Journal of Spatial Analysis

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The Spatio-Temporal Variations of Aerosol Concentration Using Remote Sensing in Sistan and Baluchestan Province (2018 - 2000)
 
 
 
Abstract
Atmospheric particles play an important role in balancing the energy budget of the Earth's surface. The Sistan and Baluchestan province because of the specific geographical conditions during the year is witnessing the spread of dust particles caused by dust storms. This paper investigates the spatial changes of this phenomenon in the region to identify the association of dust accumulation and the reasons for these concentrations. In this study, the AOD Index data of the Aqua and Terra Modis Satellite Sensor (MODAL2_M_AER_OD) with 10 × 10 km spatial resolution were used. Then, by using statistical methods, a spatial analysis was done and the temporal and spatial changes trends at 95% and 99% significance level were performed using the nonparametric Mann-Kendall method. The results showed that the maximum concentration of aerosol in areas such as Zabol, Zahak, Hirmand, Hamoun, Iranshahr, Bampour, Jazmurian basin, Chabahar, and Konarak. On average, the highest variations in aerosol concentration were in the southern regions of the province include Dashtiari, Polan, and Chabahar, and the least in the northern part of Polan, Chabahar, Konark, and Bampour areas. The trend of changes was evaluated at two significant levels of 95 and 99%. The results of this section showed that the AOD had a positive and increasing trend in June, July, and August in the areas of Dalgan, Iranshahr, Bampour, Bazman, Mirjaveh, Nokabad, Zahedan, Nosratabad, Zaboli, Qasrqand, Irandegan, and Sib-va-Soran Plain and areas such as Korin, Zabol, Zahak, Sirkan (Bamposht), Hamoun have a negative and decreasing trend. The average changes in aerosol concentration in June, July, and August show a significant increase in the aerosol concentration from 2015 to 2018 up to 0.8.
 
Keywords: Environmental Changes, Dust, Environmental Hazards, Climate.

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Zoning the possibility of landslides downstream of Sanandaj Dam
1-Introduction
The purpose of this study is to select the best model and identify landslide risk areas in the downstream basins of Sanandaj Dam. Every year, mass movements in the region cause damage to roads, power lines, natural resources, farms and residential areas, and increase soil erosion. Kurdistan province, with its mostly mountainous topography, high tectonic activity, diverse geological and climatic conditions, has the most natural conditions for mass movements. According to the available statistics, this province is the third province in terms of landslides after Mazandaran and Golestan. (Naeri, &Karami, 2018). The Gheshlagh River Basin is a mountainous region with a north-south trend. In terms of construction land, it is located on the structural zone of Sanandaj-Sirjan. The study area with an area of 970.7 square kilometers is located downstream of Sanandaj Dam. The city of Sanandaj is being studied within the region. Due to the type of climate and morphological processes, effective parameters are provided for landslides in the geography of the region.
2-Methodology
In this study, 9 effective factors for landslides, including slope, slope direction, fault distance, road distance, waterway distance, lithology, land use and precipitation were used. Using Google Landsat 8 ETM satellite imagery, Google Earth software identified 237 slip points. Then, the coordinates of the slip points were transferred to the Arc GIS software and a map of the landslide distribution area in this environment was prepared. Also, in this study, 89 non-slip points were prepared for use in the training and testing stages of Persephone neural network inside slopes less than 5 degrees. Artificial neural networks are made up of a large number of interconnected processing elements called neurons that act to solve a coordinated problem and transmit information through synapses. Neural networks begin to learn using the pattern of data entered into them. Learning models, which is actually determining their internal parameters, is based on the law of error correction. In this method, by correcting the error regularly, the best weights that create the most correct output for the network are identified. The neurons are in the form of an input layer, an output layer, and an intermediate layer. ahp includes a weighting matrix based on pairwise comparisons between factors and determines the level of participation of each factor in the occurrence of landslides. In this model, a large number of factors can be involved and the weight of each factor can be obtained using expert opinion.
3-Results
According to the results of the high-risk class neural network model, which occupies 31% of the basin area, it is the widest risk zone in the region. The middle class also accounts for more than 29 percent of the area, followed by the low-risk class. The results of the AHP model show that the middle class, with 32% of the area, has the highest dispersion in the region, the low-risk class and then the high-class are in the next position. The AHP model was used to prioritize the parameters affecting the landslide. The parameters of slope, lithology and land use play the most important role in the occurrence of landslides, respectively, and have the least role for slope direction, distance from fault and height. The results of the models used are consistent with the reality of the region's wide-risk hazards, and high-risk areas based on the models used are mostly located in the west and southwest of the basin. These areas correspond to the mountain unit and the steep slope. Based on the results of AHP model, the impact of human factors in the occurrence of landslides is weaker than the natural factors of the region and human factors play a stimulating and aggravating role in primary factors. Five methods for error detection were used to evaluate the models used
4-Discussion and conclusion
 .Due to the sensitivity of unstable slopes in the region, any planning to change the use and construction that increases the weight of the load on unstable slopes should be done in terms of geomorphological and geological conditions of the region.
Keywords: hazard zoning, landslide, neural network, AHP. Sanandaj Gheshlagh Watershed
 

