نشریه جغرافیا و مخاطرات محیطی
پیاپی 26 (تابستان 1397)

Geomorphometry is the science of quantitative land-surface analysis. The main purpose in geomorphometry is to extract the parameters of the earth's surface and the shape of the earth from a DEM (digital elevation model), which first refers to the continuous properties such as slope, aspect and so on. It is produced and extracted in the form of raster maps and images. The latter also refers to discrete spatial features such as alluvial fan, drainage network, and watershed border, which are produced as a vector map in the form of lines, maps and, polygons. Soil erosion in the Monj Watershed is damaging; therefore, the main objective of this research is to analyse the geomorphometric parameters and prepare a soil erosion susceptibility map using VIKOR algorithm and CF method in this watershed. Since the hydrological units are based on the analysis of geomorphometric parameters, the use of the stream networks, and the contour lines in the topographic maps at 1: 50000 scale and the digital elevation data derived from Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) images version 2 in ArcGIS10.4 software along with Arc Hydro and SAGA GIS v.3.0.0 attempted to determine the boundaries of hydrological units and determine the sub-watersheds. Then, the streams were ranked. Digital elevation data derived from Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) images version 2 are based on the extraction of basic, linear, shaped, and topographic morphometric parameters. The mentioned geomorphometric parameters were prepared using the ArcGIS10.4 software and other data needed for the next step. After extracting and analyzing the geomorphometric parameters in each sub-watershed, using VIKOR algorithm and CF method, sub-watersheds are prioritized. Then, soil erosion susceptibility map of the study area was prepared with both methods and was verified by the PSIAC method. In this research, the quantitative analysis of the Monj Watershed and its 11 sub-watersheds were carried out to evaluate the geomorphometric characteristics of each sub-watershed and to investigate the susceptibility of erosion in each of the sub-watersheds. In this regard, 22 geomorphometric parameters were investigated, and the results indicate the basic, linear, shape, and topographic characteristics of the watershed. Based on the ranking of the streams, the Monj watershed was classified as a five-order watershed with an area of ​​71/70 km2 and a perimeter of 373/123 km. The total number of streams in the watershed is 2204. The total length of the streams in the watershed is 327.393 km. The lengths of the streams in the watershed vary from a minimum of 4.62 km for the sub-watershed 6 to a maximum of 91.62 km for sub-watershed 7. The mean values ​​of the stream length vary from a minimum of 0.1216 for the sub-watershed 6 to a maximum of 0.1187 for the sub-watershed 8. In the next step, the geomorphometric analysis of watershed was carried out to prioritize the sub-watersheds in different scales and sub-watersheds. Finally, all sub-watersheds were categorized into 4 classes in terms of susceptibility to erosion according to the values of VIKOR algorithm and CF model. The determination of the importance of the effective parameters in erosion using AHP method showed that the parameters of drainage density, slope, and infiltration number with scores (0.125, 0.116 and 0.104),had the greatest effect on the erodibility of sub-watersheds. In contrast, the parameters of form factor, elongation ratio, and the length of overland flow with the lowest scores (0.008, 0.011 and 0.023) had the least effect on the erodibility of the sub-watersheds. The classification of sub-watersheds in terms of susceptibility to erosion in the superior method of VIKOR showed that 27.21 km2 (38.48%) was located in the very high susceptibility class, 1.60 km2 (2.27%) was in the high susceptibility class, 37.62 km2 (53.21%) was in the moderate susceptibility class, and 4.26 km2 (6.032%) was in a low susceptibility class from the total area of watershed (70.707 km2). In addition, from the total study area in the CF method, 62.83 km2 (88.87%) was located in the very high susceptibility class, 6.37 km2 (4.50%) was in the high susceptibility class, and 4.75 km2 (3.36 %) was in the moderate susceptibility class.

