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In this research, for determining the synoptic patterns of dust storm occurrence in northwest and northeast of Iran; four types of data were used including: Hourly data of dust phenomena and horizontal visibility for 30 meteorological stations in northwest and northeast of Iran. Six-hourly global data analysis from NCEP/NCAR reanalysis, including air temperature, geo-potential height, U-wind and V-wind components, relative humidity, soil moisture and omega from 1000hPa to 500hPa, were used for the preparation of maps and identify the synoptic patterns by using GRADS software In order to identify the source of dust generation, tracing and simulating the path of dust particles, HYSPLIT model Lagrangian approach of backward trajectory was used. And to detect dust, the unreal images of METEOSAT-9 second generation for EUMETSAT satellite were used. Synoptic studies have shown that low and high pressure, and the vertical motion of air are the main causes of dust storms in Iran. The circulation of the atmosphere during dust storm, shows that a low pressure cell has been stretched from Pakistan to the south of Iran and from there to the deserts in Iraq, Syria.This condition causes the formation of cyclonic circulation in the East of Syria and west of Iraq on 31 July. Wind speed Increasing, cyclonic circulation, dry soil and lack of coverage, provided the conditions for removing the soil particles. Due to the extended ground surface's low pressure and weakening of the stable conditions of low level of troposphere, the approaching of trough has led to the beginning of a dust storm in Iraq deserts on jul31 and this unstable condition providing enough power to carry the soil particles away from its origin. Besides that, the stable location of ridge on Iran made anticyclone circulation in the wind blowing and it cause that the dust storm cycle the northern part of Iran and enter from northeast in to the country.

Tropical storm is a one of the major hazards that threat the southern coastal zones of Iran. Understanding of such hazards and knowledge of the time of their occurrence could be useful in the management of accidents caused by them. The aim of this study is analysis of the dynamism and hazards of recent tropical storm formed over the Arabian Sea is known as the Hurricane Nilofar. The data used include re-analyzed data of SLP (Sea Level Pressure), Geopotential Height, wind (U and V components), Omega, specific humidity, CAPE (Convective Available Potential Energy), Vorticity advection and SST (Sea Surface Temperature) for Nilofar storm activity in end days of October 2014 obtained and plotted than were analyzed. The results showed that the depth of the trough level of 500 mb with the axis southwest - northeast, creates a cut of low on 25 and 26 October on the Arabian Sea that following the practice causing a divergence in the eastern side of the cut of low on level of 500 mb and creating a strong convergence zone in the lower levels of the atmosphere and on the surface of the sea. Eastward movement of trough on third day of the formation of hurricanes and out of the activity storm, also, its change the mechanism of action following the availability of energy from the ocean surface (conversion of thermal energy into mechanical) to strengthen the updraft and downdraft currents on the wall of the eye and eye of storm has helped, as of this day and the next day the storm activity, increase speed to low level jet stream than the upper levels of atmosphere, causing the energy source the storm is chanced from upper levels to the lower levels of the atmosphere, also the interaction of tongues and anticyclonic centers located on the Arabian Sea, direction and movement of the storm has created to overturn it on 31 October.

Air pollution is one of the most important environmental hazards in Tehran metropolitan that with understanding and cognition of factors which affecting pollution can reduce adverce effects of it. In order to reduce these effects, accurate studies on the basis of effective factors on pollutant is essential. The goal of this research is to analysis variation of air quality index(AQI) in relation to atmospheric conditions and traffic in Tehran. The Pearson correlation coefficient and regression analysis were used in order to compute the relationship between air quality indices(average and maximum) with traffic and meteorological variables. This study was done during 60 days (November,6th to January 5th) for the 2010 to 2012 years. The results revealed that atmospheric unstability index (ki-index) has the most impact on air pollution variations. Multiple linear regression  models for the year 2011 was the most accurate model to estimate maximum air quality index with the least relative deviation, RD (RD of -0.05 for first model and -0.1 for second one). An important achievement of this study was indirect correlation between number of vehicle and air quality index which is not happened to the reality. It seems that pollutant production in two cases including car’s movement or stop are quite different from each other and should be investigated using other methods.

  The drought has been known as a complex and perilous phenomenon at the whole of the world especially in Iran. Determining and predicting its severity can be effective at managing the hazards due to it. To determine the drought severity, the indices have been used that can be divided into two broad categories of meteorological (M) and remotely-sensed (RS) indices. The most important M index has been the standardized perception index (SPI), and the common RS indices have been those extracted from the vegetation index (NDVI) and land surface temperature (LST) index. For modeling time series behavior of these indices and also predicting their future values, the machine learning methods can indicate the high efficiency. This paper also aims to evaluate the performance of four important machine learning methods, i.e. neural network (NN), support vector regression (SVR), least squares support vector machine (LSSVM) and also an adaptive neuro fuzzy inference system (ANFIS) for modeling the M and RS indices of Eastern district of Isfahan during 2000 to 2014 and predicting their values at 2015 and 2016. The data used in this paper are the NDVI and LST time series of MODIS, and the rainfall time series of TRMM satellite of study area. At first, the vegetation condition index (VCI) and temperature vegetation index (TVX) have been built by NDVI and LST and 12-month SPI has been built by rainfall data. Next, the time series behavior of three these indices has been modeled by four aforementioned methods that according to the results, SVR has a highest efficiency and NN has a lowest efficiency among these methods. The speed performance of LSSVM and then ANFIS have been higher than the other methods. Finally by designing a fuzzy inference system (FIS), the drought severity at spring and summer of 2000 to 2016 has been monitored that the results have shown the normality of the spring in all years except 2000 and 2011 and severe drought in the summer in all years except for the four years 2000, 2010, 2011 and 2014. In fact, this research has aimed to present a strategy for modeling drought behavior and predicting and monitoring it at future using machine learning methods and the remotely-sensed and meteorological time series data and fusing them in a FIS system.