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One of the causes of environmental hazards is the change in the pattern of surface water flow in floodplains following the construction of flood Spreading networks. The purpose of this study is to prepare a zoning map of vulnerable areas of the flood Spreading station of Musian plain  in Ilam province after the implementation of the aquifer project in this plain. To prepare this map, five factors influencing the change in flow pattern including elevation, slope, flow direction, geological formations, and landuse change were examined. Then, in the GIS environment, each class of the mentioned factors was given a score of zero to 10 based on the range and the corresponding weight layers were created. Then, by combining the created weight layers, the vulnerability zoning map of the area was created based on 5 classes: very low, low, medium, high and very high. The results showed that the most important threat and danger factor is the concentration of waterways behind erosion-sensitive embankments. Also, the study area in terms of vulnerability includes three classes with medium risk, high and very high and covers 16, 62 and 22% of the area, respectively. Flood and upland Spreading areas, risk areas and lowland lands are the most vulnerable parts of the basin in terms of floods and sedimentary deposits.

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Risk modeling of plant species diversity and extinction in Sorkheh_hesar National Park
 
Zahra Mosaffaei¹, Ali Jahani^2*, ³MohammadAli ZareChahouki, ⁴Hamid GoshtasbMeygoni, ⁵Vahid Etemad
 
¹ Masters of Natural Resources Engineering, Environmental Sciences, College of Environment, Karaj
^*2Associate Professor, Department of Natural Environment and Biodiversity, College of Environment, Karaj.
³ Professor, Department of Restoration of arid and mountainous regions, University of Tehran, Karaj
⁴ Associate Professor, Department of Natural Environment and Biodiversity, College of Environment, Karaj
⁵ Associate Professor, Department of Forestry and Forest Economics, University of Tehran, Karaj
 
 
Abstract
Full identification of hazards and prioritizing them for non-harm to nature is one of the first steps in natural resource management. Therefore, introducing a comprehensive system of evaluation, understanding, and evaluation is essential for controlling hazards. This study aimed to model and predict environmental hazards following increased degradation in natural environments by ANN. Thus, 600 soil and vegetation samples were collected from inhomogeneous ecological units. Soil samples were prepared by strip transect method according to soil depth in four profiles (5, 10, 15, 20 cm). Vegetation samples were also collected using a minimum level method using 2 2 square plots according to the type, density, and distribution of vegetation. Sampling was done in two safe zones and other uses were modeled using ANN in MATLAB environment. The optimal model of multilayer perceptron with two hidden layers, sigmoid tangent function and 19 neurons per layer and coefficient of determination of 0.90. The results of sensitivity analysis showed that soil moisture content would be effective in decreasing biodiversity and flood risk as well as increasing the risk of extinction of endemic species in the region, and then the apparent and true gravity and soil porosity and distance from the road play a key role in the degradation of cover. Vegetation has increased flooding and extinction risk. Therefore, it is recommended that measures related to soil and vegetation restoration in this park be taken to reduce future damages as soon as possible.
 