Sustainability of natural resources is directly or indirectly related to surface cover of the region. Therefore, the maintenance of coordination between sustainable resources and socioeconomic needs and the increasing environmental awareness and efforts to manage sustainable natural resources require studying land use monitoring and land cover and its changes for time scales and in different locations. Land cover and its changes are important variables which have significant effects on the environment and its processes. The increase in population and the development of human activities over the last few decades have significantly affected the earth's surface. The change in land use and non-use of land has increased the suitability of the destruction process. Therefore, it is necessary to investigate the relationship between changes made in different uses and each of its consequences for their correct and optimal management. Attention to the development of remote sensing science in the past years along with these changes, various methods, and algorithms have been developed to investigate the changes in applications. One of these methods, which focuses on the quantization of the spatial structure of the terrestrial landscape (In fact, it means the surface of the earth, where there are different spots that set up a particular arrangement of topography, vegetation, and land use and in which a combination of local ecosystems or land uses have been replicated in a similar form) is the landscape metrics. These metrics are able to provide a great deal of information about the structure and modifications of the constituent parts of the land in a patches space of time. Landscape metrics are in three levels, including the entire area of the landscape (the integrated and various types of classes and patches in the landscape), the level of user classes and land cover (all patches representing a type of user or a type of cover), and the surface of the patch (defined as single patches and spatial properties, the type of content, and the texture of the patches) are measurable. In this research, by studying and reviewing scientific sources and obtaining expert knowledge of the bachelor, regarding the suitability of the measures with the purpose of the research and considering the correlation between their concept, set of measures of composition and distribution of facial features were selected for the present study. The assessment of the number of patch on the class level showed that the greatest change during this period was in the number of patches pertaining to the agricultural and human-made class, which indicates the fragmentation and the disturbance in the land reated as a result of the expansion of agricultural land and human beings. The comparison of patch density at the level of the class show that the expansion of human land and increasing agricultural use, the development of activities, and user changes have caused the density of rangeland patches to be reduced and have a greater fragmentation than other classes. The results of the increase in the number of patch from 67291 to 112382 at the surface of the landscape indicate the decomposition and reduction of continuity with the help of which it is possible to detect the processes involved in the decomposition and fragmentation of the landscape surface. In addition, the results of the increase in the patch density on the surface of the landscape from 34.28 to 57.25 per 100 hectares indicates the fragmentation of the landscape during the studied period. The results of the surface of the landscape for a Contag metric indicate a decrease in integrity and an increase in fragmentation, and for Shannon diversity metric, an increase in diversity in land use change. Generally, in order to understand the changes in the landscape structure areas, changes in natural environments should all be assessed on a time basis. Therefore, in this research, it was necessary to analyze landscape in the time frame of the study in order to evaluate the changes in the applications. The determination of the uses indicates that the watersheds have created patches in the region over the past years (various agricultural and human resources). Using the metrics at the level of the class and landscape, the results of the study indicate that the shape of the land is generally fragmentary in terms of the integrity of the structural elements.

Geomorphology can contribute to the management of fluvial systems through study of channel stream hazards. Hazards have been identified for geomorphic systems, being defined as any landform change, natural or otherwise, that adversely affects the geomorphic stability of a place (Chin & Gregory, 2005). River hazards include flood, erosion, and deposition. Among human modifications, urbanization has the most irreversible impacts on river systems. Urban development can have two direct or indirect effects on the rivers. Direct modifications of river channels, such as straightening and channelization along with indirect modification changes the Earth’s surface by replacing the natural land cover with impervious surfaces (Chin et al., 2013).
In this research, the city of Noshahr has been studied. Noshahr is located in north of Iran in Mazandaran Province. The city is situated in south of the Caspian Sea and western coastal plain of Mazandaran. In this area, the width of coastal plain is less than 5 Km and it is geologically bound by Alborz Mountain Ranges. Urban geology is composited with marine and alluvial sediments. The climate of the region is temperate with an average annual rainfall of 1273 mm and the mean of temperature is 16.2C. Three major streams, Mashlak, Gerde-kal, and Korkorsar cross the urban area. The paper has proposed a classification method for channel stream hazards in urban regions. The work is done in three steps: a) The channel reach was identified based on the geomorphic characteristics and the stream adjustment indicators. The step assesses the river sensitivity of each reach based on its capacity for adjustment and classifies the reach scale adjustment based on the magnitude and rate of the response observed in aerial photographs (Reid & Brierley, 2015). Geomorphic sensitivity of each reach was ranked as high (H), moderate (M) and low (L); b) In the second step, each stream reach was divided based on direct human activity (management) and stream structures. The stream reach has categorized into four classes: A, B, C and D. Class A shows the most interventions, while class D is at least interventions in each stream reach. c) In this step, channel stream was classified into twelve classes by combining the two previous steps (geomorphic adjustment and human activity). The intensity of geomorphic process activity are marked with values 1, 2 and 3. Result and Discussion: In this study, 14 reach of urban streams were investigated. Dimensions of three main streams of Mashlak, Gerde-kal and Kurkorsar were measured using aerial photos (1999-2016) and the field work. All stream reach in study area are limited between alluvial terraces. The average height of these terraces varies from 2 to 4 meters and has been created in the last phase of the retreat of the Caspian Sea. The capacity of geomorphic adjustment is moderate (M) and low (L) in all stream reaches. Channel types are classified according to natural adjustment capacity and human interventions. According to this, the reaches of Korkorsar (1-4) and Mashlak streams (12-14) have near naturally channels and fall into classes of MD and MC. These channels have a moderate natural adjustment capacity, and the human interventions to protect of rivers are less than 10%. Channel reaches in the Gerde-Kal were categorized into the classes of LA and LB. These channels have a low adjustment capacity and their banks have protected by bank revetments such as concrete and boulder more than 60 percent. After classification, the river channel hazards including erosion, sedimentation, human activity, and hydrology were investigated at each reach of channel. In the class of MD, erosion is dominant and natural adjustment occurs during floods. The observed human interference is occupying the flood plain, urban debris accumulation and the quarrying of channel sediments. In LB and LA classes, sedimentation forms are observed in all reaches. Sedimentation has reduced the channel capacity; hence, flood has exited from the alluvial terraces and has damaged urban areas. Also, removing the arch of the rivers (creating a direct channel), the construction of transverse walls in the channel bed and the reduction of the channel slope are effective factors in the outflow of the channel. Channel stream classification based on river hazards can accommodate channel reaches with similar processes and forms in a group, and it provides an analysis of the available and probable hazards in stream channels. In addition, the effects of upstream river can be studied in the downstream channel. Such a spatial view provides a useful framework for management strategies.

