Journal of Spatial Analysis Environmental Hazards
Year:2020 | Volume:6 | Issue:4|Papers Count:11

Nowadays, determining the effect of a climate change in the various aspects of human life is quite evident. In such a situation, it is very important to determine the base period, which determines the effects of a climate change than in this period. Choosing a course-based course plays an important role in choosing future courses to conduct research on the effects of climate change. Many researchers in the research use the LARS-WG dynamic downscale method or the statistical method to measure the weather variables, which should be the same for the years of the base period and the upcoming period. This research was conducted to select the appropriate base course for estimating minimum temperature, maximum temperature and precipitation at the synoptic station in Birjand. The station is located at latitude 32 degrees and 53 degrees east and 59 degrees and 17 degrees north latitude. In order to evaluate and accuracy of the methods in this research, seven criteria for estimating root mean square error (RMSE) and mean absolute error (MAE), relative error (RD), mean relative error of the month of the year (MRDM), average relative error of the month in the year (RDMM), PBIAS and RSR. In this study, using GCM models, we assessed the selected base courses for the synoptic station in Birjand. To doing in the research, an amount of 27 base courses from 35 models of the fifth report of the change were compared with similar periods obtained from the station in Birjand. The results showed about precipitation that the duration of the base periods such as 1960-2005 and 1960-2000 is less of the RMSE and MAE errors than the rest of the courses, and the base period of 1965-1990 between periods less than 30 years and the period The 1990-1960s are also well suited to the precipitation data of the synoptic station. The maximum temperature of the 1960-1990, 1960-1985 and 1960-1995 is the lowest RMSE error. However, short-term courses of 1980-1960 and 1965-1985 present satisfactory results. In the case of minimum temperatures, periods of 21 and 31 years 1960-1980, 1960-1985, 1960-1990 and 1965-1985 have a percentage error of RMSE and a lower percentage of PBIAS. Variable variation range can also be used to show the appropriate base course. The result showed that the periods 1960-2005 and 1970-2005 had a lower range of rainfall variation than the other variables and seems to be more suitable. However, courses such as 1990-2000, 1975-1995, and 1995-2005 have less certainty. The more courses that go into periods with shorter periods of time, the more modest and less certainty they will be. Also, if you look at changes in the 1975-2005 periods and the 1965-1995 periods, it will be clear how much each year towards the years closest to 2005 will be deducted from the precipitation daily average. The results also show that maximum temperature changes are better than precipitation, and all courses have less variation range. Nevertheless, the period of 1960-2005 has the highest degree of certainty and the period of 1975-2005 has the least degree of certainty compared to the rest of the courses. In contrast to precipitation, there are periods such as 1970-1990, which, if considered as the basis for research, provide more certainty than the longer period of 1965-2005 for maximum temperature. Also, what's most clear about the maximum temperature is the higher the period with years closer to 2005, the temperature increases, which will increase the temperature over time. The process of minimum temperature variations also indicates that in addition these changes are similar to the change in temperature, with the difference that the range of variations in the minimum temperature is somewhat higher than the maximum temperature. The period of 1960-2005 has the best degree of certainty and the period from 1975-2005 has the least degree of certainty than the rest of the courses. Although long periods of time are less certain than short periods, the result is that the longer the interval between periods increases, the more precise the results will be. The result is not entirely correct, 1975-2000 is less certainty than the 1965-2000 period and has better results in minimum temperatures. Therefore, the evaluation of selected periods of GCM models with similar periods from observations of Birjand station shows that for rainfall variables, periods with a number of years yield more satisfactory results, but for two variables the minimum temperature and maximum temperature of the periods, not long or short periods, provide less risk of RMSE and PBIAS than long periods.

