نشریه تحلیل فضایی مخاطرات محیطی
سال نهم شماره 4 (زمستان 1401)

Recognition of spatial patterns of drought plays an important role in monitoring, predicting, confronting, reducing vulnerability, and increasing adaptation to this hazard. This study aims to identify the spatial distribution and analyze the spatial patterns of annual, seasonal, and monthly drought intensities in Iran. For this purpose, the European center Medium-Range Weather Forecast (ECMWF) data for the period 1979-2021 and the ZSI index were used to extract the drought intensities. To achieve the research goal and explain the spatial pattern of the frequency of drought intensities (Extreme, severe, moderate, and weak), spatial statistical methods such as global Moran’s I, Anselin local Moran’s Index, and hot spots were used. The results of the global Moran’s I showed that with increasing intensity, the spatial distribution of drought events has become clustered. The spatial distribution of the local Moran’s Index and hot spots also confirms this. Very clear contrast was observed in the local clusters of high (low) occurrence as well as hot (cold) spots of severe (Extreme) yearly droughts in the south, southeast, and east. In autumn, weak to Extreme droughts show a southeast-northwest pattern. But in spring and winter, the spatial pattern of drought is very strong as opposed to severe and moderate drought. Despite the relatively high variability of maximum positive spatial Autocorrelation of severe and Extreme monthly droughts, their spatial pattern is almost similar. The spatial clusters of severe and very severe droughts in the northwest, northeast, and especially on the Caspian coast, are a serious warning for the management of water resources, especially for precipitation-based activities, such as agriculture.

Flood risk maps and Flood zoning techniques are useful tools to manage this hazard in the catchment and mitigation of flood impacts. In South Baluchestan and Kahir Basin, due to the existence of winter and summer precipitation regimes, the occurrence of flash floods is inevitable due to the establishment of rural communities and settlements in flood-prone areas, the flooding has caused many damages to the region's vulnerable population. In order to zone flood risk and prepare flood risk maps, climatic data, hydrological, land cover, and topography of the basin were prepared from reliable sources and according to scientific studies, 12 variables affecting flood risk in the form of five main components (Hydrology, vegetation, land cover, climate, and topography) were prepared. According to the regional conditions of the basin, using the opinions of experts based on scientific methods, the weight of each variable and component was determined by Analytical Hierarchy Process(AHP). Using two methods of fuzzy overlay, Weighted Overlay, and the Geographical Information System facilities, a map of variables and components was prepared after reclassification and fuzzy membership function with appropriate operators. The results showed that the fuzzy overlay method concerning its dominant logic has a better distinction of flood-prone areas and can help determine flood hazard micro-zonation in the drainage basins like the Kahir basin. By comparing the results from the real data of the January 2020 flood obtained from satellite images. Due to poor infrastructure and high economic, the risk of flooding may be more harmful and widespread in the future.

Drinking karst water resources, especially in arid and semi-arid regions, like Iran, are considered as valuable and strategic water resources. A sharp decrease in rainfall reduces the quality and quantity of karst water sources (Christensen et al., 2007). On the other hand, urban and industrial development, which is accompanied by the increase in population growth, increases the risk of underground water pollution caused by the dumping of chemicals, waste and change of use (McDonald et al., 2011). Protection of karst aquifer is one of the most important measures in the management of karst water resources due to its vulnerability and high sensitivity to pollution (Khoshakhlagh et al., 2014, Afrasiabian, 2007). Therefore, With the advancement of geographic information system technology, rapid progress was made in the ability to identify and model groundwater pollution, as well as the vulnerability of water sources from these pollutants (Babiker et al., 2004, Rahman, 2008). The pollution potential decreases from the center to the periphery (Saffari et al., 2021).

