Classifying daily climate circulation patterns has always been considered by climatologists. Investigating climate changes such as rainfall and the temperature in a same single time and place suggests that these changes are strongly influenced by atmospheric circulation patterns.
Regarding so, climate changes, known as variables here, such as rainfall, temperature, and other related phenomena, which are exemplified as flood, drought, glacial, and etc. are associated with special types of climate circulation patterns. The continuity and alternation of the systems are classified or identified climatically, therefore weather classification system is one of the main objectives of the synoptic climatology (Huth, 1996). Since every weather type creates its own special environmental condition, lack of identification in weather type frequencies leads to a difficult environmental explanation and alternation (Alijani, 1380: 64).
Identifying atmospheric circulation patterns different things that can be expressed inductively such as frequency, intensity, and spatial distribution of climate changes in rainfall and its physical causers (VicenteSerrano and LopezMoreno, 2006).
Heavy rainfall in many watersheds, particularly in the basin and sub-basin which involve less time exposure, causes floods and it also damages human, natural resources, infrastructure utilities and equipment. Before the occurrence of this kind of rainfall, it requires a deep understanding of the synoptic systems of their creator. This understanding is only possible through the classification and identification of rainfall patterns which used to cause floods in the studied basins.
The present study also aims at identifying and classifying the synoptic patterns of rainfall during the statistical stage of the study in the basin which caused flood in Taleqhan basin.
Taleqhan basin with area of (65/1242) per square kilometers is located in "36֯, 5', 20" to "36֯, 21', 30" north latitude and "50֯, 36', 26" to eastern longitude "51֯, 10', 18".
The study area is 120 kilometers away from North West of Tehran and located in a relatively high mountainous area in Alborz Mountain. This area is ranging from 1700 meters to 4400 meters above sea level. Average rainfall in this basin ara is 515/16 mm and its annual temperature fits 10.5 centigrade. About 79 percent of rainfalls occurs from the cold weather period in November to March. It is also know as semi-humid cold weather based on the De Martonne classification.
Circulation algorithm (CA) and pattern clustering algorithm (PCA) were determined based on the daily methods in synoptic scale by applying information from stations in Taleqhan basin (Gateh deh, Dehdar, Dizan, Snkranchal, armouth, Ange, Joostan, Zidasht). In order to classify the weather type, daily average rate of 500 HPa and the sea level pressure (SLP) were extracted and reconstructed over the period (1980-2011) at the 2.5 degree of NCEP. Selected range includes 608 points from latitude of 10 to the 60 of northern degree, and latitude of 10 to 80 of eastern degree.
Principal components method mixes the interrelated points and reduces the matrix size, so 13 main components are remained that they includes 93 percent of the total variance. This study employs S array and Varimax rotation to identify different types of weather. It also makes use of K-Means clustering method to classify daily weather types. And finally, a matrix was formed in 118×608 dimension for 118 common days of rainfall among stations. All days were divided into four groups. They offer the most common climate circulation patterns in the proposed area. At the end, and finally integrated maps of sea level pressure and 500 HPa were drawn for each weather type.
According to the results from factor analysis, 13 main elements were selected that they included 93% of the total variance of the data. According to the above mentioned method, all days (118 days) during the statistical period (1980-2011) were divided into 4 groups which provide the most climate circulation patterns in the study area. Then, integrated maps of sea level pressure and 500 HPa range were drawn for each of the types. Clusters were numbered according to the K-Means arrangement, and they were named based on the pressure patterns and the way circulation lines were ordered.
The classification shows two different resources for rainfall in this basin.
A: Those rain systems that are entered to the country from the West and South affect this basin. These systems humidity are caused by the Red Sea, the Mediterranean sea, the Black Sea, and the Atlantic Ocean. (B) Some parts of the Caspian coast rainfalls and the northern part of the Alborz mountain that has received their humidity from the Caspian Sea and it has infiltrated northern high-land, causes the rainfalls. It enters the basin from the wide valley of Sefid Rood. According to the rainfall measuring stations data, the least rainfall area is in western, which includes low-land areas. And the most rainfall area is its northern east. Rainfall in this area, in terms of rainfall time distribution in a year, is the Mediterranean. It does not involve a complete dry climate in summer and it takes 3 to 4 percent of the total rainfall. Rainfall in the basin, respectively, is distributed in winter, spring, fall, and summer.