Keywords: Modeling, Artificial Neural Network, Environmental Hazards, National Park, Vegetation
 

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Abastract
Introduction
Road accidents is the outcome of driver behavior, road condition, vehicle status, and environmental factors. Therefore, identification and assessment of effective parameters on road accidents can be considered as an appropriate way to reduce the accident events, driving violations and increase the road safety. Determining the effects of meteorological factors on the road accident events has gained more attention in recent years.
  The The main objective of this study was to investigate the relationship between the number of road accidents and the meteorological variables in the intercity road of Grmi-Ardabil in the Barzand route.
Methodology:
In this regard, the effects of climatic factors (including rainfall amount, the minimum absolute temperature, and the number of frost days) on the frequency of perilous events were analyzed. The data of accident events (in recent 4 years) were obtained from the trooper department of Ardabil Province along with the meteorological parameters of Germi station through a 11-year period. The statistical tests were performed using R programming software through statistical analysis.
Findings and Discussion:
The results showed that the majority of accidents were occurred in winter season which is in consistent with the frequency of frost days and also corresponded to the absolute minimum temperature. According to the results, the highest significant positive correlation at (R²= 0.43) was observed between the number of injured people and frost days. In addition, the relationship between the absolute minimum temperature and the number of were identified as significant negative correlation.
Conclusion:
As a concluding remark, the poor road conditions caused by climate element can be considered increasing the frequency of accident events. Accordingly, the proper strategies related to behavior change could be
considered in setting the rules and regulations to reduce the accidents and the number of injuries.

Keywords: Climatic hazards, Correlation analysis, Frost days, Minimum absolute temperature, Germi-Ardabil road


 

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Considering the increase in housing construction in developing societies such as Iran, it is necessary to address the issue of reducing construction accidents, especially in metropolises, and related safety measures with the help of emerging technologies. Therefore, the main goal of the current research is to investigate the use of Internet of Things to monitor and control high-risk points in order to reduce accidents and improve safety in the spaces of construction site in Tehran.
In this applied research, first, a library study was conducted regarding the concept and application of Internet of Things in the safety field of the construction industry. Then, high risk points and activities were identified. After that, in the field study phase, this list was corrected and completed by 52 competent building safety consultants. After that, ten semi-structured interviews were conducted with safety experts and knowledgebale in the field of IoT. Therefore, effective solutions based on Internet of Things were extracted to control and monitor high risk points. Also, in this regard, the current situation and required platforms were explained from the aspects of technology, organization, cost and outsourcing.
In fact, the main findings of this research, in the form of a conceptual model, show that paying attention to the stages of choosing the incident, choosing the desired point and activity, determining the appropriate solution for the determined situation (monitoring the amount of movement and health of the structure, monitoring the proximity of flammable materials with other materials, monitoring the proximity of people and machines and preventing the continuation of movement and determining the limits around the openings) and checking the required platforms (infrastructure, support, accreditation, culture, budget, employers and law), respectively, in order to design and implement IoT-based safety systems in the spaces of construction sites is vital.

 

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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.
 

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Explaining the spatial patterns of drought intensities in Iran