Increasing population and anthropogenic activities have brought about many environmental problems globally. One of such problems is land subsidence described as the gradual differential settling or sudden sinking of the ground surface due to the movement of ground materials. Land subsidence is generally caused by human activities, alterations to the earth’s surface and underground geologic processes. Specific causes include underground mining of solid minerals, and the collapse of such mines; withdrawal of groundwater and petroleum; dewatering or drainage of organic soils; sink holes, wetting of dry low density soil; and, natural sediment compaction. Land subsidence has received researchers׳ attention in different parts of the world. In this research, land subsidence problems resulted from the overuse of ground water in Khoy is investigated. The study area is Khoy basin located in the north of West Azerbaijan Province. latitude and longitude of the area include 44° 47´ 37״ to 44° 55´ 08״ E and 38° 35´10״ to 38° 37´ 24״ N. The study utilized water extraction data obtained to model the subsidence susceptibility surface of the study area. Total quantity of water extracted in the study area was calculated by combining extraction figures that including the annual discharge for all the hand pump boreholes. Since the data required for the study have spatial components that can change over time. GIS was proved useful in the storage, integration and display of the data. The study used water discharge figures to model the susceptibility of the study to land subsidence in a GIS environment. The map produced showeds that the very high and high subsidence susceptibility zones are found in the surrounding areas of Khoy. Using a GIS for the modeling enabled a data base to be created which could be updated as new facts would emerge. The data on water extraction was linked to an existing data base of the base map of the study area. Data on subsidence susceptibility index of the study was used to produce subsidence surface map which was divided into 4 subsidence zones using a reclass tool of arc map’s spatial analyst extension. Figures 11 and 12 show the spatial distribution of the subsidence, while Table 3 shows the areal distribution of the zones. , As seen in the table very high zone covers 10%, while the low zone covers 28%. The analysis using water extraction is a good estimate of land subsidence; therefore, it serves as a good tool for policy makers to monitor environmental hazards. Areas of special interests could also be monitored. For example, the map shows that areas of high and very high zones are found in the established Firuragh area of Khoy. The study demonstrated the use of GIS to visualize the subsidence of the study area. This environment allows for the ease of data editing, integration, analysis, and storage. The resultant product will help to identify, and locate sensitive areas that can be impacted by subsidence so that emergency managers can customize disaster relief efforts. Using a GIS for the modeling enabled a data base to be created so that it could be updated as new facts emerge. It is recommended that a subsidence unit should be established within Khoy so that the rate land subsidence could be monitored, especially in the vulnerable areas identified in the study. On the one hand over-exploitation of groundwater resources leading to low capacity levels, but on the other hand it results in land subsidence in some parts of Iran. Due to the easy access and simply tapping of underground water resources, the use of these resources has increased substantially in recent years, and unfortunately in some areas the exploitation of groundwater resources is more than their store. The main criteria for zoning include the presence or absence of fissures, the extent of water-table drop, the kind of deposits, and the original depth of water table. In general, four zones were separated and mapped, including very high, high, medium. The map produced shows that the very high and high subsidence susceptibility zones are found in the Firuragh area. From the map it can be seen that very high zone covers 10%, while the high zone covers 29%. According to the results, the water level of the Firuragh Plain had dropped about 5/04 meters over the last 12 years, whereas, the annual average drop in water level in the Firuragh plains is about 42 cm. Thus, the drop in water level has caused land subsidence in the plain.

Protected areas (PAs) are the basis of biodiversity protection. Societies invest in utilizing, managing, and protecting the primary roles of the PAs. Thus, performing management plans need much time, cost, and workforce by the increase in number and area of the PAs in recent years. In this research, the early warning system (EWS) is proposed as a solution to decrease the management cost of PAs and other significant and inaccessible areas. EWS is a general idea that can be used as a useful and cheap tool to ease the access to primary global strategic goals of protection of stable development. In some studies, it is attempted to utilize the EWS to describe biological mobility, environmental elements related to ecological security, to prevent the loss of resources in environmental disasters, and to decrease the flood damage. This study is based on research RS_GIS research and the pressure-status-response (P-S-R) model on the ecological security status in Darmiyan PA, located in the eastern part of Iran. The primary goal of this paper is to present the EWS for in time and appropriate monitoring, maintaining the mobility in relations, and preserving the health of the ecosystem of PAs. In this study, it is attempted to determine the ecological security index (ESI) of Darmiyan PA according to the P-S-R model to propose the EWS with the aid of this index for the study area. In this approach, 12 environmental indicators in three categories of pressure (the average annual temperature, annual precipitation, fragmentation, the hunter presence risk), status (distance from human-made areas, distance from farms, cover vegetation status, soil brightness, finite rate of increase wildlife), and response (the increment rate of governmental financing in the region, the Incompatibility percentage of the region with protection use, utilization and development of technology in protection) were chosen. These indicators were measured by the images of TM and OLI sensors of the LANDSAT satellite, DEM Aster, thermal data of Modis from the earth surface, and statistics and information of the environmental and meteorology organizations of South Khorasan. The ESI for each of the 30-meter pixels of the study area was determined by the Multivariate Composite Estimator (MCE) method using Weighted Linear Combination (WLC). According to the defined features for the EWS indicators, the leading and final indicators to act on the EWS system were chosen using decomposition to main components and multivariate regression. Finally, with the calculation of the thirty-year average of the mentioned indicators in the study area, the confidence interval for each of these indicators with the confidence factor of %95 was achieved. The results declared that the average ESI changed from 0/315 in the year 2000 to 0/518 in the year 2014. Checking the variance plot of the standard value of the useful indicators in ESI declared that except three indicators of distance from human-made areas, distance from farms, and the incompatibility percentage of the region with protection use, the other indicators held a better status in 2014 in comparison to the year 2000. These results represent the practical impact of protection and management in the region. However, the decrease in the standardized value of the three mentioned indicators declares the lack of attention to the exceptions of the PA and the increasing trend of land tenure in the study area.