Dust particles are important atmospheric aerosol compounds. The particles are resulting performance of strong winds at the soil surface desert areas. Sources of dust are 2 types: 1- Natural Resources 2- Human Resources. Iran is located in the desert belt which this problem cause increased the frequency of dust storms, especially in South East (Sistan) and South West. China Meteorological Administration Center classifies storms based on particles type, visibility and speed storms to 4 kind: Floating Dust, Blowing Dust, Sand/Dust Storm and Sever Sand/Dust Storm. In general, the effects of dust storms in 7 of Environment (particles into remote areas, the effect of dust particles on the material, climate, oceans and deserts), public health and health (increase of respiratory diseases , cardiovascular problems, digestive, eye, skin, reduced hearing, infections, reduced life expectancy and premature death, etc.), economic (unemployment, road accidents, damage to communication lines, air, land, sea, increase water turbidity in water utilities, creating uncertainty for all economic activities, etc.), Agriculture and Livestock (negative effect on the growth of plants and animals, reduced productivity and diversification, intensification of plant and animal pests and diseases, rising costs maintenance of livestock, etc.), socio-cultural (poverty and the loss of local jobs, destruction of subcultures, rural migration to the cities, closure of educational premises, industrial units, services, etc.) and military-security (disabling weapons, food and beverage contamination, the threat of sensitive electronics and power transmission systems, and reduce the useful life sitting on warehouse equipment, logistics cargo weight gain, etc.) can be evaluated. One way to identify, evaluate and forecast dust storm modeling. Dust cycle consists of 3 parts, dust emissions, dust and subsidence transfer dust that can be simulated by models.
In this study using the WRF_Chem model with FNL[1] input data and GOCART schema, sever dust storm in Sistan region was simulated to date 14 & 15 July 2011. Satellite images of the event was received by the MODIS sensor. Dust concentration data was received from the Department of Environment. The dust storm code, minimum visibility data and maximum wind speed data was received from the, Meteorological Organization.
The results of the simulation for dust concentration which peak amount of dust was for 21Z14July2011 and 03Z15 July 2011. Model output showed maximum wind speed 20 m/s with North to South direction in the study area. The model predicts maximum dust concentration for the latitude 31 degree North and longitude 54 degree East to 66 degree East (Within the study area). MODIS sensor images showed clearly the sever dust storm. Simulated time series in Figure 3-1 Changes in dust concentration during the event show in the Sistan region. As can be seen from the peak of the concentration of dust in 21 hours on 14 July (350 micrograms per cubic meter) and 03 hours on 15 July (425 micrograms per cubic meter) 2011 was created. Model simulation and satellite images indicated which the Sistan region, especially dry bed of Hamoun wetland in East of Iran was main source of sand and dust storm. Also, based on the model output blowing wind direction from North to South on Iran which converging these currents in East Iran caused by strong winds in the lower levels (According to the meteorological data), arise dust, increasing the dust concentration (According to Department of Environment data), increasing the dust and being transferred to the Southern regions, especially Oman sea. To identify the source of the sand and dust storm, the path of the particle and anticipated this event cant actions and warned to stop and reduce effects its. . Simulation of dust particles in the resolution of 10 and 30 kilometers, the plains of Sistan in Iran's East region as the main source screen. The findings suggest that compliance with the maximum concentration limits on known sources of particles (especially Sistan plain dry bed of plain wetlands) is. Check drawings wear rate showed that the source of dust in the Sistan region, particularly the high potential of our wetlands dry bed of soil erosion in wind activity 120 days during the hot and dry conditions, and silt and clay up to thousands of kilometers away from their source transfers. Vector lines on maps wear rate, indicative of converging flow north-south and severe dust storms in history is this. It is better than models forecast dust events and rapid alert
[1] Final Reanalysis
One of the geomorphologic issues that many human activities affect is the landslides. Natural factors and human activities on the other hand, these events are triggered. Landslide one of the most active hazards are natural processes that lead to erosion and changes in the landscape. Iran is a predominantly mountainous topography, seismic activity and high landslide, diverse climatic and geological conditions of natural conditions for a wide range of slip is important. Located in second place in the sector of industry, population of 1695094 people, proximity to major faults of Tabriz and occurrence Landslides of different city of Tabriz, the city has become one of the most dangerous cities in the environmental hazards, especially landslide. In these circumstances and completed a comprehensive review and a detailed zoning of land for landslide susceptibility seems absolutely necessary. The purpose of the present paper, the occurrence of landslide susceptibility assessment and mapping potential occurrence of landslides in the city of Tabriz in this range.
