مجله مخاطرات محیط طبیعی
پیاپی 8 (تابستان 1395)

In this study Seismic hazard assessment is carried out for 25 – 31.5 ˚E and 58.8 – 63.3 N ˚ including Sistan and Baluchestan province. There are several active faults within this area that many destructive earthquakes occurred along them. At the first we identified these active structures then seismic catalog of period of 1900-2014 and historical earthquake have been investigated. 33 potential seismic sources have been identified. For each seismic sources, seismic parameter estimated. Using these data and choosing convenient attenuation relationship in EZ-FRISK software in a network of dots with the distance of 20 *20 km we obtained peak ground acceleration on bedrock in sites for exceedance probability 10% and life time 50 years for return period of 475 years. The results show Sistan and Baluchestan province is divided to 5 different seismic zones as follow: The area with PGA more than 0.35g that named Very High Seismic Zone and the area with PGA between 0.3 g to 0.35g that named High Seismic Zone includes parts northeast and east of northern part of province and in the middle of Sothern part of province. The area with PGA between 0.25g to 0.3g that named Moderate Seismic Zone, the area with PGA between 0.2g to 0.25g that named Low Seismic Zone and the area with PGA less than 0.2g that named very Low Seismic Zone mainly includes north east and south west parts of province.

Malaria as a mosquito-borne disease is largely dependent on climatic conditions. Temperature, rainfall and relative humidity considered as climatic factors affecting the geographical distribution of this disease. Southern and eastern regions of Kerman province is a malaria endemic area in Iran. The purpose of this is to evaluate the effect of climatic factors and ENSO on the incidence of malaria in the south of Kerman. Data, including are meteorological data, ENSO and patients with malaria in the period 2003-2013. The results show that the epidemic in this region is very much dependent on annual and monthly temperature, humidity and precipitation. The relationship between temperature and disease is significant at 0.95. Level so the disease increases with temperature up to 40-c˚ threshold. As well as, the result shows that the epidemic malaria is decreasing with increasing relative humidity and precipitation in south Kerman. The statistical analysis shows that malaria has reaction to ENSO. This relation is different at phase El Nino and La-Niño. In the El-Nino phase is increasing malaria because increasing temperature at this phase but the La-Niño phase is decreasing malaria because increasing relative humidity and precipitation in Southern and eastern Kerman province. Regarding to the occurrence of ENSO in January and the appearance of its effects with 6-9 month delay in the Southern and eastern parts of Kerman province, so, by the analysis of the ENSO phases and the predication of the temperature, relative humidity and precipitation we can provide more efficient malaria control programs.

The research area of this study is the city of Khorramabad . The data of this study are 23 wells and springs in Khrorramabad and from 1381 to 1392, which is seasonal. Information and data on the chemical elements present in the water parameters: ph., total hardness (TH), electrical conductivity (EC), Total Dissolved Solids (TDS), sulfate (SO4), chlorine (Cl), nitrite (NO2) and nitrate (NO3). . The results showed that Ph. of all wells and springs allowed within acceptable limits and standards. The total hardness (TH) is higher than the desirable standards in all seasons in all of resources and is lower than the allowed maximum of standards. According to the conducted researches, the amount of the electrical conductivity, total dissolved solids (TDS) and sulfate (SO4) are lower than optimum and maximum in all wells and springs in all seasons. The amount of chlorine (Cl) in all wells and springs is lower than the limit on the number of allowable standards but is higher than the desirable standard of EPA. In all seasons the amount of nitrate (NO3) on all resources is lower than the allowed Iranian national limit, and desirable and permissible World Health Organization (who), and the limit of EPA standard, but in all of the resources is higher than the desirable limit of (EPA). Also, in all seasons, the amount of nitrites (NO2) in all wells, springs and the study area is lower than the standards.

