نشریه جغرافیا و مخاطرات محیطی
پیاپی 47 (پاییز 1402)

Dashkasan is one of the historical villages of East Azarbaijan province, located in Shiramin village, part of the suburbs of Azarshahr, located south of Tabriz, the west of Sahand volcano. In this paper, to investigate the increase in instability in the Azarshahr Dashkasan mineral region, tectonic studies were conducted. Based on field observations, the normal Dashkasan fault has led to a displacement of 10 cm folding units at a height of 1373 meters above sea level. Therefore, the activation of tectonics is quite evident in terms of field observations. Adaptating the results with the remote sensing map of the studied area, it was determined that the most displacement, and by which stone was fractured, occurred along the normal sub-faults in the northwest-southeast part. Considering that shear joints are also developed in the northwest, mines should also have abundant fractures in the central and southern parts of the Dashkasan region, so extracting and exploring this range is not correct. In addition to the railroad, the tunnel and part of the main road are at risk of the normal active fault zone and slope instability. The density of mineral activities in Dashkasan region is very high and necessary where the slope of the range is very steep, especially in mineral areas and abundant fractures that are adjacent to engineering projects such as tunnels and railway lines. There must be necessary measures for slope stabilization. Therefore, the activity of mining and exploration in the environment should not put people at risk.

This study investigated the impact of active tectonics, specifically the Dorubeh fault and an oblique-slip reverse fault, on the morphology of alluvial fans situated between Kashmar City and Ali Abad Keshmar Village in Bardaskan. The research employed a cartographic-analytical approach, utilizing 1:25,000 topographical maps, 1:100,000 and 1:250,000 geological maps, Landsat satellite images, and Google Earth. Mapping and image processing were conducted using such software as ArcMap, ArcView, Google Earth, and QGIS. The results demonstrated that fault activity plays a crucial role in shaping the predominant geomorphic features within this region, specifically the formation of alluvial fans known as bajada. The oblique-slip reverse fault, specifically, has induced significant modifications in the alluvial fans. It has repositioned the primary channels from central to peripheral and lateral positions, leading to alterations in sediment deposition patterns. Consequently, certain alluvial fans now intersect at three transverse surfaces and two longitudinal and transverse surfaces. The Doruneh fault’s activity is characterized by the manifestation of uplifts, pressure ridges, and pressure anticlines occurring at various sections within the alluvial fans, including the upper, lower, and basal regions. This fault caused left-lateral offsets in certain sub-channels on the fan's surface, resulting in the development of single-surface and nested two-surface transverse and longitudinal alluvial fans at the base of the fan and the base of the pressure ridges. Furthermore, it modified the point of intersection of the primary alluvial channels, leading to the formation of segmented fans downstream of Doruneh fault.

Erosion is primarily caused by precipitation and runoff, while erodibility results from the type of the formations at the catchment scale, which is subject of this study. The objective of this study was to investigate the relationship between geologic units and erosion intensity. Initially, two models of MPSIAC and Fargas were used to study erosion intensity. The Fargas model was presented based on the theoretical principles of two erosion and the erodibility factors, while MPSIAC model was based on 9 factors. BLM method was used to separate the intensities of a type of erosion according to the S.S.F table. RUSLE model was used to estimate soil erosion in the studied sub-basins. To determine the risk of erosion using the value coefficient, Fargas model was used. In the MPSIAC model, coefficients were considered for each of the nine factors. Based on the results of MPSIAC model, 79% of the basin surface had high erosion intensity and 21% had very high erosion intensity, while according to Fargas model, 0.3% had moderate erosion intensity, 10% had high erosion intensity, and 4.7% and 85% were characterized with severe erosion and very severe erosion, respectively. Moreover, in both models, 18% corresponded to very high erosion intensity (very severe), while 7.2% had high erosion intensity. In Fargas model, E1t1, E1t2, E2ig3, Q2f, Qt1, and Qt2 had very strong erosion intensity, whereas, in MPSIAC model, E1t1, Qt1, and Qt2 had high erosion intensity on their surfaces. One reason for this phenomenon could be the erodibility of the formations. Most of E1t2 and Q2t are highly eroded, which contributes to a large amount of drainage in addition to the erodibility of the formations.