Abstract
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.
Introduction
Drought or lack of precipitation over some time is the most widespread natural hazard on the earth compared to its long-term average. This risk negatively affects various sectors such as hydropower generation, health, industry, tourism, agriculture, livestock, environment, and economy. To reduce these negative or destructive effects, it must be determined how often drought occurs during the period and in which areas it is most severe. Doing so requires determining the characteristics of the drought. These characteristics include area, intensity, duration, and frequency of drought. Discovering the geographical focus, recognizing the pattern governing the frequency of occurrence and temporal-spatial distribution as well as changes in the dynamics of this hazard facilitate an important role in drought monitoring, early warning, forecasting, and dealing with these potential hazards; this information can be used to create a drought plan by providing analysts and decision-makers with ideas about drought, helping to reduce the negative and vulnerable effects and ultimately make it easier to protect or replace for greater adaptation. Many researchers have been led by these approaches to the use of statistical analysis. Numerous studies have been conducted in the study of climatic phenomena such as drought with space statistics techniques in various regions, including China, India, South Korea, and even Iran. Part of the domestic research on spatial patterns of drought is without the use of spatial statistics and a limited number of others who have used these analyzes have only studied the overall intensity of drought and have not studied the spatial patterns of different drought intensities. The main purpose of this study is to identify the distribution and spatial patterns of drought intensities in Iran using spatial analysis functions of spatial statistics based on the frequency of drought intensities (Extreme, severe, moderate, and weak) with yearly, seasonal and monthly multi-scale approach. Therefore, this study will answer the questions: a) What is the spatial distribution of drought intensity data in Iran? And b) What is the variability of spatial patterns of Iranian droughts at different time scales?
Material &Method
ERA5 monthly precipitation data for a period of 43 years from 1979 to 2021 were used for this study. an array of dimensions of 78×59×504 of data were formed in MATLAB software in which 78×59 is the number of nodes with a spatial resolution of 0.25 degrees and 504 represents the month. After creating the database, the ZSI index was used to calculate the severity of drought in annual, seasonal, and monthly comparisons. Finally, to achieve the research goal and explain the spatial pattern governing the frequency of drought intensities (Extreme, severe, moderate, and weak), spatial statistical methods such as global Moran’s I, Anselin local Moran I and hot spots was used.
Discussion of Results
Due to its ecological conditions, geographical location, and location in an arid and semi-arid region of the world, Iran is among the most vulnerable countries due to natural hazards, including drought. It has experienced many severe droughts in the last century. The occurrence of drought and its effects is one of the major challenges of water resources management in this century. The results of the Global Moran’s Index for all three annual, seasonal, and monthly scales showed a highly clustered pattern of drought events in the country. Spatial clustering of the occurrence of severe and Extreme yearly droughts in the eastern, southeastern, and southern regions is also an interesting result. These conditions are due to low precipitation and high spatial variation coefficient in these areas. This contrast of spatial clusters of drought intensities indicates the relationship between drought and temporal-spatial anomalies of precipitation so that with increasing precipitation, spatial variability of precipitation decreases, and consequently spatial homogeneity of precipitation increases. severe and moderate-intensity spots in the south-southeast in autumn and spring can be affected by fluctuations in the beginning and end of the monsoon season in South Asia due to the high variability of atmospheric circulation at the beginning and end of precipitation in these areas. Some studies have also shown the relationship between precipitation in these areas and the monsoon behavior of South Asia. Extreme drought events in winter and spring have had a positive spatial correlation pattern in the southwest, west, and northwest. However, precipitation at this time of year is concentrated in these areas. Warm clusters or concentrations of very severe drought events in the northern strip of the country, especially in the Caspian region, can be due to the high variability of precipitation at the beginning of the annual precipitation season (late summer and early autumn).  Observations of these conditions in the northern strip indicate that an event with a high frequency of severe droughts, even in rainy areas, should not be unexpected. Spatial clusters of Extreme, severe, moderate, and weak drought every month using both local Moran and hot spots statistics show the fact that in Iran, the most severe droughts have occurred in the western, northwestern, and coastal areas of the Caspian Sea. However, the absence of severe droughts or spatial clusters has been the occurrence of low drought in the southeast and to some extent in the south. On a yearly scale, the south, southeast, and east have played a significant role in the spatial cluster of severe and extreme droughts. So that these areas of the country have had positive spatial solidarity. However, in these areas, negative spatial correlation prevailed in the autumn for severe drought. This may indicate an anomaly and a tendency to concentrate more precipitation in Iran, as well as many changes in seasonal and local precipitation regimes. According to the research results, a high incidence of severe and extreme drought on all three scales (monthly, seasonal and annual) even in the wettest climate of the country (northern Iran, especially the southern shores of the Caspian Sea) shows that High-intensity droughts can occur in all parts of the country, regardless of the weather conditions.
Keywords: Natural hazards, spatial patterns, Moran statistics, spatial autocorrelation, hot spots


 

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Introduction
A flood is a natural disaster caused by heavy rainfall, which causes casualties and damage to infrastructure and crops. Trend of floods in the world increasing due to climate change, changing rainfall patterns, rising sea levels in the future, and in addition, population growth and urban development and human settlements near river have caused floods to become a threat to humans. One of the most important and necessary tasks in catchments is to prepare flood risk maps and analyze them. In recent decades, researchers have been using remote sensing techniques and geographic information systems to obtain flood risk maps in an area. Due to the numerous floods that have occurred in the Neka river catchment, it is necessary to conduct a study entitled zoning of flood sensitivity in Neka river catchment for more effective management in this area.