Introduction Nowadays, Determining the effective factors on fire is so important, because the plenty areas of forests around the world are destroyed annually by fire and recurrence of that in the long term can irreparably damage to the earth and its inhabitants. It helps us to identify most dangerous locations and times in forest fire. Hence, we can prevent many of driving factors of forest fire by law enforcement, efficient forest management policies and more supervision. In the current study, we identified the effective factors on the fire in Golestan forest through integration of three different methods including multiple linear regression, logistic regression and multivariate adaptive regression spline with Genetic Algorithm. Study Area Golestan Province is in the North of Iran and 18% of it is covered by forests. Golestan Province is a touristic province and several roads pass through its forests and according to statistical records, most of the occurred fires were in proximity of these roads. Our study area is located in 36° 53′-37° 25′ N and 55° 5′-55° 50′ E and its area is about 3719. 5 km2. We selected this area, because includes the most of fires have been occurred in Golestan Province in recent years. Materials and Methods A big fire was occurred on 12 December, 2010 in our study area and we used it as the dependent variable. The actual burnt area and some other data, such as Digital Elevation Model (DEM), the roads network, the rivers, the land uses, and soil types in the area were provided from Golestan Province Department of Natural Resources. Also, geographic coordination of the synoptic weather stations near the area and their data, including maximum, minimum, and mean temperature; total rainfall, as well as maximum wind speed and azimuth in December 2010 were obtained from National Meteorological Organization of Iran. The land use and soil layers were in scale of 1: 100000 and the roads and the rivers layers were in 1: 5000 and all of them were provided in 2006. The region DEM is generated from topographic maps of Iran National Cartographic Center in scale of 1: 25000 with positional resolution of 30m and we produced the slope and the aspect layers from it in ArcGIS software with the same resolution. The roads and the rivers were in vector format, hence, we used the Euclidean Distance analysis to generate rasters that each cell of them shows the distance from the nearest road or river. At first we had 5 weather stations, which is very few for GWR. In this regard, we generated 1000 random points in the area and interpolated data to these points using Ordinary Kriging method with exponential semivariogram model in 30m resolution in ArcGIS software. The multiple linear regression (MLR) model is the generalization of simple linear regression that is modeling the linear relation between one dependent variable and some independent variables. The general formula of MLR is seen below: (1)The unknown coefficients are obtained using least squares adjustment as follows: (2)The logistic regression (LR) model is a nonlinear model for determination of the relation between a binary dependent variable and some independent variables. If we use the values of 0 and 1 for non-fire and fire points respectively, then the probability that a point be a fire point is obtained by Eq. (3): (3)If the number of parameters is insignificant compared to the observations, then we use the unconditional maximum likelihood estimation shown by Eq. (4) to compute the unknown coefficients of this model. (4)The multivariate adaptive regression spline (MARS) model is a flexible non-parametric model that requires no assumption about the relation between the dependent andindependent variables. Hence it has a high ability in determination of complex nonlinear relations among the variables. The general formula of MARS is seen below: (5) is the m’ th basic function that is obtained by Eq. (6): (6)These basic functions are chosen in such a way that leads to minimum RMSE of model. We use the genetic algorithem (GA) with the fitness function of the normalized RMSE to select the optimum combination of effective factors on forest fire. Results and Discussion In this paper we study the dependence of the forest fire to 14 factors shown in table 1, in the study area. Our results are shown in figures 1 to 3. Conclusion This research shows that both of the biophysical and anthropogenic factors have significant effects on forest fire in our study area. Just two factors were identified as impressive factors in all three cases including the minimum temperature and the maximum speed of wind. This study concluded to the NRMSE=0. 4291 and R2=0. 9862 for the multiple linear regression, NRMSE=0. 9416 and R2=0. 9912 for the logistic regression and NRMSE=0. 1757 and R2=0. 9886 for the multivariate adaptive regression spline and totally the multivariate adaptive regression spline method showed a better performance in comparison to the other two methods.

Sultry phenomenon occurs due to the combined effect of high temperature and humidity. Sultry intensity increases with increasing relative humidity and decreases with decreasing temperature. This phenomenon has a tremendous impact on comfort and other human activities. Various indices have been used to study this phenomenon in Iran and in the world. According to previous studies, and as far as information is concerned, there has not been a comprehensive study across Iran on the characteristics of sultry days based on degree of severity. Therefore, the purpose of this study is to investigate the frequency, duration and severity of sultry days and its temporal and spatial analysis throughout Iran. To do this research, daily temperature, relative humidity and partial water vapor pressure of 101 synoptic stations were used for a 28-year period (1987-2014). In choosing the indices of sultriness, the goal was to select indices that show the sultry state on a daily scale. For this purpose, in the first stage, 16 empirical sultry or sultry-related indices were used, all of which used climatic parameters such as temperature, relative humidity, water vapor pressure and cloudiness to calculate the sultry state or comfort. Among them, 13 indices were eliminated because they surveyed the phenomenon on a monthly or annual basis or were not consistent with the objectives of this study. Finally, according to the objectives of the study, three indices were chosen: 1-Sultry Intensity Index (Lancaster-Carstone empirical equation), 2-Partial Water Vapor Pressure Index (partial water vapor pressure equal to or greater than 18. 