Location changes in the ESI of a particular year have a close relation to the land shape. In the under study area, as we move from the flat areas to the heights, the ESI increases. Studying the categorized map of the sensitivity of the study area in 2014 indicated that 95 percent of the study area is located in medium and high sensitivity categories. The living locations of urials wild sheep in this map indicated that this species had chosen areas with medium and low sensitivity where are hilly with high ecological security to live.
Three indicators, including annual precipitation, cover vegetation status, and soil brightness, were chosen as the appropriate indicators to be utilized in the EWS of Darmiyan PA. While monitoring, the warning areas in the study area were determined by studying the status of these three indicators. This EWS was utilized in the study area in 2014. Based on the results, some parts of south-west and east of the area have been subject to danger. After determining the vulnerable areas, the operation accuracy of the proposed EWS was assessed using the field visit. This system had good accuracy. With the presented approach, one can have regular monitoring of the critical and inaccessible areas. This approach is practical with its minimum cost in optimum and oriented managing of Pas even though the choice of general and useful indicators in ecological security remains the most crucial part of this approach. In this research, one can see a reduction in managing expenses through the use of technology. The effective indicators on the ecological security of an area with a semi-arid climate are proposed. This research helps the ecosystem existence of the areas where they are the habitat to international species. In this study, the minimum number of indicators was used for a warning system even though the necessity for research on a warning system with more indicators and comparison with the presented results remains considerable. We believe this research is an appropriate starting point for discussion on the use of the warning system for essential and inaccessible areas of all around the world.

Airborne dust is an important environmental hazard in arid and semi-arid regions. Dust deposition rate is one of the most important characteristics of airborne dust which needs to be measured for risk assessment and source determination. During the past decade, by increasing the dust deposition in Iran, many investigations have been conducted to document the dust deposition characteristics and identify the regional atmospheric and land surface processes controlling dust transport. The objective of this study is to measure the dust deposition rate and investigate the effect of climatological factors on airborne dust in Khorasan Razavi Province located in the northeast of Iran. Khorasan Razavi Province is located in the northeast of Iran. Elevations range from 235 m in Sarakhs in east to 3211 m at Binaloud Mountain in north of the area. Mean annual precipitation varies from 111.5 to 306.3 mm and the mean annual temperature is between 12.7°C to 18.9°C. The Kopeh Dagh and Binaloud Mountains are in the northern part of the area. There are several playas (including clay flats, salt crusts, and sand dunes) in the south and western of the Province. Airborne dust samples were collected monthly from May 2014 to April 2015. A dry flat collection tray with an area of 1 m2 was used to sample airborne dust. Fifty trays were placed on the roof of buildings ~3- 4 m above the ground level. Dust trapped on the trays were collected by a rubber spatula and then were weighted. Totally, 600 samples were collected from 50 sites in the Province. Interpolation in this study was carried out using surfer software 14. Furthermore, the Grads software was used to draw the average monthly wind speed, direction patterns, and synoptic pattern of dusty days. The Pearson coefficient was used to determine the correlation between the characteristics with normal distribution. The measured dust deposition rate indicated the significant spatial and temporal variations during the studied period. The lowest and highest average monthly dust deposition was 9.97 and 20.96 g m-2 which occurred in December and June, respectively. The annual dust deposition rate showed high variations from 313.14 g m-2 y-1 in Gonabad with desert climate regime in southern to 74.62 g m-2 y-1 in the city of Quchan with temperate-mountainous climate in northern part of the area. In spring and summer, the dust deposition rate was the highest in the west and the south of the Province and also indicated the high range of variations. In autumn and winter, the range of dust deposition rate decreased and also the highest amount of deposition occurred in the east. The lowest amount of deposition was found in the mountainous northern part of the area. There was a significant positive correlation between the average dust fallout and the mean wind velocity and the maximum and minimum monthly air temperatures, while there is a significant negative correlation between this parameter and relative humidity. The spatial distribution analyses showed the highest amount of dust fallout in the southern and western parts of the Province, which includes the desert and sub-desert climate and also the most storm occurrences in spring. Also, in the months with higher rainfall, the amount of fallout rates decreased in most areas except the east of the Province. The high speed of wind, the dryness of the soil and the high occurrence of dust storm in June and July have caused the dust to be carried a long distance as compared with other months. The results of this study indicated the hazard of dust deposition rate, especially in the south and west of the Khorasan Razavi Province in spring and summer. The dust deposition was the highest in the areas at margin of the desert with low relief, sparse vegetation and high wind velocity. Monthly variations in dust fallout rates were related to some climatological parameters. There was a significant positive correlation between the average atmospheric airborne dust fallout in 12 sampling intervals, the maximum and minimum temperatures, and wind speed and there was a significant negative correlation between this parameter and relative humidity at P-value<0.05. These findings are closer to the results of Noroozi and Khademi (2015) (in Isfahan), Al-Harbi (2015) (in Kuwait), and Kaskaoutis, et al. (2016) (in the southwest of Asia). Furthermore, through the change of the direction in prevailing winds from east and northeast in dry months to the west and northwest, the rate of airborne dust fallout declined in most regions in the months with more precipitation, but not in the east of the Province where the