Materials and methods
Study area: Neka river catchment area with an area of ​​1922 Km2 is part of Mazandaran province in terms of political divisions. This basin is between 53º 17´ 54 º44´ east and 36 º 28 ´to 36 º 42´ of north latitude. The highest point of the basin is 3500 m (Shahkuh peak) and the height of the lowest point of the basin in the Ablo station is about 50 m and at the connection to the Caspian Sea is -27 meters. The seven sub-basins of this basin are Laksha, Golord, Burma, Metkazin, Kiasar, Alarez and Sorkh Griyeh. Geologically, the basin is mostly of calcareous and marl formations. In the south and southwest of Neka River, the rock material is mostly clay and calcareous marl, which makes this basin has a high erosion potential
To study the flood zoning of the area using a multi-criteria decision model, 1: 25000 maps of the surveying organization and a digital elevation model with a resolution of 12.5 meters (Alos Palsar) were extracted. In order to study the flood risk in Neka river, 4 criteria of height, distance from the river, land use and slope have been used. In the present study, modeling and preparation of flood risk zoning map in 4 stage including descending valuation, normalization of each class, normalized index weight and integration of criteria has been done by the following linear weighting method. Performing linear weighting operations depends on the weighted average of a number of selected parameters in the opinion of the expert. According to the weight assigned to each criterion based on the expert opinion, each of the criteria was multiplied by the assigned weight and at the end the criteria were added together and the final zoning map was obtained.

Results and Discussion
In this study, using a multi-criteria decision-making system model, a flood risk zoning map in the Neka river catchment was prepared. According to the weight assigned to each criterion based on expert opinion, the final risk probability map has a value between 0.02 to 0.2, which is ultimately divided into 5 classes in terms of flood risk. Value range 0.02 to 0.06 component of very low risk zone, range 0.08 to 0.11 component of low-risk zone, range 0.11 to 0.13 component of medium-risk zone, range 0.13 to 0.16 component of high-risk zone, and finally domain 0.16 to 0.20 components of the area with very high risk potential have been obtained. According to the final divisions in the flood risk zoning map of the catchment area, a safe area means areas where the probability of flooding is very low and close to zero, and in contrast, the area with a high and very high risk potential for flooding has the probability of high-risk floods. According to the final flood risk zoning map, about 982 Km2 (51%) has high and very high vulnerability, as well as about 510 Km2 (26.69%) has medium vulnerability in Neka catchment area.

Conclusion
The results obtained from the model indicates that the highest risk of flooding points are located in the western parts of the Neka catchment area and the end of the catchment area that reach the city of Neka. According to the research findings, the most important factors in increasing the risk of floods were the slope in this area and the distance from the drainage network. According to the results of the model, a large area of ​​the basin is a component of high risk zone, that means the Neka river watershed has a high potential for floods. Evidence and documented reports show that the Neka river Basin has experienced several floods in the last two decades. The major part of the occurrence of floods is due to the natural conditions of the basin, thus it is necessary to reduce flood damage by changing the locations of various land uses based on flood vulnerability maps. Using multi-criteria decision making method can be used to prepare flood risk zoning maps in basins that do not have hydrometric data; It is also a more cost-effective method in terms of time. One of the important issues in the final result of this model is due to the weight of the layers, which should be used by experts, who are familiar with the region and this method and adapt to field evidence.

Keyworlds: Flood, Multi-criteria decision making system(MCDA), Hazard zoning, Nekarod, Natural hazard.