8 hPa), and 3-Heat Index (HI). The results of this study showed that two indices of Sultry Intensity and Partial Water Vapor Pressure are suitable for explaining the conditions in Iran and their outputs are not significantly different. But Heat Index did not lead to desirable results. According to the results of the Sultry Intensity Index, the sultry phenomenon is not comprehensive in the country and is limited to 21 stations adjacent to the Caspian Sea coasts in the north (besides Parsabad Moghan Station) and the Persian Gulf coasts (besides Ahwaz station) and the Oman Sea coasts in the south. In other parts of the country, due to their internal and leeward position, being away from moisture sources, poverty or lack of vegetation and insufficient penetration of wet and rainy systems, there is no sultry condition and, on average, even one day is not seen with sultry circumstances. On the southern coasts, on average, sultry conditions begin on April 3 and end on November 16. Therefore, in this area, 7 months and 11 days of the year have sultry conditions. This is natural due to the lower latitude and the Azores high pressure sovereignty in the south. But on the northern coasts, the sultry period is shorter and with a 48-day delay compared with the southern coasts, the average sultry day begins on May 22 and ends on October 12. Therefore, the duration of the sultry period is on average 4 months and 19 days. In terms of the number of sultry days, the most frequencies belong to the southern coasts stations. The largest number of sultry days related to the Chabahar port on the coasts of the Oman Sea with 291 days, followed by Jask port with 264 days. The lowest number of sultry days is also from Ahwaz station with 1 day and then Mahshahr port with 42 days. Among the stations on the southern coasts, the Oman Sea stations compared with the Persian Gulf stations have more sultry days due to lower latitudes, Azores high pressure sovereignty and Southeast Asian monsoon moisture influence. In contrast, the number of sultry days on the northern coasts is much lower and averages 140 to 150 days a year. Sultry severity is also less, so that there are no extreme severe sultry days in any of the stations on the northern coasts. But the number of extreme sultry days is remarkable on the coasts of the South, to 160 days in the port of Chabahar and 111 days in the port of Jask. At Parsabad Moghan in the north and port of Mahshahr in the south, due to distance from the coast and lack of sufficient moisture, the duration and severity of sultry is much lower and there are basically no days of severe and extreme sultry states. The annual trend of the number of sultry days at any station is not significant.

Iran has seasonal rivers because of dry climate, low rainfall and different topography. These river-valleys have main role in forming, genesis, and sustainability of human settlements and provide different ecological services. The main services include beauty, store of green spaces, water supply, reduce and create temperature differences, local air flow and natural ventilation which are part of the functions. Tehran is roughly the same area as 730 square kilometers and its population is 8. 7 million people. It is located in51° and 17´ to 51° and 33´ east longitude and 35° and 36´ to 35° and 44´ north latitude. The height of this city is 900 to 1800 meters. The north and north east of this city are located in peculiarity range of the southern part of the middle Alborz. This city includes 7 river valleys to the names Darabad, Golabdareh, Darband, Velenjak, Darakeh, Farahzad and Kan. The ecological role of these river valleys is reduced because of non-ecological axis developmental interventions by urban management and citizens. These interventions have changed river valleys to high risk space of skirt movements and flood. Kan is the most important river valley because of the breadth of the basin and permanent water discharge rate. The part of this river valley has changed to park (Javanmardan) by municipality. The purpose of this research is that to provide factors and criteria of ecosystem based management to organize this river valley. ANP has been used in this research. To use this method for analyzing factors and criteria of ecosystem based management to organize this river valley, firstly, these factors have been identified by library studies and scrolling. These factors include 4 criteria (natural: 15 sub criteria, social: 3, management: 6, economic: 2). the books, journals, reports, maps, aerial photos, satellite images and internet sites have been studied in library studies. In site studies, some information from library studies have been edited. After that, the findings of these two methods in form of questionnaire called factors and criteria of ecosystem based management to organize Kan River valley, was in charge academics and professionals. They were elected among pundits of urban management science, urban planning, geography and environment in Tehran. At first the number of them was 30 people came to agreement in two process about 4 factors and 18 criteria and determined importance and priority by Delphy method. Findings in Delphy method were analyzed through ANP and SUPER DECISIONS. In this process, firstly, a conceptual model and relation inter and intra clusters and nodes determined. These relations in this process are very important because paired comparison depends on this process. Assumption of equality of effects and similar relations in these factors is illogical because there are the grading of effects and relations in this research. Second, the factors have been compared to each other to create a super matrix based on paired comparison. Generally, in this process decision makers compare two different factors to each other and paired comparisons have grading of between1to9. In double-sided valuation, each factor is used to show initial inverse comparison. Inconsistent rate in paired comparison must be less than 0. 1 like AHP. Third initial super matrix is created. It is the weights created from paired comparison and identified the importance of each factor in each cluster. Forth, the weighted super matrix was created. The weights of clusters was calculated in this process to identify the weight of final super matrix. Fifth, limited super matrix was created. The weighted super matrix reached for infinity band each row convergenced to a number and that number was the weight of factor. By this way limited super matrix was reached. Based on ANP and table 1, management: 46%, natural – ecological: 26% and economic and social factors: 14% are important respectively in ecosystem based management to organize Kan River valley. Based on reached results, inconsistent rate is 0. 003 and it shows that the weight is valid and review is not necessary. Among sub criteria in management factor, organizational pattern: 32%, method of management: 23% and policies: 21% are the most important respectively in ecosystem based management to organize Kan River valley. Among sub criteria in natural-ecological factor, flood, domain movements and building and texture of soil are the most important respectively 23%, 18% and 11. 5% also in social factor, participation, security and public trust have the importance respectively equal to 49% 31% 19%. In economic factor, environmental assets and stakeholder’ s economic participation have the same importance. Based on this research, management factor (organizational pattern and the method of management) is the most important in ecosystem based management. But this approach, the management pattern and intervention to organize this river valley, need comprehensiveness and integrity of the subject (nature, society, management and economic), purpose (protection, resuscitation and use), factors (government, city council, municipality, private sector and people), duties (policy making, planning, designing and perform), method (collaborative), tools (knowledge, skill, rule, program, budget, machinery and materials) and management domain. Use of these factors and criteria need some infrastructure and reforms. The most important reform is reform of management structure, production of subject matter and topical program special to organize river valleys by ecological approach to release Kan of loading and contradictory grabbing. so this management can follow protection, resuscitation, sustainable use and continuity of ecological services.