area was exposed to the highest wind speed in spring and summer. It is noted that the increase of temperature causes a decrease in soil moisture; this issue is, in turn, considerably important in decreasing the speed of the threshold, which consequently increases the wind force and soil movement (Rahimi, 2015). In addition, rainfall and temperature can indirectly play an effective role in amount of the fallout rate through affecting vegetation due to the effect of these two parameters on the plant coverage (Makhdoum, 2006). The results of the analysis of climatic synoptic maps related to stormy days in the sea level pressure map showed that the establishment of the cyclone center in Afghanistan and the south of Khorasan, and the anticyclone center on the Caspian Sea and Turkmenistan cause heavy winds and dust storms in the region. Considering the geographical location of the Province (sharing borders with both Turkmenistan and Afghanistan) and the wind direction, it could be suggested that the sources of these storms are found in the surrounding areas. However, the determination of the source of the atmospheric suspended particles in Khorasan Razavi Province requires further study and more comprehensive laboratory analyses.

Heat waves as a climatic extreme phenomenon had more occurrence in recent years in which case it is an evidence of the earth climate change. The heat wave is generally defined as a period of consecutive days with unusual high temperatures which has become a common risk in the world due to its effects on the nature and human beings, including health, hygiene, water resources, and agriculture. The identification of these effects requires recognizing the heat wave and determining its thresholds. Due to the climate change, heat waves can occur more intensely with higher frequency longer than before (Esmailnejad, 2013; Jinghong et al., 2015; Keggenhoff et al., 2015; Rusticucci et al., 2015). The research attempts to determine the temperature threshold of the heat wave in different regions of the country during the warm period of the year. To meet this purpose of the study, the statistics of daily maximum temperature of the 90 synoptic stations during the statistical period of 1986-2015 from April to September was collected through the country's meteorological organization. After the primary processing of raw data, the temperature threshold of the heat wave during the warm period of the year was then determined based on three global indexes (Percentile 95, Baldy, World Meteorological Organization).
Baldy indicator: Tmax daily ≥ Tmean max daily + 1.5 sdmax daily To determine the temperature threshold necessary for extracting the heat waves according to Baldy indicator, first the mean and standard deviation of daily maximum temperature of each station were calculated. Next, the relation of Tmean max daily + 1.5 sdmax dail was calculated as a dot for each station and it gained one threshold as such. Finally, the days which their maximum temperature of each station is ≥ p 95 and at least continue for a few consecutive days are named as heat wave.
Percentile 95 index: when the daily maximum temperature is equal or larger than percentile 95 and continues at least for 2 days, it is known as a heat wave.
World Meteorological Organization (WMO) index: when daily maximum temperature is 5°c more than a long term mean for 5 consecutive days, it is defined as a heat wave.
Fomyaki index (NTD): when the temperature is +2 standard deviation from mean (NTD) and continues at least for 2 days, it is defined as a heat wave. The purpose of using different indexes was to select the appropriate index and finally to determine the threshold according to that index. To determine which index is more appropriate to define the threshold, first it was necessary to measure the ability of these indexes to extract the heat waves. But after using the indexes in question and extracting the heat waves by these methods, it was found that these indexes have the ability to detect heat waves. Although it may differ in terms of the characteristic of heat waves such as continuity, intensity, and extent, the main problem is that these indexes do not show an equal threshold. Therefore, although the results of each of these indexes according to the basis of scientific and statistical rules are valid, it is not possible to select an index as a arbitrarily better and more appropriate index and determine the temperature threshold based on it. Consequently, the smallest threshold was considered among the different thresholds for each station in order to determine the final threshold. In addition, the days which were equal or larger than this threshold was selected as a hot and wave day. It is important to note that because the output of Fomyaki index (NTD) is a coefficient, the index was not used to determine the final threshold; it was only used as a confirmative index to investigate the heat wave occurrence. Then in ArcGIS environment using a hybrid method of IDW and regression, the temperature threshold was interpolated for the whole country, considering the latitude and altitude (as the two important and effective factors in the amount of the temperature threshold of the heat wave).The results showed that the temperature thresholds in the country's different times and places are not the same in the warm period of the year, and they have different ranges. The temperature threshold ranged between 15 - 40 Celsius in April, between 21-46 Celsius in May, between Celsius 25-50 in June, between 29- 49 Celsius in July, between 32- 52 Celsius in August, and between 27- 47 Celsius in September. In the months of April, May, and September, the temperature threshold is higher from the local differences, while in the months of June and July and August it has almost the relative uniformity, which is due to the presence of Azores subtropical high pressure which dominates all parts of Iran from the south of Alborz Mountains. On the other hand, this phenomenon decreases the effect of local factors such as altitude and latitude on the value of temperature threshold in these months leading relative integration in temperature threshold. Also, the results show that the highest temperature threshold of the heat wave in the warm period of the year is related to Khozestan Province and the lowest temperature threshold of the heat wave is related to the parts of the north and north west of the country. The results of this research indicate this scientific fact that in order to obtain accurate temperature threshold for different regions of the country, different indices should be used because these indicators complete each other, and we cannot achieve the accurate results in this field by using just one index.