 

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Extended abstract
Landslide risk zoning is one of the basic measures to deal with and reduce the effects of landslides. Vernesara watershed is one of the areas where many landslides have been observed in different parts of it. In this research, in order to zone the risk of landslides using the entropy index, first the ranges of landslides were determined, then the effective factors in the occurrence of range movements were prepared in the ArcGIS software environment, and a landslide susceptibility map of the studied area was prepared. . The prioritization of effective factors using Shannon's entropy index showed that the slope layers, land use, surface curvature, topographic humidity index and topographic position index had the greatest effect on the occurrence of landslides in the region. Also, zoning landslide sensitivity with the mentioned model and evaluating its accuracy using the ROC curve shows the very good accuracy of the model (79.6 percent) with a standard deviation of 0.0228 for the studied area. The zoning map shows that the low-risk areas cover only 13% of the area and more than 56% of the area is in the area with high risk of landslides, which indicates the high potential of the area in the occurrence of landslides. . Construction at a distance from fault lines, waterways and the steep Asmari Formation and safety of communication routes are the most important measures to reduce the amount of damage caused by landslides in Vernesara watershed.
Key words: natural hazards, landslide, entropy, folded Zagros.
 

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Urban planners consider historical fabric as the beating heart of cities. However, cities and specifically their historical fabrics are constantly under influence of natural and human-induced hazards.  This study aimed to assess the vulnerability of Ferdowsi neighborhood as an example of Tehran’s historical fabric. The data was obtained from geographical information system (GIS) files and a survey, as well as historical contexts and documents were analyzed as part of this study. Ten municipal experts were also asked to provide a score of 1 to 5 for each of the 29 indicators compared to standard levels. The mean value of these scores was then used to evaluate the role of each parameter in the vulnerability of this neighborhood.  Study findings indicate a high potential for the occurrence of natural and human-induced hazards in the study area. The abundance of unstable multistory buildings and derelict electricity and water networks, storage of flammables in warehouses, and lack of sewage network for half of the buildings were the most significant factors contributing to the vulnerability of this ancient fabric. Problems such as insecurity, drug abuse in public spaces, overcrowding and daytime congestion have also led to rapid relocation of neighborhood residents, who subsequently were replaced by commercial activities and warehouses. In conclusion, numerous problems are contributing to the vulnerability of historical fabric of this neighborhood and such problems are highly likely to be applied to other urban historical fabrics in Tehran. 
 

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This study aimed to systematically explain the potential of the landslide occurrence to provide a prediction model of the possibility of this phenomenon in the Yamchi catchment in Ardebil province. In this regard, both approaches of discrete and continuous variables were used by means of overlay and logistic regression, respectively. Independent variables included elevation, slope, aspect, lithology, annual rainfall, roughness, general curvature, topographic wetness index, vegetation index, distance to fault, distance to stream and distance to road. The results, firstly, revealed the areas with high landslide potential by the matching layers of independent variables with the landslide layer in the geographical information system (GIS). These areas were in the middle elevation, high slopes, northern slope, high roughness, erodible formations, high rainfall, medium vegetation, surroundings of faults and rivers. Secondly, the results of the logistics regression model by providing a prediction equation of probability of landslide occurrence showed that the resulting model with pseudo r² and ROC 0.22 and 0.86, respectively, had good power and efficiency to predict landslide through the catchment. In addition, the resulting beta coefficients for independent variables indicated that the importance of the variables was as follows: vegetation index distance to road, rain, lithology, distance to fault, elevation, topographic wetness index, roughness index, aspect, slope, and distance to river. In the end, the need to pay serious attention to the supporting and protection of vegetation cover of the mid -range and upstream of the catchment was determined because of unstable geomorphic conditions of these areas.
 

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In order to plan, manage and exploit water and land resources, awareness of the spatial variability of resources, as well as understanding the response behavior of the watershed in order to model physical processes, has an identical significant role. Due to its location in arid and semi-arid areas, special climatic and geomorphological conditions, Qom-Roud basin is prone to flash floods. Due to the lack of hydrometric and topographical data with high accuracy in the basin, the use of hydraulic models does not lead to accurate results of the hydraulic characteristics of floods. In such a situation, the methods based on the geomorphological features of the basin can be advantageous. In this article, Variable flood stage method (VFS) method is used, which combines the hydraulic characteristics of the river with the geomorphic characteristics of the basin in order to estimate the water depth in the river caused by floods with different return periods. The water depth was investigated for different return periods of two, five, ten, twenty-five, fifty and hundred years. In each period, the highest water depth was in the parts near the outlet and the lowest water depth was in the upstream parts of the river. The research illustrations there is a direct relationship between the depth of water and the area of the sub-basin. The results of this research can be used for basins without hydrometric and topographic statistics with high accuracy in order to estimate the peak speed and flood depth.
 