Iran is located the spatial geographical position in the south of the temperate region and north of the tropical region between the northern latitudes 40 to 25 degrees north and 65-44 degrees eastern along the seas, oceans and warm and great desert, on the other hand, with complex topography in the Alpine-Himalayas mountain belt (the world's largest mountain belt). These conditions have caused the climate of Iran to experience a variety of the prevailing natural hazards (33 of 43 world-wide risks). One of the natural hazards is the drought that happens over the Iranian plateau since the distant past, with the name of Dave of Drought, and so far. The Iranian plateau has undergone various drought periods over the past decades and various civilizations have faced this risk, and some of the Iranian ingenuity and management have emerged about this risk of the Iran. These include qanats, reservoirs built on commuter routes and cities, historical gardens, and so on. Today, this risk is dominant over the Plateau of Iran every year, and with increasing population and growth in different sectors and, in some cases to mismanagement, followed by a larger crisis called the water crisis and the crisis Economic-social, immigration, and so on. So, given the importance of the subject, different researchers have studied different aspects of this hazard. The fact is that in the past few decades, with the advent of computers and software and data, research has become easier and more scientific, naturally, in Iran, with these tools and data, researchers has been done on different parts of the crisis. What was the achievement of these studies, and most importantly, did the researchers contemplate a practical solution to the crisis on the Iranian plateau? This study provides an overview of past studies of drought and their achievements over the last few years. In this study, used Four hundred and three of scientific articles were published in various journals to termed "drought" in the article titled of scientific information database (SID), one of the most important sources of internal research in Iran. The distribution of the time of research and distribution of various scientific fields that investigated the drought was identified. By studying the articles and the results from them, we found that 384 scientific articles with a specific output. Based on these findings, the frequency of articles in different fields of study was determined and analyzed. researches of drought in the past years (1379 to 1391) had increasing trend and since 1394 has been decreas in Iran. The most drought research has been done in agricultural sciences with 166 papers from 403 papers (41. 2%), geographic sciences with 118 papers (29. 3%) and Medical and basic sciences and engineering sciences have the least research, 0. 2, 2 and 5% respectively. 78% of the studies have examined the drought in different parts of Iran And 11 percent of the articles evaluated the consequences of this phenomenon. 7% of drought studies have predicted this phenomenon with different statistical models and 2. 5% and 2% are dedicated to drought management and zoning in different regions of Iran respectively. Most drought studies hase been in Iran, Khorasan, Fars, Sistan and Baluchestan, Tehran, Isfahan and Kermanshah, but in other parts of Iran, studies have also been conducted in different regions. Therefore, the drought phenomenon has been studied in all regions of Iran and drought assessments have been carried out. The reduction of drought researches in recent years suggests that quantitative and qualitative research has been carried out in this basin before 1395, and drought has been studied and evaluated with different indicators in different regions of Iran. The reality of Iran's climate and research shows that every part of Iran experiences a drought phenomenon, which is an Inherent characteristic of the climate of Iran, that given the geographical location and atmospheric patterns affecting these latitudes on the planet. The consequences of drought have also been reflected in different parts of the environment, social, economic, and so on. As part of the newspapers has indicative of the damage to this climatic phenomenon in recent years. It seems that the dominant section of the phenomenon is associated with the unconscious and real perception of managers and people of this phenomenon (which has a cultural root). At present, the consequence of severe and droughts in recent decades is the lack of proper planning and environmental degradation and crisis in various parts of Iran's environment. On the other hand, the negative consequences of global warming for the climate of Iran and similar climates are more and more worrying. Therefore, it is essential to take practical and practical solutions instead of evaluations and mere studies. The practical solutions and the production of technology and operational program in relation to these environmental crises require group research in the sub-sectors with together. While, for example, engineers play the most role in controlling superficial fluid (water and dam), But the smallest drought-research related in this area. Therefore, the separate study of each part of these hazards is merely an evaluation and is not a practical way of solving the risk for managers and planners; For example, a water crisis requires a team of researchers such as hydrology, climateology, meteorology, agriculture, urban management, rural, etc. Of course, it should be noted that our researchers have not been trained and not accustomed to group work, and the idea of teamwork is poor in our culture; But there is no way and should start from one point. Perhaps we should start with kindergartens and elementary schools in order to find suitable solutions for at least the next 20 years, researcher’ s teams. Finally, it is necessary to address the sustainable development and drought, localization of indicators, operational and management plans based on the environmental capabilities and knowledge of the native area of each region.