In this study to evaluate the vulnerability of Bisotun and Paraw aquifer which is karstically developed and has, crack and fissure and various landforms; COP and PI vulnerability models have been used to identify areas at risk of contamination. The COP model includes three main factors including concentration of flow (C), overlaying layers (O) and precipitation (P). Factor C, which indicates surface features (Sf), slope and vegetation (Sv). It was obtained between 0.8-0.0 in 5 classes. From the overlap of the subfactores soil, layer index and lithology, the O factor map was prepared in three classes, including class 2 with low protection value, 2-4 with medium protection value and 4-8 with high protection value.  The P factor, which is the temporal distribution of precipitation along with the intensity and duration of precipitation, can show the ability of precipitation to transfer pollutants from the surface to the underground water. P factor was 0.8 in 2 layers in the northwest of the study area and 0.8-0.9 with low protection value. Furthermore, top Soil, precipitation, net recharge, fracture density, bedrock and lithology maps were used for the protective cover factor (P) in the PI model. The zoning of the P factor showed 2 classes such as very low and low most of the study area is in the low class. The infiltration condition factor (I) using the characteristics of the soil, the slope layer, and the land use in four layers showed high, aamedium, low, very low, which due to the high slope of the area of ​​the high layer has the highest dispersion, which causes the reduction of the protective cover.

Consequently, COP vulnerability map in 5 classes with very high vulnerability (0-0.5) equal to 38774.74 hectares (41.4%) and very low vulnerability (4-9-4) with 57.86 hectares (0.06%) of the largest and smallest area respectively. Also, the PI vulnerability map of the combination of these two factors showed very high vulnerability with the largest area of ​​about 68,783 hectares and 72.9% scattered throughout the study area and the high vulnerability class with an area of ​​about 25,526 hectares and 27%.

The results of this research showed that the simulation performance of each COP and PI vulnerability model is closely related to the amount of pollution in the environment. It seems that the COP vulnerability model can better and more accurately showed the level of vulnerability in the karst aquifers of Bisotun and Paraw.

The results of pathological evaluation of seismic zones in the terrestrial space indicate a significant concentration of residential spaces, especially cities. It has been economic and human. Therefore, one of the desirable models in identifying, analyzing and reducing damage in urban spaces is to use the structural and functional framework of passive defense. In many recent studies, the subject of reducing earthquake damage in the territory of the physical-spatial field has been to increase the building's resistance to earthquakes. While this study by recognizing environmental components, physical-spatial, social, economic and effective indicators in each component (45 indicators) to determine the pathology and risk areas of earthquakes in a comprehensive and desirable and based on that reduction strategies Redefines risk. In other words, by recognizing and analyzing the basic concept of threat network and risk ring with passive defense approach in earthquake assessment and vulnerability in Kermanshah metropolis to form the required database structure in appropriate software environment, appropriate policy and urban crisis management measures It is designed in proportion to the earthquake risk.

This regard, this research was conducted with the general purpose of designing a proposed sustainable food security model in drought conditions. The statistical population consisted of a number of food safety experts and agricultural experts. Therefore, for selecting the samples, targeted snowball sampling (chain referencing) was used. Sampling continued until data saturation, in the end, the number of participants in the study reached 31 . The research method was of qualitative type based on the data theory method of the foundation. The research data were collected using a deep interview and group discussion and analyzed with three open, axial and selective coding methods.The results of the review of the requirements of sustainable food security in the form of data approach of the foundation consisted of 68 initial codes. Finally, in order to design a safety improvement model, the improvement of food security in drought conditions was subject to 8 requirements (managerial, technological, policy and supportive,infrastructure, cultural and empowerment requirements, Diversification, conservation, stabilization) and were inserted into the Strauss and Corbin model.Access to adequate nutrition and nutritional health is one of the main pillars of development and is the basis for the future development of the country. According to studies on the role of nutrition in health, its efficiency and its relation with economic development has been confirmed. Also, access to adequate and desirable food is one of the earliest human rights, but various studies show that rural communities, which themselves are responsible for food security, face food insecurity, which is in a drought condition much more inferior to the situation. Because rural households are always at the forefront of drought vulnerability and, in the absence of risk mitigation systems, they quickly lose their resilience and go out of the agricultural sector. Therefore, measures must be taken to enable them to continue to operate in agriculture in drought conditions and to maintain the backbone of food security in the country.