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The vulnerability of rural settlements to environmental hazards necessitates attention to local resilience. The aim of this study was to prioritize the factors affecting the physical-environmental and institutional resilience of Divshal rural district. The approach of the present study is descriptive-analytical and survey. Data collection was done in two forms: documentary and field (expert questionnaire). The statistical population of the study is 16 Rural managers of Divshal rural district. Using DEMATEL and ANP techniques, the obtained data were analyzed. According to the results of the ANP method, the sub-criteria of respecting the privacy of roads and preserving indigenous and cultural identity in new constructions have the greatest impact on the resilience of the study area. Also in the quality index of passages, sub-criteria of observing the privacy of passages; In the index of quality of access to services and infrastructure, quality of access to welfare and administrative services; In the shelter index, the existence of a strong public shelter in critical situations; In the index of quality of housing and constructions, preservation of indigenous and cultural identity in new constructions; In the environmental quality index, waste collection and disposal; In land use quality index, proper location of land uses; In the context of institutions, the existence of administrative organizations and institutions to help people; And in the Index of Institutional Relations, the cooperation of institutions in facilitating laws and giving credit to the people has the greatest effect on physical-environmental and institutional resilience.

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Objective: “The main and overall objective of this research was to identify natural hazards threatening Saluk National Park and Protected Area. In this regard, based on the assumptions of this research, in addition to the main objective, three sub-objectives were also determined for it. The sub-objectives include identifying hazards arising from climatic, geomorphological, and hydrological conditions.
Method: This research was conducted using field and library methods and descriptive analytical methods. The aim of the field studies was to identify the plant and animal species of this park and protected area, which was done using interviews with environmentalists, people living in villages adjacent to the park, and the results of censuses conducted by the Environment Organization. In library studies, concepts and definitions related to the environment and natural hazards were extracted from books available in libraries and documents of the Environment Organization. Statistics from meteorological stations in the region were used to study the climate of the region.
Results: Initial studies suggested that climatic, geomorphological, and hydrological hazards may be the most important natural hazards of the park. Based on the studies, climatic hazards including drought, frost, and frost have greater impacts in the study area. Geomorphological hazards of the park resulting from external dynamic processes including landslides, landslides, and erosion are ranked second, and hydrological hazards, especially river floods in the eastern part of the park in the Ruin River valley and the southern alluvial fans of the park, are ranked third.
Conclusions:
The most important conclusion of this research is that the natural hazards of this park naturally act as an ecological moderator. And these hazards can have detrimental effects on this park when they interact with negative human interventions, but if they are aligned with positive human actions, their effects will not have a significant destructive impact on this park.





 

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Objective: Investigating the occurrence of land subsidence in the country and the extent to which rural settlements are exposed to the phenomenon of land subsidence.
Methods: The present study was based on library surveys and studies, field observations and impressions. Using information received from the National Mapping Organization, a map of the country's subsidence zones and the degree of risk of each zone, including very low, low, medium, high and very high risk, was drawn, and the aforementioned maps were compared with the location of the villages.
Results: According to the analysis of the available data, 302 villages are at very high risk, 768 villages are at high risk, 834 villages are in the medium risk zone, and 573 villages are in the low risk zone. In terms of percentage weight, about 4 percent of the country's villages are at medium to very high risk of subsidence, of which 1,904 villages are at medium to very high risk, and 573 villages are at low risk.
Conclusions: The highest provincial distribution of villages at risk of subsidence in the country with a very high degree is in the provinces of Alborz, Tehran, Khorasan Razavi, Qazvin, Kerman, Golestan and Hamedan, and the highest provincial distribution with a high degree is in the provinces of West Azerbaijan, Isfahan, Alborz, Tehran, Khorasan Razavi, Semnan, Qazvin, Kerman, Golestan, East Azerbaijan, Hamedan and Yazd. Also, the highest provincial distribution of villages at risk of medium-level subsidence is in the provinces of East and West Azerbaijan, Isfahan, Alborz, Tehran, Semnan, Qazvin, Kerman, Golestan, Mazandaran, Markazi, Hormozgan, Hamedan, and Yazd.