This research of the type applied- development research and of the research method is descriptive - analytic. In this study, using a variety of sources including satellite imagery, aerial photography, global positioning system (GPS) and field studies landslide occurred in the study area were identified and these data were analyzed using the software ILWIS and use of library studies and expert opinions should identify the criteria and sub-criteria and range were classified. Then, using fuzzy TOPSIS model, the importance of the criteria and sub-criteria specified in pixel units and finally combining fuzzy-TOPSIS model and overlapping functions in ARC / GIS final map was extracted.
Geomorphologic and lithology conditions of the city with its mountainous location where the trigger landslides. The final results indicate that over 30% of the areas of the city of Tabriz are medium to high risk that this areas of land in the north and northeast is sparse. The accuracy of the final map and the map of the distribution of faults and the accuracy of the study proved to be that hazardous zones roughly corresponding to the final map lapses occurred. So we can conclude that the method and the model presented in this paper is an effective method for landslide hazard zonation within the cities.
Climate and weather conditions are among the most important factors in controlling our daily and even long-term activities. Since the emergence of human beings, the weather has been effective in our lives. Changes in precipitation and temperature, solar radiation and other climatic parameters, have had so much impact on people’s lives that as far back as the first periods of human lives, we have been witnessing the climate change, and these factors have determined the way of our lives. Since the old days, the scientists of criminology, sociology and psychology have considered the influence of nature and different circumstances on the crime and its rate. Hippocrates and Montesquieu were the oldest ones that studied about the impact of climate on effects and aggressive behavior. The main objectives of this research are as follows: Understanding the climatic regions of Kurdistan Province, and assessing the relationship between the climatic regions of the provinces and the aggression rate. From a psychological perspective, aggression is a behavior whose aim is to harm others or oneself with a conscious intent. The main idea of this study is to consider the theory that whether there is any connection between natural factors, especially the weather, and the mood, temperament and the aggression rate of people. For this purpose, and for climatic zoning of Kurdistan, we have used the surface data of all synoptic stations in Kurdistan as well as the stations around the province from their establishment until 2005 (25 stations). Using these data, 2068 cells (with approximate dimensions of 7/3 * 7/3 km²) in Kurdistan were appraised every day according to the Kriging interpolation. By applying the cluster analysis to these data, two main climatic zones were identified in Kurdistan. The hot-humid region was including the cities Bane, Marivan, Sarouabad, Sanandaj and Kamyaran, and the cold-dry region, was including the cities Saghez, Diwandareh, Bijar, Ghorveh and Dehgolan. Then in each of these regions, in the number of the samples which were obtained through Cochran formula (768 samples), the Buss and Perry questionnaires were distributed and collected. The new version of the Aggression Questionnaire, whose previous versions was hostile questionnaire, was revised by Buss and Perry (This is a self-report questionnaire that contains 29 words and four subscales).The prototype questionnaire has 52 questions, but a lot of weak questions of the questionnaire have been excluded using the factor analysis method, and it has turned into a questionnaire with 29 questions. Finally, the results of the questionnaires were analyzed through SPSS, using the t test for the independent groups. The results of this study indicate that the physical and verbal aggression rate and the level of anger and hostility among the residents of the cold regions of Kurdistan are higher than the residents of warmer regions. The results also showed that the level of aggression among the men is higher than women. The aggression among the men mostly appears in a physical form, while women make it in its verbal form. Also, in the hot-humid areas, the level of anger and hostility among the women is more than men. According to the data analysis, we can say that the results of this study are consistent with the findings of some researchers, though in some cases the results are not consistent with other researches. The assessment of the geographical environment has not concerned the scientists alone, and philosophers like Ibn Sina, Sociologists like Ibn Khaldun, and writers and thinkers such as Al-Jahiz have looked at geographical factors from other perspectives, and have examined its relationship with ethics and human behaviors. In conclusion, we can say that the results of this study are non-aligned with the results of the studies that have examined the effect of weather conditions on the temperament or real aggression. But the results of this study are consistent with the researches that have investigated the potential of aggression. Therefore, we can say that in a short period of time, warm weather conditions can predispose one to aggression, but to live in the warm climates, may raise people`s patience at the end, and make them able to control themselves at the occurrence of aggression. The results of this study indicate that in Kurdistan province, the extent of potential aggression is higher among the residents of the cold regions (Saghez, Diwandareh, Bijar, Ghorveh and Dehgolan) than the inhabitants of the tropic ones (Bane, Marivan, Sarouabad, Sanandaj, and Kamyaran). To justify these findings, we can say that freezing creates a sense of insecurity in people because we experimentally see that the residents of a cold region need to work constantly in order to keep their bodies warm. They need to have a secure plan for the winter, so that they can make enough food, fuel and clothing. This coherent planning makes them more active in comparison with the residents of the tropical regions. An unfavorable and difficult living environment emboldens people. The people who belong to these areas are pragmatic, and their approach to the environment is competitive or aggressive. In contrast, the people who live in the relatively warmer climate have usually less activity. The property of this kind of temperament is laziness and inertia. Working in hot places is unpleasant because it makes people sweat, and it makes them tired soon. Another finding of this study is that in the whole province, in both cold and warm climates, the aggression among men is more than women, and this difference is greater in cold areas. The men spend most of their time outside the houses, and because of this, the effect of climate is more on them, but women are living most of their time at home, and they can take advantage of the air conditioning equipment. Thus, they have a more relaxed and flexible temperament.