Air pollution is the results of industrial development increased continuously by overpopulation urbanization expanse and use more fossil fuels. One of the most important air pollution consequences is breathing disease, intensification of heart and pulmonary diseases and also increasing mortality in the cities. Tehran is one of the most polluted cities in the world, so that; it is polluted by a pollutant or some pollutant one day of each 3 days. On the other hand, topographic situations and locating in Alborz Mountains increase it. In both July and August 2013, when the temperature reached over 40c° most of the times in heat waves, the air go stable and the quality of the air decreased and unhealthy conditions overcame for several weeks in Tehran.Based on the reports of meteorology organization, Tehran had the hottest days in summer 1392 (2013) ( Tir(July) and Mordad(August)) in recent 60 years. Air stability caused decrease of air quality and unhealthy conditions development for three weeks. Recognition of air pollutions origins and their synoptic patterns is useful for forecasting unhealthy conditions and control them. paper, temperatures data were received from meteorology organization;, pressure, altitude and temperature maps in sea level, 700 and 500 HCT Pascal conditions were gotten from NCEP/NCAR and Skew-T was got from UniversityofWyoming to recognize the synoptic pattern of the conditions. The results of the study showed Gang Cyclone tongue in SLP map and Anticyclone Azore and also inversion in middle and upper atmosphere caused air stability and increase of the temperature and then trapped the polluters near the ground caused decrease of air quality in Tehran.    

The Study of quality groundwater in karstic areas are great important. In this research, the hazards of karstic water chemical pollution in Qouri-Qalae cave are assessed. Rigorous tests have been conducted using samples, field works and interview with professionals to identify the role of human and natural factors contributing to the pollution of water in the cave. Samples have been taken from the cave entrance and end part of the cave during the six-month period. And the density of heavy metals and major cations  have been measured in the laboratory. Apart from these, electrical conductivity, acidity or alkalinity, rate of oxygen consumption by organisms in water and nitrate has also been measured. In tests, arsenic and lead have been measured by atomic absorption spectrometry, Iron, magnesium and manganese by flame and lithium, sodium, calcium and potassium by Photometry methods. PH with PH meters, EC with EC meters, BOD with BOD meters have been measured and nitrate by ion chromatography IC. Drinking water density obtained from the laboratory results were compared with standard criteria. Based on the results, the density of some elements such as lead and arsenic within the water is higher than the permissible limit of drinking water. This is a serious risk to human health. Also the results show that the origin of this type of pollution is in relation to geological factor of mineral streaks, fuel emission of lime kilns and sewages. High density of iron, magnesium and manganese is in relation to the water crossing on the soils and rocks and then penetrating into the cave. Recent elements changed the color, turbidity and flavor of water. The high BOD can be linked to the sewage and waste by visitors. Considering the above points, the following actions are required for elimination of risks threatening groundwater of Qouri-Qalae cave: continuous monitoring, use of international standards and practices in management, increasing public awareness of visitors and limiting their number, removal of waste and polluting elements inside and outside of the cave particularly across the catchment area of the cave. 

Geomorphological risks are One of the major landslide. Identification of risk areas susceptible to landslides is one of fundamental  steps in the  management of natural resources and reduction of  the risks .Kashtr with an area 26 square kilometers south-west of Kurdistan Province is located on the eastern edge of the mountains Shahoo. To zoning first sliding zones was examined with field visit، that about 28 sliding zones were identified and after processing in GIS application came as a layer. With underlying landslides distribution map landslide weighting parameters took place، including geology، slope and direction of the slope، elevation، soil texture، land use، soil erosion، distance from fault، waterways density، and distance from road. Logistic regression model was run in SPSS and the results showed that the influencing factors on landslides occurrence in the region are distance from the fault، geology، soil erosion، direction of the slope، etc. Finally study area in terms of Sensitivity to the risk of landslides was classified into 5 classes، based on that: 2/6  has a very high risk، 6/4  high risk، 3/19 average risk، 7.9  low risk، and finally 5/6  has very low risk.  

Introduction: Subsequent to earthquakes, an updated and reliable map of environment often is not available; terrestrial substructure is either not appointed or ruined and mission time is turned into a vital element for hazard management, search, and rescue of patients. Referring to these facts, hazard management and monitoring of areas struck by earthquake is one of noteworthy applications of autonomous systems, which can enhance the excellence of search-relief missions. Utilizing of unmanned aerial systems as multi-sensor platforms in destruction surveillance is transformed into a novel economic procedure for enhancing autonomy and efficiency of natural hazard management tasks. Nowadays, tendency in the development of unmanned aerial systems is toward autonomous navigation or hybrid tasks. In this field, development of comprehensive, efficient methodologies for path planning, control, navigation, and processing of UAS sensor information has attracted an increasing momentum among researchers as one of the fundamental steps for achieving to autonomous navigation of aerial systems. In this article, a new meta-heuristic algorithm is proposed based on gravimetric measurements in physical geodesy studies. The aim of this algorithm is achieving an efficient method for solving complex optimization problems with different constraints such as hazards monitoring tasks. Evaluation of the precision, quality of results, success rates, and CPU running times of implemented algorithms demonstrates that gravitational potential optimization algorithm outperforms other methodologies for monitoring of regions struck by an earthquake.