Solifluction is the displacement of mud crust on surface of fixed foundation that occurs in areas near glaciers and mountains, which is underestimated as a natural disturbance factor and its ecological role in maintaining biodiversity is ignored. This process affects the denudation of mountains less than fast processes (landslides) and geochemical transitions, but due to its extent, has a great impact on the evolution of mountain landscapes. In order to investigate the physical and chemical properties of different solifluction soils, 4 sites were selected in the Daronagar River basin, located in the north-east Iran, based on the lobe or terrace type. Then, sampling was done from different microtopography, including the riser, tread and ridge parts. Texture, organic carbon, available phosphorus and potassium, pH, electrical conductivity, equivalent calcium carbonate, saturated moisture, soil stability, and porosity were then measured. The results showed that the impact of investigated factors on soil porosity and available phosphorus was not significant. In other studied characteristics, only the simple effect of the type of the studied site was significant. The values of pH, electrical conductivity, saturated moisture, and available potassium in Sites 1 and 2 were lower compared to the other two sites and there was a significant difference. This trend was the opposite in terms of organic carbon, soil stability and equivalent calcium carbonate. The highest value of these parameters was observed in terrace-type solifluctions. It seems that the impact of soil displacement in all types of solifluctions, as well as mutual relationship of some soil characteristics and their effect on each other caused the emergence of different characteristics in the investigated solifluctions.

In addition to their importance and role in providing water resources, karstic water resources also have a high potential for vulnerability, which is why these resources are always exposed to pollution. Given the importance of the issue, this study identifies vulnerable areas in Ravansar basin. The research data includes 1:50,000 topographic maps, 1:100,000 geological maps, a 10-meter-high digital model, and digital layers from various organizations like soil layer. After collecting the required data, using COP and EPIK methods, the areas vulnerable to contamination were identified and then the results were compared and evaluated. The results estimated by COP and EPIK methods showed that Ravansar basin has a high potential for vulnerability, so that based on the results of both methods, many parts of the region are vulnerable. Based on COP method, 27.8% of the area has a very high vulnerability potential, and based on EPIK method, 29.5% of the region has a high vulnerability potential. Moreover, in terms of spatial distribution of vulnerabilities, based on the results obtained from both methods, the northern regions have the highest vulnerability potential and the southern regions have the lowest vulnerability potential.

Air pollution is one of the most harmful natural hazards in Tehran metropolitan. Particles with a diameter of less than 2.5 micrometers (PM2.5) as one of the most harmful pollutants have endangered the health of people living in Tehran. One of the PM2.5 estimation techniques is the use of Aerosol Optical Depth (AOD) products derived from satellite observations. Various AOD products are retrieved with different algorithms that do not have the same accuracy and spatial resolution. Due to the differences in many assumptions and approximations adopted in the AOD retrieval process, the generated AOD products involve uncertainties. This issue reduces the accuracy of PM2.5 concentration estimation. The purpose of this study was to investigate the possibility of fusing AOD products obtained from MODIS sensor observations (retrieved by Deep Blue and Dark Target algorithms) to estimate PM2.5 more accurately. First, the performance of different machine learning algorithms in estimating PM2.5 from AOD data was evaluated. As a result, the XGBoost algorithm with the highest performance was selected as the base model for PM2.5 estimation. Then, the AOD products were fused using a weighted averaging based on the retrieval quality of the primary products. Finally, the fused AOD product along with meteorological data were employed to estimate PM2.5 using XGboost. The results demonstrated that the accuracy of PM2.5 estimation from the fused AOD product is better than when the AOD products are used individually (= 0.77, MAE = 7.00 , RMSE = 9.59 ). Thus, the retrieval quality of AOD products will lead to more accurate estimation of PM2.5 in the end.