Industrial and agricultural activities in the world have led to an increase in the concentration of greenhouse gases such as carbon dioxide, methane and nitrogen oxide and have caused the earth's climate to become warmer. This phenomenon has caused climate change and has changed the thermal and rainfall patterns. Climate change in Iran in recent years has caused a decrease in rainfall and an increase in temperature and continuous droughts. Agricultural production in Iran has been affected by climate change and has faced a decrease in the production of crops such as wheat. Therefore, according to the government's policy of self-sufficiency in wheat production and the establishment of sustainable food security in the country, it is necessary to use climate smart agricultural technologies to sustainably increase agricultural productivity, Adapting and resilience of agriculture to climate change and reduction greenhouse gases emission from agriculture. The purpose of this study was to design a behavioral model for the use of climate smart agricultural technologies with an emphasis on motivation. The research method was quantitative, in terms of practical purpose, and research data was collected through a cross-sectional survey.The conceptual model was designed using the theory of planned behavior and the theory of norm activation. Bayesian structural equation modeling was used to test the model and hypotheses. The statistical population of this research was 800 wheat farmers of Nazarabad city, Alborz province. The sample size was calculated using Cochran formula 260 people, and stratified random sampling method with proportional assignment was determined as the sampling method. A researcher-made questionnaire was used to collect research data. The validity of the questionnaire was confirmed through agricultural extension and education experts, and its reliability was also confirmed through the pre-test and calculation of Cronbach's alpha coefficient. The findings of the research show that subjective norms, personal norms and perceived behavioral control related to the use of climate smart agricultural technologies have a significant effect on the intention to use these technologies. While the attitude towards the use of climate smart agricultural technologies do not have a significant effect on the intention to use these technologies. The variable of intention to use climate smart agricultural technologies also has a significant effect on the behavior of using these technologies.

One of the most important issues that has always affected the Iranian climate and has left many socio-economic consequences and financial losses climate change is. On the other hand  Sea level pressure is one of the most important climatic elements that can affect other climatic elements such as temperature, humidity and wind. The study aimed to evaluate CMIP5 models based on CORDEX and Verdai dynamics Seasonal pressure anomalies in Iran among CMIP5 models based on CORDEX project dynamic models BCC-CSM, HadGEM2-ES, GFDL and MIROC model HADGEM2-ES had a higher level of correlation and efficiency than other models.The data of 36 synoptic milestones during the statistical period (1960-2005), the data of the HadGEM2-ES model were applied by using the CORDEX model and the RCPs scenarios for the two historical periods (1960-2005) and predicted during Three periods of near future (2040-2011), middle future (2070-2041) and distant future (2099-2071) were used. Six methods R2, MAE, MBE RMSE, t-Jacovides and t-Jacovides / R2 ratio were used to evaluate the model performance. The results showed that the model has good performance in low altitude areas. Seasonal anomalies in all seasons, scenarios and time periods studied are positive and winter shows the maximum pressure anomalies between seasons.The maximum seasonal pressure anomaly of Iran in all seasons, scenarios and periods studied corresponds to the altitudes, including its epicenter in the Alborz and Zagros heights and high geographical offerings and the minimum pressure anomaly corresponding to low and low areas such as Khuzestan plain and The southern coast of the country.

evapotranspiration is one of the most important components in water balance and management. In this research, to evaluate the effects of climate change on the amount of potential evapotranspiration in the southern part of the Aras River Basin using the downscaled data of the GFDL-ESM2M model in the CORDEX dynamic downscale under the RCP8.5 scenario during the period of 2021-2050 and its comparison. It is treated with the values ​​of the base period (1985-2005). Data with a horizontal resolution of 22 x 22 km from the GFDL-ESM2M model were used in this research. The findings of the research showed that the minimum and maximum temperature and, accordingly, the ETp of the future period will increase compared to the base period in all six studied stations of Aras Basin (Ardebil, Ahar, Jolfa, Khoi, Mako and Pars-Abad). The value of this minimum temperature increase is estimated between 1.4 and 3.8 ºC and for the maximum temperature between 1.7 and 2.2ºC. The range of annual ETp increase varies from 133 mm to 189 mm. In the monthly ETp scale of all stations from January to July with an increase between 3.9 and 1.64 mm and from August to December with a decrease of 0.7 to 38.2 mm. Estimating the increase of ETp in the future period in the basin, especially in the months of spring, which is very important in terms of water demand, requires special attention to the possibility of this estimated increase in the planning of the water and energy sector.