The main purpose of this research is synoptic analysis for the occurrence of springtime heavy rainfall in the Northwest of Iran. Therefore, daily precipitation data were obtained from 15 synoptic stations for a period of 34 years (1981-2014). Then by using percentile index of above 95th, it was identified 98 days with heavy precipitation. So, to determine the synoptic patterns by applied the NCEP/NCAR reanalysis dataset, the maps of geopotential height, sea level pressure, streamlines, vorticity, and specific humidity at different levels were prepared and the regional pattern flow and atmospheric conditions two days before the occurrence of precipitation analyzed. The results indicate that heavy precipitations in North West of Iran are categorized into four synoptic patterns. At the first pattern, the main cause of heavy precipitation in North West is passing cyclone or low-pressure migratory systems and the regional dynamic convergence and its association with cyclonic circulation. The main factor for the transferring of moisture to the inner side of these cyclones is the anti-cyclone stationed in Saudi Arabia. At the second pattern, the couple blocking system in the middle level of troposphere system is caused heavy precipitation with stop-motion circulation systems in the middle and lower levels of the atmosphere. At the third pattern, a deep cyclonic circulation center has not been formed on their area and seems deepening a trough of extratropical and stimulates the local convergence condition dynamically, and is regarded as the main mechanism of precipitations occurrence.

It is very difficult to assess desertification and criteria and indices are considered as key tools to measure the destruction. Evaluate the most effective desertification indices assessment and determination of their priorities and importance using systematic methods including Attribute Decision Making can increase the efficiency of controlling projects and, reclamation of disturbed lands, and also to avoiding investment wasting. Therefore, in this study TOPSIS and Analytic Hierarchy Process algorithm were used to determine the most effective indices and ranking their priorities and importance. The first, based on previous study in Iran and other parts of the world, 32 of effective indices on desertification were selected and weighted by relevant experts via questionnaires. Using Shannon entropy model suitable criteria for evaluating the indices were weighted, and then the most effective factors to assess desertification were determined and weighted by TOPSIS algorithm and Analytic Hierarchy Process respectively. The results showed that the criteria of sensitivity to minor changes and cost and time with the weight of 0.341 and 0.111 have the highest and the least importance among the studied criteria respectively. Among 32 ranked indices, 20 indices were determined as the most effective indices on desertification. The indices of annual rain fall, salinity, vegetation cover have the highest importance respectively. Also the results showed that indices of land use changes and annual rainfall with the weight of 0.217 and 0.166 have the highest priorities between human and natural indices respectively; so they should be prioritized in management and combat to desertification.

The aim of this study was to evaluate the effects of global warming over the coming decades is frost country. For this, the first two time periods 2015-2026 and 2039-2050 in the minimum temperature data from the database at the Max Planck Institute in Germany EH5OM was extracted under A1B scenario. Then, using a dynamic model of regional climate temperature in at least two time periods mentioned in size 0/27 × 0/27 Degrees latitude areas with dimensions of approximately 30 × 30 km, covering an area of deals were downscaled. Each period of 12 years with cell size (2140 * 4380), the rows indicate the time (days) and columns represent the location (cell) via code in MATLAB days with temperatures below zero degrees Celsius, while mining and Zoning days Ice in the cold months, the slope of the trans-detector computed by Mann-Kendall and tilt sensing and maps that were drawn in the oven software. The results showed that most cold months in the period 2050-2039 of frost days over the period 2026-2015 are entitled. Most of frost days in February and in the mountainous Zagros and Alborz heights of Azerbaijan and Khorasan with 300 days appear.

In principle, the appearance of a village more than anything is dependent upon the environmental conditions and geographical position. Thus identifying the environmental factors which influence the formation of rural habitats is highly important. The Silakhor plain in the northeast of Lorestan Province is an area with its favorable environmental factors for inhabitation, and a dense drainage network of major and minor faults. But it has a variety of natural hazards. In this paper, descriptive – analytical and statistical research methods have been used along with tools like topography, geology, and geomorphology maps, water resources and satellite imagery. To overlay the layers, Arc GIS software tools and AHP methods were used. Results indicate that the most important geomorphic factors in the dispersal establishment of villages are alluvial plains. The most stable Ecological factors which affect the distribution of villages in the Silakhor plain is the slope factor and the most instable ones are several faults that cause earthquakes in the region. From the natural hazards viewpoint, the results show that in the Silakhor plain from among 223 villages, 18 villages are at the risk of flooding, 41 villages at the risk of landslides, and 66 villages are located in high earthquake risk regions. Finally, the compilation hazard maps show that 18 villages are highly vulnerable to natural disasters.