Intra-urban air pollution is a major environmental and public health concern worldwide. As the capital of Iran, Tehran is increasing its population day by day, and it has caused problems such as air pollution, and its severity is subject to change every year. The aim of this study was to find a relationship between Remotely Sensed Indices with pollutants and air pollution modeling in Tehran. Pearson correlation coefficient was used to investigate the relationship between independent variables and pollutants and multivariate linear regression model was used to model it. Independent variables in this study are Land Surface Temperature (LST), Normalized Vegetation Difference Index (NDVI), Apparent Thermal Inertia (ATI), and Normalized Difference Built-Up Index (NDBI). The data obtained from Landsat 8 satellite images and MODIS sensor were used. Moreover, air pollution parameters were CO, NO2 and SO2, which were prepared in two spring (April) and summer (August July) of 2017. ENVI, ArcGIS and SPSS software were used to analyze the images and evaluate the relationship between the Remotely Sensed Indices and air pollutants and modeling. The results showed that the highest correlation between LST and SO2 is in the spring (0.24), NDVI and SO2 is in the spring (-0.36), ATI and CO is in the summer, and between NDBI and SO2 is in the summer. Also, the results of the model for the statistical coefficient of determination (R2) showed a value between 0.33 and 0.8, and for the statistical root-mean-square error (RMSE) showed a value of 5.05-47.47. It was also found that NDVI and LST are inversely related, and that NDBI was indirectly related to air pollutants.

This research was conducted with the aim of investigating the ecological assessment of Jiroft region under the influence of land use changes. For this purpose, from the satellite image in 1990 (Landsat 5-TM) and 2020 (Landsat 8-OLI) to extract land surface temperature with the help of single-band algorithm and land use map with the support vector machine (SVM) classification method. used. Next, to investigate the role of land cover in the creation of thermal islands, the contribution index (CI) and UTFVI index were used to evaluate the ecological situation. The results showed that in 2020, barren areas had the highest land-use change since 90 and decreased by 7,300 hectares, but man-made, agricultural, and irrigated land uses increased the most. The water area has increased with the construction of water dam in the region. The reduction of barren areas and the increase of water levels, agricultural use and gardens have improved the ecological situation compared to 1990, while the temperature of the earth's surface has increased by 11 degrees in 2020, which can be attributed to the increase in global warming. It can be said that although the ecological situation of the region is in a better state than in 1990, the presence of desert lands and rocky outcrops around Jiroft has caused the formation of thermal islands in Jiroft region.

Nowadays, the creation of a spatial distribution map for assessing fire risk is widely recognized as a crucial management tool at various levels. This tool helps monitoring natural resource sustainability and the effective control of this environmental hazard. Through the integration of field operations, remote sensing data, geographic information system techniques, and diverse statistical methods, it becomes feasible to develop a dependable spatial prediction of fire hazard potential for different regions. In this research, nine factors were identified to be effective in fire risk modeling, including altitude, slope, aspect, distance from the road, NDVI, LST, TWI, and TPI. Fuzzy Analytic Hierarchy Process (FAHP) and Logistic Regression (LR) were employed to identify risk areas and determine the most significant factors influencing the occurrence and spread of fire. Historical fire areas were identified using Google Earth Engine and MODIS images. The initial results showed that both models assign the highest coefficients to NDVI, LST, and distance from the road. However, during the verification phase, the performance characteristic curve of both models was relatively similar (0.847 for FAHP method and 0.837 for LR method). Upon examining historical fire pixels, it was found that FAHP method correctly identified approximately 87% of the pixels belonging to classes with high and very high risk, whereas LR method only overlapped with 22% of these pixels. This suggests that FAHP method is better at identifying areas with a high risk potential compared to LR method. While it is important to acknowledge that the creation of risk prediction maps using various models cannot completely eliminate all fires, it can greatly diminish their frequency and help their management by offering effective solutions.