Floodplains and adjacent rivers are always at risk from flood events due to their specific circumstances. Flood prone area identification in the watersheds is one of the basic solutions for destructive flood control and mitigation. Flood mapping is one of the best methods for flood prone area planning and identifying. Considering the importance of fl ood hazard, it is important to understand the role of uncertainty and incorporate that information in fl ood hazard maps. The hydrodynamic modeling approach is suitable for accounting various uncertainties, and thus lends itself to creating probabilistic fl oodplain maps. For this purpose, flow boundary conditions, peak instantaneous discharge with different return periods, cross sections and their distance and roughness coefficients for each cross section were entered to HEC-RAS hydraulic model in Kaan watershed located in the Tehran province, Iran, and this model was then run and flood water surface profile at different return periods were estimated. In the Kaan Basin, most residential and agricultural lands are located in a very small distance from the river bed. The rapid growth of construction, human activities and land use change in the downstream of the basin have caused a change in the hydrological cycle and runoff production. Floodplain mapping using hydrodynamic models is diffi cult in data scarce regions. Additionally, using hydrodynamic models to map fl oodplain over large stream network can be computationally challenging. Some of these limitations of fl oodplain mapping using hydrodynamic modeling can be overcome by developing computationally effi cient statistical methods to identify fl oodplains in large and ungauged watersheds using publicly. The aim of this study is to determine flood areas within 20 kilometers of the Kaan River by using the HEC-RAS model and Arc GIS software to identify flood lands in different return periods. The Kaan basin is located in the central Alborz Mountains. This basin is limited to south, north, east and the west respectively to Tehran, Jajrood Basin, Darakeh Basin and Karaj River Basin. The most important River in the area is the Kaan River and originated from high mountains. Most commonly, the hydrodynamic modeling approach is used to create fl ood hazard maps corresponding to a rare high fl ood magnitude of 100-year return period or higher. Although this approach can provide very accurate fl oodplain maps, it is computationally demanding. As a result, the modeling approach to fl ood hazard mapping works well for individual streams, but its effi ciency drops signifi cantly when used to map fl oodplains over a large stream network. In this research, floodplain areas in the Kaan basin in return periods of 2 to 20 years are determined using the HEC-RAS model and the HEC-geoRAS extension. For this purpose, digital maps 1: 25000, DEM (10m), discharge values of Sulaghan Station, morphological characteristics of the river bed and cross sections have been used. Digital Elevation Models (DEMs) play a critical role in fl ood inundation mapping by providing fl oodplain topography as input to hydrodynamic models, and then enabling the mapping of the fl oodplain by using the resulting water surface elevations. Finally, the data is entered into the HEC-RAS software and analyzed. After determining the flood ranges in the various return periods at each cross-section, enter the results to the Arc GIS software and the flood zoning maps were obtained. In this research roughness coefficients (Maning, s coefficients) for each cross section were obtain be the n= (nb+n1+n2+n3+n4) m (Eq. 1) Geological map and field observations have shown that the main difference between the widths of the valley in the study area is related to the type of rock. The results of the hydrodynamic model show that in the river upstream, the increase in discharge had led to the water level increase and expansion in the floodplain surfaces. But in the middle and low slopes in the downstream of the river, due to the reduced discharge, the river has a larger lateral extension and the flood areas are larger than the upstream of the river. Also, for a longer period of return, the discharge rate and the water level increase and the flood plain was more extensive. The results show that in the downstream of the basin due to instability the bed, existence of wide and eroded chanels, high ability in sedimentation, erosion of the channel bed, and low impact of vegetation, this section They can be restored and regenerated and constantly changing. Due to the location the Tehran-North high way from the Kaan basin, had the construction of roads and structures, the flood plain areas of the river should be fully observed or retrofitted.

