14 tons per hectare. G3 was dveloped from a cross between Khazar, a high-yielding cultivar, and Domsiah, a local cultivar. G3 was bred with the aim of maintaining the favorable characteristics of cv. Khazar and improving the quality of its cooking through cross with Domsiah, and its average yield was 6.51 ± 0.21 tons per hectare. Both genotypes G7 and G3, with high grain quality (amylose content of 22.02 and 22.09, gel consistency of 42 and 40, gelatinization temperature of 4.71 and 3.96, grain elongation rate of 1.60 and 1.57 for genotypes G7 and G3, respectively) and medium maturity (125.34 and 122.14 from sowing, respectively) can be released as new rice cultivars for target areas.