Throughout human life, there have always been threats to the lives of humans and their habitats. These threatening factors can be divided into two groups of natural factors and human-made factors. In the real-time locational process, these factors (flood, earthquake, fire, etc.) sometimes hit the human society and destroy their lives and activities. Hence, communities have used several policies and actions, including resettlement policy to protect villagers against all kinds of hazards when planning for settlements at risk, including the villages damaged or destroyed by natural disasters.
Different approaches can be used to assess the effects of the resettlement policy, one of which is the sustainable livelihood. In this approach, it is emphasized that any transformational factors, such as environmental hazards, will endanger the human community capitals (assets), and will lead to their weakness. The integrated orientation of this approach toward the five capitals and its emphasis on the structures and factors affecting the sustainable livelihood provide a framework which can be used as a proper basis for evaluating policies and actions.
This research was conducted with a sustainable livelihood approach with the aim of evaluating the effects of implementing resettlement policy on rural settlements in Avaj County and Qazvin Province in Iran (Abdare, Changureh, & Saeedabad, in 2016), which were relocated due to the earthquake in 2002. This research has a positive paradigm and quantitative methodology based on a descriptive-analytical method and applied objectives. Documentations (libraries), cyberspace, and fieldwork were used for data collection. The data and the main and applied information of the research were obtained using the field method. The interviews and questionnaires were used for collecting data. The sample size was estimated using the Cochran formula as 212 households in three villages. Statistical methods such as run, Kolmogorov-Smirnov, path analysis, regression, independence of error, and Durbin–Watson tests were used in the SPSS software for data analysis. GOOGLE EARTH, GSMD, and ARC GIS were used to draw maps and introduce the study area. Based on impact assessment (both direct and indirect), all independent capitals (influenced by settlement policy) has had effects on the sustainable livelihood. These effects have not been the same among the capitals. Here we will explain how they were effective:•Natural capital in the studied villages reached a good condition after displacement in terms of improving the position of the villages regarding slope and topography compared to pre-resettlement, vegetation and the absence of pollution (sound and air). This improvement led to the fact that the natural capital component strengthened the sustainable livelihood in villages only with its direct impact and β=0.600, which was slightly different from the β of the financial capital. It is worth noting that this component is not in good conditions due to the mountainous nature of the studied region, sloped farms and the resulted erosion of soil, and water scarcity and contamination in some cases.
•The social capital of the studied villages was in good conditions after displacement in terms of support network and kinship relations, villagers’ interaction, security, trust among villagers, coherence, etc. It created the basis for the positive development of sustainable livelihood under the influence of those factors. The status of trust between villagers and state institutions, the freedom to express beliefs or social demands, participation in financial affairs, etc. were however in poorer conditions, which undermined sustainable livelihood. As a result, this component ranked fourth in terms of affecting sustainable livelihood (β=0.4331).
•Human capital was in a moderate condition only in terms of the ability to provide clothing and food and has had a positive effect on the sustainable livelihood in some cases. Other components such as health, treatment, sports, leisure, innovation, competition, knowledge and skills, workforce, and training were in very poor conditions. As a result, human capital (with a beta of -0.1047) has negatively affected the sustainable livelihood.
•The financial resources in the studied villages after displacement has somewhat improved in terms of private ownership of housing and the lack of informal activities, credits, and savings. Nonetheless, they are not in good conditions in terms of access to banks, insurance, occupation, etc. Having been affected by resettlement, financial capital, however, has been able to lead to the sustainable livelihood with a beta of 0.6256.
•The physical capital of the studied villages after the displacement was in good conditions in terms of access to a paved road to the city, safe haven, access to electricity and healthy water sources. Ranked first with a total beta of 0.7948, it laid the ground for improving the sustainable livelihood. On the other hand, the physical capital component remained in bad conditions in terms of the waste collection system, access to gas, transportation network, etc. However, the improvement of the physical capital conditions of the village is undeniable as compared to the pre-displacement conditions.