Among the important challenges facing water resources of the country, one can mention the phenomenon of climate change and its impacts. The General Circulation Models (GCMs) can provide the best information about the response to increasing the concentration of greenhouse gases. Since the outputs of this model do not have sufficient time and space accuracy for studies on the effects of climate change, the output data of small general circulation models need to be quantitative. In this study, the SDSM statistical magnitudes and the CanemS2 model for climate change assessment, which are presented in the fifth report of the IPCC Comes under three scenarios RCP2. 6, RCP4. 5 and RCP8. 5. The daily minimum temperature, maximum and precipitation rates of the synoptic station of Shahrekord (Cold mountain region) and Bandar Anzali (very humid and temperate climatic zone) are utilized and the parameters are for the period of 2040-2011, 2070-2070, and 2071-2099. Is. The results of the study show that the SDSM model has high accuracy and high efficiency in the climatic zone of very humid and temperate (Bandar Anzali) relative to the cold cliff (Shahrekord). However, the model has an acceptable ability to simulate the parameters in both areas. Under all three scenarios, RCP will experience the minimum and maximum temperature and precipitation in both climatic zones in all three times, but the cold climatic zone will be more affected by the climate change phenomenon.

One of the natural hazards of the collapse of rocks from the foothills of the mountains, causing great financial losses and loss of life. Especially when it comes to the path of communication. The rock fall is a rapid movement of a mass without cohesion in the powder or a mixture of soil and rock, so that the initial construction is not discernible, the level that occurs along that rupture it is often unclear. The falling stones of a mountain depend on several factors, which have the natural origin or origin of human origin. Natural factors influencing the fall can be rock factors, slopes and altitudes, geological structure, fault and slope of the geological layers, rainfall and temperature changes distance from the river, etc. human factors can also be referred to as road, land use and mining, destruction of vegetation, etc. in Iran, the collapse of rock parts on mountain roads causes massive loss of life and financial damage. Therefore, it is necessary to identify and classify the roads in terms of risk of suitable methods. In the north west of Iran it has mountainous topography and due to the state of tectonic and its seismic and climatic conditions, suitable conditions for landslide are provided in some domains. So, due to the fact that the area studied in the mountainous north-west region and the possession of all the crumbling conditions are very prone to collapse. The research method is applicable in terms of practical purpose and the process of doing work on a combination of library and field methods. In this study, it has been used to determine the prone areas of collapse and zoning of anp models and frequency ratio. Two models that differ in terms of process and mechanism. In order to organize the research framework, first, a field study of the study area has been studied and the mathematical position of falling points is recorded with gps. Then, in order to model the mentioned models, the layers of GIs for the shape of the Georeferenced and digital were prepared. to provide the zoning layers of geology, slope and Aspect, elevation levels, land use and vegetation, fault, and land cover maps, annual temperature and precipitation, distance from the road, distance from the stream were used. The 20 m x 20 m contour line were originally prepared using the topography map of 1: 25, 000 in the ArcGIS environment. Then, the contour line and Dem of the area were constructed. The slope and Aspect maps, elevation levels, Isothermal and isohyet map frost and stream network were created via Dem and meteorological data. Geological map and fault map were created using digital map 1: 100, 000 Zanjan and map and vegetation map and road distance using Landsat 8-2017 OLI and ArcGIS images. To produce linear layers, the Distance function was used. Using the statistical method, the frequency ratio and the network analysis method are using the landslide hazard zonation using the statistical method, the frequency ratio and analysis of network analysis to zoning the risk of falling by combination and sum of maps in class were low-risk to very high. From the tangible results of this study, the relationship between slope maps, elevation levels, rock material, Isothermal and isohyet is done. So that each side of the road had operated on the five factors that had happened. With regard to the output of the maps, the risk zones were high to very high for ANP models 14/17, 35/27 and FR 02/6, 35/14 percent. Ranges from high to very high with slopes between 40 and 80 percent and Sedimentary formations such as sandstone, siltstone with tuff layers, elevation levels 1, 500 – 2300, Southern and Eastern slopes, Distance between 0 and 500 faults, Road and stream have adaptations. The changes in the percentage of area in both models show despite the difference in the size of the risk zones, Follow a similar process. To assess the zoning accuracy of these methods, two sets of quality and accuracy index (experimental probability) were used. The evaluation of the models showed that in the network analysis model, the indexes were 0. 76 and 0. 88, respectively, that the relation of frequency ratio coefficient model had optimal quality and accuracy. In this research, various factors influencing the occurrence of rock falls on Zanjan-Taham-Tarom road were investigated. From there, mass movements such as rock fall on the roads act as a system, as a result, all factors play a role in the occurrence of such phenomena. But some elements have a more vibrant role. In the studied area, among the factors affecting lithology, slop, elevation levels, precipitation, temperature changes, number of freezing days and distance from the road and land use are more than other factors in the occurrence of rock fall. Assessing the quality and accuracy of zoning maps while confirming zoning accuracy showed that the network analysis method has better performance. The risk of collapse on Zanjan – taham-tarom road is always exists. Therefore, we need to use sustainable methods to reduce the risks. Domain stabilization methods are generally done in the form of mechanical, biological and bio-mechanical which, according to the long course of the road and the duration of the road, Mechanical methods such as unloading, embankment, drainage, use of separation walls as well as the use of net Grid are suggested.