Disaster risk which is the potential loss expressed in lives, health status, livelihoods, assets and services, can occur in a particular community or a society due to the impact of a natural hazard. Disaster Risk Reduction is a systematic approach to identify, assess and reduce that risk. Or (in identifying, assessing, and reducing …) To be specific, the purpose of this or (the current) approach is to minimize vulnerabilities and disaster risks throughout an education factors (throughout an educational factor Or throughout educational factors) to avoid or limit the adverse impacts of natural hazards.
Knowledge and education are recognized as the key components of disaster risk management. Occurrence of enormous disaster in the world shows ( or pinpoints) the need to use (or for using , in order to prevent repetition of the same structure) knowledge, innovation and education to build a culture of safety and resilience at all levels. The role of education for disaster risk reduction strategies can thus be presented based on three types of activities, including Save lives and prevent injuries should a hazardous event occur; Prevent interruptions to the provision of education, or ensure its swift resumption in the event of an interruption, and finally Develop a resilient population which is able to reduce the economic, social and cultural impacts should a hazardous event occur. Education for Disaster Risk Reduction promotes critical thinking and problem-solving as well as social and emotional life skills which are essential to the empowerment of groups threatened or affected by disasters.
Iran is crossed by several major faults, 90% of whom are seismically active and subject to many earthquakes each year. Qazvin Province, which is located among active zones, suffers less earthquakes, but these may be more powerful because stresses have longer to build. Occurring earthquakes often affected rural settlement and societies. The main aim of the article is to respond how is the role of education in risk management and decreasing vulnerability level of rural areas based on earthquake in Qazvin province? The purposes of this article are to outline the existing seismic risk in Qazvin and to identify the crucial role of education in advancing culture of safety and the resilience of Qazvin rural communities to destructive earthquakes.
From objective points of view, this paper is practical kind of research and from analytic points of view; it would be categorized as the qualitative and quantitative research. The information contained in this article is based on a variety of sources and have been collected by means of both documentary and questionnaire techniques.
This research has adopted or adopts the qualitative and quantitative methods to respond to (or to answer a basic question) a basic question. To formulate the strategies of earthquake risk reduction 29 villages were selected by cluster sampling and then it was estimated the samples by Cochrane method. For data collection, 386 households were selected by random method.
According to the research topic, the main criteria divided into two groups: formal and informal education. The formal education includes indicators as the number of showed films, corrugated education about earthquake and the informal education encompasses indices as the effect of media or institutions raising awareness for earthquake, the effect of the earthquake, affected rural and peoples and finally experiences concerning the earthquake training.
Based on the results of the current research, the level of education plays an important role in enhancing the effects of hazards and ensuing vulnerability of rural areas after the occurrence of natural hazards (earthquakes).
The result of this research also shows that the rural or regions of Qazvin province are the more vulnerable and the range of knowledge of peoples about earthquake risk is low. It is necessary to consider the earthquake risk management to (or so as to) decrease the earthquake risk among the studied regions/areas in all earthquake phases. In order to reduce the vulnerability of rural settlements in Qazvin County, it is necessary to increase awareness and knowledge.
Regarding/ considering the results of this research and the role of education in risk reduction to reduce the vulnerability of rural spaces, some strategies such as strengthening disaster risk management awareness, increasing knowledge among rural residents, improving communication skills regarding/concerning disaster risk management have been proposed.