•An analysis of the correlation between the capitals and the sustainable livelihood has shown that the effect of physical capital was high, while the effect of natural, financial, and social capitals was moderate and the effect of human capital was poor. Based on the findings, the following results were obtained:•Since rural settlements act as a system, they always follow different trends in the components (sub-systems) when influenced by events (including resettlement policy). Within the scope of the study, the trends were not formed in the framework of the sustainable livelihood. In this regard, some capitals had more favorable conditions than others. This event has not been able to meet the needs of the studied villages, therefore, an integrated approach to the implementation of this policy is necessary.
•The orientation of the policy-making system towards the priority of environmental renovation in the displaced villages has provided the grounds for improving the conditions of physical capital.
•Paying attention solely to the needs of the villagers from the viewpoint of external factors and the lack of attention to the demands of the villagers as well as seasonal migrations has reduced the sustainability of livelihood from the social aspects.

Iran due to geological and geographic conditions, has always been exposed to various natural hazards. One of these disasters is the earthquake, which has caused significant damage to the country's economic and social complex. This issue is a serious threat, especially in areas with active faults and Every year, it brings about life and financial losses. Therefore, attention to the importance of locating and zoning of high risk areas in terms of having a hazardous hazard potential is essential and significant. Based on this, the present study uses a deterministic approach to determine the high risk areas of seismicity.
Study Area: The present study was conducted in Semnan city with an area of 11017.8 km2 From that is limited west to Garmsar city and Firooz Kooh district, east to Damghan city, south to central Iran desert, Nain city and Isfahan province, and north to Sari city in Mazandaran province, there have been. The maximum altitude of the city is 2065 meters and it was located at a minimum easterly distance of 52 degrees and 46 minutes and a minimum latitude of 35 degrees and 15 minutes. On the other hand, the population concentration of and unsuitable constructions in this province, indicates that the occurrence of such a major earthquake could be very dangerous. In this paper, seismic hazard analysis using definite method is performed for this area. For this reason, single faults and important fault systems in the region at first step, were identified using Landsat 8 satellite imagery using remote sensing techniques. In the next step, due to the geological and tectonic characteristics of the area, geological fragmentation and seismicity of the study area were investigated and were identified fault mechanisms and fault map was created in the Arc GIS software environment. Then, was calculated and averaged by using valid empirical equations, the maximum expected magnitude of the major faults in the region. Finally, by selecting several valid decreasing relationships, maximum severity and horizontal earthquake acceleration for the study area, calculated using a deterministic approach and the average of calculated values as the maximum intensity and ground acceleration associated with each fault was used to analyze the hazard of the study area. Result and Discussion: The results of study indicated that the maximum intensity of the earthquake was about 8 and the lowest of it was 5. Also, the maximum horizontal motion of the earthquake in the study area was 0.37 and the lowest value of it was 0.048. According to the results, the areas with low risk, medium risk, high risk and very high risk based on maximum values of earthquake severity form 17.45, 24.81, 33.62 and 24.10%, respectively. On the other hand, the areas with low risk, medium risk, high risk and very high risk based on the maximum values of the earthquake motion form 36.34, 29.77, 17.77 and 16.16 percent of surveying area of the region, respectively. Finally, in order to investigate the accuracy of the research, the results were matched with the instances of ground reality, and the results showed that there is a conformity between the results and the ground reality. This study concludes that most PGA occurs in the area with NW to SE trend, which fits very well with the area fault strike. The results of this study showed that the area of with high risk and very high risk with regard to population density was significant. It can be stated that the reason for the high risk of seismicity in the northern part of the city is the existence of active faults related to the quaternary period. There are several faults in the northern part of the city which among the biggest faults in this area is the Attari fault with a length of 85 km that which dates back to the Quaternary period and runs across the west to the east from the north of the city. This issue should be carefully considered by officials, planners, and engineers.