Flood is considered as one of the most destructive natural disasters worldwide, because of claiming a large number of lives and incurring extensive damage to the property, disrupting social fabric, paralyzing transportation systems, and threatening natural ecosystems. Flood is one of the most devastating natural disasters causing massive damages to natural and man-made features Flood is a major threet to human life (injure or death of man and animal life), properties (agricultural area, yield production, building and homes) and infrastructures (bridges, roads, railways, urban infrastructures). The damage thet can occur due to such disaster leads to huge economic loss and bring pathogens into urban environments thet causes microbial development and diseases Therefore, the assessment and regionalization of flood disaster risks are becoming increasingly important and urgent. Although it is a very difficult task to prevent floods, we can predict and compensate for the disaster. To predict the probability of a flood, an essential step is to map flood susceptibility. The methodology of the current research is includes the following steps: Flood inventory mapping; Determination of flood-conditioning factors; Modeling flood susceptibility and its validations. Et first, 146 flood locations were identified in the study area. Of these, 102 (70%) points were randomly selected as training data and the remaining 44 points (30%) cases were used for the validation purposes. In the next step 1 flood-conditioning factors were prepared including geology, landuse, distance from river, soil, slope angle, plan curvature, topographic wetness index, Drainage density elevation, rainfall. Then, the probability of the flood occurring for each class of parameters was calculated. Et the end, the obtained weights for each class in the Geographical Information System (GIS) were applied to the corresponding layer and flood risk map of th studied region was prepared. Subsequently, the receiver operating characteristic (ROC) curves were drawn for produced flood susceptibility maps. To determine the level of correlation between flood locations and conditioning factors, the FR method was used. The results of spatial relationship between the flood location and the conditioning factors using FR model is shown in Table 2. In general, the FR value of 1 indicates an average correlation between flood locations and effective factors. If the FR value would be larger than 1, there is a high correlation, and a lower correlation equals to the FR value lower than 1. The analysis of FR for the relationship between flood location and lithology units indicates thet Cenozoic group has the highest FR value. In the case of land-use, it can be seen thet the residential areas and agriculture land-use have values. One of the most important factors affecting the flood is distance from the river. The results showed thet the class of >500 m FR was the most effective one. The analysis of FR for the relationship between flood location and slope angle indicate thet class 0-6. 1 has the highest FR value. In the case of slope aspect, flood event is most abundant on flet and East facing slopes According to the analysis of FR for the relationship between flood location and plan curvature, flet shape has the highest FR value., A flet shape retains surface run-off for a longer period especially during heavy rainfall. Flood locations are concentrated in areas with a TWI >6. 8 drainage density > 4. 6 km/km2 and altitude classes of 1200 m. In the soil layer, the tallest weight is from the earth with a small transformation of gravel. Finally, the maximum weight is the maximum rainfall. In this study, all parameters of WofE model were calculated for each conditioning factor. In the lithology unit, the Cenozoic class has the highest flood susceptibility. Among the different land-use types, agriculture categories had the highest values. The distance from the river from 0 to 1000 m indicated positive influence in flooding, while the areas more than 1000 m or far from the river represented the negative correlation with flood occurrence. In the soil layer, clayey soil and tuberous soil had the highest weight. The analysis of WofE for the relationship between flood occurrence and slope angle indicated thet slope angle from 0 to 6. 21 had positive influences in flooding. In the case of slope aspect and plan curvature, flet area had a strong positive correlation with flood occurrence. Effectiveness increases wit increasing TWI classes. The results of drainage density indicate thet areas with higher drainage densities are more susceptible to flood occurrence. By increasing the height of the flooding reduced sensitivity classes. byn flooding rainfall and flood events increased with increasing rainfall. The prediction accuracy and quality of the development model were examined using the area under the curve (AUC). Specifically, the receiver operating characteristic (ROC) curve was used to examine the basis of the assessment is true and false positive rates. So the results showed thet based on the area under the curve, the FR and WofE models show similar results and can be used as a simple tool for verifying the map prepared for flood sensitivity and reducing its future risks. Floods are the most damaging catastrophic phenomena in the worldwide. Therefore, flood susceptibility mapping is necessary for integrated watershed management in order to have sustainable development. In this study, flood susceptibility zones have been identified using FR and WofE methods. Et first step, a flood inventory map containing 146 flood locations was prepared in the kermanshah Province using documentary sources of Iranian Water Resources Department and field surveys. Then, eleven data layers (lithology, landuse, distance from rivers, soil texture, slope angle, slope aspect, plan curvature, topographic wetness index, drainage density, and altitude) were derived from the spatial database. Using the mentioned conditioning factors, flood susceptibility maps were produced from map index calculated using FR and WofE models, and the results were plotted in ArcGIS. Finally, the AUC-ROC curves using validation dataset were prepared for the two models to test their accuracy. For this reason, of 146 identified flood locations, 102 (70%) cases were used as training data and the remaining 44(30%) was used for validation. The validation of results indicated thet the FR and WofE models had almost similar and reasonable results in the study area. Based on the overall assessments, the proposed approaches in this study were concluded as objective and applicable. The scientific information derived from the present study can assist governments, planners, and engineers to perform proper actions in order to prevent and mitigate the flood occurrence in the future.