Spatial analysis models provide a single model and solution to solve various problems in the field of study, one of the applications of these models is in measuring urban risks. In recent years, with the occurrence of various crises in urban communities, the urban management system and development plans are seeking access to models of prevention and dealing with these crises. The purpose of this research is to review the literature about the use of spatial analysis models in measuring urban risks in a meta-analytical way, so this research is conducted by reviewing and summarizing foreign articles (research statistical community) in relation to this issue in order to identify, analyze and Analyzing and summarizing the solutions of the investigated backgrounds. The statistical population is discussed with four standard criteria of spatial analysis, including description and identification of hazard dispersion, hazard dispersion argument, interpolation, and spatial planning. The statistical population is research, studies, and articles indexed in Sciencdirect, Willey, Web of Science databases in the period 2021-2000. Out of 99 articles, 78 articles have been selected and analyzed by screening method according to research objectives and indicators. The analysis was performed in two ways: descriptive statistics in SPSS software and inferential statistics in CMA2 comprehensive meta-analysis software. The results indicate that in the component of hazard dispersion descriptions, most of the researches in their used models have not been able to provide a tangible and appropriate general description, but in the three components of hazard dispersion, interpolation, and spatial planning of urban hazards based on score The average effect size, the applied models used in the research, have been able to provide a proper justification and tangible results with the applied model of spatial analysis in their studies.

Climate is one of the determining factors in the quantity and quality of agricultural products, therefore, in this study, the relationship between precipitation and temperature (as explanatory variables) with rice yield in 40 cities and wheat yield in 30 cities (as dependent variables) was investigated in the Caspian coastal area during 2000-2017. Spatial statistical analyses were performed with using the Moran autocorrelation test and geographically weighted regression. Based on the results (Moran index, z = 0.4342121 for rice and z = 0.719571 for wheat, respectively), it was revealed that the spatial distribution pattern of rice and wheat yield had a cluster pattern. The results of the geographic weighted regression analysis showed that the temperature increase was more desirable than the precipitation increase so the increasing temperature could lead to yield increases. In the eastern parts of the study area, the positive effect of precipitation on rice yield (with 0.020 to 0.540 regression coefficients) was remarkable; the results also revealed a negative relationship between temperature and rice yield in the southeast and eastern parts and a positive effect on rice yield in other areas. Also, the effect of precipitation on wheat yield was negative in the west and central parts of the study area (with -0.481 to -0.871 regression coefficients). According to the results, a negative relationship was dominant between temperature and wheat yield in the east and southeastern parts of the study area and a positive relationship was detected in other areas. Finally, the results indicated that in the western and central parts, due to heavy rainfall and a low number of sunny hours, an increase in temperature is more favourable than an increase in rainfall. In the eastern and southeastern regions of the region, where the amount of precipitation is lower than the threshold required for rice and wheat, an increase in precipitation is more desirable.

In the study of the trend of dust storm index, the results showed that the study period of 2003-2007 in Semnan province has an increasing trend and has shown significant changes in the 95% confidence range, but the lack of significant changes in the last decade shows the effects of various events. In cross-cutting decisions in the field of dust in the region. The zoning of the DSI index changes in different regions of the province in a 15-year statistical period indicates that from the west to the east of the province due to the increase in the frequency of stormy days with moderate dust (MDS), dust has increased. The correlation between drought and DSI index in Semnan province showed that although DSI index increased during the period under analysis with increasing drought intensity and its correlation with drought during the 15-year period was not significant, but the pattern of DSI index is consistent with It is the pattern of the drought process. According to the results, it can be acknowledged that the dust situation has always been affected by climate, but the relationship between drought and the DSI index has always fluctuated with respect to droughts and wetlands. However, different climatic parameters are different and their impact is different. In addition to human activities, the main role of wind in the amount of dust or the existence of another source of dust should be considered.

In the present study, the data of the ECMWF for a period of 1979 to 2018 was adopted to analyze the long term changes (trends) of the number of cyclones centers of the Mediterranean Sea.There are many methods (e.g. parametric and non- parametric)  for examining changes and trends in a given dataset. The linear regression method is of parametric category and the most common nonparametric method is Mann-Kendall test. By fitting the Mann-kendall model and the linear regression model, the frequency of the cyclone centers of the Mediterranean basin was evaluated in seasonal and annual time scales. Analyzing the trend of changes of the number of cyclone centers on a seasonal scale showed that the five-day duration have had a significant trend in spring, autumn and summer. Whilest on an annual scale, there was no significant trend in any of the duration. By fitting the regression model on seasonal and annual scale, one- and two-day duration have a positive regression line slop.