Modeling of land use change is largely a problem. Nevertheless, theoretical and empirical methods have increased in this framework, and studies are carried out on land use change in these areas. Few researchers are able to use models to predict land use variations (Iacono, Levinson, El-Geneidy, Wasfi., 2015).Generally, land use change is a deformation of a piece of land. This change is the foundation of the desired goals, and it is not necessary to have only a change in the coverage of the land. This change may be due to intensity change and management (Verburg, Chen, Soepboer, Veldkamp., 2000). Land use and land cover change is greatly worrying as it reduces biodiversity and impacts human lives as such (Geoghegan, Klepeis, Mendoza, Yelena, Chowdhury, Turner, Vance., 2001). There are a variety of methods for modeling land cover and land use change variations, which can be used to model mathematical equations, system model, statistical model, evolution model, cellular model, and hybrid model. The cellular model includes cellular automatic models (Parker, Manson, Janssen, Hoffmann, Deadman., 2002).An integrated model of automatic and chain cells (CA-Markov) is a combination of the Markov chain model (from the category of empirical estimation models) and the model of automatic cells (from the category of dynamic simulation models). In fact, by adding a spatial contiguity feature, this model simulates land use through a random Markov chain model for the next years. In recent years, due to the easy access to satellite imagery and the capabilities of the GIS, modeling of land cover change and its prediction for the future has been carried out, and many studies have been done in this field (Zare Garizi, Sheikh, Sadodin, Salan Mahini., 2012). Dezful is among the cities of Khuzestan Province, which suffered a lot during the eight years of the 'Holy Defense' in the Iraq war against Iran. The purpose of this research is to investigate the land use change in pre-war and post-war situations and predict the changes for the forthcoming years. In this study the Landsat 5 satellite images was used by Path No.166 and Row No.37 in 1985 before the war. The ETM+ Landsat 7 satellite images was used by Path No. 166 and Row No.38 in 2005 after the war. Satellite data was prepared in GeoTIFF format in seven spectral bands, which were not used from band 6 because of the low spatial resolution (60 m) and the failure to address the thermal properties of the phenomena in this study. In this study land use and land cover maps was used from Landsat images, and simulated land use change by using Marcov chain and cellular automatato in Dezful city. After cutting the satellite images according to the boundaries of the study area, the images were classified to determine the existing use around the region. Of course, by evaluating and analyzing the characteristics of the spectral reflection of different wavelengths, it was possible to separate the different classes of use. Using the IDRISI 15 software, classifying the images was used by using the controlled classification method and maximum likehood algorithm for the two years. This method, using the mean and matrix of covariance of educational data, provides a better analysis than other methods of classification, such as the classification of the smallest distance from image data(Richards & Xiuping, 2006). Finally, four classes of classification were identified, including the city and industrial facilities, agricultural lands, rivers and ranges for all images. Then, matrix of land use and land cover changes probability was calculated in IDRISI 15 software and the Markov method. In the matrix, the rows represent the older layers/cover of the older lands and the columns represent the newer enclosure classes. An automatic method was used to locate these changes and the map of the probability of the conversion of each land use was achieved for 2018-2030. The results of the classification of the images using the error matrix indicate that the accuracy of the overlapping of the classification for 1985 and 2005 was 99.6% and 99.5%, respectively, and the Kappa coefficient for both years was 99.99, which is acceptable at an appropriate level. The results of the classification of the images showed that in 1985, the total surface area of the region was about 1475.7 hectares covered by urban areas, while the non-urban lands constituted an area of 10555 hectares. In 2005, the area of urban areas was about 218.29 hectares, while the non-urban land was 12.91 million hectares. The results of the comparison of the two maps of the beginning and the end of the given period showed that during this period, 6172,200 hectares (about 87.8%) were added to urban areas and 1040.58 hectares (about 4.61%) were added to agricultural lands, which indicates the expansion of the region in urban and agricultural development during the postwar period. The probability of converting each of the cabrivals to another user in the years 2018 and 2030 was derived using the transmission probability matrix via the automatic network method. In the next step, the probability transformation matrix was obtained using Markov chain analysis based on observed changes in 2018-2030.By detecting land use and land cover changes, we can determine growth and destruction natural resources and mange them. Markov generally processes the future status of a system based on pre-model status. Coverage and usage changes from one time to another. The use of Markov analysis is the basis for estimating the likelihood of future system changes. In this type of analysis, a matrix of the probability of land use change is created from time t of time t+1. Based on the maps of land cover/land use obtained from satellite imagery (1985 and 2005) and the Markov model, the changes in the coverage/land use and urban growth rate were successfully simulated in the city of Dezful. In this paper, the analysis and prediction of urban growth and land use change were considered using remote sensing data and Markov chain analysis. Accordingly, in the years 2018 and 2030 urban lands will increase with an increase of 130.71 and 334 hectares respectively, and agriculture will be reduced to 320.22 and 273.24 hectares, respectively. In the period of 20 years, the residential lands increased and the agricultural land decreased. Simulation of land use change and land cover for the years 2018 and 2030 indicates a decrease in agricultural areas and an increase in urban areas. Dezful, like other cities of Khuzestan Province, suffered a lot during the eight years of the Holy Defense, but after that has started to grown and improved. Based on the results of land use planning and landslide modeling in Dezful, it can be confirmed that agricultural, rangeland and river utilization will be likely to decrease in the forthcoming years and land use will be further enhanced. Considering the growing human population and the urgent need to exploit the resources of these changes, But these changes must be taken into account in order to ensure that resource utilization is carried out in a systematic manner near future, and that it will not lead to the destruction of resources. Thus, with the development of sustainable development policies, the growing trend of urban areas will not reduce agricultural land and other limited lands in the future and transform them into lands built. Simulated user-mapped maps can be used as a system to alert the actions taken and their possible future effects in one area for other locations. Of course, this simulation is based on the current situation and the continuation of the future changes that may affect a series of changes in policies in a cross-sectional and specific manner, such as government policies in Mehr Housing and other cases. Using time-domain remote sensing data to identify changes and see how it was used in the past, and simulation of land cover and land use in the future can help planners and designers manage, plan, and apply developmental policies. In fact, the simulation and modeling of urban growth for the future is considered as the future management and planning requirements of the city. Since land use maps are of particular importance as the basic information for different planning, the results of this research can be used in the future planning of the region concerning its land use change.