Landslide phenomenon is a kind of danger in mountainous areas, which has always caused a lot of damages in Iran. Therefore, identifying areas that are prone to landslides can prevent the occurrence of this phenomenon and save human life and property. The purpose of this research was to prioritize the effective components in the occurrence of landslides and zoning the risk of its occurrence in Bagh Malek county. For zoning the risk of landslides, 9 factors were considered, including: slope, geology, water drainage network, height, rainfall, land use, fault, slope direction and road. The method used in landslide zoning is AHP. Geographic information system (GIS) software was also used to combine the layers. In the Hierarchical Analysis Process (AHP) method, the weight of each of the nine factors was calculated and applied to the desired layers according to the importance of each of them in the occurrence of landslides, and by stacking the layers, a landslide risk zoning map was produced. The results showed that the factor of slope, land type and surface water network with the highest rank of 1 to 3, and the road and slope direction with the 8th and 9th rank have the least impact on the occurrence of landslides in this region. Low risk areas have 43.25% and high risk areas have 4.01% of the area. The results showed that most landslides in the region are related to the slope and type of land. The most sensitive parts of the region to landslides are the southwest and parts of the east and west of the region, and the most resistant parts of the region are some parts of the north, northwest, and some parts of the east of the region.

Urmia city is a region with high potential for the development of industrial centers. However, in the last few decades, the indiscriminate development of industries in this area has led to environmental and socio-economic problems. This study aimed to identify areas prone to the construction of an industrial town in this city and evaluate the existing areas. In order to collect the required data of this descriptive-analytical study, library studies were used. Moreover, in order to achieve the goals of the research, the combined Boolean and fuzzy multi-criteria evaluation method were used. At first, relying on seven criteria of distance from the city, slope, height, fault, waterway, communication lines and land use, maps of restrictions and factors were drawn. In the second step, the fuzzy primary suitability map and the Boolean primary suitability map were prepared and finally, based on the correlation coefficients and standard deviation of the operators, gamma 0.5 was chosen as the most appropriate gamma to overlap the two mentioned maps. The results showed that about 94% of the area of ​​the region is completely unsuitable for the establishment of industries and only about 6% of the area are approximately suitable to completely suitable. Regarding the evaluation of the establishment of the existing industrial areas, it was found that the industrial town of Phase 1 and 2, Karimabad industrial area and the electronics and food industry town are located in the inappropriate area of ​​establishment. Moreover, ​​8 square kilometers of the Phase 3 of the industrial town is located in the suitable area for settlement and 1 square kilometer is located in the unsuitable area for settlement.

Floods are occurring as an environmental hazard in many parts of the world, especially in countries that have been ineffective in crisis management and resource conservation. This natural hazard has become one of the most damaging natural disasters since the reckless activities of human beings in exploiting the natural environment have increased. One of the ways to deal with this danger is to predict the occurrence of floods. The models that are used to predict the occurrence of floods may not have the same accuracy in predicting precipitation events in different seasons of the year. Due to the importance of this issue, in this study, the results of the the Geomorphological Instantaneous Unit Hydrograph (GIUH) model in predicting floods in winter and spring in Minab catchment (Brentin) were compared. The data include the maximum hourly flow and their corresponding precipitation for three spring and three winter events. First, the required parameters of GIUH model including branching ratio, length ratio and area ratio for the basin were estimated using GIS softwar. Then, the events of winter and spring seasons, the peak discharge values, and the time of the peak discharge were compared. The results of this comparison showed that GIUH model predicts peak discharge and peak flood time occurring in winter (with average values of 20.09 and 45.64%, respectively). It is less distant from the observed data, and has a higher accuracy than spring events (with average values of 57.3 and 119.7, respectively).