Climate change is one of the crucial factors, which threaten many sector such as agriculture, water resource for decades, and the sector is more sensitive to climatic conditions. Communities are the most vulnerable to the adverse impacts of climate change and variability because of their low adaptive capacity. One of the challenges of climate change and human spatial dimensions of climate change in international borders where climate change, and creates special challenges. Populated places in the East where rapid urbanization, industrialization and agricultural intensification result in vulnerability to climate change, water shortages as the main concern arises.
Adaptation to climate change is the adjustment of a natural or human system to moderate the impacts of climate change, to take advantage of new opportunities or to cope with the consequences. Trying to identify the attitudes of people and their mental models of climate change can provide application to manage the post-change. Culture and engineering modeling approaches minds of scientists for climate risk management and climate change consequences have adopted. The review focused on farmers’ perceptions on changes in temperature, precipitation (rainfall), adaptation measures taken by farmers, barriers inhibiting these adaptation measures and the socioeconomic determinants of adaptations to climate change in Sistan plain.
The aim of this study is to provide mental system model, and understanding of climate change is to adapt these areas. To carry out this study to develop a theoretical framework for the model to adapt to climate change was discussed in Helmand. The field study was to assess the views of people on climate change action. The review found out that most farmers in this region are aware that the continent is getting warmer, and precipitation or rainfall patterns have changed. People with new changes and features adaptive approach to the challenges ahead were investigated. This data is based on knowledge (awareness) of water and climate change adaptation and mitigation strategies and be ready. So how compliance action is preventive in nature and to reduce the repercussions of climate change and the potential benefits of a region in the face of these side effects are formed. Most respondents aged over twenty years are at least a decade to climate change are felt to be most frequent subjects 30 to 40 years old. The data collected were processed using statistical techniques and modeling for ranking and evaluation of adaptation strategies were created and ASI index. The results for the insights, policy makers and service providers for local development is important, and can be targeted measures used and the promotion and adoption of coping mechanisms with the potential to build resilience and adapt to climate change and the resulting effects environmental prepare.
The results showed that most people in the region following the election of climate change is adaptive behavior. In total, there are 15 strategies in the region. The ASI index rating of strategies to change the pattern of cultivation, selection of resistant strains, reducing the amount of land-cultivated variety is the pattern of adaptation to environmental changes. Ensuring awareness of and adaptation to climate variability call was conducted with the cooperation of the people. Therefore, variability of climate and natural features of the area was measured by various options. The results show that already sampled respondents in the community are aware of climate change. 60% of respondents strongly observed signs of climate change and the dry season and low rainfall and warmer temperatures to believe. The main adjustment options adopted by farmers to temperature in the region include change of product types and number of ships that 61.6 percent of the farmers that their efforts. Another priority is that 39 percent of them tend to change sowing dates and planting varieties resistant to drought. The main recommendations for adapting to new circumstances in this region to stimulate the economy and livelihood of local people can be to diversify crop production (food for example, and cash crops, annual and permanent crops greenhouse) and the use of foreign income from farm sources (ecotourism, rural tourism) can be cited.
Drought is a concept that is generally understood on a basic level, but is difficult to quantify. Palmer defined a drought as a meteorological phenomenon that is characterized by ‘‘prolonged and abnormal moisture deficiency. A drought can alternatively be broadly defined as a temporary, recurring reduction in the precipitation in an area.
Aridity and drought are not synonymous. Aridity is a measure of long-term average climatic conditions. Both humid and arid regions experience droughts. However, the inter-year variation in precipitation is greater in arid regions and there is a greater probability of below average precipitation in any particular year. Arid regions are thus more prone to droughts and may experience more severe impacts from droughts.
In this research was used temperature and precipitation monthly data of Urmia, Tabriz, saghez, Maragheh, and Mahabad station in statistically period 1985-2014. Run test was used to study the homogeneity of data. Randomness and homogeneity of data was approved.at a confidence level of %95. SEPI Index and ANFIS model was used for determining and forecasting drought in Urmia lake basin. SEPI index is more complete than SPI. Results of SEPI were used in ANFIS model.
Fuzzy index SEPI[1]: Standardized precipitation index and evapotranspiration (SEPI) to address some of the disadvantages of SPI index is provided. Evapotranspiration and precipitation index SPI index and SEI standardized integration is achieved. The index is the result of drought monitoring phase of architectural models using fuzzy logic in a fuzzy inference system is designed. How to design this model and determine SEPI is described below.