Human health is influenced by weather variables in all circumstances, including atmospheric pressure, humidity and temperature around them. Based on climate hazard and climate changes, different parts of human life and economic and social strategies such as health, hydrological pollutants And agriculture had a profound effect, including the discussion of the effects of thermal stress on human health over the last few decades, and has become a major issue in the world's scientific circles. Heat and cold stresses, the exposure of humans to extreme heat and cold, are part of the extreme events, often encountered by people during daily activities or in the workplace, and affecting human physical activities. It is important that, if the body is not cooled through transpiration or cooling mechanism, severe deaths are inflicted on human health; therefore, the person has to reduce his activity in order to reduce the adverse effects of heat stress. Hence, many researchers consider the thermal stress component more important than other components in assessing human health. In this study, using the physiological equivalent thermometer of PET thermal stress assessment and zoning of human thermal physiological stresses in Iran, with the length of the common statistical period from 1959 to 2011, and for the arsenal of thermal physiological stresses of Iran Forty stations have been used as representatives of Iranian cities. To calculate the physiological equivalent thermal temperature, all the effective meteorological elements in the human energy bill are measured at an appropriate height of climate biology, such as 1/5 meters above the Earth's surface. Data on climatic elements are provided by the Meteorological Organization of Iran. In the absence of data for some courses, linear regression method was used to reconstruct these missing data. After calculating the indices, the frequencies were also monitored and finally, using the GIS technique, the Kriging method of the study area was based on the frequency of occurrence of the indicators. Therefore, in order to achieve the results and objectives of the present study, software such as SPSS for data normalization as well as missing data was analyzed and analyzed using Ray Man's model based on meteorological elements to calculate the equivalent thermal physiological temperature of humans. Also, using the GIS software and Ordinary Kriging method, the best interpolation method was used to zon the human cysiological stresses. Today, in the planning of human health and comfort, the study of the physiological thermal stress plays an important role. In this regard, weather conditions can be used in the long-term planning of climate and in the short term planning of atmospheric conditions. In the present study, using the thermophysical Thermal Equivalent Thermal Index (PET), the climate climatic Atlas of Iran was prepared on a monthly basis. Calculated values for 40 stations in the country with a total statistical period of 52 years (1959-2011) were prepared. The results of this study showed that the spatial distribution of the physiological equivalent thermal temperature index in the country follows the altitudes, roughness and latitude. Accordingly, the low values of the indicator, which relate to the stresses of the cold, are consistent with the high and mountainous regions as well as the high latitudes, and vice versa, the thermal stresses occur in low and low elevations, as well as low latitudes, which of course, severe heat stresses occurred in the summer. Because throughout this season, the entire country of Iran is dominated by high tidal altitudes at high and low levels of ground pressure (1000 hp) with its warm and dry air, causing extreme heat and The term effects of heat waves on humans, heat loss, thermal contraction of the muscles and skin dryness, infectious or skin diseases, inflammation, sunburn, dizziness, fatigue, and mortality due to an increase in allergies can be mentioned. Significant differences in the environmental conditions of the mountainous masses of Kerman, Yazd and Sistan and Baluchestan provinces with their surrounding areas or low and low northern areas, and especially the Moghan Plain and Sarakhs plain, located in the upper latitudes of the country The issue is that the role of elevation in spatial distribution of the country's climate is much more colorful than factors such as latitude and longitude. The results of the analysis of the monthly thermal physiological stress maps showed that in terms of the area without tension, the march of the month with 47/8% of the area (778424/2km2) is in the first place and has the most favorable environmental conditions, The moon with 43/5 percent of the area (709275/2km2) is in the second position and also in March with 22. 6 (359128/9km2) in the third, August and the last month. The highest thermal stresses (29