Considering devastating events like the 2003 Bam earthquake (M_w~6.6), it is essential to develop up-to-date earthquake hazard maps to design structures in this area. In this study, a seismic catalog including historical and instrumental events was compiled and then 21 seismic sources were identified in Kerman province and its surrounding. Seismicity parameters were estimated for all 21 source zones and an attenuation relationship was selected to obtain local site effect-based seismic hazard maps. Finally, seismic hazard maps, which is one of the basic requirements of seismic design and seismic regulations, were presented in form of the peak ground acceleration (PGA) measures for the return period of 475 and 2475 years, and the high risk areas in Kerman Province were introduced. To investigate the depth of events on Iranian plateau, according to the studies conducted in this study, it is suggested to use only the data obtained from local seismic networks. The results were presented as seismic hazard maps for the parameters of maximum intensity of horizontal ground acceleration, taking into account construction effects with a probability of 2% and 10% over 50 years for all parts of Kerman province to provide all design needs according to 2800 regulations. Using the obtained maps, the earthquake parameter in the Iranian Seismic Code (Code 2800) can be updated. Results showed that, as expected, two areas in Kerman province are with the highest accelerations: The first is the Kuhbanan-Golbaf-Bam fault systems with a northwest-southeast trend and the second is the northeast termination of Zagros toward Makran. Both of these ranges are seismic and of great importance in seismic surveys. These areas include Kuhbanan-Golbaf-Bam fault systems and Jiroft-Kahnooj.

The present study was conducted to investigate the trend of land use changes and its impact on erosion and sediment, using Landsat satellite images of 1987, 2010 and 2019 and EPM model in the Kal-Aji watershed of Golestan province. Land use map was prepared using the maximum likelihood method. Training data were used to evaluate the accuracy of the results. Then, the most important methods of accuracy assessment, including total accuracy and classification kappa coefficient, were extracted. Those for 1987, 2010 and 2019, the total accuracy were 95, 98 and 95 and kappa coefficient were 0.93, 0.96 and 0.93, respectively. Erosion and sedimentation zoning maps were performed using the resulted land use maps, and such factors as slope, lithology, soil and precipitation were performed using the EPM method. The results showed that one of the most important factors in the Kal-Aji watershed is the loss of rangeland vegetation and its conversion into agricultural land. According to the hypothesis, the role of land use changes in the amount and increase of erosion and sediment was significantly determined. That is, with the change of land use, erosion and sediment have also increased. The reasons for the increase in the amount of sediment in the Kal-Aji area are the development of agricultural land uses and the decrease in rangeland between 1987 and 2019 (16.83%). These changes have reduced the important role of rangelands and vegetation of Kal-Aji watershed and have increased the amount of sediment in the outflow of sub-watersheds. Based on the obtained results, the total amount of special sediment was related to the period of 1987 (4353 cubic meters), which increased to 5164 cubic meters in 2019, which indicates the changes in land use that occurred in the watershed.

The main purpose of this applied research was to analyze the norms in the theory of planned behavior to predict the behavior of rural households in the protection of Zagros forests. The data required for the research was collected by survey method and a questionnaire. The collected data were analyzed by SPSS and Amos, using structural equation modeling approach. The statistical population of this study consisted of rural households in four villages of Dowreh Chegeni (N=2020) that based on Krejcie and Morgan table, a sample of 300 households was selected. The sample was studied using stratified sampling method with proportional assignment. Findings showed that the behavior variable has a positive and significant relationship with the attitude, subjective norm, perceived behavior control, moral norm, and intention variables. The results of structural equations of path analysis showed that the variables of moral norm, intention, and behavior control perceived have a positive, direct and significant effect and the variables of moral norm, attitude and behavioral control have an indirect and significant effect on behavior variable. Finally, the theory of planned behavior mediated by the moral norm variable can predict respectively 52% and 38% of the changes in the variables of intention and behavior of rural households towards forest protection. The results showed that the constructs of the theory of planned behavior such as attitudes, moral norms and perceived behavioral control are good predictors of Zagros forest protection behaviors in the studied area. ThTheese findings may be useful to executives, because instead of trying to change behavior, they can focus first on conceptual and persuasive changes, such as changing attitudes toward forest protection