Fuzzy architecture drought monitoring: for derivatization indices SPI and SEI using Fuzzy Inference System, Due to the structure of fuzzy models were considered.
SPI index[2]: Standardized Precipitation Index is an indicator widely used in Drought Monitoring. This index is one of the few indicators drought monitoring and could even say the only indicator that the time scale is considered. Depending on the time scale to determine the effect of different sources of agricultural drought, hydrological and so determined. Time scale can be determined from one month to several years. SPI index is used to calculate the only element rainy climate. Monthly precipitation amounts for each station in the desired time scale is calculated.
SEI index[3]: Since the index SPI Single Entry, rain, The SPI index values under the influence of changes in temperature and evapotranspiration parameter that is powerful factor in the drought, it will not be. So to enter the effect of temperature and evapotranspiration in SPI, SEI (evapotranspiration index Standard) To calculate this index, before any measures should reference evapotranspiration for the period to be estimated.
define the rules for combining indicators SPI and SEI: Different classes index SPI and SEI rules or the same combination of conditional statements in the form if, as a class of SEPI index in the lead, is defined. This rule only a combination of different modes SPI and SEI indices that lead to SEPI index shows. In this regard, the rules can be combined to fit different for successive written and stored in the knowledge base. Since the output of the resultant composition, indices SPI and SEI are involved in determining the status of SEPI, Weight each of the indicators with regard to the effect of precipitation and temperature parameters on the severity of the drought was considered As a result, SPI indices and weights 0.667 and 0.333, respectively SEI were included in the calculations.
According to the results, according to the research, education Anfis model with 75 percent of the data series is well done SEPI and much has been done to ensure education is nearly 100 percent. So that the graphic maximum of 0.26 percent error in saghez station on a scale of 6 months and the lowest average error of 0.10 percent in Urmia station is on a scale of 6 months. In modeling, validation data, the average error modeling is naturally higher than the average training error. Most average forecast error saghez on a scale of 6 months at the station 0.34 percent and 0.10 percent, the lowest on a scale of Urmia station is 6 months. But the coding maximum of 0.65 percent error in saghez station on a scale of 6 months and the lowest average error of 0.32 percent in Tabriz station is on a scale of 6 months. SEPI index in the time scale of 6 and 12 months is used for investigate the characteristics of adaptive neuro-fuzzy inference system in order to drought and drought forecasting model. According to the findings in this study, the frequency of drought in the stations of Urmia and Saghez and Maragheh on a scale of 6 months is more than the scale of 12 months in the basin of Lake Urmia but in Tabriz and Mahabad Stations situation is the vice versa. The drought in Urmia Lake basin is increasing trend but temperature has increasing trend with more intensity. The highest and lowest percentage of drought was seen in Urmia and Mahabad station respectively. The results of the forecasting of index by ANFIS model showed that the most training error is in Tabriz station (0.51) and the lowest training error is in Maragheh station (0.36) in a scale of 12 months in coding. In validation data modeling the average of modeling error is higher than the average training error naturally. According to the definition of drought SEPI was presented based on amounts of 0.73 or higher or mild drought to higher floors as dry conditions arise The scale of 6 months in Urmia station with 13.14 percent to 10.89 percent saghez station, Tabriz stations with 5.58 percent, with a 5.1% Mahabad station and Maragheh with the amount of 4.82 percent, the drought has occurred. The time scale of 12 months in Tabriz station by 9%, saghez station with 7.26 percent, with 6.11 percent of Urmia station, Maragheh with 5.5% and the amount of Mahabad stations with a 3.44 percent, from months of study in the series, drought has occurred.
Results of SPEI are:
Results of ANFIS Model are:
In study area and in ANFIS model whatever forecasting coming years is shorter; confidence of forecasting will be more.
Due to the errors amount obtained in model validation, in study area forecasting of drought by ANFIS model was done with confidence 94%.
[1] - The combination of indices SPI (Standardized Precipitation Index) and SEI (evapotranspiration index standard) based on the rules of the Fuzzy Inference System.
[2] - Standardized Precipitation Index
[3] - Standardized Evapotranspiration
Has been stated in various sources, soil as one of the most important natural resources has a major, role on the lives of humans. Today soil erosion and sediment production, a problem that is increasing day to day process and loss of surface soils and sediment accumulation in dam reservoirs, canals and also sedimentation damage to the country's economy. One of the most important types of water erosion, gully erosion or (Galli formation). This type of erosion and loss of soil due to sediment production and enormous damages to land, roads and infrastructures, is of great importance. Soil erosion is one of the most important factors that threatens large areas of Iran annually and decreases or eliminates the quality of agricultural lands and rangelands. Due to highlands of Iran in comparison with the grounds and surrounding plains (mean elevation of 1250 m), it has been affected by water erosion. So it is very important to study erosion and present management strategies to reduce the impacts of erosion in basins of Iran. This study to Target morphometry gullies and the influencing factors on gully erosion in the South West sub-basin of ILAM (Cham Fusel).
The average height in the area between 50 and 1,200 meters above sea level and has a dry climate with an average annual rainfall of less than 200 mm and the average annual temperature is above 25 degrees C°. In terms of the main geological formation of this area is affected by gully erosion, Aghajari formation (red mudstone, siltstone and sandstone) are related to Miocene period. Basin area of over 150 hectares affected by gully erosion and slope threshold for gully erosion in the area between 8-2 percent.
The research method in this study is field research, library study and morphometric measurements of gully erosion forms. Besides, on the basis of the geological maps of 1/100000 and topographic 1/50000 and DEM 30 meter area, the software of GIS Arc has been used to make the required maps. Furthermore, the GPS device and a camera has been used in the field to harvest. o
The average height in the area between 50 and 1,200 meters above sea level and has a dry climate with an average annual rainfall of less than 200 mm and the average annual temperature is above 25 degrees C°. In terms of the main geological formation of this area is affected by gully erosion, Aghajari formation (red mudstone, siltstone and sandstone) are related to Miocene period. Basin area of over 150 hectares affected by gully erosion and slope threshold for gully erosion in the area between 8-2 percent. The study, which the sub basin in Cham Fusel ILAM province is located in the South West, with the aim of gully morphometric including deep, height, length, height from sea level, and geographical location as well as classification criteria in three sample gully gully of area, In order to identify factors affecting the development of erosion in the basin plain Cham Fusel was evaluated. The results of morphometric and field visits to the region, factors such as climate factors, slope and aspect, geology (Land genus), tectonic activity and faulting, land use, overgrazing of amount plants, including the most important factors recognized were identified in the development of gully. Which layers to extract some of these factors in Arc GIS software designed and based on creation of maps and data to analyze each of these parameters and their impact on Gully Erosion percent has been paid.
According to the morphometric data, it can be concluded that the gullies basin largely toothed and clawed, permanent, of medium to large gullies, which have expanded continuously. Below you can see images of morphometric gullies sample was collected during the field visit of the area. The results show that due to the widespread earthquake in the region in recent years and local faults can be concluded that one of the most important factors in the formation Galli uplift of the Earth. Also overgrazing by cattle ranchers in the area Tuesday Abdanan city, murmury, Dahlgren and ranchers outside the province of Hamedan and Kermanshah provinces such as ranchers who use the area as Qishlaq, Another important factor in the development of gully erosion in the area. Due to the climatic amount of rain, sleet, snow, ice, temperature and wind could be the climate factors in the rise of water erosion. As the geographical location and local climatological data suggests, the study area is influenced by the Mediterranean winter rains. Which are imported to Country from the West in winter and more in the form of showers and hail rainstorm conditions caused severe erosion gully in the area easy. Lack of growth of vegetation and bare Land is another contributing factor is considered in the development of gully erosion in the area. That is because the rainy season in the winter when the soil in the area is almost devoid of vegetation. The lack of vegetation in the region as one of the important factors, has caused soil erosion, its most destructive erosion of the gullies show. Also according to the map slope and aspect of the region was marked within the range of between 2-8 percent and Create Gully and aspect with the West and the South West and North West are more affected by gully erosion. Finally, all factors except factors of land use, all other factors were named among the important factors affecting the development of gully erosion are the region. It was also found other factors in the evolution of land use contrary to gully erosion region. That is because of the lack of culture in this area and dropping land by farmers as wasteland, and also because of the recent drought in the region has caused more and more extend of gully erosion and land with the ability crop damage and destroy all. The results obtained showed that the study area in terms of of gully erosion in critical condition.
Climate risks are the inherent features of Earth's climate. The occurence of heat wave is one of these natural phenomena. Heat waves, one of the basic appearances of climate change, are very important because of frequency and damage of life and property, (Haddow et al, 2008). Frequency of heat wave occurence in recent years, is one of the aspects of climatic changes and extreme weather (Matthies et al, 2008), and resulted in heavy financial loss and increasing p mortality. From statistical point of view, heat waves are the positive changes and upper extremes of maximum average daily temperature, which continuing during consecutive days, weeks or months in certain geographical areas. According to the available definitions, two dimensions of time and space are important in the occurrence or non-occurrence of heat waves (Smith,2013). Due to the positive slope of temperature and increase in temperature extremes and many changes in values of maximum temperature in Iran, main purpose of this study is the spatial and time distribution of heat waves on the plateau of Iran.
The daily maximum temperatures recorded in 49 synoptic stations of 31 years (1980-2010) climate normal period were used for the spatial distribution of heat waves. In order to determine heat waves, using the 95th percentile index, the temperature threshold for each month and each station was determined separately. The reason of studying heat waves in the monthly scale is temperature differences and different consequences in different parts of Iran, as an example, maximum temperature 30 degrees in May for south of Iran is normal, but for the northern regions of Iran is a heat wave and causes damage. So the basis in this study is determining heat waves and spatial differences of these phenomena in monthly scale. In this study, the heat wave has been defined as temperatures above the 95th percentile threshold per month, continuing for three days and more. So with specifying the threshold temperature for each month at each station in different parts of the country, temperatures above the threshold continuing for three days and more, defined as a heat wave for each month and the spatial distribution of heat waves was plotted in the whole area of Iran plateau for each month. In order to determine changes in heat waves in the whole country, the number of heat waves has been specified for the whole country in three decades (80-90-2000).
The spatial distribution of heat waves: Maximum temperature thresholds are related to the southeastern, southwestern and southern stations; and the lowest thresholds are northern coast and northwest mountains stations. In general, the minimum temperature thresholds are visible in the northern half and towards the heights; however, the maximum thresholds are visible in southern half. In this temperature variable, the role of latitude and altitude is dominant in lines with the same threshold of extreme temperature like other temperatures properties in Iran. Spatial variations of this temperature parameter throughout the year, increased from the Caspian Sea and North West of Iran to the South East and South West of Iran. In the entire study period, the number of heat waves in different parts of Iran indicates that most heat waves were occurred in the mountainous regions of Iranbased on the zoning temperature Alijani. The number of heat waves decreased from this area to the north and south coastal areas and East of and Central of Caspian has the lowest number of heat waves during the entire period of the study in Iran.
Time, temporal and decade distribution of heat waves: Time changes in heat waves shows increasing trend, As we can see the increase in the number of heat waves, from mid-90s and then, in 2010 most of it.Also, the 5-year average and decade-long average of heat waves, show a significant increasing trends and the most of the heat waves occur in Iran during 2000s. Time series of heat waves in Iran; show a significant increase over time.Hence, from the late 90's onwards, the spatial average of heat waves rather than the average before these years has increased. Iranian plateau in 1992 and 2010 has experienced the minimum and maximum of heat waves, respectively.
The results showed the minimum temperature threshold along the heights in northern half of the country and maximum temperature threshold at the southern half. Spatial variations of this thermal parameter throughout the year, is increased from the Caspian Sea coast and the North West of Iran toward the South East and the South West of the country. In general, this parameter that is associated with the extreme temperatures in Iran is under latitude and heights distributions the same as distribution of maximum temperature areas in Iran. But spatial distribution of heat waves as a natural hazard is different from the distribution thresholds and maximum temperatures. So that, the most heat waves are in Zagros Mountains, the East foothills of Zagros, South of Western and central Alborz and also southern Binalud foothills in the North East. The number of heat waves is reduced toward the center of Iran and the Great Plains (Lut and Kavir deserts). The minimum heat waves occur on the coasts of Caspian Sea, southern coasts of Iran, South-West and West Zagros and central Iran. The occurrence of heat waves in Iran have an average between 9 and 14 heat waves during all months of the year except for May with a maximum of 6 heat waves and June, with a maximum of 16 heat waves (months of minimum and maximum occurrence, respectively). This shows minimum increase in cold months and maximum increase in warm months. Therefore, the occurrence of heat waves in Iran is possible in warm and cold periods of whole year and there is a little difference between these two periods. This indicates both internal (local) and external factors (air masses) involved in occurrence of heat waves in Iran. The number of heat waves increase and decrease since January and June, respectively. This temporal sequence is disrupted by a sharp decrease in May (6 heat waves less than previous month).
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